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Title: Essays on asset return predictability using options market information
Author: Tuneshev, Ruslan Sergeevich
ISNI:       0000 0004 6350 3123
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2017
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In this dissertation, I study the effects of option-type measures of investors’ beliefs on expected asset returns. The key contribution of the thesis lies in exploiting options trading information to summarize a wide range of traders’ directional beliefs via the measures of investor sentiment and differences in investors’ expectations and showing their superior forecasting power for future asset payoffs. Chapter 1 constructs the proxy for investor sentiment in the options market, using the volume-weighted average moneyness level, and explores its market-wide predictability. Consistent with the existing literature, I find that option-implied sentiment is a strong in- and out-of-sample predictor of stock market returns, both at short and long investment horizons. Chapter 2 proposes a firm-level measure for differences in expectations among options traders, obtained from the dispersion of equity options trading volume across various moneyness levels, and examines its cross-sectional profitability. In line with the theoretical predictions of Miller (1977), I demonstrate that stocks with high differences in expectations consistently earn lower returns than otherwise similar stocks. Moreover, this underperformance pattern is more pronounced for firms that incur higher short-sale costs and relatively high arbitrage risk and is robustly distinct from that shown by previously revealed cross-sectional return predictors. Finally, in Chapter 3, I extend the prior analysis and investigate the mechanism and timing of the Miller (1977) hypothesis, using the option-implied measure of belief dispersion. In particular, I document that stocks with high differences in expectations exhibit a clearly pronounced overvaluation in the earnings pre-announcement period and a more severe subsequent price correction upon the release of new information. Additionally, I show that the differences in expectations among options traders tend to better capture the Miller (1977) predictions, relative to analysts’ forecasts dispersion, for stocks with listed options.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available