AY 2003 ANNUAL REVIEW OF: Gordon H. Dash, Jr. Associate ... · is not only superbly unique, but it was done completely on-line using FX traders in both Michigan and Switzerland (sample

AY 2003 ANNUAL REVIEW OF: Gordon H. Dash, Jr. Associate Professor of Finance College of Business Administration University of Rhode Island Kingston, RI 02881 [email protected]

COMPLIANCE: Article XV, Section 4b, AGREEMENT BETWEEN RHODE ISLAND BOARD OF GOVERNORS AND UNIVERSITY OF RHODE ISLAND CHAPTER AMERICAN ASSOCIATION OF UNIVERSITY PROFESSORS 2000-2003 (as amended). This document includes: Body of the Annual Review plus Appendices A - D. PERSONAL STATEMENT

Teaching Curriculum All reviewers should note that under the current administrative classification scheme that characterizes the status of CBA assigned faculty, for the last two-decades my workload classification status has been Teaching Profile. Stated differently, except for my first 6 years of employment (1974 - 1980), I have never enjoyed the resource support that is now (or then) typical for faculty who are classified as Research Profile. My teaching record since the last annual review (for which there was no peer review process within the CBA), shows a higher than average production of credit hours for Teaching classified faculty, with extremely strong non-solicited student support as well as equally strong URI standard SETs. It is also important to note that in addition to being the most active teacher in the finance area, I am also the only Area member to develop of a new class. The CBA's inaugural market trading class, FIN 430x, Management and Valuation of Global Currencies, is not only superbly unique, but it was done completely on-line using FX traders in both Michigan and Switzerland (sample student trading assignments are attached). Additionally, this course was developed under the pressure of the five (5) week summer term without the assistance of graduate students, graders, or the typical support that is generally made available to faculty who develop new courses. The course carries both graduate and under-graduate credit and has been attended for credit by students from URI, Bryant College, and Babson College. Honor level quality and state-of-the-art challenges characterize Dash's classes. I am pleased to report that over the review period I was able to successfully implement: a) Value-at-Risk (VaR) statistical methods for managing domestic and international portfolio decisions (capital budgeting and FX portfolios - MBA 570); b) high-frequency forecasting of FX exchange rate volatility for day traders (FIN 430x); and c) simulation models for solving advanced option-spread hedges (FIN 420). Research Program The personal research program presented below demonstrates strength in nonlinear finance. Specifically, owing to a unique strength in mathematical optimization and programming methods, the Dash research program demonstrates: a) a long, but successful, maturation period and b) publications in peer-reviewed journals that have begun to position new optimization algorithm's in a competitive balance against standard, but less contemporary methods. Also, please note that unlike every other senior-level faculty member in the FIN Area, I have not had the benefit of serving as the major professor of any finance Ph.D. student. Hence, the research reported below has not had the benefit of any support other than that of the listed co-author(s). Nevertheless, I trust you will find, by comparative review, that my research productivity is near or at the top of the charts within the Area.

Annual Review AY 2003, Gordon H Dash Jr Page: 2 of 87 Although the buzz in the CBA today is about publication in CBA Target journals, I need to note that the development history of my recent three publications (two reported here) have a history that pre-dates the existence of Target list. While I am happy to note that one publication is in a target journal, only new research projects can be influenced by the recent introduction of the Target journal list. Award-Winning Research presented at a recent OR/MIS conference in March (the peer-reviewed publication is not reported here as it was finalized after the close of the review period). Service Contributions Service remains an important component of my daily life. No doubt faculty reviewers have noticed the Faculty Senate minutes that report the very busy period the CBUM committee has had over the past two years. I am pleased to be a part of restoring the integrity of the University Manual. Assignments to CBA committees are under the sole discretion of the Dean. Outside contributions are extremely noteworthy. My recent and current contributions to the State of Rhode Island focus on reaching junior- and senior-high school students on the topics of sex, drugs, and destructive lifestyles. To that end, I am pleased to have been a part of the host and fund-raising efforts that brought Team Impact to school assemblies around Rhode Island. Team Impact presents young adults who demonstrate feats of strength for the purpose of getting the attention of young people in order to deliver a non-religious message about abstinence, drugs, and the destructiveness of other social ills.

RESEARCH, ARTISTIC, CREATIVE AND SCHOLARLY ACTIVITY

REFEREED ARTICLES

Dash Jr., Gordon H. and Kajiji, Nina. “New Evidence on The Predictability of South African FX Volatility in Heterogeneous Bi-lateral Markets.” African Finance Journal, Vol. 5,1, 2003. Dash Jr., Gordon H. and Kajiji, Nina. “Evolving Economy Bank Asset-Liability and Risk Management Under Uncertainty with Hierarchical Objectives and Nonlinear Pricing.” Journal of Multi-Criteria Decision Analysis, Vol 11 (4-5), 247-260, 2002. CBA TARGET JOURNAL.

FUNDED RESEARCH – Non URI Supported

Dash Jr., Gordon H., Principal Investigator, "Application of A Closed Form Bayesian Enhanced Stratification Radial Basis Function Neural Network to the Classification of Chemical Descriptors of Psychotherapeutic Compounds." Pfizer Global Research and Development, the Pfizer Corporation, Groton, CT. Initial contract funded at US$10,000. (with Nina Kajiji). July, 2002.

Annual Review AY 2003, Gordon H Dash Jr Page: 3 of 87 SOFTWARE: SEMINAR

Peer Reviewed Conference Presentation (all on-file with Office of the Dean) Dash Jr., Gordon H. and Kajiji, Nina. “Simulated Trading and Risk Management of FX Contracts Using ETS from Dynamic Financial Resources.” Presented at the 28th Annual Conference of the Northeast Business and Economics Association, September 27-28, 2001, Windsor Locks, CT.

REFEREED ACADEMIC CONFERENCE PROCEEDINGS * Dash Jr., Gordon H., Hanumara, Choudary R., and Kajiji, Nina. “Neural Network Architectures for Modeling FX Futures Options Volatility” For presentation at The 2003 Northeast Decision Sciences Institute Annual Conference, Providence, RI, March 27–29, 2003. * Winner of two (2) Best Paper Awards: a) Pearson Family Award for Best Theory Development Paper and b) Babson College / CIMS Award for the Best MIS/DSS/Microcomputer Paper. Dash Jr., Gordon H. and Kajiji, Nina. “South African Economic Risk Stabilization in Heterogeneous Bi-lateral FX Markets.” Presented at The 4th Annual African Investment Conference, Cape Town, South Africa, October 24–25, 2002. Dash Jr., Gordon H. and Kajiji, Nina. “Modeling Heterogeneous Risk Behavior of the South African Rand via A Closed-form Radial Basis Function Neural Network: A Preliminary Analysis.” Presented at The First Annual International Emerging Markets Finance Conference, Manchester, UK. September 12–13, 2002. Dash Jr., Gordon H. and Kajiji, Nina. “Optimal Bank Structure in Evolving Economies: The Utility of Stochastic Nonlinear Multiple Objective Asset-Liability Models.” Presented at the 6th World Multiconference on Systemics, Cybernetics, and Informatics, Orlando, Florida. July 14-18, 2002. Dash Jr., Gordon H. and Kajiji, Nina. “Comparative Radial Basis Function Neural Network Modeling of FX Futures Options Volatility in Heterogeneous Markets.” Presented at the 9 th International Conference on Forecasting Financial Markets, London, England, 31 May -02June, 2002. Dash Jr., Gordon H. and Kajiji, Nina. “APT Induced Efficient Insurance Indices for the Sharpe Mean-variance Model.” Presented at the 28th Annual Conference of the Northeast Business and Economics Association, September 27-28, 2001, Windsor Locks, CT. Dash Jr., Gordon H. and Kajiji, Nina. "Hedging Optimal Bank Structure in Evolving Economies: The Utility of Stochastic Nonlinear Multiple Objective Asset-Liability Models." Presented at the 3rd Annual African Investment Conference & Exhibition, August 22-24, 2001, Cape Town, South Africa.

Dash Jr., Gordon H. and Kajiji, Nina. " Prediction of FX Volatility via an RBF Neural Network with Closed-Form Regularization." Presented at the 8th International Conference on Forecasting Financial Markets, London, England, 31 May -01 June, 2001.

Dash Jr., Gordon H. and Kajiji, Nina. "Predicting FX Volatility via an Augmented RBF Neural Network." Presented at the 51st International Atlantic Economic Conference, Athens, Greece, 13-20 March 2001.

Annual Review AY 2003, Gordon H Dash Jr Page: 4 of 87

TEACHING AND CURRICULUM CONTRIBUTIONS

Semester Course Title Credits # of Students Spring 2001 FIN 420 Speculative Markets*** 6 54 Spring 2001 FIN 660 Managerial Economics 3 12 Spring 2001 FIN 660 Managerial Economics (EMBA) 3 14 Summer 2001 FIN 660 Managerial Economics 3 25 Summer 2001 FIN 660 Managerial Economics 3 24 Summer 2001 FIN 433 Commercial Bank Fin Mgt 3Summer 2001 FIN 430X Global Currency Trading

13

And Valuation**** 3 10 Fall 2001 FIN 660 Managerial Economics 3 13 Fall 2001 FIN 660 Managerial Economics (EMBA) 3 10 Fall 2001 FIN 625 Adv Portfolio Theo & Mgt** 3 06 Fall 2001 FIN 460 Basic Managerial Economics 3 14 Spring 2002 FIN 420 Speculative Markets (K) 3 37 Spring 2002 FIN 420 Speculative Markets 3 22 Spring 2002 FIN 660 Managerial Economics 3 16 Spring 2002 FIN 660 Managerial Economics (EMBA) 3 10 Beta Gamma Sigma Teaching Excellence Award Summer 2002 FIN 660 Managerial Economics 3 21 Summer 2002 FIN 660 Managerial Economics 3 18 Summer 2002 FIN 433 Commercial Bank Fin Mgt 3 11 Summer 2002 FIN 430X Global Currency Trading And Valuation 3 14 Fall 2002 FIN 433 Com. Bank Financial Mgt. (K) 3 29 Fall 2002 FIN 433 Com. Bank Financial Mgt. 3 16 Fall 2002 MBA 570 Managerial Economics 3 17 Fall 2002 MBA 570 Managerial Economics (EMBA) 3 09 Spring 2003 FIN 420 Speculative Markets (K) 3 49 Spring 2003 FIN 420 Speculative Markets 3 25 Spring 2003 MBA 570 Managerial Economics 3 0***** Summer 2003 MBA 570 Managerial Economics (K) 3 24 Summer 2003 MBA 570 Managerial Economics 3 22 Summer 2003 FIN 460 Basic Managerial Economics 3 19 Summer 2003 FIN 430X Global Currency Trading And Valuation 3 13 Fall 2003 FIN 433 Com. Bank Financial Mgt. (K) 3 33 Fall 2003 FIN 433 Com. Bank Financial Mgt. 3 19 Fall 2003 FIN 420 Speculative Markets 3 30 Fall 2003 MBA 570 Managerial Economics (EMBA) 3 08

• Inaugural Distance Education class for College of Business Administration

• ** Internet only distance education class

• *** Large section release

• **** Inaugural Trading Room Technology class (Internet based)

• ***** Canceled after week 3 for insufficient enrollment. First semester that the course was offered as an elective (not required under new MBA program format). Activity replaced with URI Financial Engineering Club ( http://www.uri.edu/student_organizations/fec/ )

• (K) – Kingston section (versus Providence campus)

• EMBA – Executive MBA weekend program (Compensated)

• Blue color: Class size exceeds CBA maximum (35) and exceeds 40 students

• Green color: Large section class

• Magenta color: Inaugural CBA implementation of a new policy thrust

• NOTE: Reported class enrollment is based on the instructor’s grade-book. Small discrepancies with the Office of Enrollment Services are possible.

http://www.uri.edu/student_organizations/fec/


USOLICITED STUDENT COMMENTS: A SAMPLE

• "…enjoy and thank you for an excellent, extremely insightful academic experience!" KD

• "I learned a lot in your class and found it really helpful to work with a group in learning WinORS." JKG

• "The electronic lecture was good. Keep it. Your use of the internet is wonderful. Your efforts to stay connected when out of the country are appreciated …You are carrying the URI flag. Finance 660 (MBA 570, sic) is more work than other classes. That is ok…You are a great instructor. I will take any and every class you teach as long as I can get through here in my allotted two years." CH

• "I want to thank you for a thoroughly enjoyable class - it helps when the professor is excited about the topic he/she is teaching to the students. I hope you are enjoying yourself in Europe and get a chance for some rest and relaxation. take care!" JG

• What can I say other than "great semester." I personally wished to thank you for the effort and the enthusiasm you brought to the classroom. With only two courses remaining before I graduate I can safely say that you were the most impressive instructor I have encountered. On a side not I wanted to share with you that I am being flown to Miami today for an interview. I will be sure to reflect upon my model building experiences from Managerial Economics. Thank you for everything and best of luck on your future endeavors. Keep up the good work! AB

• I want to take this opportunity to tell you that I have really enjoyed your class and I learned a great deal from it. Also, thank you for taking time out of your busy schedule to conduct the help session last Saturday. I can imagine how much you must have had to do and how tired you must have been after your long trip so it was very much appreciated. LH

DOCTORAL PROGRAM CONTRIBUTIONS

Student: Xia Pan Dept.: Management Information Systems Degree: Doctor of Philosophy, May, 2003 Thesis: SPC for Quality and Risk: Monitoring Processes with Cross-Sectional And Serial Interdependence, and Higher Moments Role: Committee Member Student: Sirapat Polwitoon Dept.: Finance Degree: Doctor of Philosophy, December, 2002 Thesis: Three Essays on Capital Market Efficiency Market Role: Committee Member Student: Joyce Hsieh Dept.: Finance Degree: Doctor of Philosophy, May, 2002 Thesis: TBA Role: Committee Member

Annual Review AY 2003, Gordon H Dash Jr Page: 6 of 87 SERVICE CONTRIBUTIONS

UNIVERSITY AND COLLEGE RELATED

AY 2002-03 Committee Member - College of Business Technology Committee Committee Member - Faculty Senate: Constitution, By-Laws, and University Manual.

AY 2001-02 Committee Member - College of Business Technology Committee

Committee Member - Faculty Senate: Constitution, By-Laws, and University Manual.

STUDENT CLUBS AND RELATED

AY 2003 Faculty Advisor, Financial Engineering Club (www.urifec.org)

AY 2002 Faculty Advisor, Financial Engineering Club

AY 2001 Faculty Advisor, Financial Engineering Club

SERVICE TO THE STATE OF RHODE ISLAND

University of Rhode Island

AY 2003-04 Investment Committee, American Association of University Professors AY 2002-03 Investment Committee, American Association of University Professors AY 2001-02 Investment Committee, American Association of University Professors State of Rhode Island

June 2002 and June and 2002 Team Impact Fund Raising and Host Committee (http://www.team-impact.com/); Sponsored by: New Life Worship Center (www.nlwcenter.org)

In our second trip to Providence, RI in as many years, Team Impact was amazed at how God worked in the lives of the people. With 39 school assemblies and five nightly evangelistic programs, we saw people's lives changed and over 600 decisions to accept salvation through Christ. We are looking forward to going back to Rhode Island and we thank the staff and congregation of New Life Worship Center for a great job with the Team Impact Crusade. (Source: 2002 Archive, Team Impact web site).

http://www.urifec.org/

http://www.team-impact.com/

http://www.nlwcenter.org/

Annual Review AY 2003, Gordon H Dash Jr Page: 7 of 87 International Community

June 2003 M.B.A. Internship Provider (Finance), Istituto Superiore Per Imprenditori E Diregenti Di Azienda (ISIDA), Palermo, Italy

June 2002 M.B.A. Internship Coordinator (Finance), Istituto Superiore Per

Imprenditori E Diregenti Di Azienda (ISIDA), Palermo, Italy May 2002 Seminar Leader: Managing and Hedging Bank Credit Risk. Presented to

Italian Commercial Bankers under the auspices of ISIDA, Palermo, Italy. June 2001 M.B.A. Internship Coordinator (Finance), Istituto Superiore Per

Imprenditori E Diregenti Di Azienda (ISIDA), Palermo, Italy May 2001 Seminar Leader: Effective Quantitative Methodologies in Bank Credit

Analysis. Presented to Italian Commercial Bankers under the auspices of ISIDA, Palermo, Italy. June 2001 M.B.A. Internship Coordinator (Finance), Istituto Superiore Per

Imprenditori E Diregenti Di Azienda (ISIDA), Palermo, Italy

PROFESSIONAL SOCIETY MEMBERSHIPS AND AFFILIATIONS

Beta Gamma Sigma Delta Pi Epsilon Delta Sigma Pi

• NONLINEAR FINANCE, International Association of Financial Engineers; (www.iafe.org) • NONLINEAR FINANCE, Global Association of Risk Professionals; (www.garp.com) • NONLINEAR FINANCE, PRMIA Risk Management; (www.prmia.org) • FINANCE, American Finance Association; (www.afajof.org)

HONORS AND AWARDS

• Babson College / CIMS Award for the Best MIS/DSS/Microcomputer Paper, presented at The 2003 Northeast Decision Sciences Institute Annual Conference, Providence, RI, March 27–29, 2003.

• Robert W. Pearson Family Award for Best Theory Development Paper, presented at The 2003 Northeast Decision Sciences Institute Annual Conference, Providence, RI, March 27–29, 2003.

• Beta Gamma Sigma Teaching Excellence Award, College of Business Administration, May 2002

http://www.iafe.org/

http://www.garp.com/

http://www.prmia.org/

http://www.afajof.org/


APPENDIX A - SAMPLE URI / SETs

FIN 420

FIN 433

FIN 660 / MBA 570





APPENDIX B - SAMPLE STUDENT PROJECTS

FIN 420, SPECULATIVE MARKETS (NOTE: formatting may be lost due to Microsoft Word import procedures)


Combined Options/Futures Project

Matthew Coyne

Lynne Picard

April 29, 2003

Finance 420

Dr. Gordon Dash


Part I. Build a Portfolio

We decided to build our portfolio with large cap value stocks. Our portfolio is shown in the table below as it stands as of April 28, 2003: Ticker

Symbol

Last Trade Trading

High

Trading

Low

Volume Market

Capitalization

Shares Out-

standing ('000)

Beta Price Paid QTY Current

Value

Weight Gain Over

Base

AXP $37.4900 $37.7600 $36.8800 4,068,800 $49,270,000,000 1,314,217 1.24 $35.1800 500 $18,745.00 4.341% $1,155.00

CVS $24.1600 $24.2500 $23.8500 2,012,700 $9,509,000,000 393,584 0.63 $25.4000 500 $12,080.00 2.797% $(619.00)

EBAY $93.6100 $93.9900 $92.5700 6,142,416 $29,446,000,000 314,560 2.80 $90.1000 500 $46,805.00 10.839% $1,755.00

GD $62.5600 $62.7500 $60.9600 1,538,100 $12,322,000,000 196,962 0.38 $56.1000 500 $31,280.00 7.243% $3,230.00

F $10.1600 $10.1700 $9.9500 12,290,500 $18,605,000,000 1,831,200 1.16 $7.6500 500 $5,080.00 1.176% $1,254.00

K $32.6800 $32.7100 $32.0000 1,099,700 $13,426,000,000 410,832 0.03 $30.0200 500 $16,340.00 3.784% $1,330.00

KKD $32.6100 $32.7400 $31.9100 370,900 $1,855,000,000 56,884 1.40 $34.1700 500 $16,305.00 3.776% $(779.00)

KRON $45.5800 $45.9500 $43.5000 464,007 $907,500,000 19,910 0.99 $35.8000 500 $22,790.00 5.277% $4,890.00

SNE $24.0000 $24.3600 $23.1600 7,358,000 $22,074,000,000 919,750 1.18 $37.2400 500 $12,000.00 2.779% $(6,619.00)

YHOO $25.2900 $25.4300 $24.5500 9,783,523 $15,111,000,000 597,508 3.60 $24.7600 500 $12,645.00 2.928% $264.00

WASH $20.5700 $20.5700 $20.4800 5,800 $268,800,000 13,067 0.40 $20.4100 500 $10,285.00 2.382% $79.00

NVDA $13.9600 $14.2100 $13.5500 5,644,966 $2,220,000,000 159,025 3.10 $14.4100 500 $6,980.00 1.616% $(225.00)

WMT $56.0900 $56.4100 $54.5000 9,186,800 $246,000,000,000 4,385,808 0.88 $53.3300 500 $28,045.00 6.494% $1,379.00

GM $36.4700 $36.6600 $35.6000 3,519,700 $20,446,000,000 560,625 1.15 $34.3300 500 $18,235.00 4.223% $1,069.00

GE $29.5200 $29.7800 $28.7500 20,062,700 $295,000,000,000 9,993,224 1.08 $26.6000 500 $14,760.00 3.418% $1,459.00

IBM $85.1200 $85.5000 $83.6200 6,365,100 $146,900,000,000 1,725,798 1.50 $81.5500 500 $42,560.00 9.856% $1,784.00

DELL $29.3300 $29.5100 $28.8600 15,569,459 $75,648,000,000 2,579,202 1.67 $27.8500 500 $14,665.00 3.396% $739.00

XOM $35.4100 $35.6000 $34.8200 11,482,100 $236,900,000,000 6,690,200 0.34 $35.8600 500 $17,705.00 4.100% $(224.00)

VZ $37.0900 $37.3300 $36.3000 6,377,900 $101,800,000,000 2,744,675 0.80 $36.0700 500 $18,545.00 4.294% $509.00

HPQ $16.1100 $16.2400 $15.6000 11,663,700 $49,175,000,000 3,052,451 1.55 $16.5800 500 $8,055.00 1.865% $(234.00)

TGT $33.1200 $33.3600 $31.7200 4,550,900 $30,159,000,000 910,597 1.17 $29.9000 500 $16,560.00 3.835% $1,610.00

JNJ $57.0100 $57.3300 $56.2000 4,361,300 $169,300,000,000 2,969,654 0.41 $56.6600 500 $28,505.00 6.601% $175.00

MSFT $25.7400 $25.9400 $25.3200 56,394,044 $276,000,000,000 10,722,610 1.75 $25.2500 500 $12,870.00 2.980% $245.00

Annual Review AY 2003, Gordon H Dash Jr Page: 15 of 87 CURRENT TOTALS 1.27 $431,840.00 100.0% $14,230.00

BEGINNING VALUE $417,609.00

II. Individual Equity: Basic Hedging Concepts

This section of the project focuses on an individual stock, which has outstanding traded options. For this project we chose to use stock

options written against General Dynamics stock. When deciding which put and call options to select, we first looked at the price of the

stock at the decision date, which was around March 28th. On that date, General Dynamics’ stock was priced at $56.34. In order to

successfully use many different options strategies in the following parts of this project, we decided to choose the May 2003 options, which

expire on the 17th of May. In deciding which exercise prices to choose for the options (in order to complete the butterfly spread), we chose 3

different calls and 3 different puts. One call/put was very close to the current value of the stock ($56.34), one call/put was below this value

and the other was above the value of the middle option. Based on this criteria we chose the following options written against General

Dynamics’ stock:

Option Expire Exercise

CALLS GD EJ-E 17-May-03 50.00

GD EK-E 17-May-03 55.00

GD EL-E 17-May-03 60.00

PUTS GD QJ-E 17-May-03 50.00

GD QK-E 17-May-03 55.00

GD QL-E 17-May-03 60.00


At this point, our portfolio was set-up and ready to solve the spread strategies simulated and analyzed in the next section of this project.


Part III. Equity Options Assignment

Spread Strategies

Call Bull SpreadGD

Instrument Price9590858075706560555045403530252015105

Pro

fit

10

0

-10

-20

-30

-40

Option Expire Remain-

ing

Contracts Exercise Last

Trade

Min

Value

B-S Price Hedge Theta Gamma Vega Rho

Implied

Volatility

GD EJ-E 17-May-03 50 10 50.00 $7.300 5.780 27.3805 0.75804 -78.0445 0.0045 6.4256 2.0415 0.22520

GD EK-E 17-May-03 50 -10 55.00 $3.400 0.780 25.9508 0.73565 -82.1719 0.0048 6.7654 2.0663 0.13588

GD EL-E 17-May-03 50 0 60.00 $2.125 0.000 24.8348 0.71226 -85.6810 0.0050 7.0543 2.0404 0.19389

GD QJ-E 17-May-03 50 0 50.00 $1.000 0.000 21.6005 0.24196 -78.0445 0.0045 6.4256 -4.8078 0.00000

GD QK-E 17-May-03 50 0 55.00 $3.375 0.000 25.1708 0.26435 -82.1719 0.0048 6.7654 -5.4680 0.13588

GD QL-E 17-May-03 50 0 60.00 $4.750 4.220 29.0548 0.28774 -85.6810 0.0050 7.0543 -6.1787 0.58818

A call bull spread is a type of money spread where two call options are involved differing only by exercise price. The call option with the lower exercise price is purchased, or long, and the call option with the higher exercise price is sold, or short. In this analysis, we decided to purchase 10 contracts of General Dynamic’s options at an exercise price of $50 expiring in May 2003. In turn, we sold short 10 call option contracts with an exercise price of $55 also expiring in May 2003. The long calls were currently priced at $7.30, while the short calls were priced at $3.40. If the stock price ends up equal to or below $50, both options will expire out of the money and the loss will be the difference between the premium received on the short calls and the premium paid on the long calls. The second profit case is if the stock price is between $50 and $55. In this case, the long call ends up in the money and the short call out of the money. This is where most of the uncertainty lies. The third profit opportunity is when the stock price is higher than

Annual Review AY 2003, Gordon H Dash Jr Page: 18 of 87 $55 and both contracts are in the money. When this occurs, the short call is exercised and the long call is also exercised. In this case, the profit is the difference between the exercise prices ($55 - $50) minus the difference between the premiums ($7.30 - $3.40). This turns out to be $1.1 per contract or $11.00 total. The maximum loss is $3.9 per contract or $39.00. Both of these results are shown in the profit graph above. As with any other bull spread, different holding periods can have an effect on these profits. The longer the position is held, the larger the profit and loss possibilities. When not held until expiration, the maximum profit is not going to be $11.00 for this strategy. It all depends on the outlook of the investor. If a bull market is expected, then we are in good shape, but if a bear occurs, there could be some trouble. Because General Dynamics is a defense contractor, we believe in a bull market for this stock with the war at hand currently in the United States. With this in mind, we expect a profit from the use of this strategy. As seen solely by the profit graph above, this strategy definitely worked. If the strategy did not work, the entire profit line would be below the breakeven profit of $0.


Call Bear SpreadGD


Pro

fit

20

15

10

5

0

-5


ing


Trade

Min

Value

B-S Price Hedge Theta Gamma Vega Rho Implied

Volatility

GD EJ-E 17-May-03 50 -5 50.00 $7.300 5.780 27.3805 0.75804 -78.0445 0.0045 6.4256 2.0415 0.22520

GD EK-E 17-May-03 50 5 55.00 $3.400 0.780 25.9508 0.73565 -82.1719 0.0048 6.7654 2.0663 0.13588

GD EL-E 17-May-03 50 0 60.00 $2.125 0.000 24.8348 0.71226 -85.6810 0.0050 7.0543 2.0404 0.19389

GD QJ-E 17-May-03 50 0 50.00 $1.000 0.000 21.6005 0.24196 -78.0445 0.0045 6.4256 -4.8078 0.00000

GD QK-E 17-May-03 50 0 55.00 $3.375 0.000 25.1708 0.26435 -82.1719 0.0048 6.7654 -5.4680 0.13588

GD QL-E 17-May-03 50 0 60.00 $4.750 4.220 29.0548 0.28774 -85.6810 0.0050 7.0543 -6.1787 0.58818

A call bear spread is a type of money spread where two call options are involved differing only by exercise price. This strategy is the complete opposite of a call bull spread. The call option with the higher exercise price is purchased, or long, and the call option with the lower exercise price is sold, or short. In this analysis, we decided to purchase 5 contracts of General Dynamic’s options at an exercise price of $55 expiring in May 2003. In turn, we sold short 5 call option contracts with an exercise price of $50 also expiring in May 2003. The long calls were currently priced at $3.40, while the short calls were priced at $7.30. If the stock price ends up equal to or below $50, both options will expire in the money and the profit will be the difference between the premium received on the short calls and the premium paid on the long calls plus the difference between the exercise prices of the two options ($55 - $50 + $7.3 - $3.4). The second profit case is if the stock price is between $50 and $55. The third profit opportunity is when the stock price is higher than $55 and both contracts are out of the money. When this occurs, the loss is the difference between the premiums ($7.30 - $3.40).

Annual Review AY 2003, Gordon H Dash Jr Page: 20 of 87 This loss turns out to be $5.5 total for the five contracts. The maximum gain in a bear market is $3.9 per contract or a total of $19.5. Both of these results are shown in the profit graph above. As with any other bear spread, different holding periods can have an effect on these profits. The longer the position is held, the larger the profit and loss possibilities. When not held until expiration, the maximum profit is not going to be $19.5 for this strategy. It all depends on the outlook of the investor. If a bear market is expected, then we are in good shape, but if a bull occurs, there could be some trouble. If we were to expect a bear market, there are high profits to be made as seen in the graph. The losses on this bear strategy are significantly lower than that of a bull strategy. As seen solely by the profit graph above, this strategy definitely worked. If the strategy did not work, the entire profit line would be below the breakeven profit of $0. One thing to keep in mind before implementing either this strategy or the call bull is the movement of the volatility of the stock price. We must be very certain as to the movement before actually deciding to use either of these strategies to hedge our position on General Dynamics’ stock.

Butterfly SpreadGD

Instr P100959085807570656055504540353025201510

o

2


ing


Trade

Min

Value

B-S

Price

Hedge Theta Gamma Vega Rho Implied

Volatility

GD EJ-E 17-May-03 50 1 50.00 $7.300 5.780 49.9941 0.94845 -68.3277 0.0006 2.1641 0.3987 0.21838

GD EK-E 17-May-03 50 -2 55.00 $3.400 0.780 49.7093 0.94520 -71.7039 0.0006 2.2711 0.4129 0.13588

GD EL-E 17-May-03 50 1 60.00 $2.125 0.000 49.4406 0.94295 -74.8735 0.0006 2.3714 0.4325 0.20219

GD QJ-E 17-May-03 50 0 50.00 $1.000 0.000 44.2141 0.05155 -68.3277 0.0006 2.1641 -6.4506 0.00000

GD QK-E 17-May-03 50 0 55.00 $3.375 0.000 48.9293 0.05480 -71.7039 0.0006 2.2711 -7.1214 0.13588

GD QL-E 17-May-03 50 0 60.00 $4.750 4.220 53.6606 0.05705 -74.8735 0.0006 2.3714 -7.7867 0.58818ument rice

Pr

-1

fit 0

1

-2

-3

A butterfly spread is a combination of a call bull and a call bear spread, but involves 3 strike prices with the middle prices close to the

current stock spot price and halfway in between the other two prices. In this case we are long one each of the high and low exercise prices

($50 and $60) and we are short 2 contracts of the middle exercise price of $55. The long calls were priced at $7.30 and $2.125, while the

short calls were priced at $3.40. There are four ranges of the stock price in relation to the exercise price and this in turn leads to 4 different

profit or loss opportunities as seen in the graph above. When the stock prices falls to below $50 a loss situation will occur. The total loss is

–C1 + 2C2 – C3. In this case this loss, or the maximum loss no matter how low the stock price falls is (-7.3 +2(3.4) – 2.125) or $2.625.

This is also the maximum loss if another situation occurs: when the stock price rises to above $60. In another case, if the stock price is

between $50 and $55. The profit in this range can be either positive or negative depending on how much the stock price drops. A very

small drop will incur a profit, while a large drop will result in a loss. The last situation is when the stock price is between $55 and $60.

When this occurs the profit declines with the higher the price of the stock. The maximum profit occurs when there is very little volatility.

Annual Review AY 2003, Gordon H Dash Jr Page: 21 of 87 This maximum profit is $1.9344 according to the WinORS software. In order to use this strategy and be profitable, we must assume and be

correct in our assumption that there will be little volatility in the price of the General Dynamic stock. As with any butterfly spread there is

two breakeven stock prices that will incur 0 profit. If we can be fairly certain that our stock price will remain between these two prices, a

butterfly spread would be a very viable option. In this analysis, the strategy was successful because the profit line was above the 0

breakeven profit. With the market as it is today and the war at hand in the country, we don’t believe a butterfly spread is the way to go. We

feel this stock, being of a defense-contracted company, will have high volatility whether it is bearish or bullish and an inverted butterfly

might be strategy to implement in this case. The inverted butterfly is discussed next.


Inverted ButterflyGD

ument ri0958065555040352520

o

20

10

0

-10


ing


Trade

Min

Value


Volatility

GD EJ-E 17-May-03 50 -10 50.00 $7.300 5.780 27.3805 0.75804 -78.0445 0.0045 6.4256 2.0415 0.22520

GD EK-E 17-May-03 50 20 55.00 $3.400 0.780 25.9508 0.73565 -82.1719 0.0048 6.7654 2.0663 0.13588

GD EL-E 17-May-03 50 -10 60.00 $2.125 0.000 24.8348 0.71226 -85.6810 0.0050 7.0543 2.0404 0.19389

GD QJ-E 17-May-03 50 0 50.00 $1.000 0.000 21.6005 0.24196 -78.0445 0.0045 6.4256 -4.8078 0.00000

GD QK-E 17-May-03 50 0 55.00 $3.375 0.000 25.1708 0.26435 -82.1719 0.0048 6.7654 -5.4680 0.13588

GD QL-E 17-May-03 50 0 60.00 $4.750 4.220 29.0548 0.28774 -85.6810 0.0050 7.0543 -6.1787 0.58818Instr P ce60 105109085757045301510

Pr

fit

-20

An inverted butterfly spread is the opposite of a butterfly spread. This spread is intended to profit in a high volatility market. This

strategy also involves 3 strike prices with the middle prices close to the current stock spot price and halfway in between the other two prices.

In this case we are short one each of the high and low exercise prices ($50 and $60) and we are long 2 contracts of the middle exercise price

of $55. The short calls were priced at $7.30 and $2.125, while the long calls were priced at $3.40. In this case we decided to purchase 20 of

the $55 call option contracts and sell short 10 each of the $50 and $60 call option contracts. There are four ranges of the stock price in

relation to the exercise price and this in turn leads to 4 different profit or loss opportunities as seen in the graph above. When the stock

prices falls to below $50 a profit situation will occur. The total profit is C1 - 2C2 + C3. In this case this profit, or the maximum profit no

matter how low the stock price falls is (7.3 -2(3.4) + 2.125) or $2.625. Because there are 10 contracts short this maximum profit is $26.25.

This is also the maximum profit if another situation occurs: when the stock price rises to above $60. In another case, if the stock price is

between $50 and $55. The profit in this range can be either positive or negative depending on how much the stock price drops. A very

small drop will incur a loss, while a large drop will result in a profit. The last situation is when the stock price is between $55 and $60.

When this occurs the profit increases with the higher the price of the stock. The maximum loss occurs when there is very little volatility.

This maximum loss is $2.24834 per contract, or a total of $22.4834, according to the WinORS software. In order to use this strategy and be

profitable, we must assume and be correct in our assumption that there will be high volatility in the price of the General Dynamic stock. As

with any inverted butterfly spread there is two breakeven stock prices that will incur 0 profit. If we can be fairly certain that our stock price

Annual Review AY 2003, Gordon H Dash Jr Page: 23 of 87 will remain outside of these two prices, an inverted butterfly spread would be a very viable option. In this analysis, the strategy was

successful because the profit line was above the 0 breakeven profit. With the market as it is today and the war at hand in the country, we

believe an inverted butterfly spread is the way to go. We feel this stock, being of a defense-contracted company, will have high volatility

whether it is bearish or bullish and an inverted butterfly will be the strategy to implement.


Ratio Spread GD

A ratio spread is a risk-free transaction involving two options weighted according to their deltas. With a ratio spread, an investor can buy an underpriced call and sell and overpriced or correctly priced call, creating a ratio of one call to the other that creates a riskless position. The riskless position is created when the ratio of the quantity of the first call to the quantity of the second call is equal to the negative inverse ratio of their deltas. (N1/N2 = -Delta2/Delta1) A ratio spread can only remain riskless if the ratio is continuously adjusted. For example, we used the General Dynamics’ options chains to determine the ratio spread of call #1 and call #2. Luckily, with the WinORS software, we do not have to manually compute the ratio spread; it is automatically computed for us. For our purposes, call #1 is the May 50 call while call #2 is the May 55 call. As of 4/6/03, the ratio spread for these two calls was –0.7605. What this means for the user of this information is that in order to maintain a riskless position, (assuming call #1 is underpriced and call #2 is either overpriced or correctly priced) the investor would have to buy 761 of the May 50 calls and sell 1,000 of the May 55 calls. As each day passes, the ratio spread will change because of the change in the risk-free rate, the stock price of General Dynamics and the time to expiration. In order to determine if a call or put is over or under priced, you must compare the Last Trade column of the options pricing with the B-S Price (Black-Scholes pricing model for options). If the B-S price is lower than the Last Trade price, then the call or put is overpriced. If the Last Trade price is lower than the B-S price, then the call or put is underpriced according to the value of the Black-Scholes model. In the example below, the 1st call option is underpriced because the Last Trade price is lower than the B-S price. In fact, all of the options listed in this table are underpriced.

Option Expire Exercise Last Trade B-S Price

GD EJ-E 17-May-03 50.00 $7.300 27.3805

GD EK-E 17-May-03 55.00 $3.400 25.9508

GD EL-E 17-May-03 60.00 $2.125 24.8348

GD QJ-E 17-May-03 50.00 $1.000 21.6005

GD QK-E 17-May-03 55.00 $3.375 25.1708

GD QL-E 17-May-03 60.00 $4.750 29.0548


StraddleGD


Pro

fit

50

40

30

20

10

0

Option Expire Remaining Contracts Excercise Last

Trade Min Value

B-S Price Hedge Theta Gamma Vega Rho Implied Volatility

GD EJ-E 17-May-03 50 1 50.00 $7.300 5.780 17.7576 0.69497 -50.8011 0.0088 7.2284 2.8778 0.23019 GD EK-E 17-May-03 50 0 55.00 $3.400 0.780 15.7865 0.64803 -53.9013 0.0094 7.6723 2.7891 0.13453 GD EL-E 17-May-03 50 0 60.00 $2.125 0.000 14.0570 0.59871 -56.0076 0.0098 7.9747 2.6492 0.20276 GD QJ-E 17-May-03 50 1 50.00 $1.000 0.000 11.9088 0.30503 -50.2993 0.0088 7.2284 -3.9621 0.00000GD QK-E 17-May-03 50 0 55.00 $3.375 0.000 14.9309 0.35197 -53.3494 0.0094 7.6723 -4.7348 0.13453GD QL-E 17-May-03 50 0 60.00 $4.750 4.220 18.1945 0.40129 -55.4055 0.0098 7.9747 -5.5587 0.57390

A straddle is the purchase of a call and a put that have the same exercise price and expiration date. Holding both a call and a put will

capitalize on stock price movement in either direction. The strategy involves 2 strike prices which are below the current stock spot price.

The profit potential of a straddle is unlimited because in theory the stock price for General Dynamics can rise infinitely. The straddle will

earn profits dollar for dollar with the stock price increase in excess of the exercise price. Profit is limited on the down side because the stock

price can go no lower than zero. The downside maximum profit can be calculated by setting the stock price at expiration equal to zero.

General Dynamics maximum downside profit would be $41.70, with the exercise price of $50.00, call premium of $7.30, and put premium

of $1.00. The worst-case scenario for a General Dynamics straddle would be for the stock price to end up equal to the exercise price of $50,

Annual Review AY 2003, Gordon H Dash Jr Page: 26 of 87 where neither the call or the put could be exercised for a gain and the premiums of $7.30 for the call and $1.00 for the put would be lost.

The straddle would be an appropriate strategy for General Dynamics as long as the stock price is anticipated to decrease below $41.70 or

increase above $58.30 before the May 17, 2003 expiration date. With the current conflict in Iraq and the uncertainty of other foreign threats

to the United States, we believe this would be a positive strategy to implement because of the defense natured industry in which General

Dynamics belongs.

StrapGD


Pro

fit

100

80

60

40

20

0

Option Expire Remaining Contracts Excercise Last Trade

Min Value


GD EJ-E 17-May-03 50 2 50.00 $7.300 5.780 17.7576 0.69497 -50.8011 0.0088 7.2284 2.8778 0.23019 GD EK-E 17-May-03 50 0 55.00 $3.400 0.780 15.7865 0.64803 -53.9013 0.0094 7.6723 2.7891 0.13453 GD EL-E 17-May-03 50 0 60.00 $2.125 0.000 14.0570 0.59871 -56.0076 0.0098 7.9747 2.6492 0.20276 GD QJ-E 17-May-03 50 1 50.00 $1.000 0.000 11.9088 0.30503 -50.2993 0.0088 7.2284 -3.9621 0.00000 GD QK-E 17-May-03 50 0 55.00 $3.375 0.000 14.9309 0.35197 -53.3494 0.0094 7.6723 -4.7348 0.13453 GD QL-E 17-May-03 50 0 60.00 $4.750 4.220 18.1945 0.40129 -55.4055 0.0098 7.9747 -5.5587 0.57390

The strap is a slightly bullish variation of the straddle, involving 2 calls for every 1 put. It is similar to a straddle in that a large stock

price change is expected, but utilizing a strap indicates that it is believed a stock increase is more likely than a decrease. The greater number

of calls used the, the more bullish the investment decision. The upside breakeven is lowered by one-half of the put premium. The downside

Annual Review AY 2003, Gordon H Dash Jr Page: 27 of 87 breakeven is lower by the call premium. This makes the upside breakeven stock price easier to achieve and the down side breakeven stock

price harder. The General Dynamics upside breakeven would be $57.80 calculated as X + C + P/2, as opposed to $58.30 using a straddle.

General Dynamics downside breakeven would be $34.40 calculated as X - P - 2C, this in comparison to the straddle downside breakeven of

$41.70. The maximum profit is infinite on the upside and $34.40 on the downside, maximum downside profit calculated as - 2C + X - P.

The worst outcome, again similar to the straddle, is for the stock price at expiration to be equal to the exercise price. The maximum loss for

a General Dynamics strap would be $15.60, compared to the straddle with a loss of $8.30. Because of our bullish out look on General

Dynamics and the defense industry, we believe the strap would be a favorable strategy. With technological superiority being the key driver

in a victory over Iraq, we believe General Dynamics will continue to grow with the high tech defense-contracting industry.

StripGD


Pro

fit

5040302010

0-10-20

Option Expire Remaining Contracts Excercise Last Trade

Min Value


GD EJ-E 17-May-03 50 1 50.00 $7.300 5.780 17.7576 0.69497 -50.8011 0.0088 7.2284 2.8778 0.23019 GD EK-E 17-May-03 50 0 55.00 $3.400 0.780 15.7865 0.64803 -53.9013 0.0094 7.6723 2.7891 0.13453 GD EL-E 17-May-03 50 0 60.00 $2.125 0.000 14.0570 0.59871 -56.0076 0.0098 7.9747 2.6492 0.20276 GD QJ-E 17-May-03 50 2 50.00 $1.000 0.000 11.9088 0.30503 -50.2993 0.0088 7.2284 -3.9621 0.00000 GD QK-E 17-May-03 50 0 55.00 $3.375 0.000 14.9309 0.35197 -53.3494 0.0094 7.6723 -4.7348 0.13453 GD QL-E 17-May-03 50 0 60.00 $4.750 4.220 18.1945 0.40129 -55.4055 0.0098 7.9747 -5.5587 0.57390


The strip goes in the opposite direction of a strap; it is a slightly bearish variation of a straddle. It involves 2 puts for every 1 call and

is used when it is believed the stock price will decrease. If the market goes down and the option expires in the money, there will be 2 puts to

exercise. If the market goes up, the cost of the put will cut into the profit. When the stock price at expiration is below the exercise price, the

extra put adds the amount X -ST – P to the profit. If the stock price ends up above the exercise price, the profit from the strip falls below the

profit from a straddle by the amount of the second put premium. The worse case is again similar to the straddle and strap if the stock price

ends up at the exercise price, because with this outcome neither the puts nor the calls are worth anything. The General Dynamics maximum

loss would be $9.30 calculated as - C - 2P. The upside breakeven reflects the fact that the stock price must exceed the exercise price by the

premiums on the call and 2 puts. On the down side the breakeven is reduced to one-half of the premium on the call. The General Dynamics

downside breakeven is $42.20 and upside breakeven is $59.30 calculated as X - P - C/2 and X +C + 2P, respectively. For the straddle the

breakevens were $41.70 and $51.30. The downside breakeven on the strip is higher, meaning the stock price does not need to fall as much

to create a profit. However, on the upside the stock price must increase more with the strip than with the straddle to generate a profit. The

maximum profit is again infinite on the upside, and $90.70 on the downside, calculated as: - C + 2X - 2P. Because of our bullish outlook for

General Dynamics, the strip strategy would not be our preferred strategy given that the strip capitalizes on a bearish outlook.

Annual Review AY 2003, Gordon H Dash Jr Page: 29 of 87 Relationships of Theta, Vega, Gamma, and Rho

Theta

Theta is the change in the option price in relation to a change in time. The value of the option decreases as time elapses and is know as time

value decay. The theta value is inversely related to the option price, which means that the rate of time decay is greater for in-the-money

options. Theta is most accurate only for a very small change in time, but the predicted price change is close to the actual price change. The

rate of time decay is important in the overall evaluation of an option, but since time itself is not a source of risk, it does not factor in on the

risk assessment of the option. The General Dynamics strap strategy put and call options 1, 2, and 3 for May 17, 2003 with exercise prices

$50, $55, and $60 respectively are shown below with the effect of time on Theta. The higher priced put and call strike prices have a more

sensitive Theta. The options have a lower Theta value three weeks before the maturity date, but as with all options, the price and Theta

value approaches zero on its maturity date.

Effect of Time on Theta

0

-20

GD

Call_1 Call_2 Call_3

Days To Maturity45 40 35 30 25 20 15 10 5 0

Thet

a V

alue -40

-60

-80

-100

GD0

-20

-40


Vega

The sensitivity of an option price to a small change in volatility is known as the Vega. The Vega value is largest when the General

Dynamics stock price is near the exercise price, showing that the option price is more sensitive to changes in the volatility. This occurred

around twenty-five days to maturity. When the stock price is high or low relative to the exercise price, the Vega is smallest, and the option

price is less sensitive to changes in the volatility. This occurs when the option approaches maturity. The option is sensitive to changes in

volatility regardless of the size change of volatility; this Vega risk can be hedged by using an offsetting position in another instrument based

on its Vega risk.

Effect of Time on VegaGD


Days To Maturity45 40 35 30 25 20 15 10 5 0

Vega

Val

ue

6

4

2

0

GD765432


Gamma

The risk that a stock price will change by a large amount in delta hedging is captured by the option’s gamma. The gamma is the change in

the delta for a small change in the stock price. The larger the gamma, the more sensitive is the delta to a stock price change and the harder it

is to maintain a delta neutral position. The gamma is always positive and is largest when the stock price is near the exercise price. General

Dynamic’s large gamma between forty and forty-five days to maturity makes it harder to delta hedge, because the delta is changing for

rapidly and is more sensitive to large stock price movements. The gamma changes as the option approaches expiration. The uncertainty of

whether the General Dynamics option will finish in-the-money or out-of-the-money is what keeps the gamma level high as expiration

approaches.

Effect of Time on GammaGD


Days To Maturity45 40 35 30 25 20 15 10 5 0

Gam

ma

Val

ue

0.015

0.01

0.005

0

GD

Gam

ma

Val

ue

0.015

0.01

0.005

0


Rho

Rho is the sensitivity of the option price to the risk free rate. The rho values for the General Dynamics call options involved in the strap

strategy follows a similar course as the vega values. When using the Black-Scholes model, the risk free rate must be expressed as a

continuously compounded rate. A simple or discrete risk free rate assumes only annual compounding. To convert to a continuously

compounded rate the natural logarithm of 1 must be added to the simple rate. In the chart below rho value as a function of days to maturity

is shown. The rho value move towards zero as the option approaches the maturity date. The General Dynamics call option is relatively

insensitive to a change in the risk free rate. The put option is inversely related to the risk free rate, as compared to the call option. The put

has a negative rho value, but similar to the call, moves toward zero as days to maturity approaches zero.

Effect of Time on RhoGD


Days To Maturity45 40 35 30 25 20 15 10 5 0

Rho

Val

ue

2

1

0

GD

45 40 35 30 25 20 15 10 5 0

Rho

Val

ue

0

-2

-4

-6

-8


Part IV. Equity Portfolio: Hedging Basics

Spread Strategies

Butterfly SpreadSPX


160

20

Option Expire Re-

maining


Trade

Min

Value

B-S

Price

Hedge Theta Gamma Vega Rho Implied

Volatility

SPX EJ-E 17-May-03 108 5 850.00 $37.000 17.270 18.6605 0.81859 -8.6042 0.0136 124.1152 204.5423 0.02427

SPX EO-E 17-May-03 108 -10 875.00 $24.000 0.000 3.7525 0.34827 -12.1083 0.0191 174.6610 88.2612 0.01780

SPX EP-E 17-May-03 108 5 880.00 $2.125 0.000 2.3606 0.26109 -10.6187 0.0168 153.1731 66.3006 0.00108

SPX QJ-E 17-May-03 108 0 850.00 $20.900 0.000 1.3905 0.18141 -8.6042 0.0136 124.1152 -46.9646 0.00232

SPX QO-E 17-May-03 108 0 875.00 $3.375 7.730 11.4825 0.65173 -12.1083 0.0191 174.6610 -170.6429 0.00045

SPX QP-E 17-May-03 108 0 880.00 $4.750 12.730 15.0906 0.73891 -10.6187 0.0168 153.1731 -194.0829 0.00208 93092091090086085083820

Pr

60

ofit

10080

140120

40

The butterfly spread on the S&P 500 Index options are a little different from the butterfly spread on an equity option as you can see

by the graph above. One good point to note first off, by looking at the graph is that the profit is always positive no matter where the

volatility of the index goes. The profit graph is always above the 0 line. A butterfly spread is a combination of a call bull and a call bear

spread, but involves 3 strike prices with the middle prices close to the current index spot price and halfway in between the other two prices.

In this case we are long one each of the high and low exercise prices ($850 and $880) and we are short 2 contracts of the middle exercise

price of $875. The long calls were priced at $37.00 and $2.125, while the short calls were priced at $24.00. There are four ranges of the

index price in relation to the exercise price and this in turn leads to 4 different profit or loss opportunities as seen in the graph above. When

the index prices falls to below $850 a loss situation will occur. The total loss is –C1 + 2C2 – C3. In this case the lowest profit, or the

minimum profit no matter how low the index price falls is (-37 +2(24) – 2.125) or $8.875. We multiply this by 5 because of the number of

contracts to come up with $44.38. In WinORS this is the minimum profit. When the index price rises to above $880, the profit is $144.375.

In another case, if the index price is between $850 and $880 the profit in this range goes from $8.875 to a high of $169.26. When this

occurs the profit increases with the higher the price of the index. The maximum profit occurs when there is very little volatility. This

maximum profit is $169.26 according to the WinORS software. In order to use this strategy and be profitable, we must assume and be

Annual Review AY 2003, Gordon H Dash Jr Page: 34 of 87 correct in our assumption that there will be little volatility in the price of the General Dynamic stock. Unlike an equity butterfly spread there

are not two breakeven stock prices that will incur 0 profit. In this analysis, the strategy was successful because the profit line was above the

0 profit point at all times no matter what happens to the stock price. With the market as it is today, we feel that using this option strategy to

hedge against the S&P 500 is a very good idea, because there will always be a profit incurred. The inverted butterfly is discussed next.

Annual Review AY 2003, Gordon H Dash Jr Page: 35 of 87 Inverted Butterfly

SPX


fi

-15

Option Expire Remaining Contracts Exercise Last

Trade

Min

Value


Volatility

SPX EJ-E 17-May-03 108 -1 850.00 $37.000 17.270 18.6605 0.81859 -8.6042 0.0136 124.1152 204.5423 0.02427

SPX EO-E 17-May-03 108 2 875.00 $24.000 0.000 3.7525 0.34827 -12.1083 0.0191 174.6610 88.2612 0.01780

SPX EP-E 17-May-03 108 -1 880.00 $2.125 0.000 2.3606 0.26109 -10.6187 0.0168 153.1731 66.3006 0.00108

SPX QJ-E 17-May-03 108 0 850.00 $20.900 0.000 1.3905 0.18141 -8.6042 0.0136 124.1152 -46.9646 0.00232

SPX QO-E 17-May-03 108 0 875.00 $3.375 7.730 11.4825 0.65173 -12.1083 0.0191 174.6610 -170.6429 0.00045

SPX QP-E 17-May-03 108 0 880.00 $4.750 12.730 15.0906 0.73891 -10.6187 0.0168 153.1731 -194.0829 0.00208 9209109008908808708582081

Pro

-25

t -20

-10

-30

-35

The inverted butterfly spread on the S&P 500 Index options are a little different from the inverted butterfly spread on an equity

option as you can see by the graph above. One very important point to note first off by looking at the graph is that the profit is always

negative no matter where the volatility of the index goes. The profit graph is always below the 0 profit mark and therefore if this strategy is

implemented, a loss will definitely be incurred. An inverted butterfly spread is the opposite of a butterfly spread. This spread is intended to

profit in a high volatility market. This strategy also involves 3 strike prices with the middle prices close to the current stock spot price and

halfway in between the other two prices. In this case we are short one each of the high and low exercise prices ($850 and $880) and we are

long 2 contracts of the middle exercise price of $875. The short calls were priced at $37 and $2.125, while the long calls were priced at $24.

In this case we decided to purchase 2 of the $875 call option contracts and sell short 1 each of the $850 and $880 call option contracts.

There are three ranges of the index price in relation to the exercise price and this in turn leads to 4 different loss opportunities as seen in the

graph above. When the stock prices falls to below $850 a loss situation will occur. The total profit is C1 - 2C2 + C3. In this case this loss,

or the minimum loss no matter how low the index price falls is (37 -2(24) + 2.125) or $-8.875. In another case, if the index price is between

$850 to $880, the loss in this range varies depending on how much the index price changes. The last situation is when the index price is

above $880. When this occurs the decreases with the higher the price of the index. The maximum loss occurs when there is very little

volatility. This maximum loss is $33.85, according to the WinORS software. As can be seen, it is impossible to use this strategy and be

profitable.

Annual Review AY 2003, Gordon H Dash Jr Page: 36 of 87 Straddle

SPX

I um P ri08584083081

20

0

Option Expire Remaining Contracts Exercise Last

Trade

Min

Value


Volatility

SPX EJ-E 17-May-03 108 1 850.00 $37.000 17.270 18.6605 0.81859 -8.6042 0.0136 124.1152 204.5423 0.02427

SPX EO-E 17-May-03 108 0 875.00 $24.000 0.000 3.7525 0.34827 -12.1083 0.0191 174.6610 88.2612 0.01780

SPX EP-E 17-May-03 108 0 880.00 $2.125 0.000 2.3606 0.26109 -10.6187 0.0168 153.1731 66.3006 0.00108

SPX QJ-E 17-May-03 108 1 850.00 $20.900 0.000 1.3905 0.18141 -8.6042 0.0136 124.1152 -46.9646 0.00232

SPX QO-E 17-May-03 108 0 875.00 $3.375 7.730 11.4825 0.65173 -12.1083 0.0191 174.6610 -170.6429 0.00045

SPX QP-E 17-May-03 108 0 880.00 $4.750 12.730 15.0906 0.73891 -10.6187 0.0168 153.1731 -194.0829 0.00208

ns tr ent ce929109008908808708600820 0

Pr

-40

ofit -20

-60

A straddle is the purchase of a call and a put that have the same exercise price and expiration date. Holding both a call and a put will

capitalize on the index price movement in either direction. The strategy involves 2 strike prices, which are below the current index spot

price. The profit potential of a straddle is unlimited because in theory the index price for the S&P 500 can rise infinitely. The straddle will

earn profits dollar for dollar with the index price increase in excess of the exercise price. Profit is limited on the down side to an actual loss

because the index price can go no lower than zero. The downside maximum loss can be calculated by setting the index price at expiration

equal to zero. S&P 500 maximum downside loss would be $15.32, with the call premium of $37 and put premium of $20.9. The worst-case

scenario for an S&P 500 straddle would be for the index price to end up equal to the exercise price, where neither the call or the put could be

exercised for a gain and the premiums of $37 for the call and $20.9 for the put would be lost. The straddle would be an appropriate strategy

as long as the index price is anticipated to increase above about $908 before the May 17, 2003 expiration date. With the current conflict in

Iraq and the uncertainty of other foreign threats to the United States, we believe this would not be a positive strategy to implement because

we do not expect the S&P’s price to increase so much with high volatility.


Ratio Spread SPX

A ratio spread is a risk-free transaction involving two options weighted according to their deltas. With a ratio spread, an investor can buy an

underpriced call and sell and overpriced or correctly priced call, creating a ratio of one call to the other that creates a riskless position. The

riskless position is created when the ratio of the quantity of the first call to the quantity of the second call is equal to the negative inverse

ratio of their deltas. (N1/N2 = -Delta2/Delta1) A ratio spread can only remain riskless if the ratio is continuously adjusted. For example,

we used the S&P 500 index option’s chains to determine the ratio spread of call #1 and call #2. Luckily, with the WinORS software, we do

not have to manually compute the ratio spread; it is automatically computed for us. For our purposes, call #1 is the May 850 call while call

#2 is the May 875 call. As of 4/15/03, the ratio spread for these two calls was –0.0143. What this means for the user of this information is

that in order to maintain a riskless position, (assuming call #1 is underpriced and call #2 is either overpriced or correctly priced) the investor

would have to buy 14.3 of the May 850 calls and sell 1,000 of the May 875 calls. As each day passes, the ratio spread will change because

of the change in the risk-free rate, the index price of S&P 500 and the time to expiration. In order to determine if a call or put is over or

under priced, you must compare the Last Trade column of the options pricing with the B-S Price (Black-Scholes pricing model for options).

If the B-S price is lower than the Last Trade price, then the call or put is overpriced. If the Last Trade price is lower than the B-S price, then

the call or put is underpriced according to the value of the Black-Scholes model. In the example below, the 1st call option is overpriced

because the B-S Price is lower than the Last Trade price. The second call is also overpriced, but the 3rd call is underpriced. The first put is

overpriced, while the second and third puts are underpriced.

Option Expire Exercise Last Trade B-S Price

SPX EJ-E 17-May-03 850.00 $37.000 18.6605

SPX EO-E 17-May-03 875.00 $24.000 3.7525

SPX EP-E 17-May-03 880.00 $2.125 2.3606

SPX QJ-E 17-May-03 850.00 $20.900 1.3905

SPX QO-E 17-May-03 875.00 $3.375 11.4825

SPX QP-E 17-May-03 880.00 $4.750 15.0906

Annual Review AY 2003, Gordon H Dash Jr Page: 38 of 87 Relationships of Theta, Vega, Gamma, and Rho

Theta

Theta is the change in the option price in relation to a change in time. The value of the option decreases as time elapses and is know as time

value decay. The theta value is inversely related to the option price, which means that the rate of time decay is greater for in-the-money

options. Theta is most accurate only for a very small change in time, but the predicted price change is close to the actual price change. The

rate of time decay is important in the overall evaluation of an option, but since time itself is not a source of risk, it does not factor in on the

risk assessment of the option. Two S&P calls and one put option were used in the strap hedging strategy. The lack of volatility in the S&P

and other index options makes it difficult to successfully use some of the hedging strategies. The lower priced call does not follow the same

trend as the other higher priced call options.

Effect of Time on ThetaSPX


Days To Maturity105 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0

Thet

a V

alue

0

-5

-10

-15

-20

-25

SPX0

-5

-10

15


Vega

The sensitivity of an option price to a small change in volatility is known as the Vega. The Vega value is largest when the S&P 500 price is

near the exercise price, showing that the option price is more sensitive to changes in the volatility. This occurred around twenty-five to

forty-five days to maturity. When the index option price is high or low relative to the exercise price, the Vega is smallest, and the option

price is less sensitive to changes in the volatility. This occurs when the option approaches maturity. The option is sensitive to changes in

volatility regardless of the size change of volatility; this Vega risk can be hedged by using an offsetting position in another instrument based

on its Vega risk.

Effect of Time on VegaSPX


Days To Maturity105 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0

Veg

a V

alue

180160

140120100

806040

200

SPX180

160

140

120

100

80

60

40


Gamma

The risk that a stock price will change by a large amount in delta hedging is captured by the option’s gamma. The gamma is the change in

the delta for a small change in the stock price. The larger the gamma, the more sensitive is the delta to a stock price change and the harder it

is to maintain a delta neutral position. The gamma is always positive and is largest when the index price is near the exercise price. The

S&P has a large gamma between twenty and forty days to maturity makes, which makes it harder to delta hedge, because the delta is

changing more rapidly and is more sensitive to large stock price movements. The gamma changes as the index option approaches

expiration. The uncertainty of whether the S&P option will finish in-the-money or out-of-the-money is what keeps the gamma level high as

expiration approaches.

Effect of Time on GammaSPX


Days To Maturity100 90 80 70 60 50 40 30 20 10 0

Gam

ma

Val

ue

0.035

0.030.025

0.02

0.015

0.01

0.005

0

SPX

0.0350.03

0.0250.02

0.0150.01

0.005


Rho

Rho is the sensitivity of the option price to the risk free rate. The rho values for the S&P 500 call options involved in the strap strategy

follows a similar course as the vega values. When using the Black-Scholes model, the risk free rate must be expressed as a continuously

compounded rate. A simple or discrete risk free rate assumes only annual compounding. To convert to a continuously compounded rate the

natural logarithm of 1 must be added to the simple rate. In the chart below rho value as a function of days to maturity is shown. The rho

value move towards zero as the option approaches the maturity date. The S&P call option is extremely sensitive to a change in the risk free

rate, as compared to the General Dynamics options, which are not sensitive to changes in the risk free rate. The put option is inversely

related to the risk free rate, as compared to the call option and it too is extremely sensitive to changes in the risk free rate. The put has a

negative rho value, but similar to the call, moves toward zero as days to maturity approaches zero.

Effect of Time on RhoSPX


Days To Maturity105 100 95 90 85 80 75 70 65 60 55 50 45 40 35 30 25 20 15 10 5 0

Rho

Val

ue

140

120

100

80

60

40

20

0

SPX0

-50

-100

-150


V. Portfolio Insurance

1st Example – Market Decline

We chose to hedge our portfolio with SPX put option contracts. We insured our portfolio against a 12% expected decline in the market over

the next 30 days with our decision date (to open the hedge) on March 28, 2003. The project hedge period is one month or 31 days. The

following verbiage shows our thinking and calculations of the SPX put options hedge assuming the markets have actually fallen by 12%:

1. Decision Date: March 28, 2003

Closing Date: April 28, 2003

2. We chose the SPX put contract with a strike price equal to the level of portfolio insurance we desire. As you will see in the

following calculations, we chose to use the May 825 puts. We assume the current value (on March 28th) of the SPX is $863.50.

3. We are assuming that we expect the market to show signs of bearish behavior over the next 31 days and because of this we

expect the SPX to drop 12% to a value of $759.88. This is actually a very low value for the S&P 500. The value of our portfolio

as of March 28, 2003 was $413,739.95. We also expect the value of our portfolio to drop by 12% to ($413,739.95 * (1 – 0.12)) =

$364,091.16.

4. We have also assumed that we have accumulated a gain in our equity portfolio up to our decision date. Because of this we would

like to insure the value of our portfolio against downside risk. The value of our portfolio as of March 28, 2003 was $413,739.95.

Since we are expecting a 12% decline in the market, we must realize it is not completely possible to be completely accurate and

reach 100% value protection. Because of this, we have decided to set an insurance floor for about a 5% decline in the market.

The value of the SPX if this were to occur would be $820.33. Because our beta for our portfolio is 1.27, it behaves very similarly


to the market index.

5. Based on these first few assumptions, we have decided to purchase the May 825 SPX puts (SPX QE-E) because they are closest

in value to the 5% decline price of $820.33 that we calculated in step 4. The amount of protection we are buying is (825 * 100) =

$82,500. With the use of this number we can calculate how many contracts we will need using the decision date value of our

portfolio of $413,739.95. With these we have ($413,739.95 / $82,500) = 5.01503 or rounded to 5 contracts.

6. Based on this, we assume that the market has fallen as predicted by 12% as measured on April 28, 2003 (This is just an

assumption for example purposes. The actual performance of our portfolio and related SPX index options is shown in the next

part of this section.) Because of this the SPX has dropped to $759.88 and our equity portfolio has dropped to $364,091.16. We

will profit as follows:

• Put options: The put options end up in the money by 65 basis points (decision price – new price) (825 – 759.88 = 65.12).

Because of this the profit on the put options is (65 * 100 * 5) = $32,500.

• Equity portfolio: If the portfolio value falls by 12% from $413,739.95 to $364,091.16, this calculates out to a dollar loss of

($49,648.79).

7. The hedge would partially offset the loss on the portfolio. The total net loss in this situation on this transaction is reduced to

$17,148.79 ($32,500- $49,648.79. This is a percentage loss of about 4.14%.

Annual Review AY 2003, Gordon H Dash Jr Page: 44 of 87 2nd Example – Market Incline

We chose to hedge our portfolio with SPX put option contracts. We insured our portfolio against a 12% expected decline in the market over

the next 30 days with our decision date (to open the hedge) on March 28, 2003. The project hedge period is one month or 31 days. The

following verbiage shows our thinking and calculations of the SPX put options hedge with the actual increase in the market over the past 31

days.

1. Decision Date: March 28, 2003

Closing Date: April 28, 2003

2. We chose the SPX put contract with a strike price equal to the level of portfolio insurance we desire. As you will see in the

following calculations, we chose to use the May 825 puts. We assume the current value (on March 28th) of the SPX is $863.50.

3. We are assuming that we expect the market to show signs of bearish behavior over the next 31 days and because of this we expect

the SPX to drop 12% to a value of $759.88. This is actually a very low value for the S&P 500. The value of our portfolio as of

March 28, 2003 was $413,739.95. We also expect the value of our portfolio to drop by 12% to ($413,739.95 * (1 – 0.12)) =

$364,091.16.

4. We have also assumed that we have accumulated a gain in our equity portfolio up to our decision date. Because of this we would

like to insure the value of our portfolio against downside risk. The value of our portfolio as of March 28, 2003 was $413,739.95.

Since we are expecting a 12% decline in the market, we must realize it is not completely possible to be completely accurate and

reach 100% value protection. Because of this, we have decided to set an insurance floor for about a 5% decline in the market. The

value of the SPX if this were to occur would be $820.33. Because our beta for our portfolio is 1.27, it behaves very similarly to the

market index.


5. Based on these first few assumptions, we have decided to purchase the May 825 SPX puts (SPX QE-E) because they are closest in

value to the 5% decline price of $820.33 that we calculated in step 4. The amount of protection we are buying is (825 * 100) =

$82,500. With the use of this number we can calculate how many contracts we will need using the decision date value of our

portfolio of $413,739.95. With these we have ($413,739.95 / $82,500) = 5.01503 or rounded to 5 contracts.

6. Based on this, we checked the value of our equity portfolio and the value of the SPX index as of April 28, 2003. Contrary to our

bearish feeling prior to this date, our portfolio and the SPX index have both increased. SPX has increased 5.95% to $914.84 and our

equity portfolio has increased 2.66% to $424,735.00. Because of our beta, our percentage change was very similar to that of the

SPX. Because this has happened, the contracts will expire out of the money and our profit will be less than that of what it could have

been had we decided not to hedge. When we made the decision to hedge, though, we reduced our upside as well as downside

potential. We will profit as follows:

• Put options: The put options end up out of the money by 90 basis points (decision price – new price) (825 – 914.84 = 89.84).

Because of this the loss on the put options is the money paid up front for the premium. The premium at the decision date per

option was $1.50. (100 * 5 * 1.50 = $750)

• Equity portfolio: When the portfolio value increased by 2.66% from $413,739.95 to $424,735.00, this calculates out to a

dollar profit of $10,995.05.

7. The hedge would partially offset the gain on the portfolio. The total net gain in this situation on this transaction is reduced to

$10,245.05 ($10,995.05 - $750)


VI. Futures Based Project

Scenario #1

Stock index futures hedges are used to hedge the risk that could occur with an equity portfolio. On March 28, 2003, we are concerned, as

our own portfolio managers, about the market over the next month. The portfolio has accumulated a profit and we wish to protect it over the

period ending April 28, 2003. The information below is analysis using the stock portfolio futures hedge assuming prices have increased in

both the futures market and in our equity portfolio. We chose to use the June SPX futures because they were the closest to the closing date

of the hedge.

March 28, 2003 Portfolio Market Value: 413,739.95

Portfolio Beta: 1.27

S&P 500 June futures contract

Price on March 28: 863.50

Multiplier: 250

Price of one contract: 250(863.50) = $215,875

Optimal number of futures contracts

Nf = -1.27( 413,739.59/ 215,875)

Nf = -2.43

Nf ≈ -2 Sell 2 contracts

Annual Review AY 2003, Gordon H Dash Jr Page: 47 of 87 April 28, 2003 Portfolio Market Value: 424,735.00



Price on April 28: 909.70

Multiplier: 250

Price of one contract: 250(909.70) = $227,425


Nf = -1.27(424,735/ 227,425)

Nf = -2.37

Nf ≈ -2 Buy 2 Contracts

Annual Review AY 2003, Gordon H Dash Jr Page: 48 of 87 Analysis

Market Value of Portfolio March 28: 413,739.95

Market Value of Portfolio April 28: 424,735.00

Profit from Portfolio: 10,995.05 (2.66% increase)

The futures loss was:

Sell 2 contracts x 215,875 per contract = 431,750 (Sale price of futures)

Purchase 2 contracts x 227,425 per contract = (454,850) (Purchase price of futures)

Loss from Futures: -23,100.00 (5.51% decrease)

Total loss: -12,104.95 (2.85% decrease)

The profit from the stocks was negated with the higher loss from the futures. The overall loss was 12,104.95 or a 2.85% decline.

Annual Review AY 2003, Gordon H Dash Jr Page: 49 of 87 Scenario #2

On March 28, 2003, we are concerned, as our own portfolio managers, about the market over the next month. The portfolio has

accumulated a profit and we wish to protect it over the period ending April 28, 2003. The information below is analysis using the stock

portfolio futures hedge assuming prices have decreased in both the futures market and in our equity portfolio. We chose to use the June

SPX futures because they were the closest to the closing date of the hedge. In hindsight, if the market value of the portfolio would have

declined by 12% instead of the actual market increase of 2.66% the following would be true:

March 28, 2003 Portfolio Market Value: 413,739.95



Price on March 28: 863.50

Multiplier: 250

Price of one contract: 250(863.50) = 215,875


Nf = -1.27( 413,739.59/ 215,875)

Nf = -2.43

Nf ≈ -2 Sell 2 contracts

April 28, 2003 Portfolio Market Value: 364,019.16

Annual Review AY 2003, Gordon H Dash Jr Page: 50 of 87 Portfolio Beta: 1.27


Price on April 28: 759.88

Multiplier: 250

Price of one contract: 250(759.88) = 189,970


Nf = -1.27(364,019.16/ 189,970)

Nf = -2.43

Nf ≈ -2 Buy 2 Contracts

Annual Review AY 2003, Gordon H Dash Jr Page: 51 of 87 Analysis

Market Value of Portfolio March 28: 413,739.95

Market Value of Portfolio April 28: 364,019.16

Loss from Portfolio: -49,720.79 (12% decrease)

The futures loss was:

2 contracts x 215,875 per contract = 431,750 (Sale price of futures)

2 contracts x 189,970 per contract = 379,940 (Purchase price of futures)

Profit from Futures: 51,810.00 (12.5% increase)

Total profit 2,089.21 (0.5% increase)

The loss on the stocks was effectively offset by the profit from the futures. The Total Profit was 2,089.21 or a .5% increase.

Results

In comparing our options hedging and futures hedging to offset risk for our equity portfolio, we noticed many differences. For

example, with the options hedge, the value of our portfolio increased about 2.66%, however the hedge was in anticipation of a 12% decline.

Because our forecast was wrong, the only loss incurred in the options hedge was the cost of the option premiums, which turned out to be

Annual Review AY 2003, Gordon H Dash Jr Page: 52 of 87 only $750. This cost offset our gain of over $10,000 on our equity portfolio. If the markets had declined as forecasted, the profit from the

options would have offset the loss on our equity portfolio. This is why it is called portfolio insurance. The insurance minimizes the

downside risk; while at the same time limits the total profit that could be earned on the equity portfolio.

In the futures hedging example, the actual market value of the equity portfolio increased as well as the S&P500 index. This occurred

because the two are highly correlated as shown by our portfolio beta of 1.27. Because of this increase in the market, we had a gain on our

equity portfolio of about $10,000. This gain was completely offset by the loss incurred on the futures contracts that we engaged in. The

loss on the futures contract was over $23,000, which made the total loss in this situation of over $12,000 or about a 2.85% decline in our

overall portfolio. If the markets had declined by 12% as anticipated, we would have incurred a loss on our equity portfolio of about

$50,000. In this situation, we would have also incurred a gain on our futures of about $51,000 resulting in a total profit of over $2,000 or

0.5% increase in our portfolio. If our predictions had been correct, the hedge would have been considered successful, because the futures

completely offset our loss from our portfolio. We would have incurred a loss if we had not entered into futures contracts. However, as seen

above, if we were not correct in our predictions, we would have incurred a loss.

Basically, we feel that the portfolio insurance using options is the better hedging strategy based on our analysis. The options are

easier to implement because they are less capital intensive than the futures because the premium on options is so little. With futures, money

must always be kept in the margin account in order to account for the marking to market of the futures contracts. Because of this, there is a

liquidity issue with futures contracts. Also, with futures, you have the obligation to settle the contract at the settlement date. With options,

there is a right, not an obligation to exercise. In this case, it is less risky to enter the options market to hedge our equity portfolio. It is

possible to offset both futures and options contracts if need be. This is one similarity between the two hedging strategies. Futures contracts

can be offset by entering into the opposite position. Options contracts can be offset by also taking the opposite position, whether it be

writing a call/put contract or buying a call/put contract. In conclusion, we feel that for our portfolio, the options hedge was more successful

and therefore has the better advantages.


APPENDIX C - SAMPLE STUDENT PROJECTS

FIN 430x, MANAGEMENT AND VALUATION OF GLOBAL CURRENCIES (NOTE: formatting may be lost due to Microsoft Word import procedures)


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Actual Transactions

Interest Added

Other - Modifications

Oanda Date/Time Type Pair Units Price Amount Balance

1 Mon Jun 23

22:26:36 2003 Funds Added USD 0 100000 100000

2 Tue Jun 24

16:00:00 2003 Interest USD 0 2.2046 100002.2

3 Wed Jun 25

16:00:00 2003 Interest USD 0 2.4501 100004.65

4 Thu Jun 26

16:00:00 2003 Interest USD 0 2.3974 100007.05

5 Fri Jun 27 16:00:00

2003 Interest USD 0 2.3975 100009.45

6 Sat Jun 28 16:00:00

2003 Interest USD 0 2.3974 100011.85

7 Sun Jun 29

16:00:00 2003 Interest USD 0 2.3975 100014.24

8 Mon Jun 30

16:00:00 2003 Interest USD 0 2.3976 100016.64

9 Mon Jun 30

20:27:35 2003 Buy Market EUR/USD 1000 1.1529 1152.9 100016.64

10 Mon Jun 30 20:30:15 Modify Order EUR/USD 1000 1.1529 0 100016.64


2003

11 Mon Jun 30

20:30:31 2003 Modify Order EUR/USD 1000 1.1529 0 100016.64

12 Mon Jun 30


13 Mon Jun 30


14 Mon Jun 30

20:46:59 2003 Stop Loss EUR/USD 1000 1.1523 1152.5 100016.04

15 Mon Jun 30

20:53:25 2003 Buy Market EUR/USD 1000 1.1532 1153.2 100016.04

16 Mon Jun 30


17 Mon Jun 30


18 Mon Jun 30

21:00:23 2003 Stop Loss EUR/USD 1000 1.1524 1152.6 100015.24

19 Tue Jul 1 16:00:00

2003 Interest USD 0 2.3976 100017.64

20 Tue Jul 1 16:05:21

2003 Sell Market USD/JPY 1000 119.43 999.75 100015.24

21 Tue Jul 1 16:18:04

2003 Buy Market USD/JPY 1000 119.47 999.75 100017.3

22 Tue Jul 1 16:18:32


23 Tue Jul 1 18:54:27

2003 Stop Loss USD/JPY 1000 119.28 1000.25 100015.71

24 Wed Jul 2 16:00:00

2003 Interest USD 0 2.3977 100018.11

25 Wed Jul 2 20:08:02 Sell Market EUR/USD 1000 1.1524 1152.4 100018.11


2003

26 Wed Jul 2 20:14:06


27 Wed Jul 2 20:15:02

2003 Buy Market EUR/JPY 1000 136.28 1152.86 100018.11

28 Wed Jul 2 20:16:35

2003 Buy Market CHF/JPY 1000 87.81 742.83 100018.11

29 Wed Jul 2 20:25:39

2003 Buy Market GBP/USD 1000 1.6656 1665.6 100018.11

30 Wed Jul 2 20:26:43

2003 Modify Order GBP/USD 1000 1.6656 0 100018.11

31 Wed Jul 2 20:27:49

2003 Sell Market EUR/GBP 2000 0.6918 2303.83 100018.11

32 Wed Jul 2 20:30:50

2003 Modify Order CHF/JPY 1000 87.81 0 100018.11

33 Wed Jul 2 20:33:35

2003 Sell Market EUR/JPY 1000 136.24 1152.86 100017.77

34 Wed Jul 2 20:33:35

2003 Sell Market EUR/JPY 1000 136.24 1152.23 100017.77

35 Wed Jul 2 20:35:22

2003 Buy Market CHF/JPY 2000 87.89 1486.64 100017.77

36 Wed Jul 2 20:42:00

2003 Sell Market EUR/PLN 1000 4.4373 1150.3 100017.77

37 Wed Jul 2 20:43:20

2003 Buy Market EUR/PLN 1000 4.4446 1150.31 100015.88

38 Wed Jul 2 20:50:31


39 Wed Jul 2 20:51:07

2003 Modify Order EUR/USD 1000 1.1524 0 100015.88

40 Wed Jul 2 20:52:54 Sell Order EUR/USD 1000 1.1521 0 100015.88


2003

41 Wed Jul 2 20:53:04

2003 Stop Loss GBP/USD 1000 1.664 1664.5 100014.28

42 Wed Jul 2 20:54:34

2003 Sell Order Fulfilled EUR/USD 1000 1.1524 1152.4 100014.28

43 Thu Jul 3 00:01:26

2003 Stop Loss EUR/JPY 1000 136.42 1151.66 100012.75

44 Thu Jul 3 00:04:00

2003 Take Profit USD/JPY 1000 118.41 1000.25 100014.27

45 Thu Jul 3 01:42:24

2003 Take Profit CHF/JPY 1000 88 742.47 100015.87

46 Thu Jul 3 02:14:23

2003 Stop Loss EUR/GBP 2000 0.6928 2303.67 100012.56

47 Thu Jul 3 03:32:48

2003 Take Profit EUR/USD 1000 1.1508 1150.6 100014.15

48 Thu Jul 3 03:33:46

2003 Take Profit EUR/USD 1000 1.1504 1150.2 100016.14

49 Thu Jul 3 16:00:00

2003 Interest USD 0 2.3977 100018.53

50 Thu Jul 3 16:00:00

2003 Interest CHF/JPY 87.71 -0.0026 100018.53

51 Fri Jul 4 16:00:00

2003 Interest USD 0 2.3977 100020.93

52 Fri Jul 4 16:00:00

2003 Interest CHF/JPY 87.7 -0.0033 100020.93

53 Sat Jul 5 16:00:00

2003 Interest USD 0 2.3978 100023.32

54 Sat Jul 5 16:00:00

2003 Interest CHF/JPY 87.63 -0.0033 100023.32

55 Sun Jul 6 16:00:00 Interest USD 0 2.3978 100025.72


2003

56 Sun Jul 6 16:00:00

2003 Interest CHF/JPY 87.63 -0.0033 100025.71

57 Mon Jul 7 16:00:00

2003 Interest USD 0 2.3979 100028.11

58 Mon Jul 7 16:00:00

2003 Interest CHF/JPY 86.14 -0.0032 100028.11

59 Mon Jul 7 18:53:22

2003 Sell Market GBP/USD 1000 1.6489 1648.9 100028.11

60 Mon Jul 7 18:54:16


61 Mon Jul 7 19:11:23


62 Mon Jul 7 19:12:43

2003 Modify Order CHF/JPY 2000 87.89 0 100028.11

63 Mon Jul 7 19:22:38

2003 Sell Market AUD/USD 1000 0.6783 678.3 100028.11

64 Mon Jul 7 19:23:21

2003 Modify Order AUD/USD 1000 0.6783 0 100028.11

65 Mon Jul 7 19:28:49

2003 Stop Loss AUD/USD 1000 0.679 678.7 100027.41

66 Mon Jul 7 19:32:03

2003 Buy Market EUR/USD 1000 1.1327 1132.7 100027.41

67 Mon Jul 7 19:40:30

2003 Sell Market USD/JPY 1000 118.18 1000.25 100027.41

68 Mon Jul 7 19:41:20

2003 Buy Market GBP/JPY 1000 195.01 1650.11 100027.41

69 Mon Jul 7 19:41:48

2003 Modify Order GBP/JPY 1000 195.01 0 100027.41

70 Mon Jul 7 19:55:02 Sell Market EUR/USD 1000 1.1327 1132.9 100027.41


2003

71 Mon Jul 7 19:59:10

2003 Sell Market EUR/USD 1000 1.1326 1132.6 100027.41

72 Mon Jul 7 20:06:48

2003 Buy Market USD/MXN 5000 10.5715 5014.23 100027.41

73 Mon Jul 7 20:31:43

2003 Stop Loss GBP/JPY 1000 194.7 1648.9 100024.79

74 Tue Jul 8 01:20:24

2003 Stop Loss CHF/JPY 2000 85.91 1457.2 99991.23

75 Tue Jul 8 02:24:43

2003 Stop Loss EUR/USD 1000 1.1343 1134.1 99989.51

76 Tue Jul 8 02:40:08

2003 Take Profit GBP/USD 1000 1.6468 1646.4 99991.57

77 Tue Jul 8 16:00:00

2003 Interest USD 0 2.3975 99993.97

78 Tue Jul 8 16:00:00

2003 Interest USD/MXN 10.5083 -0.5609 99993.41

79 Wed Jul 9 16:00:00

2003 Interest USD 0 2.3971 99995.81

80 Wed Jul 9 16:00:00

2003 Interest USD/MXN 10.519 -0.6769 99995.13

81 Thu Jul 10 16:00:00

2003 Interest USD 0 2.3972 99997.53

82 Thu Jul 10 16:00:00

2003 Interest USD/MXN 10.452 -0.6769 99996.85

83 Fri Jul 11 16:00:00

2003 Interest USD 0 2.3971 99999.25

84 Fri Jul 11 16:00:00

2003 Interest USD/MXN 10.413 -0.6777 99998.57

85 Sat Jul 12 16:00:00 Interest USD 0 2.3972 100000.97


2003

86 Sat Jul 12 16:00:00

2003 Interest USD/MXN 10.4155 -0.6777 100000.29

87 Sun Jul 13 16:00:00

2003 Interest USD 0 2.3972 100002.69

88 Sun Jul 13 16:00:00

2003 Interest USD/MXN 10.4155 -0.6777 100002.01

89 Mon Jul 14

16:00:00 2003 Interest USD 0 2.3973 100004.4

90 Mon Jul 14

16:00:00 2003 Interest USD/MXN 10.4238 -0.6769 100003.73

91 Mon Jul 14

22:30:09 2003 Sell Market USD/JPY 1000 117.74 999.75 100003.73

92 Mon Jul 14

22:30:21 2003 Modify Order USD/JPY 1000 117.74 0 100003.73

93 Mon Jul 14

22:32:56 2003 Sell Market EUR/USD 1000 1.1261 1126.1 100003.73

94 Mon Jul 14

22:52:09 2003 Sell Market USD/MXN 5000 10.3838 5014.45 99913.15

95 Mon Jul 14


96 Tue Jul 15 01:32:14

2003 Stop Loss EUR/USD 1000 1.127 1126.8 99912.25

97 Tue Jul 15 05:00:56

2003 Take Profit USD/JPY 1000 117.56 999.74 99913.77

98 Tue Jul 15 08:53:04

2003 Sell Market GBP/USD 2000 1.6083 3216.6 99913.77

99 Tue Jul 15 16:00:00

2003 Interest USD 0 2.3957 99916.16

100 Tue Jul 15 16:00:00 Interest GBP/USD 1.592 -0.0666 99916.1


2003

101 Wed Jul 16

10:39:07 2003 Buy Market GBP/USD 2000 1.5945 3188.2 99943.52

102 Wed Jul 16

10:39:07 2003 Buy Market GBP/USD 2000 1.5945 3189 99943.52

103 Wed Jul 16

10:39:53 2003 Sell Market GBP/USD 2000 1.5938 3188.4 99942.12

104 Wed Jul 16

10:39:53 2003 Sell Market GBP/USD 2000 1.5938 3187.6 99942.12

105 Wed Jul 16

10:40:18 2003 Sell Market GBP/USD 4000 1.5935 6374 99942.12

106 Wed Jul 16


107 Wed Jul 16


108 Wed Jul 16

10:41:24 2003 Sell Market USD/JPY 2000 118.21 1999.49 99937.32

109 Wed Jul 16

16:00:00 2003 Interest USD 0 2.3954 99939.72

110 Wed Jul 16

16:00:00 2003 Interest USD/JPY 118.17 -0.0164 99939.7

111 Thu Jul 17 16:00:00

2003 Interest USD 0 2.3958 99942.1

112 Thu Jul 17 16:00:00

2003 Interest USD/JPY 118.77 -0.0745 99942.02

113 Fri Jul 18 16:00:00

2003 Interest USD 0 2.3959 99944.42

114 Fri Jul 18 16:00:00

2003 Interest USD/JPY 118.31 -0.0745 99944.34

115 Sat Jul 19 16:00:00 Interest USD 0 2.396 99946.74


2003

116 Sat Jul 19 16:00:00

2003 Interest USD/JPY 118.48 -0.0745 99946.67

117 Sun Jul 20 16:00:00

2003 Interest USD 0 2.396 99949.06

118 Sun Jul 20 16:00:00

2003 Interest USD/JPY 118.5 -0.0745 99948.99

TThhee ffoolllloowwiinngg iiss aa ddeessccrriippttiioonn ooff tthhee

ttrraannssaaccttiioonnss

LLiisstteedd aabboovvee…………

#1 - #8

On Monday, June 23 my Oanda account was opened. The beginning balance was $100,000. The account

collected interest until its first use on Monday, June 30. The interest collected totaled $16.64.

#9

This transaction involved the currency pair of EUR/USD. Since this was my first trade, I decided to buy the

currency that I was most familiar with and experiment a little. The rate is very volatile, but since it was my

first trade, I hadn’t paid much attention to the fact that the currency had been continuously dropping at that

point and tried to make some money on an intraday trade.

#10 - # 14

These transactions consisted of modifying the trade of EUR/USD that I had made. I was getting familiar

Annual Review AY 2003, Gordon H Dash Jr Page: 64 of 87 with using the stop loss and take profit options, which was a good move, because as it was I lost $0.60 by

buying that pair! Good thing it was a conservative trade!

#15 - #18

Unfortunately, I did not learn from the first loss that I took and proceeded to by 1000 more units of the same

pair (EUR/USD). Within seconds the same thing happened again and I took another loss of $0.80. Those

two trades did not have any theory basis to them; they were just basic experimentation of the game.

#19

This was an interest collection.

#20 - #23

The first trade in this collection was for the Yen. I had originally meant to buy the currency, so transaction

#20 was a mistake, # 21 was made to correct the mistake made before it, and #22 was the transaction that I

had originally tried to make. This trade had been made by looking at the volatility of the exchange rate.

There is constant movement in the Yen and if you can catch the right moment, you can make a nice profit.

Unfortunately, by the time I figured out exactly what I wanted to do, the rate turned around and went the

other way, so I was stopped out, once again.

#24

This was an interest collection.

#25

This was an intraday trade that I made based on the volatility of the EUR/USD. The Euro had peaked in the

middle of June, so it was foreseen that it would continue to go down. Also with the Fourth of July being so

close (the date was July 2nd) it was forecasted that the rate would continue to depreciate.


#26

As I have stated before, the Yen is a very volatile rate. I purchased this option because the rate had reached a

low and was beginning to appreciate again. Being an intra day trade, I had intentions of watching the rate

grow and then selling it when it had peaked for the day.

#27 - #28

Since the Yen is so volatile, I decided to diversify the portfolio I had began to develop and buy some more

pairs, including the EUR/JPY and the CHF/JPY. These were also intraday trades, so I watched them closely

hoping to make some money from the consistent changing in the price. The Japanese government has shown

that they are striving for volatility in their exchange rates so that can continue making money by driving their

exchange rates up and down. So, I decided that this would be a good currency to try to make some money

with.

#29 - #32

While looking at the different rates, I decided that another good rate would be the Pound. So, I purchased

the pairs of GBP/USD (buy) and EUR/GBP (sell). The pound/dollar pair had been rising for a few days and

since this also was an intraday trade, I decided that it would be a definite profit. The euro/pound pair has

seemed to peak for the day, so I forecasted that it was going to drop. The rate had a lot of change in it, and it

did continue to drop but at a very inconsistent trend. The other two transactions in the section are

modifications made to earlier trades (stop losses and take profits).

#33 - #34

These two transactions are related to an earlier one. I had purchased EUR/JPY with the idea that the rate was

going to rise, instead the opposite happened and the rate changed direction. So, I sold the original pair that I

had purchased and then sold 1000 more, to keep the option open and make some money on the drop.

#35

Annual Review AY 2003, Gordon H Dash Jr Page: 66 of 87 This trade consists of CHF/JPY. I had originally purchased this pair for $87.81, but then as it began to rise

to $87.89, I decided to buy 2000 more. If the rate was continuing to rise, it was better to have more of the

pair and then that way there was more chance of profit. Since the trade was also intraday, I would be

watching the volatility and could sell the pair if the rate peaked and dropped.

#36 - #39

This section consists of a mistake and a modification. The mistake was in the purchase of EUR/PLN. I had

thought that the rate was going to drop but instead it immediately went up. I sold the pair right away and

took the loss of a little over a dollar.

#40 & #42

In both of these transactions, I purchased another 2000 of EUR/USD with the hopes of again making some

money on the depreciating exchange rate. I had made a similar transaction earlier and realized that I should

be a little more courageous a risk some more money, so I decided to go with 3000 units.

#41

In this transaction I realized that I had made the wrong forecast with the guess that the pound would

appreciate against the dollar. I was stopped out because the price had changed so much.

#43 - #45

This transaction was with the Yen, which is very volatile and changed direction in the middle of the night.

Fortunately, I had three open trades going in this currency and only lost money on one of them. I was

stopped out on the euro/yen pair, but took a profit on the USD/JPY and CHF/JPY pairs. Yea! Finally a

correct forecast!

#46 - #48

These transactions all involve the Euro dollar. Unfortunately the pound appreciated during the night and was

Annual Review AY 2003, Gordon H Dash Jr Page: 67 of 87 stopped out, giving me a small loss, but in accordance with my prediction, the EUR/USD pair depreciated

and I took a profit on all of the units that I had purchased. ☺

#49 - #58

These transactions are all involving interest paid and received.

#59 - #60

In this transaction, I decided to give the pound another chance to depreciate. Looking at the history of this

currency you can tell that it peaked and then turned and went down. Selling the currency was a good idea

because it was obvious that the rate had to change direction and bottom out. The second transaction is just

the modification of the prior, making sure that it had a proper stop loss.

#61

In this transaction, I went back to the Yen. This currency attracts me because of its constant volatility. It is

fun to predict which way the rate will go. This particular time, I predicted that the rate was going to

appreciate because it had dipped low and looked like it would make a turn around.

#62 & #64

Both of these transactions are modifications of different trades (stop losses and take profits).

#63 & #65

In these two transactions, I decided to diversify my portfolio a little and dabble in the Australian dollars.

Unfortunately, I set my stop loss to close because although the price did drop (my prediction was correct), it

did so with a small amount of fluctuation first. So I was stopped out before I could make a profit.

#66

Annual Review AY 2003, Gordon H Dash Jr Page: 68 of 87 Since the fourth of July had come and gone, I figured it was time for the EUR/USD rate to begin rising

again. The rate had bottomed out and past histories showed that it would not keep dropping, that it would

rise again slowly. So, in this transaction I bought another 1000 units of this pair with the prediction that it

would rise again.

#67 - #69

Like iron to a magnet, I am drawn back to the volatility of the Yen. I am amazed at the fluctuation in the

price, so I make two more transactions, I sell USD/JPY and I buy GBP/JPY. Both of these were going in the

directions that I predicted, so I waited for them to go in the appropriate way. (Transaction #69 was setting

the stop loss for the pound transaction.)

#70 - #71

In these transactions, I had been watching a sale of the EUR/USD pair that I had made earlier drop and rise

back to the price that I had bought it for. Watching it make this move, I forecasted that the price was going

to drop even lower. So, when the price rose back to what I had bought it for, I sold the pair that I had and

then sold 1000 more, based on the fact that it would keep dropping like it had been.

#72

The purchase of the USD/MXN pair was a mistake that I made in forecasting. I should have sold the pair,

but instead, I looked at old rates and thought that the rate would keep rising. Instead of appreciating the way

I predicted, the rate dropped considerably and I took a loss on the pair.

#73 - #75

The following transactions are stop losses that incurred because of wrong forecasting on my part. The loss

with the CHF/JPY was the only that was a bigger loss that than the others of around $25.

#76


This transaction was a take profit from the GBP/USD. If I had set the boundary lower there would have been

continued profit because the rate continued to depreciate lower.

#77 - #90


#91 - #92

In these two transactions I have sold more Yen and modified them. The USD/JPY had peaked and began to

drop again, so I caught it when it was on its way down again. The rate is constantly going up and down, so it

is important to set the stop losses and take profits at spots where they will prevent too much loss and enough

profit without being to timid.

#93, #95, & #96

These transactions all involve the EUR/USD currency pair. I thought that I could sell the pair and make a

quick profit based on the volatility that had been happening in the past few hours. Unfortunately the rate

went up and the transaction was stopped out.

#94


#97

This transaction involves the pair that has been rising and falling daily. The transaction is a profit that was

made because the USD/JPY continued to fall.

#98, #101 - #107


These transactions are all involving the currency pair, GBP/USD. They are all buys and sells, evening each

other out. The pair continued to drop over time, but it was very volatile during the day so it was challenging

to see if a profit could be made on the rise and fall. Unfortunately that was not the case, so I sold all of the

units before a real loss could incur.

#99 - #100


#108

The final transaction involves the ever changing Yen and US dollar. I have sold more units with the hope of

making one last profit. The position has been open for a few days and I have watched it rise and fall, not

very far in either direction. I have the prediction that it will fall but with this currency it could go either way.

#109 - #118


TThheessee aarree tthhee rreessuullttss ooff tthhee $$2200,,000000

tthhaatt wwaass iinnvveesstteedd uussiinngg RReeffccoo…………

C L O S E D T R A D E L I S T

Ticket Placed Closed Type Payout Currency Barrier Up/Down Expiration Premium PnL


1349

7/14/2003

22:34

7/16/2003

5:00

One

Touch 100 EUR/USD 1.1288 Up

7/16/2003

5:00 86.24 100

1350

7/14/2003

22:37

7/16/2003

5:00

No

Touch 100 USD/JPY 118.82 Up

7/16/2003

5:00 100 100

1351

7/14/2003

22:39

7/16/2003

5:00 Digital 100 EUR/USD 1.14 Down

7/16/2003

5:00 100 100

1352

7/14/2003

22:45

7/16/2003

5:00 Digital 100 GBP/USD 1.605 Down

7/16/2003

5:00 39.82 100

Total 326.06 400

A C C O U N T A C T I V I T Y

Time Posted Code Description Ticket Amount Balance07/14/2003,

22:34 Option

Options

Premium 1349 -86.24 19,913.76

07/14/2003,

22:37 Option

Options

Premium 1350 -100 19,813.76

07/14/2003,

22:39 Option

Options

Premium 1351 -100 19,713.76

07/14/2003,

22:45 Option

Options

Premium 1352 -39.82 19,673.94

07/16/2003,

05:00 Option Options Payout 1349 100 19,773.94

07/16/2003,


07/16/2003,


07/16/2003,


Total 73.94

Using this program, I made four trades, one no-touch, one one-touch, and one digital. The way I chose the currency

pairs that I was going to use was by studying the way that they fluctuated on the Oanda charts. This allowed me to

make decisions about the rising and falling of the exchange rates. I forecasted the way that they would move, and I

was correct for all four transactions. The total profit made was $73.94.


TThhee FFiinnaall rreessuullttss……

Beginning Balance Oanda $100,000.00

Loss Oanda $ 51.01

Total Oanda $ 99,948.99

Beginning Balance Refco $ 20,000.00

Profit Refco $ 73.94

Total Refco $ 20,073.94

Ending Balance Overall…….. $120,022.93!

The overall strategy that I followed was to find a volatile exchange rate and forecast whether or not it was

going to rise or fall. I was very conservative with the amounts that I would risk, so I never really had any

drastic gains or losses. This game taught me how to read what an exchange rate is going to do and it helped

me to develop my skills of forecasting and prediction. It also showed me that it is necessary to take chances

in order to gain a bigger profit, the old risk/return theory. If I had been more open to taking chances and

risking my money, I think that I could have made a bigger profit, hopefully not a loss, but I think that I

would still learn the same lessons from the game. This game has perked my interest in seeing how much

money I could make trading real money in the foreign exchange market. When I have more time over the

summer, I plan on using what I have learned, to be a bigger risk-taker, and maybe earn some real cash.

Overall, this was a really good experience and it was an excellent example of what real-life trading is like.


APPENDIX D - SAMPLE STUDENT PROJECTS

MBA 570, MANAGERIAL ECONOMICS (MBA, PMBA, and EMBA) (NOTE: formatting may be lost due to Microsoft Word import procedures)


The Determinants of

Winning in

Major League Baseball

Alan Pape

Carl Blahnik Erick Nordan Robert Byron

MBA 570

Managerial Economics Dr. Gordan H. Dash, Jr.

Summer Session 1, 2003


I. Abstract

Baseball has been touted as being America’s game of choice along with football. However, the reason that a

determinants model was chosen for the project is because it is the Twenty-fifth Anniversary of the Cobb-

Douglas Production Function. Thousands of statistics are collected every year for every baseball team, but

in the end only one can team can be the winner of the World Series.

Our team decided to conduct this study because baseball is such a popular sport. That and we all had dreams

of one day becoming a professional baseball player and riding the same pine as some of the game’s greats.

Also our team wanted to test to see if the information contained in the Cobb-Douglas Production Function

was still valid. We can not say at this point what factors fell out when our regression was complete,

otherwise it would ruin the final product.

Baseball has a long line of history within the United States, and also Canada, considering the one Canadian

team. The game has inspired children and adults alike, along with a number of movies. The game also

inspired our group to find out exactly what it took to have a winning season.

II. Introductory Section

Another summer is under way and once again a heated Boston Red Sox-New York Yankees rivalry rules the

sports page. The Red Sox are beloved by all New Englanders, but they have not won a World Series since

1918 and thus we set about to construct an empirical model to determine why baseball teams win.

CE Zech previously published a study based on the 1977 season. Due to his previous work we thought a 25th

anniversary model would be appropriate to analyze the changes in the game since 1977. Many things have

changed in baseball since 1977. The game is timeless, but in the past 25 years the game has added four

expansion teams, opened 17 new ballparks, and inter-league play has been introduced.

Major League Baseball is the only major sport in the United States without a salary cap and financial

disparity between the teams has become a major part of the newspaper headlines. The Red Sox spend a lot

of money relative to the majority of teams in baseball, but the New York Yankees consistently outspend

Annual Review AY 2003, Gordon H Dash Jr Page: 76 of 87 every team by a wide margin. Due to the large gap between the team with the highest payroll and the team

with the lowest payroll in the game we added total payroll to our model in order to see if money can buy

wins. Another new variable we introduced was attendance. Do more fans in the park cheer the team to

victory?

And so we began to the process of putting together an empirical model and determining what variables

contribute to a winning team’s success.

III. Previous Literature

We decided to follow along the lines of the Cobb-Douglas Production Function, but we used a determinants

model, based upon the Theory of Demand, for our project. There are literally thousands of articles that deal

with the Cobb-Douglas Production Function and even more websites, including the NKD Group. For the

baseball model we found over 100 websites with information about baseball models and different spins on

the use of the data. However, we decided to use our own model formulation and set off down a different

path. There have been papers written about this model as far back as 1977 and as recent as 1999.

The Cobb-Douglas Production Function Model has also been used on other sport subject matter, including

the National Football League, the National Hockey League, the National Basketball Association and even a

German Soccer League. But with such a strong model we found that it is also being used for other research

projects including the subjects such as the impact of cigarette taxes, stadium subsidies, the impact of SUV’s

on the economy and even the effect of the Kyoto Protocol, the impact of greenhouse gases on the earth.

IV. Model

A determinant model was used in evaluating the factors of winning baseball games at the professional level.

A determinant model is based on the Theory of Demand, and the following linear demand equation applies:

Qw = B0 + B1TS+ B2G+ B0HG+ B2R+ B3AB+ B4H+ B5D+ B6T+ B7HR+ B8BB+ B9SO+ B10SB+ B11CS+

B12HP+ B13SF+ B14RA+ B15ER+ B16ERA+ B17CG+ B18SHO+ B19S+ B20HA+ B21HRA+ B22BBA+

B23SOA+ B24E+ B25E+ B26DP+ B27FP+ B28A+ B29BPF+ B30PPF+ B31AL


Where:

Qw = The number of wins a team earns TS = Team Salary

G = Games HG = Home Games

R = Runs Scored AB = At Bats

H = Hits D = Doubles T = Triples

HR = Home Runs BB = Walks (Base on Balls)

SO = Strikeouts SB = Stolen Bases

CS = Caught Stealing HP = Hit by Pitch SF = Sacrifice Fly

RA = Runs Allowed ER = Earned Runs

ERA = Earned Run Average CG = Complete Games

SHO = Shutouts S = Saves

HA = Hits Allowed HRA = Homeruns Allowed

BBA = Walks Allowed SOA = Strikeouts Allowed

E = Errors DP = Doubleplays

FP = Fielding Percentage A = Attendance

BPF = Ball Park Factor Index PPF = Pitching Factor Index

AL = American League Dummy Variable


The expected effects of each variable are as follows: Variable Type Hypothesized Sign

Qw End Dependent TS Exo + G Exo +

HG Exo + R Exo +

AB Exo + H Exo + D Exo + T Exo +

HR Exo + BB Exo + SO Exo - SB Exo + CS Exo - HP Exo + SF Exo + RA Exo - ER Exo -

ERA Exo - CG Exo +

SHO Exo + S Exo +

HA Exo - HRA Exo -

Variable Type Hypothesized Sign BBA Exo - SOA Exo +

E Exo - DP Exo + FP Exo + A Exo +

BPF Exo + PPF Exo + AL Exo +

Annual Review AY 2003, Gordon H Dash Jr Page: 79 of 87 V. Data

In order to construct our model we needed to find a source for baseball statistics. The sport of baseball has

produced more statistics than quite possibly any other subject known to man, but we needed a source that we

could easily transfer information from without having to type in every data figure. Luckily for us there is a

website called www.baseball1.com which has every season from 1871-2002 entered in a database that is

available for any baseball fanatic or amateur sabremetrician to use.

In addition to the database we also used salary information from www.usatoday.com.

We selected the past two regular seasons, 2001 and 2002, to run the model with all 30 Major League

Baseball teams included.

Five different categories of variables were used: General, Offense, Defense, Pitching and Miscellaneous.

Outlined below is a list of variables that we used in determining what statistics we indicate are relevant in

determining why baseball teams win games.

Games Wins

Home Games Losses

General VariablesAt Bats Hits RunsDoubles Triples Home Runs

Offense Variables

Walks Strikeouts Stolen BasesCaught Stealing Hit By Pitch Sacrifice Flies

Runs Allowed Earned Runs Allowed Earned Run AverageComplete Games Shutouts Saves

Hits Allowed Home Runs Allowed Walks AllowedStrikeouts

Pitching VariablesFinancial - Team Salary

Fan Support - AttendanceBall Park Adjustment Factor - 3-year Ball-Park Index Ball Park Adjustment Factor - 3-year Ball Park Index

Miscellaneous VariablesPutouts Errors

Double Plays Fielding Percentage

Defense Variables

In addition to the

aforementioned variables we also added a dummy variable to differentiate between American League and

National League clubs.

VI. Estimated Model

Qw = -0.123 + 0.887HG + 0.076R + 0.013BB – 0.083RA + 0.351S – 0.013BBA

First a stepwise regression was performed on the data to eliminate insignificant variables from the original model. Stepwise did an excellent job, reducing the 31 variables down to 6 statistically significant variables. An Ordinary Least Squares (OLS) regression was run for the remaining variables and produced a solid model. The values of the variables are displayed below:

http://www.baseball1.com/

http://www.usatoday.com/


Parameter Standard t For Ho: P-Value Partial Variable Estimate Error Est = 0 (95%=0.05) Corr VIF

Intercept -0.123 37.347 -0.003 0.99275 -0.000 n/a

Home Games

0.887 0.454 1.952 0.05282 0.067 1.124

Runs 0.076 0.006 12.728 0.00001 0.753 1.512 Walks 0.013 0.007 1.819 0.07054 0.059 1.547 Runs

Allowed -0.083 0.006 -13.732 0.00001 -0.781 1.964

Saves 0.351 0.064 5.513 0.00002 0.364 1.999 Walks

Allowed -0.013 0.007 -1.690 0.09251 -0.051 1.518

Dependent: Wins


VII. Econometric Results

Dep: Wins Sources SSQ MSQ Df F-Value

Model 10760.684 1793.447 6 207.766 Error 457.499 8.632 53 P-Value

C.Total 11218.183 59 0.00001

Association Test

MLE Stats

Root MSE 2.938 Lambda ====> n/c SSQ(Res) 457.499 LogLiklihood ====> n/c Dep.Mean 80.883

Coef of Var (CV)

3.632

R-Squared 95.922% Adj R-Squared 95.460%

Auto Correlation

Diagnostic Tests

Rho n/c White's ====> 26.539

Durbin n/c Homoskedasticity ====> 0.48886 Durbin H n/c

D Low Limit n/c Average VIF ====> 1.611 D Upper Limit n/c Ho: Rho = 0 Correct Using Rho: Pos &

Neg n/c

Rho: Positive n/c Rho: Negative n/c

The results indicate that this model is statistically solid. The independent variables explain between

95.9% (r2) and 94.5% (adj r2) of the variation of the dependent variable (wins). The F-value is 207.8 with a

p-value of 0.00001. Because the data is cross-sectional, no auto correlation would exist, and a Durbin-

Watson test was not performed. The average VIF value is 1.611, indicating there is no muti-collinearity

issues. The White’s test produced a Homoskedasticity of .49, which allows us to accept the null hypothesis

at a 95% confidence level. Statistically, the error terms exhibit constant variance.


All independent variables were statistically significant, with Runs (R), Runs Allowed (RA), and

Saves (S) being significant at the 95% confidence level. Walks (BB), Walks Allowed (BBA) and Home

Games (HG) are significant at the 90% confidence level. The average elasticities for each independent

variable are as follows:

Home

Games

Runs Walks Runs

Allowed

Saves Walks

Allowed

I I I I I I

0.91095 0.73157 0.08930 -0.81890 0.17633 -0.08664

All the independent variables are inelastic (<1) on average. The Home Games and Runs Scored

variables have a greater positive effect on the dependent variable (Wins) based on the elasticity results. Runs

Allowed has a much greater negative effect on Wins than Walks Allowed, according to the results listed

above.

Below are the associated graphs for Constant Variance, Predictive Ability, and Normality:




VIII. Uses of Estimated Model

The regression results confirm that our model for determining wins by a major league team is valid and

significant. The next question is what these results imply in terms of policy changes and/or behavior by

major league clubs.

One implication of the results is that owners of baseball teams should be spending their money on players

who draw walks or prevent them, help to score runs or stop them from scoring, and those pitchers who are

able to save games routinely. Relief pitchers who save games already receive large salaries. What is more

interesting is that most of the highly paid players in baseball hit a lot of homeruns; this is not statistically

significant in determining wins according to the model. Therefore, owners should redirect this cash flow

toward players who draw walks and score runs. As for the highly paid starting pitchers who have high strike

out totals, they too maybe overpaid. Instead the relievers who save games and pitchers with good control

who walk few players should receive the higher paycheck.

Mentioned early in the paper is the fact that this work is a 25th anniversary edition of previous work. This

model shows that the game has changed in the last 25 years and shows the emphasis on runs, saves and

walks which was not the case 25 years ago. Major League Baseball, the governing body over the teams,

could use these results to instill policy changes which help to level the playing field.

Another key result is the altered perception of what wins games. Although some of the results are inline

with most subjective views of the fan, factors like fielding ability and salary were not factors in the number

of wins a team accumulated, that’s not to say that the team with the most wins every year wins the World

Series (Sorry, Mariner fans!). Another new perception is that the team with the best starting pitching and

ERA do not wind up with the most wins according to our work.

Since attendance was thrown out, owners need not worry about anymore Nomar Garciaparra bobble head

doll nights. If increasing attendance won’t put W’s on the board, save the money and use it get a better save

converting pitcher or a player who scores more runs.

Annual Review AY 2003, Gordon H Dash Jr Page: 86 of 87 Finally, what about the role of government in the Major League Baseball workings? Perhaps the anti-trust

legislation currently in place for baseball needs to be reevaluated based on the lack of importance of

attendance and salary. It seems to us that all the teams should be able to compete. The real governing body

of the game, Major League Baseball, need not worry about salary caps after all. Let teams like the Mets and

Dodgers spend as much as they’d like to finish 3rd in their division.

IX. Overall Conclusions

The model presented in this paper does a statistically significant job of determining the number of wins by a

major league baseball team. More specifically, by looking at the elasticity values it is easy to see that teams

with more home games and runs scored, as well as those that allow fewer runs, accumulate the most wins.

Also a factor is the number of walks drawn and allowed as well as the number of saves.

This paper allows objectivity in the often subjective evaluation of what wins baseball games. Most fans

would not agree that fielding percentage, salary and starting pitching are not important, but the value of an

objective model like the one used here is that opinions don’t count.

An extension of this study would be to increase the data to include say the last 15 or 20 years of baseball. It

would be interesting to see if the same variables were selected by the regression as significant and whether

elasticities changed, meaning that the importance of a relative factor was greater or less than over the last

few years.

Ultimately the model was a fun way of driving home the principles of regression and model building and

allowed an unbiased look into what wins games. Unfortunately, it did not provide much insight into why the

Red Sox can’t seem to win a World Series. It did show that ‘Closer by Committee’ is not the answer!

X. Bibliography

www.business.baylor.edu

www.economics.miningco.com

www.baseball1.com

www.usatoday.com

http://www.business.baylor.edu/

http://www.economics.miningco.com/

http://www.baseball1.com/

http://www.usatoday.com/


End.

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