introduction: the relationship between different market levels is an essential issue in economy. understanding of linkages between different market levels will help to assess the potential impact of agricultural policies. given the importance of the vertical market relationship, the present study examines price volatility spillover in vertical market levels of iranian livestock and poultry mark...

We propose and test the idea that investor perceptions exhibit volatility ‘after-effects’ whereby perceived volatility is distorted after prolonged exposure to extreme volatility levels. Using VIX to measure perceived volatility in S&P 500 stocks, we find evidence of significant perceptual distortions in the aftermath of volatility regimes, consistent with the after-effect theory and recent exp...

Volatility characterizes the amplitude of price return fluctuations. It is a central magnitude in finance closely related to the risk of holding a certain asset. Despite its popularity on trading floors, volatility is unobservable and only the price is known. Diffusion theory has many common points with the research on volatility, the key of the analogy being that volatility is a time-dependent...

In this paper we use “Clustering Method” to understand whether stock market volatility can be predicted at all, and if so, when it can be predicted. The exercise has been performed for the Indian stock market on daily data for two years. For our analysis we map number of clusters against number of variables. We then test for efficiency of clustering. Our contention is that, given a fixed number...

Empirical volatility changes in time and exhibits tails, which are heavier than normal. Moreover, empirical volatility has sometimes quite substantial upwards jumps and clusters on high levels. We investigate classical and nonclassical stochastic volatility models with respect to their extreme behavior. We show that classical stochastic volatility models driven by Brownian motion can model heav...

Horizon-matched historical volatility is commonly used to forecast future volatility for option valuation under the Statement of Financial Accounting Standards 123R. In this paper, we empirically investigate the performance of using historical volatility to forecast long-term stock return volatility in comparison with a number of alternative forecasting methods. Analyzing forecasting errors and...

In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredict...

American electoral volatility is in a free fall. Overtime variation in the partisan balance of presidential elections across states has matched an all-time low in American history and is a fraction of its 1970’s peak. The current decline in volatility parallels declines during the Gilded Age and Franklin Roosevelt’s presidency. Trends in electoral volatility vary regionally, and the South’s pat...