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Presentation 4

Presentation 4. Kunal Jain April 7, 2010 Economics 201FS. Pairs Trading. Market Neutral Strategy looking at correlations within day-to-day price movements of certain equities Competitors in same sector Liquid Equities Used to Hedge sector- and market-risk.

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Presentation 4

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  1. Presentation 4 Kunal Jain April 7, 2010 Economics 201FS

  2. Pairs Trading • Market Neutral Strategy looking at correlations within day-to-day price movements of certain equities • Competitors in same sector • Liquid Equities • Used to Hedge sector- and market-risk. • Finds some sort of index or relative mean • Calculate Standard Deviations • Mean Reversion • When correlation breaks, one equity trades up, while other trades down: • Sell outperforming stock • Buy underperforming stock • Convergence Trade

  3. HAR-RV Model Adaptation

  4. HAR-RV Model Adaptation

  5. HAR-RV Model Adaptation • Adapt HAR-RV Model to calculate Realized Betas between two competitor equities within same sector to predict Betas: • t=1 corresponds to daily Beta, t=5 corresponds to weekly Beta, t=22 corresponds to monthly Beta. • This model uses betas realized over a 1-day, 5-day, and 1-month time interval to build the conditional betas. Βt+1 = β0 + αDβt + αWβt-5,t + αMβt-22,t + εt+1

  6. HAR-RV Model Adaptation • Intuition: Test whether the HAR adaptation, using daily, weekly, monthly Betas, can be implemented specifically in terms of Pairs Trading to predict Beta and take advantage of strategy. • Negates Drift associated with Pairs Trading • Unless the relative prices return closer to their historical levels, the pair trade will not be profitable • Take advantage of high-frequency data • Potential better ways of calculating Beta?

  7. HAR-RV Model Adaptation • Chose liquid competitor equities and Time Interval • Coca Cola (KO): 4/9/1997-4/14/2000 • Pepsi (PEP): 4/9/1997-4/14/2000 • Calculate HAR-Beta coefficients (D,W,M) • Implemented in MatLAB • Find conditional Beta using observed data and Beta-coefficients from model • Found using observed Betas (Alphas) • Calculate expected relative return based on conditional Beta • Calculate/Compare actual return to estimate differential

  8. HAR-B Model • Model implemented in MatLAB • Calculate HAR-Beta coefficients (D,W,M) • Implemented in MatLAB • 5-minute sampling • Conditional Beta obtained • Utilized Conditional Beta to calculate expected relative return • Calculated Differential: Observed minus Expected • Mean differential: 1.9869e-004 • Calculated Autocorrelations for Equities: • Expect Negative autocorrelation between differential of equities • Expect approximately Zero autocorrelation with log-returns of equity with itself • Mean Autocorrelation: -0.1120 • Autocorrelation with self (Pepsi): -0.0873

  9. HAR-B Model

  10. Further Research • Significance Levels • More Competitor Pairs • Different Time Intervals • Autocorrelation for all returns • Calculate Strategy Returns and Profitability

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