Why Do Option Prices Predict Stock Returns?

2012 ◽  
Author(s):  
Joost Driessen ◽  
Tse-Chun Lin ◽  
Xiaolong Lu
Keyword(s):  
Stock Returns ◽  
Option Prices

Option Prices, Takeover Announcements, and Stock Returns

2011 ◽  
Author(s):  
Edward J. Podolski ◽  
Cameron Truong ◽  
Madhu Veeraraghavan
Keyword(s):  
Stock Returns ◽  
Option Prices

STOCK RETURNS AND OPTION PRICES: AN EXPLORATORY STUDY

1990 ◽  
Vol 13 (3) ◽  
pp. 173-185 ◽  
Author(s):  
Esther Weinstock Ancel ◽  
Ramesh K. S. Rao
Keyword(s):  
Stock Returns ◽  
Exploratory Study ◽  
Option Prices

scholarly journals Why Do Option Prices Predict Stock Returns? The Role of Price Pressure in the Stock Market

2020 ◽  
Vol 66 (9) ◽  
pp. 3903-3926 ◽  
Author(s):  
Luis Goncalves-Pinto ◽  
Bruce D. Grundy ◽  
Allaudeen Hameed ◽  
Thijs van der Heijden ◽  
Yichao Zhu
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Option Price ◽  
Option Prices ◽  
Options Markets ◽  
Stock Return Predictability ◽  
Price Pressure ◽  
Primary Driver ◽  
Stock Values

Stock and options markets can disagree about a stock’s value because of informed trading in options and/or price pressure in the stock. The predictability of stock returns based on this cross-market discrepancy in values is especially strong when accompanied by stock price pressure, and it does not depend on trading in options. We argue that option-implied prices provide an anchor for fundamental stock values that helps to distinguish stock price movements resulting from pressure versus news. Overall, our results are consistent with stock price pressure being the primary driver of the option price-based stock return predictability. This paper was accepted by Tyler Shumway, finance.

Information Content of Skewness Risk Premium

2018 ◽  
Vol 26 (4) ◽  
pp. 391-423
Author(s):  
Seok Goo Nam ◽  
Byung Jin Kang
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Asset Returns ◽  
Investment Strategy ◽  
Investment Strategies ◽  
Option Prices ◽  
Underlying Asset ◽  
Variance Risk Premium ◽  
The Difference ◽  
Variance Risk

The variance risk premium defined as the difference between risk neutral variance and physical variance is one of the most crucial information recovered from option prices. It does not, however, reflect the asymmetry in upside and downside movements of underlying asset returns, and also has limitation in reflecting asymmetric preference of investors over gains and losses. In this sense, this paper decomposes variance risk premium into downside - and upside-variance risk premium, and then derives the skewness risk premium and examines its effectiveness in predicting future underlying asset returns. Using KOSPI200 option prices, we obtained the following results. First, we found out that the estimated skewness risk premium has meaningful forecasting power for future stock returns, while the estimated variance risk premium has little forecasting power. Second, by utilizing our results of skewness risk premium, we developed a profitable investment strategy, which verifies the effectiveness of skewness risk premium in predicting future stock returns. In conclusion, the empirical results of this paper can contribute to the literature in that it helps us understand why variance risk premium, in most global markets except the US market, has not been successful in forecasting future stock returns. In addition, our results showing the profitability of investment strategies based on skewness risk premium can also give important implications to practitioners.

scholarly journals The Equity Curve and Its Relation to Future Stock Returns

2020 ◽  
Vol 13 (2) ◽  
pp. 19
Author(s):  
Olaf Stotz
Keyword(s):  
Stock Returns ◽  
Term Structure ◽  
Investment Strategy ◽  
Absolute Difference ◽  
Option Prices ◽  
Positive Slope ◽  
Short Term ◽  
Theoretical Predictions ◽  
Expected Stock Returns

Using option prices, a new method for estimating the term structure of expected stock returns (equity curve) is proposed. We analyse how the equity curve relates to future stock returns and obtain three main results. First, a higher level of the equity curve is associated with higher future stock returns. Second, a positive slope is followed by future realized returns which are lower in the short term (1 month) than in the long term (1 quarter or 1 year). Third, a steeper slope (either positive or negative) is associated with a larger absolute difference between short-term and long-term returns. Therefore, the equity curve is consistent with theoretical predictions. We also analyse an investment strategy that uses the slope of the equity curve to determine the allocation to stocks. This strategy earns an outperformance of up to 200 basis points per annum.

Deviations from Put-Call Parity and Stock Return Predictability

2010 ◽  
Vol 45 (2) ◽  
pp. 335-367 ◽  
Author(s):  
Martijn Cremers ◽  
David Weinbaum
Keyword(s):  
Stock Returns ◽  
Implied Volatility ◽  
Option Prices ◽  
Stock Return Predictability ◽  
Put Options ◽  
Short Sale Constraints ◽  
Short Sale ◽  
The Difference ◽  
Underlying Stocks ◽  
Abnormal Performance

AbstractDeviations from put-call parity contain information about future stock returns. Using the difference in implied volatility between pairs of call and put options to measure these deviations, we find that stocks with relatively expensive calls outperform stocks with relatively expensive puts by 50 basis points per week. We find both positive abnormal performance in stocks with relatively expensive calls and negative abnormal performance in stocks with relatively expensive puts, which cannot be explained by short sale constraints. Rebate rates from the stock lending market directly confirm that our findings are not driven by stocks that are hard to borrow. The degree of predictability is larger when option liquidity is high and stock liquidity low, while there is little predictability when the opposite is true. Controlling for size, option prices are more likely to deviate from strict put-call parity when underlying stocks face more information risk. The degree of predictability decreases over the sample period. Our results are consistent with mispricing during the earlier years of the study, with a gradual reduction of the mispricing over time.

scholarly journals Testing the Information-Based Trading Hypothesis in the Option Market: Evidence from Share Repurchases

2019 ◽  
Vol 12 (4) ◽  
pp. 179 ◽  
Author(s):  
Badshah ◽  
Koerniadi ◽  
Kolari
Keyword(s):  
Stock Returns ◽  
Market Share ◽  
Private Information ◽  
Stock Prices ◽  
Implied Volatility ◽  
Share Repurchases ◽  
Share Repurchase ◽  
Open Market ◽  
Option Prices ◽  
Abnormal Stock Returns

The informed options trading hypothesis posits that option prices lead stock prices. In this paper, we extended the research on this hypothesis to open-market share repurchases. Empirical tests showed that the implied volatility spread was not significantly related to buy-and-hold abnormal stock returns. However, further evidence reveal a significant relationship between implied volatility spread and subsequent stock return volatility around open-market share repurchase events. We concluded that option traders have private information on the volatility of stock returns and superior information processing ability that accounts for prescient pricing behavior in options relative to stocks.

Stock Return Extrapolation, Option Prices, and Variance Risk Premium

2021 ◽  
Author(s):  
Adem Atmaz
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Stock Return ◽  
Dynamic Equilibrium ◽  
Investor Sentiment ◽  
Option Prices ◽  
Market Returns ◽  
Stock Market Returns ◽  
Variance Risk Premium ◽  
Variance Risk

Abstract This paper presents a tractable dynamic equilibrium model of stock return extrapolation in the presence of stochastic volatility. In the model, consistent with survey evidence, investors expect future returns to be higher (lower) but also less (more) volatile following positive (negative) stock returns. The biased volatility expectation introduces a new channel through which past returns and investor sentiment affect derivative prices. In particular, through this novel channel, the model reconciles the otherwise puzzling evidence of past returns affecting option prices and the evidence of variance risk premium predicting future stock market returns even after controlling for the realized variance.

Freedom Indices and Capital Asset Pricing Model: Some Malaysian Evidence

2020 ◽  
Vol 1 (1) ◽  
pp. 1-21
Author(s):  
Ying Tay Lee ◽  
Devinaga Rasiah ◽  
Ming Ming Lai
Keyword(s):  
Human Rights ◽  
Asset Pricing ◽  
Stock Returns ◽  
Firm Size ◽  
Explanatory Power ◽  
Least Square ◽  
Press Freedom ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Cross Sectional

Human rights and fundamental freedoms such as economic, political, and press freedoms vary widely from country to country. It creates opportunity and risk in investment decisions. Thus, this study is carried out to examine if the explanatory power of the model for capital asset pricing could be improved when these human rights movement indices are included in the model. The sample for this study comprises of 495 stocks listed in Bursa Malaysia, covering the sampling period from 2003 to 2013. The model applied in this study employed the pooled ordinary least square regression estimation. In addition, the robustness of the model is tested by using firm size as a controlled variable. The findings show that market beta as well as the economic and press freedom indices could explain the cross-sectional stock returns of the Malaysian stock market. By controlling the firm size, it adds marginally to the explanation of the extended CAP model which incorporated economic, political, and press freedom indices.

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