Author: Scott Murray
Publisher:
ISBN:
Category :
Languages : en
Pages : 61
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Book Description
I investigate the relation between option prices and daily stock return serial correlation. I demonstrate that the variance ratio, calculated as the ratio of realized to implied stock return variance, has both a contemporaneous and predictive relation with stock return serial correlation. The ability of the variance ratio to predict future stock return serial correlation gives rise to a daily trading strategy that implements reversal trading on stocks predicted to exhibit large negative serial correlation and momentum trading on stocks with high predicted serial correlation. The trading strategy generates risk-adjusted returns in excess of 6.5% per year.
Author: Benjamin M. Blau
Publisher:
ISBN:
Category :
Languages : en
Pages : 29
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Book Description
A broad stream of research shows that information flows into underlying stock prices through the options market. For instance, prior research shows that both the Put-Call Ratio (P/C) and the Option-to-Stock Volume Ratio (O/S) predict negative future stock returns. In this paper, we compare the level of information contained in these two commonly used option volume ratios. Our comparison of the return predictability contained in these ratios yields some new results. First, we find that P/C ratios contain more predictability about future stock returns at the daily level than O/S ratios. Second, in contrast to our first set of results, O/S ratios contain more predictability about future returns at the weekly and monthly levels than P/C ratios. In fact, our tests show that while P/C ratios contain predictability about future daily returns and, to some extent, future weekly returns, the return predictability in P/C ratios is fleeting. O/S ratios, on the other hand, significantly predict negative returns at both the weekly and monthly levels, respectively.
Author: Cliff Moll
Publisher:
ISBN:
Category :
Languages : en
Pages : 114
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Book Description
ABSTRACT: In Chapter 2, we use a sample of firms with actively traded single stock futures (SSF) to examine the information content of implied risk premiums embedded in SSF and option prices for future stock and portfolio returns. We believe this to be the first comprehensive study relating embedded risk premiums in cost-of-carry and put-call parity deviations to future stock returns. In addition, we test the possibility of a maturity dependent relation between the embedded risk premia and future returns. Overall, our results indicate that investors cannot profit from perceived mispricings in the SSF and option markets. The absence of a consistent relation between the implied risk premia and future returns implies that SSF and option markets are efficient in that any perceived mispricings in the SSF or option markets cannot be used to forecast future equity returns.
Author: Stephen J. Taylor
Publisher:
ISBN:
Category :
Languages : en
Pages : 64
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Book Description
The volatility information content of stock options for individual firms is measured using option prices for 149 U.S. firms during the period from January 1996 to December 1999. Volatility forecasts defined by historical stock returns, at-the-money (ATM) implied volatilities and model-free (MF) volatility expectations are compared for each firm. The recently developed model-free volatility expectation incorporates information across all strike prices, and it does not require the specification of an option pricing model.Our analysis of ARCH models shows that, for one-day-ahead estimation, historical estimates of conditional variances outperform both the ATM and the MF volatility estimates extracted from option prices for more than one-third of the firms. This result contrasts with the consensus about the informational efficiency of options written on stock indices; several recent studies find that option prices are more informative than daily stock returns when estimating and predicting index volatility. However, for the firms with the most actively traded options, we do find that the option forecasts are nearly always more informative than historical stock returns. When the prediction horizon extends until the expiry date of the options, our regression results show that the option forecasts are more informative than forecasts defined by historical returns for a substantial majority (86%) of the firms. Although the model-free (MF) volatility expectation is theoretically more appealing than alternative volatility estimates and has been demonstrated to be the most accurate predictor of realized volatility by Jiang and Tian (2005) for the Samp;P 500 index, the results for our firms show that the MF expectation only outperforms both the ATM implied volatility and the historical volatility for about one-third of the firms. The firms for which the MF expectation is best are not associated with a relatively high level of trading in away-from-the-money options.
Author: Allen M. Poteshman
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
We present strong evidence that option trading volume contains information about future stock prices. Taking advantage of a unique data set, we construct put-call ratios from option volume initiated by buyers to open new positions. Stocks with low put-call ratios outperform stocks with high put-call ratios by more than 40 basis points on the next day and more than 1% over the next week. Partitioning our option signals into components that are publicly and nonpublicly observable, we find that the economic source of this predictability is nonpublic information possessed by option traders rather than market inefficiency. We also find greater predictability for stocks with higher concentrations of informed traders and from option contracts with greater leverage.
Author: Joel S. Sternberg
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
A persistent anomaly in option pricing is the volatility skew. Many have attempted to explain it with stochastic volatility and/or jump diffusion models with mixed results. We propose a model that incorporates positive serial correlation in the stock price process and test it on empirical data for four quot;momentumquot; stocks and their heavily traded options. Although the notion of serial correlation seems to challenge the notion of arbitrage enforced option valuation, in fact, the existence of transaction costs, discontinuities and other frictions in the market allow for fairly wide arbitrage-free bounds on option prices. Within these bounds, serial correlation seems to explain not only the often-noted skew in stock option prices, but also the rarely noted upward bias of implied volatilities over actual volatilities.
Author: Anthony Sanford
Publisher:
ISBN:
Category :
Languages : en
Pages : 42
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Book Description
Finance researchers keep producing increasingly complex and computationally-intensive models of stock returns. Separately, professional analysts forecast stock returns daily for their clients. Are the sophisticated methods of researchers achieving better forecasts or are we better off relying on the expertise of analysts on the ground? Do the two sets of actors even capture the same information? In this paper, I hypothesize that analyst forecasts and forecasts constructed using option prices will be different because they draw on different information sets. Using hypothesis tests and quantile regressions, I find that option-based forecasts are statistically significantly different from analyst forecasts at every level of the forecast distribution. Then, using cross-sectional regressions, I show that this difference originates in the distinct information sets used to create the forecasts: option based forecasts incorporate information about the probability of extreme events while analyst forecasts focus on information about firm and macroeconomic fundamentals.
Author: Robert A. Jarrow
Publisher:
ISBN:
Category : Derivative securities
Languages : en
Pages : 472
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Book Description
Written by a number of authors, this text is aimed at market practitioners and applies the latest stochastic volatility research findings to the analysis of stock prices. It includes commentary and analysis based on real-life situations.
Author: Vladimir Kuzin
Publisher:
ISBN: 9783865585097
Category :
Languages : en
Pages : 0
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Author: Shigenori Shiratsuka
Publisher:
ISBN:
Category : Assets (Accounting)
Languages : en
Pages : 56
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