-to-date market data. Arguably, the most important variable in the valuation of embedded equity derivatives is implied volatility …. However, accurate long-term volatility estimation is difficult because of a general lack of tradable, liquid medium- and long … a comprehensive, critical evaluation of the long-term volatility models most commonly used in practice, encompassing …

In this paper, we challenge the traditional assumption of a linear relationship between exchange rate volatility and … volatility positively and significantly influences economic growth when growth in government spending is below 6 percent. Above … this 6 percent threshold, volatility exerts an insignificant effect on economic growth. In light of the adoption of a free …

and Heston's stochastic volatility model. Leveraging a total of five years of individual equity and index option data, and …-of-sample hedging errors than competing models. This comparison includes versions of Markov Tree and Black-Scholes models in which … accurate and less risky single instrument hedges than Heston's stochastic volatility model. A statistical resampling method …

With the innovation of derivatives, the Standard and Poor's (S&P) 500 index -- as an underlying asset of the volatility …. Since the financial crisis of 2008, the degree of market volatility has increased substantially. In addition, a random … different hedging strategies based on different diffusion models …

, Dow-Jones, Nikkei, S&P 500, Brent, and WTI futures can be effective hedging instruments. We use a wavelet-based dynamic … hedging model to account for heterogeneous investors in the Bitcoin market. For a short-term horizon, soybean futures reduce … are the best for in-sample hedging in a long-term horizon, whereas live cattle futures have the best out …

This study investigated the impact of investor sentiment impact on sectoral returns and their volatility on the … to consider the impact of market-wide investor sentiment on volatility and returns. …