Abstract not found

The efficient market hypothesis has been widely tested and, with few exceptions, found consistent with the data in a wide variety of markets: the New York and American Stock Exchanges, the Australian, English, and German stock markets, various commodity futures markets, the Over-the-Counter markets, the corporate and government bond markets, the option market, and the market for seats on the New York Stock Exchange. Yet, in a manner remarkably similar to that described by Thomas Kuhn in his book, The Structure of Scientific Revolutions, we seem to be entering a stage where widely scattered and as yet incohesive evidence is arising which seems to be inconsistent with the theory. As better data become available (e.g., daily stock price data) and as our econometric sophistication increases, we are beginning to find inconsistencies that our cruder data and techniques missed in the past. It is evidence which we will not be able to ignore. The purpose of this special issue of the Journal of Financial Economics is to bring together a number of these scattered pieces of anomalous evidence regarding Market Efficiency. As Ball (1978) points out in his survey article: taken individually many scattered pieces of evidence on the reaction of stock prices to earnings announcements which are inconsistent with the theory don’t amount to much. Yet viewed as a whole, these pieces of evidence begin to stack up in a manner which make a much stronger case for the necessity to carefully review both our acceptance of the efficient market theory and our methodological procedures.

pp.567-611. Contents

In this paper a stochastic volatility model is presented that directly prescribes the stochastic development of the implied Black-Scholes volatilities of a set of given standard options. Thus the model is able to capture the stochastic movements of a full term structure of implied volatilities. The conditions are derived that have to be satisfied to ensure absence of arbitrage in the model and its numerical implementation is discussed.

Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the S&P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a non-zero market price of volatility risk. It is widely believed that option prices provide the best forecasts of the future volatility of the assets which underlie them. One reason for this belief is that option prices have the ability to impound all publicly available information – including all information contained in the history of past prices – about the future volatility of the underlying assets. A second related reason is that option pricing theory maintains that if an option prices fails to embody optimal forecasts of the future volatility of the underlying asset, a profitable trading strategy should be available whose implementation would push the option price to the level that reflects the best possible forecast of future volatility.

In this paper, we examine the use of GARCH models, Neural Network Regression (NNR), Recurrent Neural Network (RNN) regression and model combinations for forecasting and trading currency volatility, with an application to the GBP/USD and USD/JPY exchange rates. Both the results of the NNR/RNN models and the model combination results are benchmarked against the simpler GARCH alternative. The idea of developing a nonlinear nonparametric approach to forecast FX volatility, identify mispriced options and subsequently develop a trading strategy based upon this process is intuitively appealing. Using daily data from December 1993 through April 1999, we develop alternative FX volatility forecasting models. These models are then tested out-of-sample over the period April 1999-May 2000, not only in terms of forecasting accuracy, but also in terms of trading efficiency: In order to do so, we apply a realistic volatility trading strategy using FX option straddles once mispriced options have been identified. Allowing for transaction costs, most trading strategies retained produce positive returns. RNN models appear as the best single modelling approach yet, somewhat surprisingly, model combination which has the best overall performance in terms of forecasting accuracy, fails to improve the RNN-based volatility trading results. Another conclusion from our results is that, for the period and currencies considered, the currency option market was inefficient and/or the pricing formulae applied by market participants were inadequate.

Abstract not found

Abstract. After a brief review of option pricing theory, weintroduce various methods proposed for extracting the statistical information implicit in options prices. We discuss the advantages and drawbacks of each method, the interpretation of their results in economic terms, their theoretical consequences and their relevance for applications. 1.

Interpretating probability density functions (PDFs) extracted from currency options data is ambiguous because PDFs combine risk neutral market views regarding the likelihood of particular exchange rate outcomes with investors ’ preferences towards risk. In order to disentangle the two effects, market expectations derived for option prices need to adjusted for the time-varying volatility risk premium that compensates risk averse option writers. Assuming rational expectations this risk premium can be extracted ex-post. The implied volatility bid-ask spread and volatility of implied volatility are considered here as proxies for the risk premium to enable the ex-ante adjustment of risk-neutral exchange rate expectations for risk preferences. The method is applied to demonstrate the impact of this adjustment on exchange rate expectations around Hong Kong SAR’s equity market intervention in 1998. The risk premium explains part of the bias found in existing empirical studies of the predictability of future realized volatility by implied volatility.

Abstract not found