Data Analysis II Mingwei Lei March 3rd, 2010 Econ 201S

Things to Improve on From Last Presentation Explain everything on slides Include graphs as well as numerical results Improve the visual presentation of the slides More ideas for research

VZ: Tests Using TP Quarticity ZTP 0.1% - 208 (9.83%) 1% - 335 (15.8%) 5% - 503 (23.8%) ZTP , l 0.1% - 137 (6.47%) 1% - 274 (12.9%) 5% - 472 (22.3%) ZTP , lm 0.1% - 125 (5.90%) 1% - 247 (11.7%) 5% - 452 (21.4%)

VZ: Tests Using QP Quarticity ZQP 0.1% - 233 (11.0%) 1% - 369 (17.4%) 5% - 576 (27.2%) ZQP, l 0.1% - 208 (9.83%) 1% - 335 (15.8%) 5% - 503 (23.8%) ZQP, lm 0.1% - 208 (9.83%) 1% - 335 (15.8%) 5% - 503 (23.8%)

HPQ: Tests Using TP Quarticity ZTP 0.1% - 312 (10.7%) 1% - 490 (16.7%) 5% - 746 (25.5%) ZTP, l 0.1% - 231 (7.90%) 1% - 445 (15.2%) 5% - 760 (26.0%) ZTP, lm 0.1% - 211 (7.22%) 1% - 427 (14.6%) 5% - 743 (25.4%)

HPQ: Tests Using QP Quarticity ZQP 0.1% - 401 (13.7%) 1% - 618 (21.1%) 5% - 914 (31.3%) ZQP, l 0.1% - 326 (11.1%) 1% - 525 (18.0%) 5% - 844 (28.9%) ZQP, lm 0.1% - 251 (8.58%) 1% - 464 (15.9%) 5% - 784 (26.8%)

KO: Tests Using TP Quarticity ZTP 0.1% - 281 (9.61%) 1% - 452 (15.4%) 5% - 706 (24.1%) ZTP, l 0.1% - 211 (7.21%) 1% - 419 (14.3%) 5% - 733 (25.0%) ZTP, lm 0.1% - 192 (6.57%) 1% - 395 (13.5%) 5% - 708 (24.2%)

KO: Tests Using QP Quarticity ZQP 0.1% - 418 (14.3%) 1% - 647 (22.1%) 5% - 947 (32.4%) ZQP, l 0.1% - 289 (9.88%) 1% - 494 (16.9%) 5% - 819 (28.0%) ZQP, lm 0.1% - 220 (7.52%) 1% - 428 (14.6%) 5% - 751 (25.7%)

VZ Jump Detection: Median Test Using TP Quarticity Results: 0.1% level – 30/2117 (1.42%) 1% level – 75/2117 (3.31%) 5% level – 186/2117 (8.79%)

HPQ Jump Detection: Median Test Using TP Quarticity Results: 0.1% level – 56/2924 (1.9%) 1% level – 115/2924 (3.93%) 5% level – 279/2924 (9.54%)

KO Jump Detection: Median Test Using TP Quarticity Results: 0.1% level – 33/2924 (1.13%) 1% level – 107/2924 (3.66%) 5% level – 261/2924 (8.93%)

A Possible Research Topic It is sometimes said that correlations between stocks increases when the market is tanking The goal is to explore the empirical relationship between coefficient of correlation between various stocks of similar industries and market returns Process: Match up individual stocks’ data and S&P data Partition data into periods to be analyzed (by week, by month, etc.) Calculate the market returns for each period Calculate the coefficient of correlation of returns (hourly, daily, etc) between stocks for each period Plot coefficient of correlation against returns and find a relationship

Another Possible Research Topic Find relationship between beta and market returns Process: Match up individual stocks’ data and S&P data Partition data into periods to be analyzed (by week, by month, etc.) Calculate time variant realized betas over periods Calculate the market returns for each period Plot realized betas vs. market returns and find a relationship