We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the size of positive and negative jumps and...

We provide new empirical evidence on volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Leverage and volatility feedback effects of the S&P 500 price and volatility dynamics are examined using recently developed methodologies to...

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

The paper describes the specification, estimation, and testing of an unrestricted structural econometric model design to explain and forecast individual returns of securities listed on the Brazilian stock market. The model's explanatory variables include macroeconomic, fundamental and...

A daily log-return can be regarded as a test statistic - specifically the (unscaled) sample mean of a sequence of intraday random variables. We discuss sufficient conditions for a dependent bootstrap to consistently and non-parametrically estimate the entire distribution of this “test...

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

This paper proposes a double tree structured AR-GARCH model for the analysis of stock index return series, which extends previous approaches to incorporate (i) an arbitrary number of multivariate thresholds in conditional means and volatilities of stock index returns and (ii) a richer...

The accuracy of variance prediction depends on both the specification and the accuracy of parameter estimation. To predict stock return variance in a large and ever-changing universe, this paper proposes to replace the classic time-series dynamics specification per each name with a...

We propose a comprehensive empirical examination of the time-varying leading properties of two high yield spreads in the United States and compare them with the leading properties of the term spread between the mid-1980s and the end of 2011. We show that high yield spreads are not reliable...

In this research paper ARCH-type models and option implied volatilities (IV) are applied in order to estimate the Value-at-Risk (VaR) of a stock index futures portfolio for several time horizons. The relevance of the asymmetries in the estimated volatility estimation is considered. The empirical...