Modeling and forecasting volatility of capital markets has been important area of inquiry and research in financial economics with the recognition of time-varying volatility, volatility clusturing, and asymmetric response of volatility to market movements. Given the anticipated growth of the Nepalese stock market and increasing interest of investors towards investment in Nepalese stock market, ...

This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility of volatility can be defined both non–parametrically, where we link it to the quadratic variation of the sto...

Using annual data from 1997–2014 of 30 provinces, municipalities, and autonomous regions, subdividing trended and cyclical volatility of macroeconomics and inflation, considering different indicators of financial development and financial structure, this paper investigated the impact of financial development and financial structure on macroeconomic volatility. The empirical results found that (...

Volatility in stock markets has been extensively studied in the applied finance literature. In this paper, Artificial Neural Network models based on various back propagation algorithms have been constructed to predict volatility in the Indian stock market through volatility of NIFTY returns and volatility of gold returns. This model considers India VIX, CBOE VIX, volatility of crude oil returns...

investing in stock markets usually is involved in more risks than the bounds and bank deposits. it is expected that resulting returns (capital gain plus yields) from trading in a stock market to be more than those of in a risk free investment. therefore, developing accurate techniques of estimation and forecasting in volatility analysis of financial markets is inevitable. sum squares of weekly ...

Various volatility estimators and models have been proposed in the literature to measure volatility of asset returns. In this paper, we compare empirical performance of various unconditional volatility estimators and conditional volatility models (GARCH and EGARCH) using time-series data of S&PCNX Nifty, a value-weighted index of 50 stocks traded on the National Stock Exchange (NSE), Mumbai. Th...

Given the price of a call or put option, the Black-Scholes implied volatility is the unique volatility parameter for which the Bulack-Scholes formula recovers the option price. This article surveys research activity relating to three theoretical questions: First, does implied volatility admit a probabilistic interpretation? Second, how does implied volatility behave as a function of strike and ...

In the paper we study the relationship between macroeconomic and stock market volatility, using S&P500 data for the period 1970-2001. We find weak evidence of long memory in volatility once structural change is accounted for and a twofold linkage between stock market and macroeconomic volatility: macroeconomic volatility explains the persitent dynamics in stock market volatility, while stock ma...