Robust Estimation in Nonlinear Modeling of Volatility Transmission in Stock Market S.B. Ebrahimi * Department of Industrial Engineering, K.N.Toosi University of Technology, Tehran, Iran * Email: [email protected] (Received: 12 September 2015; Revised: 8 May 2016; Accepted: 24 June 2016) Volatility transmission means the connection between different markets in a way that volatility can be tr...

This paper constitutes a first analysis on stock returns and stock return volatility of energy corporations from the Eurozone. According to our results, the gas market does not play a role for the pricing of Eurozone energy stocks. However, changes in the Euro to U.S. Dollar exchange rate as well as developments at the money and especially at the oil market strongly affect returns of the energy...

How does a surprise movement in stock market volatility affect our forecasts of future output across countries? This paper studies the time series and cross-sectional responses of output to variation in stock market volatility across 27 countries over 40 years, controlling for a number of country-specific characteristics. High levels of stock market volatility are detrimental to future output g...

In the financial market, the volatility of financial assets plays a key role in the problem of measuring market risk in many investment decisions. Insights into economic forces that may contribute to or amplify volatility are thus important. The financial market is characterized by regime switching between phases of low volatility and phases of high volatility. Nonlinearity and long memory are ...

This paper studies the volatility implications of the introduction of derivatives on stock market volatility in India using the S&P CNX Nifty Index as a benchmark. To account for non-constant error variance in the return series, a GARCH model is fitted by incorporating futures and options dummy variables in the conditional variance equation. We find clustering and persistence of volatility befo...

We propose a market-based approach to the modelling of implied volatility, in which the implied volatility surface is directly used as the state variable to describe the joint evolution of market prices of options and their underlying asset. We model the evolution of an implied volatility surface by representing it as a randomly fluctuating surface driven by a finite number of orthogonal random...

We study the cascading dynamics immediately before and immediately after 219 market shocks. We define the time of a market shock T{c} to be the time for which the market volatility V(T{c}) has a peak that exceeds a predetermined threshold. The cascade of high volatility "aftershocks" triggered by the "main shock" is quantitatively similar to earthquakes and solar flares, which have been describ...

Since its introduction in 2003, volatility indices such as the VIX based on the model-free implied volatility (MFIV) have become the industry standard for assessing equity market volatility. MFIV suffers from estimation bias which typically underestimates volatility during extreme market conditions due to sparse data for options traded at very high or very low strike prices, Jiang and Tian (200...

Article history: Received 23 August 2011 Received in revised form 16 April 2012 Accepted 19 April 2012 Available online 5 May 2012 This paper proposes a two-state Markov-switching model for stock market returns in which the state-dependent expected returns, their variance and associated regime-switching dynamics are allowed to respond to market information. More specifically, we apply this mode...