The theory of fair geometric returns, F theory for short, rejects the generally accepted notion that volatility is the risk of risky assets. Instead, it claims that capital market volatility, in turn, constitutes the maximum achievable geometric return. In order to get to the point, F theory, in...

This paper empirically examines the relationship between trading volume and conditional volatility of returns in the Tunisian stock market within the framework of the mixture of distribution hypothesis (MDH) and the sequential information arrival hypothesis (SIAH). Through this study, we...

In an empirical study of Standard & Poor's 500 index options, this paper analyses the predictability of future market excess returns by means of decomposed higher-moment risk premiums. The study proposes a new measure of kurtosis risk premium and suggests a decomposition of higher-moment risk...

This paper provides an empirical study on the predictability of implied volatility using dataset collected from the London over-the-counter currency option market. The present work is motivated by the lack of empirical studies that address implied volatility characteristics across various...

The research paper is an effort to review the relevance of option implied volatility in the modern day financial markets. Volatility indices such as VIX, VFTSE and India VIX act as efficient predictors of market volatility over the near term. The role implied volatility plays in providing a...

This article introduces the rough path-dependent volatility (RPDV) model, a model structurally adapted to jointly capture two major empirical features of volatility: its rough behavior and its path-dependence.After presenting it in its general form and its link with other existing models in the...

The investment industry lacks an unified framework for handling derivative instruments in general portfolio management. With the increased use of derivatives, there is a need for a framework that aligns fundamental terminology and concepts. The main challenges with the current practices are...

We investigate the pricing of risk-neutral skewness in the stock options market by creating skewness assets comprised of two option positions (one long and one short) and a position in the underlying stock. The assets are created such that exposure to changes in the price of the underlying stock...

We propose a nonparametric Bayesian approach for the estimation of the pricing kernel. Historical stock returns and option market data are combined through the Dirichlet Process (DP) to construct an option-adjusted physical measure. The precision parameter of the DP process is calibrated to the...

This study provides an in-depth analysis of how to estimate risk-neutral moments robustly. A simulation and an empirical study show that estimating risk- neutral moments presents a trade-off between (1) the bias of estimates caused by a limited strike price domain and (2) the variance of...