Preliminary Data Analysis

Angela Ryu

Economics 201FSHonors Junior Workshop: Finance

Duke University

February 10, 2010

Data

• XOM (Exxon Mobile) – Dec 1 1999 – Jan 7 2009 (2264 days)

• GOOG (Google)– Aug 20 2004 – Jan 7 2009 (1093 days)

• WMT (Wal-Mart)– Apr 9 1997 – Jan 7 2009 (2921 days)

Getting hands dirty…

• Prices, Log Returns, Spotting Outliers• Realized Volatility• Bipower / Tripower / Quadpower Variation• Z-scores

Huang-Tauchen (2005)

vs. Prices

XOM GOOG

WMT

vs. Log Returns (5 min)

vs. RV (5 min, daily)

vs. BV (5 min, daily)

vs. RV & BV (5 min, daily)

Volatility Signature Plot

vs. TP (5 min, daily)

vs. QP (5 min, daily)

XOM: Jump Detection using Z-score (5 min)

Test Fractions of days over sig. level

Zlog, TP, 0.95 0.1767

Zlog, TP, 0.99 0.0892

Zlog, TP, 0.999 0.0420

ZRJ, TP, 0.95 0.1480

ZRJ, TP, 0.99 0.0623

ZRJ, TP, 0.999 0.0221

GOOG: Jump Detection using Z-score (5 min)

Test Fractions of days over sig. level

Zlog, TP, 0.95 0.2351

Zlog, TP, 0.99 0.1226

Zlog, TP, 0.999 0.0631

ZRJ, TP, 0.95 0.2068

ZRJ, TP, 0.99 0.0961

ZRJ, TP, 0.999 0.0375

WMT: Jump Detection using Z-score (5 min)

Test Fractions of days over sig. level

Zlog, TP, 0.95 0.2372

Zlog, TP, 0.99 0.1287

Zlog, TP, 0.999 0.0681

ZRJ, TP, 0.95 0.2081

ZRJ, TP, 0.99 0.0965

ZRJ, TP, 0.999 0.0421

GOOG: Kernel Density (5 min)

• Mean: 0.7643 ; Variance: 1.8278 ( ~N(0,1)?)

Results & Plans

• Got more used to MATLAB– more efficient data analysis

• Better understanding in volatility measures

• Possible interests: RCOV, Volatility Risk Premium

• Background Reading

Comments &Suggestions