Portfolio Performance Report

Team name: Finman

Team members:

Taoran Nong(UTD ID:2021182655)

Ying Zhou(UTD ID:2021183712)

Jueying Tao(UTD ID:2021156723)

Zhipeng Hu(UTD ID: 2021171799)

1. Investment Climate

The overall global economy is weak except for the U.S. The

growth in the 18-member Eurozone has basically been stagnant

for three years. In addition, the CPI growth rate (0.3% in Nov.) is

far lower than target level (2%), composite PMI fell to 16-month

low (51.1 in Nov.) and unemployment rate is still in the high level

(11.5% in Oct.). This combined indicate the threat of deflation.

What’s more, the financial restrictions in Russia not only would

hurt Russia but also hurt Europe area further. And Europe is

considering a quantitative easing program of its own to stimulate

the economy. The condition in Japan is worse. The 2nd and 3rd

quarter GDP quarter-over-quarter growth are negative, which

means the Japanese economy basically is in recession. As a result,

Bank of Japan announced more QE, in which BoJ backed an 80

trillion yen target for expanding the monetary base. That’s up from

a previous target of 60 to 70 trillion yen. In addition, Japanese

government faces problem of huge debt liabilities, which account

for 226% of total GDP. And Moody downgraded sovereign ratings

of Japan to A1. This might also further weaken Japanese yen. For

China, the economic growth rate is going to decline.

Manufacturing PMI fell to 8-month low (50.3 in Nov), fixed assets

investment is declining (15.9% from Jan. to Oct. 2014) and CPI is

declining as well (1.6% in Oct.). In Nov. 23 2014, China Central

Bank cut interest rates in order to lower funding costs for

businesses, especially small and private entrepreneurs and it stops

sell repo in Nov. when previous one was due, which means China

Central Bank expanded 20 billion yuan into market. However, the

U.S economic growth is much stronger. The economic

fundamentals are good. Manufacturing ISM (similar to PMI) is

increasing (58.7 in Nov.), unemployment rate is declining (5.8% in

Oct.), IPC is stable for past 3 month (1.66% in Oct.) and

University of Michigan’s Consumer Confidence Index is increasing

as well (89.4 in Nov.). And the meanwhile Federal Reserve has

winded down the QE and it starts to consider when to raise

interest rate. These different economic prospects and monetary

policies contribute to strong dollar, which also makes U.S stock

market and debt market more attractive to global investors,

because investors could get higher return due to strong dollar

when they covert dollar back to their country currencies. So we

would put most of our money into the U.S. market. Besides, this

gives us the great opportunity in currency futures.

On the other hand, the crude oil price is continuing to decline, mainly because global economy is in the

downturn, shale oil is booming in the U.S., which increases the oil supply, and at the same time OPEC rejects

to cut oil output due to competition in oil market share. The continuing declined oil price would also hurt the

industries related to oil production and sale and benefit such as airline industry.

2. The purpose of our portfolio

Our purpose is to win the benchmark’s performance, which is S&P 500 index. Our target clients are the

ones who want to win the market return and also can bear the risk to some extent.

3. The strategy to manage portfolio

Our investment strategy focuses on active management strategy. So we would adjust our strategy

according to the overall investment climate. Our initial fund is limited to 1 million, which cannot allow us

to put too many stocks into our investment pool, so in the beginning we only choose to invest 20 stocks

in our original pool. These 20 stocks are comparably better in our opinion and all of them are from S&P

500 index. In addition, we would add, remove or adjust stocks based on the overall investment climate

change. In order to keep our portfolio relatively “safe” in the market, we try to reduce idiosyncratic risk

as much as possible by selecting stocks in S&P 500 from different sectors. This makes possible for us to

diversify idiosyncratic risk and also win the S&P 500. In fact we adjusted our strategy a little bit by start

using derivatives, such as future and option, in order to reduce risk or make profit but we will not use

derivatives to speculate. Because we believe the changed investment climate supports what we were

doing. And by investing in future market, we could invest fewer in the U.S stock market, which might also

mitigate downside risk of stock market. We know the change would increase leverage in our portfolio

and risk as well. However, we would set the limit orders and control the leverage to reduce the downside

risk.

The allocation of a portion of fund into stocks we elected is based on sharp ratio. We designed a

model which can be run in the MATLAB to calculate the most appropriate allocation in our equity

portfolio in order to maximize the sharp ratio.

The Sharpe ratio model is (Refer to the appendix 1):

𝑀𝑎𝑥 𝑓(𝑥) = (𝜇𝑇𝑥 − 𝐴)/√𝑥𝑇𝒱𝑥

s.t. 𝑒𝑇𝑥 = 1

𝛽𝑇𝑥 = 1

2% ≤ 𝑥 ≤ 15%

Explanation:

A is constant, which is monthly risk free return rate

μ is vector of monthly expected return

𝒱 is vector of covariance matrix for stocks we selected

β is vector of Beta for each stocks we selected

x is vector of allocation weight within stocks we selected

f(x) is the equation of sharp ratio, in which μTx (portfolio monthly expected return) minus monthly risk

free return which then divides by √xT𝒱x (portfolio monthly return standard deviation)

eTx = 1 means that sum weight on each stocks equals 1

βTx = 1 means that the beta of our equity portfolio equals to 1, because we also want to control the

systematic risk in our portfolio.

2% ≤ x ≤ 15% means the minimum and maximum weight on each stock are 2% and 15%, respectively,

because we don’t want to put too much or too little money into a stock.

4. The strategy to select stocks

i. Find the industry information

We try to understand every industry environment condition, especially for industry life cycle stage and

industry expected annual growth rate in next 5 years. We prefer to invest the companies which are in the

growing stage or at least mature stage. And we also prefer the industries that have higher annual expected

growth rate in next 5 years. (Source: http://clients1.ibisworld.com)

ii. Compare the firms’ fundamental ratio with industry’s ratio

After understanding the overall industry environment condition, we want to find out the companies

that have better performances than industry’s level in latest quarter or LTM. The criteria are:

1) Current ratio[Latest Q] → Close to the industry’s ratio is better

2) Quick ratio[Latest Q] → Close to the industry’s ratio is better

3) Receivables turnover [Latest Q] → Close to the industry’s ratio is better

4) Inventory turnover [Latest Q] → Close to the industry’s ratio is better

5) Ave cash conversion cycle [LQ] → Close to the industry’s ratio is better

6) Total asset turnover [Latest Q] → Close to the industry’s ratio is better

7) Fixed asset turnover[Latest Q] → Close to the industry’s ratio is better

8) Gross margin[LTM] → higher to industry’s ratio is better

9) Operating margin[LTM] →Higher to industry’s ratio is better

10) Net income margin [LTM] → higher to industry’s ratio is better

11) Return on capital [LTM] → higher to industry’s ratio is better

12) Return on equity [LTM] → higher to industry’s ratio is better

We assume that operating profitability has higher priority than operating efficiency and internal

liquidity. We choose at least two companies in each sector, according to the performance in operating

profitability, operating efficiency and internal liquidity. Generally, we choose the companies with more

ratios meeting our criteria.

iii. Compare P/E ratio

Due to we already screen two companies in each sector, we can compare them in term of P/E ratio, in

which we also consider the effect of required return and expected growth rate. Then we will choose only

one with lower adjusted P/E ratio in each sector. We use 5-year beta to measure required return. For

example, firm A has 14 PE, 9% expected growth rate and 1.4 Beta; and firm B has 13.3 PE, 11% expected

growth rate and 1.3 Beta. Based on these data, firm A should have lower PE ratio, but its PE is actually

higher than that of firm B. So firm A is overvalued.

iv. It’s better for a firm with stable sale growth, gross profit growth, operating income growth, net

income growth rate for past 5 years and positive opinion in current year in Yahoo analyst opinion.

After the process of 1 to 3, we already choose many companies in each sector. Then we need to look

at those firms’ financial statements for past 5 years. Besides, we also look at the analyst opinion in

current year in Yahoo Finance in order to make sure our judgment is not wrong.

Internal Liquidity

Operating efficiency

Operating profitability

v. The stocks we selected and allocation (Initial stock allocation in 9/17/2014).

symbol Weight beta symbol Weight beta symbol Weight beta symbol Weight beta

M 9.26% 0.95 QCOM 4.25% 0.89 SRE 5.66% 0.28 HAL 2.71% 1.99

DLTR 3.76% 0.34 GOOGL 2.00% 1.06 GILD 6.34% 0.95 XOM 4.92% 0.89

LEN 7.67% 1.57 AAPL 4.46% 0.83 LH 5.46% 0.74 NBR 2.16% 3.22

GMCR 2.02% 0.82 EMN 6.12% 1.82 LUV 5.71% 0.82 DFS 5.36% 0.91

KR 2.00% 1.01 NU 6.04% 0.37 UNP 8.26% 1.02 NDAQ 5.86% 0.83

The weight is not based on total 1-million asset, because we don’t put all the money into stock market.

5. Performance Summary

i. Top Ten Stock Holdings (Ending date: 2014-11-28)

Rank Description Industry % Net assets % Gain/Decline

1 Union Pacific Corporation Railroads 5.78% 6.38%

2 iShares 20+ Year T-Bond ETF NA 4.79% 2.33%

3 Gilead Sciences Inc. Biotechnology 4.44% -3.56%

4 SPDR S&P 500 ETF NA 4.33% 10.07%

5 Eastman Chemical Co. Chemicals 4.29% -1.00%

6 Northeast Utilities Diversified Utilities 4.23% 10.83%

7 The Nasdaq OMX Group, Inc Diversified Investments 4.10% 2.25%

8 Southwest Airlines Co. Regional Airlines 3.99% 20.97%

9 Sempra Energy Diversified Utilities 3.96% 5.36%

10 iShares Japan Large-Cap (ITF) NA 3.86% -3.11%

As you can see, the top ten stock holdings include different stocks with different industries and several

ETF and ITF. Besides, most of our top ten holdings contribute to total gain in our portfolio and 5 out of

top 10 holdings outperform the S&P 500 Index benchmark.

ii. Our worst performing stocks (Ending date: 2014-11-28)

Rank Description Industry % Net asset (Rank) % Decline

1 Nabors Industries Ltd. Oil & Gas Drilling & Exploration 1.51% (21) -46.16%

2 Halliburton Company Oil & Gas Equipment & Services 1.89% (20) -36.75%

3 Google Inc. Internet Information Providers 1.40% (24) -7.55%

4 Exxon Mobil Corporation Major Integrated Oil & Gas 3.44% (13) -6.90%

5 QUALCOMM Inc. Communication Equipment 2.97% (16) -3.99%

9% 4%

8% 2% 2%

4%

2%

4%

6% 6% 6% 6%

5%

6%

8%

3%

5%

2% 5%

6%

Asset Allocation Weight M DLTRLEN GMCRKR QCOMGOOGL AAPLEMN NUSRE GILDLH LUVUNP HALXOM NBRDFS NDAQ

There is no doubt that the oil related section lost most because of continued declining oil price in this year. 3

out of 5 companies here belong to oil related industries. The loss in Google might by caused by strong dollar

because about 55% of total revenue from overseas. And the loss in QUALCOMM mainly is due to bad 4Q

results. And you should notice that these 5 stocks are allocated comparable fewer assets among all 25

holdings we have.

iii. Our best performing stocks (Ending date: 2014-11-28)

Rank Description Industry % Net asset (Rank) % Gain

1 Yahoo! Inc. Internet Information Providers 2.52% (18) 23.04%

2 Dollar Tree, Inc. Discount, Variety Stores 2.63% (17) 21.92%

3 Southwest Airlines Co. Regional Airlines 3.99% (8) 20.97%

4 iPath S&P GSCI Crude Oil NA -5.93% (Short sell) 18.01%

5 Apple Inc. Electronic Equipment 3.12% (14) 17.28%

The gain in Yahoo mainly is due to improved 3Q result and the Alibaba stock it owned. The gain in Dollar Tree,

Inc. is because of bad news of its major competitor, Family Dollar and better 3Q result. The gain in Apple Inc.

is because strong new IPhone sale. And the gain in Southwest Airlines Co. is mainly due to benefits from

lower oil price.

iv. Stock portfolio performance (excluded bond, future and option)

As the chart shows, our stock portfolio’s accumulated return outperforms S&P 500 Index and

Russell 1000 Index by 0.13% and 0.44%, respectively. Our stock portfolio’s accumulated return even

takes the trading loss in the first day into account, because we made trades near the end of the U.S.

market close. As a result, we lost 0.25% in the first day, compared to 0.13% and 0.13% up for S&P

500 index and Russell 1000 index. (Refer to the appendix 2)

-8.00%

-6.00%

-4.00%

-2.00%

0.00%

2.00%

4.00%

6.00%

Daily Accumulated Net Asset Return (deducted transaction fee)

Our stock portfolio accumulated return S&P 500 Index Accumulated Return

Russell 1000 Index Accumulated Return

Ending date: 2014-11-28

v. Overall portfolio performance

As the chart shows, every component in our portfolio has positive net return. And the total net return in the

end of 11/28/2014 is 7.34%, which is far more than the net return of S&P 500 Index (3.43%) and Russell 1000

Index (3.13%) during the same period.

vi. Beta and diversification level of our stock portfolio

We did the regression with excess net return of our stock portfolio and that of S&P 500 index. The beta of

our stock portfolio is 0.725, which is different from 1. Because the beta of each stock we picked changed all

the time. We did not adjust the total beta equal to 1 due to high transaction fee. Besides, the R Square is

0.91, which means the diversification level is ok. (Refer to the appendix 3)

vii. The Sharpe, Treynor, and Jensen measures of our stock portfolio (Ending date: 2014-11-28)

Our stock portfolio S&P 500 Index

Sharpe ratio 0.0798114 0.059587025

Treynor ratio 0.0007046 0.000500904

Jensen ratio 0.0001478* NA

All the ratios are daily bases

Daily risk-free rate of return as proxy by the bond equivalent yield of the current 3-month T-bill.

*:not significant different from 0 in 5% significant level

Our stock portfolio outperforms S&P 500 Index in terms of Sharpe ratio and Treynor ratio. Even though the

Jensen alpha is positive, it’s not significant different from 0 in 5% significant level. So we cannot conclude

that our stock portfolio adds extra value.

3.56%

1.80% 1.75%

0.15% 0.09%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

4.00%

Stocks net return Future net return Bond net return Cash Interest netincome

Option net return

Overall Portfolio’s Components Net Return (deducted transaction fee)

Ending date: 2014-11-28

6. Extra transactions’ rationales: (The extra transactions are the trades after we already bought those 20

stocks we selected.)

Symbol: LEN Action: SELL Date: 9/18/2014

Rationale: In 9/17/2014 there is good news that the homebuilder beat Wall Street's earnings expectations

by a landslide. Separately, new data from the National Association of Home Builders showed confidence

among the nation's home builders hit a near nine year high. U.S. Steel (X) was another winner, it shot up

about 9.65 percent. In 9/18/2014, we sold 7,00 shares of LEN at 40.85, because of the news that annualized

housing starts in Aug is 95.6 million units, which is far lower than expected units of 103.7 million, Which

made us think that there still is uncertainty in homebuilder industry.

Symbol: Yahoo Action: BUY Date: 9/18/2014

Rationale: we bought 600 shares of YHOO at 42.05, because the initial inquiry of ALIBABA increases from

80-83 to 92-93, which made us think that the value of rest of holding by Yahoo is worth more. What’s more,

YHOO could find a way to avoid paying capital gain tax, which could increase the value of YHOO a lot.

Symbol: M Action: SELL Date: 9/19/2014

Rationale: we sold 565 shares of M at 60.34, because we think there is no good news about retail sales

month rate on recent month and the weight on Macy is little high

Symbol: T-bond Action: SELL Date: 10/07/2014

Rationale: we sold 200 shares of T-bond at 1100, because if we hold them until they mature, we only realize

1000 principal plus 11.875 interest income, which are much lower than 1100.

Symbol: TLT Action: BUY Date: 10/10/2014

Rationale: we bought 900 shares of TLT as 119.7, because the bad performance of U.S stock market due to

depressed European economy, China slowdown and geopolitical tension. We believed TLT, 20+ Year

T-bond-based ETF, could be a safe place to go.

Symbol: UVXY Action: BUY&SELL Date: 10/16/2014

Rationale: we bought and then sold it immediately. It’s operation mistake. If you look at my order history, we

plan to short sell UVXY, a volatility-based ETF, because the U.S overall stock market drop significantly in the

beginning of that day, which made the UVXY rise almost 20%. However, the economic data issued in that

day is not bad. Industrial production in Sept. grew 1% more than expectation of 0.4% and Philly Fed

Manufacturing Index in Oct is +20.7 more than expectation of +20. So we believed the overall stock market

would go up and UVXY would go down. We want to grasp the opportunity to gain. However, we made a

mistake and opportunity loss.

Symbol: SPY Action: BUY Date: 10/17/2014

Rationale: we bought 230 shares of SPY at 188.24. Because the price is cheap due to huge decline in stock

market and the fundamentals of the U.S. economy is still good: new house start in Sept. increased 6.3%

meeting the expectation and University of Michigan’s Consumer Confidence Index in Oct. increased to 86.4

more than expectation of 84.1. Besides, the several large players had good 3Q earnings: GE, HON, and MS

beat the expectation. So we believe it’s a good opportunity to buy it at low price.

Symbol: OIL Action: SHORT Date: 10/27/2014

Rationale: we short sell 3000 shares of OIL, oil-based ETF, at 19.77. Because we want to hedge the decline

risk of two energy-related stock (HAL and NBR) holdings, which are positive correlated to crude oil price.

Besides, The global economy is in downturn, OPEC didn’t decide to reduce oil production and the shale oil is

becoming popular and competes to expand its market share, and the production of shale oil in the U.S.

reached its high level. So we tend to believe the crude oil price would continue to drop.

Symbol: TLT Action: SELL Date: 10/31/2014

Rationale: we sold 500 shares of TLT at 118.86. Because Federal Reserve’s QE program ends and U.S. stock

market performance is more attractive.

Symbol: ITF Action: BUY Date: 10/31/2014

Rationale: we bought 1950 shares of ITF, Japan-based ETF, at 51.49, because Bank of Japan announced more

quantitative easing. This would devalue Japanese yen and contribute to export, which is good for Japan

economy. So it’s good news go Japan stock market. Besides, GPIF, Japan’s largest government pension

investment funds, was set to pump $186 billion into stock market. The pension manager allocated 35% of its

holdings to domestic bonds, down from 60%, and increased long-term holdings in Japan stock market to

34%, up from 18%.

Symbol: DX/Z4 Action: BUY Date: 11/3/2014

Rationale: we bought 4 contract of U.S. Dollar future, because the U.S. Federal Reserve is winding down its

bond buying program while Japan is still pumping reserves into its banking system and Europe is considering

a quantitative easing program of its own. On the other hands, there is the difference in growth rates

between the U.S. and the rest of the world. Growth in the 18-member euro zone has basically been stagnant

for three years now, with the most recent readings showing that the usual engines of its economy, Germany

and France, shrank or stalled in the second quarter of 2014. Japan, meanwhile, has only had one quarter of

real GDP growth above 2% in the past five years, which makes the U.S. economy’s latest quarterly growth

reading of 4.2% look a lot better. So we believe U.S. dollar would be strong in the long-term.

Symbol: LH1422K100 Action: SELL Date: 11/4/2014

Rationale: we sold 3 contract of LH call option. Because Laboratory Corp. of America (LH) announced on

Monday that it will acquire contract research organization company Covance Inc. (CVD) in cash and stock

deal whose equity is valued at $6.1 billion. The stock price of LH declined about 7%, which made us afraid

the stock price would continue drop. So we sold call option to hedge the downside risk.

Symbol: BZ/Z4 Action: SHORT Date: 11/5/2014

Rationale: we short 2 contracts of crude oil future in 11/5/2014, the same reason as we short sell OIL.

However, due to high leverage effect and high fluctuation, we set a stop order as $82.6.

Symbol: J./Z4 Action: SHORT Date: 11/5/2014

Rationale: we short 2 contracts of Japanese Yen future in 11/5/2014, because of more loose monetary

policy in Japan, huge debt liabilities, QE ended in the U.S. and more stronger economic performance in U.S. .

We also set a stop order at 0.8705.

Symbol: QCOM1407W73.5 Action: BUY Date: 11/6/2014

Rationale: we bought 3 contracts of QCOM put option at $4, because the firm announced that 4Q results

and guidance were below Street estimates, and uncertainty on China royalty collections continues. Besides,

anti-monopoly investigation by China regulator increases the uncertainty of this company.

Symbol: DX/Z4 Action: BUY Date: 11/6/2014

Rationale: we bought more 2 contracts of dollar index future in 11/6/2014. Firstly, Republican Party won the

America’s mid-term election on Tuesday. The market believed the election will largely shift government

gridlock, which includes more free export policy of U.S. energy, relaxing limitation on banks, and signing new

international trade agreement. Secondly, European Central Bank said that the Governing Council “is

unanimous in its commitment to using additional unconventional instruments within its mandate.” And ECB

expect that its balance sheet would increase to the level of year 2012. Which means about 860 billion Euro

could be increased.

Appendices

Appendix 1

function f=fun01(r)

x1=r(1);

x2=r(2);

x3=r(3);

x4=r(4);

x5=r(5);

x6=r(6);

x7=r(7);

x8=r(8);

x9=r(9);

x10=r(10);

x11=r(11);

x12=r(12);

x13=r(13);

x14=r(14);

x15=r(15);

x16=r(16);

x17=r(17);

x18=r(18);

x19=r(19);

x20=r(20);

x=[x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,x11,x12,x13,x14,x15,x16,x17,x18,x19,x20]';

e=ones(1,20)';

B=[0.95 0.34 1.57 0.82 1.01 0.89 1.06 0.83 1.82 0.37 0.28 0.95

0.74 0.82 1.02 1.99 0.89 3.22 0.91 0.83]';

u=[0.0290 0.0034 0.0250 0.0156 0.0136 0.0101 0.0080 -0.0006 0.0173 0.0113 0.0124

0.0124 0.0092 0.0257 0.0146 0.0223 0.0054 0.0136 0.0350 0.0123]';

v=[covariance matrix];

f=-(((u'*x)-0.0061)/(x'*v*x)^0.5)+10000*e'*((x<0.02).*exp(e.*x))+1000*(e'*x-1)^2+10000*(B'*x-1)^2+10000

*e'*((x>0.15).*exp(e.*x));

end

Covariance matrix=

0.89

%

0.34

%

0.46

%

0.60

%

0.05

%

0.21

%

0.30

%

0.46

%

0.36

%

0.00

%

0.00

%

0.07

%

0.12

%

0.32

%

0.33

%

0.34

%

0.04

%

0.53

%

0.27

%

0.10

%

0.34

%

1.28

%

0.09

%

0.10

%

0.05

%

0.11

%

0.10

%

0.04

%

0.02

%

-0.03

%

-0.07

%

0.07

%

-0.07

%

0.15

%

-0.01

%

0.09

%

-0.03

%

-0.02

%

0.05

%

0.07

%

0.46

%

0.09

%

1.03

%

0.18

%

0.13

%

0.23

%

0.26

%

0.19

%

0.39

%

0.09

%

0.03

%

0.06

%

0.17

%

0.27

%

0.29

%

0.35

%

0.15

%

0.65

%

0.33

%

0.20

%

0.60

%

0.10

%

0.18

%

5.86

%

0.30

%

0.39

%

0.39

%

-0.05

%

1.31

%

0.03

%

0.05

%

0.31

%

0.08

%

0.38

%

0.12

%

0.99

%

0.15

%

1.19

%

0.68

%

0.35

%

0.05

%

0.05

%

0.13

%

0.30

%

0.31

%

0.05

%

0.02

%

-0.04

%

0.10

%

0.05

%

0.04

%

0.06

%

0.07

%

0.08

%

0.04

%

0.24

%

0.12

%

0.30

%

0.09

%

0.08

%

0.21

%

0.11

%

0.23

%

0.39

%

0.05

%

0.41

%

0.24

%

0.27

%

0.28

%

0.08

%

0.07

%

0.03

%

0.10

%

0.14

%

0.19

%

0.27

%

0.14

%

0.29

%

0.23

%

0.25

%

0.30

%

0.10

%

0.26

%

0.39

%

0.02

%

0.24

%

1.39

%

0.10

%

0.14

%

0.03

%

0.05

%

-0.01

%

0.08

%

0.19

%

0.14

%

0.26

%

0.09

%

0.43

%

0.23

%

0.21

%

0.46

%

0.04

%

0.19

%

-0.05

%

-0.04

%

0.27

%

0.10

%

6.27

%

0.35

%

-0.08

%

-0.08

%

0.23

%

0.10

%

0.13

%

2.23

%

0.00

%

0.10

%

0.04

%

0.21

%

0.04

%

0.36

%

0.02

%

0.39

%

1.31

%

0.10

%

0.28

%

0.14

%

0.35

%

1.43

%

0.06

%

0.07

%

0.08

%

0.12

%

0.31

%

0.24

%

0.44

%

0.12

%

0.49

%

0.44

%

0.12

%

0.00

%

-0.03

%

0.09

%

0.03

%

0.05

%

0.08

%

0.03

%

-0.08

%

0.06

%

0.15

%

0.10

%

-0.01

%

0.02

%

0.08

%

0.03

%

0.05

%

0.07

%

0.03

%

0.06

%

0.08

%

0.00

%

-0.07

%

0.03

%

0.05

%

0.04

%

0.07

%

0.05

%

-0.08

%

0.07

%

0.10

%

0.15

%

0.01

%

0.03

%

0.09

%

0.04

%

0.05

%

0.05

%

0.04

%

0.03

%

0.05

%

0.07

%

0.07

%

0.06

%

0.31

%

0.06

%

0.03

%

-0.01

%

0.23

%

0.08

%

-0.01

%

0.01

%

1.21

%

0.02

%

0.18

%

0.06

%

-0.05

%

0.02

%

-0.01

%

0.14

%

-0.04

%

0.12

%

-0.07

%

0.17

%

0.08

%

0.07

%

0.10

%

0.08

%

0.10

%

0.12

%

0.02

%

0.03

%

0.02

%

0.22

%

0.09

%

0.14

%

0.11

%

0.06

%

0.22

%

0.07

%

0.08

%

0.32

%

0.15

%

0.27

%

0.38

%

0.08

%

0.14

%

0.19

%

0.13

%

0.31

%

0.08

%

0.09

%

0.18

%

0.09

%

0.67

%

0.25

%

0.26

%

0.00

%

0.42

%

0.20

%

0.17

%

0.33

%

-0.01

%

0.29

%

0.12

%

0.04

%

0.19

%

0.14

%

2.23

%

0.24

%

0.03

%

0.04

%

0.06

%

0.14

%

0.25

%

1.08

%

0.22

%

0.10

%

0.32

%

0.18

%

0.13

%

0.34

%

0.09

%

0.35

%

0.99

%

0.24

%

0.27

%

0.26

%

0.00

%

0.44

%

0.05

%

0.05

%

-0.05

%

0.11

%

0.26

%

0.22

%

1.01

%

0.17

%

1.07

%

0.32

%

0.17

%

0.04

%

-0.03

%

0.15

%

0.15

%

0.12

%

0.14

%

0.09

%

0.10

%

0.12

%

0.07

%

0.05

%

0.02

%

0.06

%

0.00

%

0.10

%

0.17

%

0.21

%

0.24

%

0.11

%

0.15

%

0.53

%

-0.02

%

0.65

%

1.19

%

0.30

%

0.29

%

0.43

%

0.04

%

0.49

%

0.03

%

0.04

%

-0.01

%

0.22

%

0.42

%

0.32

%

1.07

%

0.24

%

1.86

%

0.44

%

0.28

%

0.27

%

0.05

%

0.33

%

0.68

%

0.09

%

0.23

%

0.23

%

0.21

%

0.44

%

0.06

%

0.03

%

0.14

%

0.07

%

0.20

%

0.18

%

0.32

%

0.11

%

0.44

%

0.53

%

0.17

%

0.10

%

0.07

%

0.20

%

0.35

%

0.08

%

0.25

%

0.21

%

0.04

%

0.12

%

0.08

%

0.05

%

-0.04

%

0.08

%

0.17

%

0.13

%

0.17

%

0.15

%

0.28

%

0.17

%

0.44

%

Appendix 2

Our stock portfolio’s

daily net return

Our stock

portfolio’s

accumulated

return

S&P 500 Index’s

daily net return

S&P 500 Index

Accumulated

Return

Russell 1000

Index’s daily net

return

Russell 1000 Index

Accumulated Return

2014-09-17 -0.25% -0.25% 0.13% 0.13% 0.13% 0.13%

2014-09-18 0.30% 0.05% 0.49% 0.62% 0.45% 0.58%

2014-09-19 -0.25% -0.20% -0.05% 0.57% -0.10% 0.48%

2014-09-22 -0.79% -0.99% -0.80% -0.23% -0.90% -0.42%

2014-09-23 -0.41% -1.40% -0.58% -0.81% -0.60% -1.01%

2014-09-24 0.60% -0.81% 0.78% -0.03% 0.77% -0.26%

2014-09-25 -1.13% -1.93% -1.62% -1.65% -1.59% -1.84%

2014-09-26 0.77% -1.17% 0.86% -0.81% 0.85% -1.01%

2014-09-29 -0.20% -1.37% -0.25% -1.06% -0.25% -1.25%

2014-09-30 -0.25% -1.62% -0.28% -1.34% -0.33% -1.58%

2014-10-01 -0.86% -2.47% -1.32% -2.64% -1.35% -2.91%

2014-10-02 0.07% -2.40% 0.00% -2.64% 0.02% -2.89%

2014-10-03 1.00% -1.42% 1.12% -1.55% 1.11% -1.81%

2014-10-06 -0.15% -1.57% -0.16% -1.71% -0.17% -1.98%

2014-10-07 -0.89% -2.44% -1.51% -3.20% -1.53% -3.48%

2014-10-08 1.07% -1.40% 1.75% -1.51% 1.68% -1.86%

2014-10-09 -1.37% -2.75% -2.07% -3.54% -2.09% -3.90%

2014-10-10 -0.99% -3.71% -1.15% -4.64% -1.26% -5.11%

2014-10-13 -1.46% -5.12% -1.65% -6.22% -1.68% -6.70%

2014-10-14 0.33% -4.80% 0.16% -6.07% 0.23% -6.49%

2014-10-15 -0.07% -4.87% -0.81% -6.83% -0.70% -7.14%

2014-10-16 0.28% -4.61% 0.01% -6.81% 0.15% -7.01%

2014-10-17 0.84% -3.81% 1.29% -5.61% 1.26% -5.84%

2014-10-20 1.08% -2.77% 0.91% -4.75% 0.93% -4.96%

2014-10-21 1.49% -1.32% 1.96% -2.89% 2.02% -3.04%

2014-10-22 -0.46% -1.77% -0.73% -3.60% -0.78% -3.80%

2014-10-23 0.79% -0.99% 1.23% -2.41% 1.25% -2.60%

2014-10-24 0.63% -0.37% 0.71% -1.72% 0.69% -1.93%

2014-10-27 -0.26% -0.62% -0.15% -1.87% -0.17% -2.09%

2014-10-28 0.83% 0.20% 1.19% -0.70% 1.23% -0.88%

2014-10-29 -0.42% -0.21% -0.14% -0.83% -0.18% -1.06%

2014-10-30 0.64% 0.42% 0.62% -0.22% 0.59% -0.47%

2014-10-31 0.80% 1.23% 1.17% 0.95% 1.19% 0.71%

2014-11-03 0.04% 1.26% -0.01% 0.94% 0.01% 0.72%

2014-11-04 -0.27% 0.98% -0.28% 0.66% -0.34% 0.38%

2014-11-05 0.23% 1.21% 0.57% 1.23% 0.50% 0.88%

2014-11-06 0.31% 1.53% 0.38% 1.61% 0.43% 1.31%

2014-11-07 0.14% 1.67% 0.03% 1.65% 0.04% 1.35%

2014-11-10 0.59% 2.27% 0.31% 1.97% 0.31% 1.67%

2014-11-11 0.17% 2.44% 0.07% 2.04% 0.07% 1.74%

2014-11-12 -0.10% 2.34% -0.07% 1.96% -0.04% 1.70%

2014-11-13 -0.01% 2.33% 0.05% 2.02% 0.01% 1.72%

2014-11-14 -0.10% 2.22% 0.02% 2.04% 0.03% 1.75%

2014-11-17 -0.28% 1.94% 0.07% 2.12% 0.04% 1.79%

2014-11-18 0.66% 2.61% 0.51% 2.64% 0.53% 2.33%

2014-11-19 -0.33% 2.27% -0.15% 2.49% -0.17% 2.15%

2014-11-20 0.14% 2.41% 0.20% 2.69% 0.23% 2.39%

2014-11-21 0.26% 2.68% 0.52% 3.23% 0.52% 2.92%

2014-11-24 0.38% 3.07% 0.29% 3.52% 0.32% 3.25%

2014-11-25 -0.08% 2.99% -0.12% 3.40% -0.10% 3.15%

2014-11-26 0.29% 3.28% 0.28% 3.69% 0.26% 3.42%

2014-11-28 0.27% 3.56% -0.25% 3.43% -0.29% 3.13%

Appendix 3

-0.005

0

0.005

0.01

-3.00% -2.00% -1.00% 0.00% 1.00% 2.00% 3.00%

X Variable 1

X Variable 1 Residual Plot

-2.00%

-1.00%

0.00%

1.00%

2.00%

-3.00% -2.00% -1.00% 0.00% 1.00% 2.00% 3.00%

Y

X Variable 1

X Variable 1 Line Fit Plot