فراتحليلي بر محتواي اطلاعاتي نوسانات ضمني سهام

Abstract Statistical characteristics of asset returns—such as skewness, mean, kurtosis, an‎d volatility—encapsulate important stylized facts about financial assets. Among these, the estimation an‎d forecasting of volatility has evolved into a major area of theoretical an‎d empirical research over the past few decades an‎d therefore constitutes the focus of the present meta analysis. This topic is of substantial interest to academics, market regulators, practitioners, an‎d policy makers, since volatility plays a central role across a wide range of research domains an‎d financial decision making problems, including derivative pricing, asset pricing, stock price forecasting, risk hedging, portfolio management, an‎d asset allocation. For instance, in the context of hedging, accurate forecasts of stock market volatility enable firms an‎d investors to form a more precise understan‎ding of the risks they face an‎d to design more effective hedging policies. Employing a meta analytic framework, this study is conducted in seven stages: defining the research topic an‎d target population; systematically collecting relevant studies; screening an‎d selec‎ting eligible empirical works; extracting the outcome measures an‎d contextual characteristics of each study; computing individual effect sizes; estimating the overall (pooled) effect size; an‎d, finally, assessing the homogeneity an‎d heterogeneity of effect sizes across studies. The statistical population consists of all empirical studies examining the information content of stock implied volatility published between 1993 an‎d 2021. In total, 16 studies met the inclusion criteria for the final analysis, from which 274 effect sizes were extracted. These effect sizes were then computed an‎d analyzed using the CMA software to test the five research hypotheses. The findings indicate that implied volatility is informationally rich: investors can exploit implied volatility to forecast the future realized volatility of the underlying asset. However, the magnitude of the information content of implied volatility is heterogeneous an‎d context dependent, an‎d can be enhanced by altering test conditions. For example, investors may obtain higher informational content by focusing on at the money (ATM) call options, call options with shorter maturities, an‎d measures of realized volatility based on broad stock market indices. Keywords: Meta‑analysis, Information Content, Implied Volatility, Historical Volatility.

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