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Author: Turan G. Bali
Publisher:
ISBN:
Category :
Languages : en
Pages : 71
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Book Description
Motivated by the nature of asset pricing models, we investigate the cross-sectional relation between the market's ex-ante view of a stock's risk and the stock's ex-ante expected return. We demonstrate that an ex-ante measure of expected returns based on analyst price targets is highly related to the market's required rate of return. Using this measure, we show that ex-ante measures of volatility, skewness, and kurtosis derived from option prices are positively related to ex-ante expected returns. We then decompose the risk measures into systematic and unsystematic components and find that while expected returns are related to both systematic and unsystematic variance risk, only the unsystematic components of skewness and kurtosis are important for explaining the cross-section of expected stock returns. The results are consistent using two different approaches to measuring ex-ante risk and robust to controls for other variables related to stock returns and analyst bias.
Author: Turan G. Bali
Publisher:
ISBN:
Category :
Languages : en
Pages : 71
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Book Description
Motivated by the nature of asset pricing models, we investigate the cross-sectional relation between the market's ex-ante view of a stock's risk and the stock's ex-ante expected return. We demonstrate that an ex-ante measure of expected returns based on analyst price targets is highly related to the market's required rate of return. Using this measure, we show that ex-ante measures of volatility, skewness, and kurtosis derived from option prices are positively related to ex-ante expected returns. We then decompose the risk measures into systematic and unsystematic components and find that while expected returns are related to both systematic and unsystematic variance risk, only the unsystematic components of skewness and kurtosis are important for explaining the cross-section of expected stock returns. The results are consistent using two different approaches to measuring ex-ante risk and robust to controls for other variables related to stock returns and analyst bias.
Author: Turan G. Bali
Publisher:
ISBN:
Category :
Languages : en
Pages : 67
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Book Description
We develop an ex-ante measure of expected stock returns based on analyst price targets. We then show that ex-ante measures of volatility, skewness, and kurtosis implied from stock option prices are positively related to the cross section of ex-ante expected stock returns. While expected returns are related to both the systematic and unsystematic components of volatility, only the unsystematic components of skewness and kurtosis are related to the cross section of expected stock returns after controlling for other variables known to be related to the cross section of expected stock returns or analyst forecast bias.
Author: Patricia Dechow
Publisher:
ISBN:
Category :
Languages : en
Pages : 54
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Book Description
We investigate the determinants of analysts' target price implied returns and the implication of our findings for investment decision-making. We identify four broad sets of factors that help explain the cross-sectional variation in target price implied returns: future realized stock returns, errors in forecasting fundamentals, errors in forecasting the expected return to risk, and biases relating to analysts' incentives. Our results suggest that all four sets help explain target price implied returns, with errors in forecasting the expected return to empirical risk proxies having the greatest impact. Collectively, these variables explain nearly a quarter of the cross-sectional variation in target price implied returns. We use our model to predict the optimistic bias in target price implied returns and evaluate whether investors correctly ignore the predictable bias. The results suggest that investors make similar valuation errors to analysts and/or do not perfectly back out the predicted bias in target prices.
Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080550673
Category : Business & Economics
Languages : en
Pages : 299
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Book Description
Forecasting returns is as important as forecasting volatility in multiple areas of finance. This topic, essential to practitioners, is also studied by academics. In this new book, Dr Stephen Satchell brings together a collection of leading thinkers and practitioners from around the world who address this complex problem using the latest quantitative techniques. *Forecasting expected returns is an essential aspect of finance and highly technical *The first collection of papers to present new and developing techniques *International authors present both academic and practitioner perspectives
Author: Grigory Vilkov
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above other option-implied variables. Stock-specific tail loss measure predicts individual expected returns and magnitude of realized stock-specific crashes in the cross-section of stocks. An investor that cares about the left tail of her wealth distribution benefits from using the tail loss measure as an information variable to construct managed portfolios of a risk-free asset and market index.
Author: Tim Bollerslev
Publisher:
ISBN:
Category : Stocks
Languages : en
Pages : 58
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Book Description
Author: David Lando
Publisher: Princeton University Press
ISBN: 1400829194
Category : Business & Economics
Languages : en
Pages : 328
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Book Description
Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand, and on a direct modeling of the default probability of issuers on the other. He offers insights that can be drawn from each approach and demonstrates that the distinction between the two approaches is not at all clear-cut. The book strikes a fruitful balance between quickly presenting the basic ideas of the models and offering enough detail so readers can derive and implement the models themselves. The discussion of the models and their limitations and five technical appendixes help readers expand and generalize the models themselves or to understand existing generalizations. The book emphasizes models for pricing as well as statistical techniques for estimating their parameters. Applications include rating-based modeling, modeling of dependent defaults, swap- and corporate-yield curve dynamics, credit default swaps, and collateralized debt obligations.
Author: Hui Guo
Publisher:
ISBN:
Category :
Languages : en
Pages : 77
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Book Description
Using options-implied variance, a forward-looking measure of conditional variance, we revisit the debate on the idiosyncratic risk-return relation. In both cross-sectional (for individual stocks) and time-series (for the market index) regressions, we find a negative relation between options-implied variance and future stock returns. Consistent with Miller's (1977) divergence of opinion hypothesis, the negative relation gets stronger (1) for stocks with more stringent short-sale constraints or (2) when shorting stocks becomes more difficult. Moreover, the negative correlation of realized idiosyncratic variance or analyst forecast dispersion with future stock returns mainly reflects their close correlation with our conditional idiosyncratic variance measure.
Author: Thomas W. Sampson
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This paper uses regression analysis to examine the relationship between today's implied volatility on AMD stock options with tomorrow's return on the underlying. An economic analyis of the options markets' micro-structure is discussed to establish the intuition and the basis behind the relationship. Four seperate models are developed to examine its statistical significance and the ability of options' prices to accurately forecast returns on the underlying security. The hypothesis of the paper is that daily changes in implied volatility can be used to earn higher than expected returns on the underlying stock. I find that implied volatility can be used to increase forecasting accuracy and may proved a means by which the Efficient Markets Hypothesis can be refuted.
Author: Johnathan Loudis
Publisher:
ISBN:
Category :
Languages : en
Pages : 153
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Book Description
This paper provides evidence that the market does not efficiently incorporate expected returns implied by analyst price targets into prices. I use a novel decomposition to extract information and bias components from these analyst-expected returns and develop an asset pricing framework that helps interpret price reactions to each component. A one-standard-deviation increase in the information (bias) component is associated with a five (one) percentage point increase in announcement-month returns. The positive reaction to bias implies the market does not fully debias analyst-expected returns before incorporating them into prices. Prices overreact to bias and reverse their initial reaction within three to six months. Prices underreact to information and returns drift an additional one percentage point beyond their initial reaction in the following 12 months. Announcement-window returns forecast future returns, which provides model-free evidence of underreaction, and that underreaction dominates overreaction. Trading against underreaction generates average monthly returns of 1.12% with a Sharpe ratio of 1.08, and the returns survive controlling for exposure to many standard factors.
