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A multivariate Kernel approach to forecasting the variance covariance of stock market returns

Becker, Ralf; Clements, Adam; O'Neill, Robert - In: Econometrics : open access journal 6 (2018) 1, pp. 1-27

This paper introduces a multivariate kernel based forecasting tool for the prediction of variance-covariance matrices of stock returns. The method introduced allows for the incorporation of macroeconomic variables into the forecasting process of the matrix without resorting to a decomposition of...

Persistent link: https://www.econbiz.de/10011823257

The factor-spline-GARCH model for high and low frequency correlations

Rangel, Jose Gonzalo; Engle, Robert F. - 2009

that characterize long-term correlation patterns. We associate such term behavior with low frequency economic variables … improves the empirical fit of equity correlations in the US and correlation forecasts at long horizons. -- Factor models ; Low … frequency volatilities and correlations ; Dynamic conditional correlation ; Spline-GARCH ; Idiosyncratic volatility ; Long …

Persistent link: https://www.econbiz.de/10003821063

Forecasting Risk with Markov-Switching GARCH Models : A Large-Scale Performance Study

Ardia, David - 2019

We perform a large-scale empirical study to compare the forecasting performance of single-regime and Markov-switching GARCH (MSGARCH) models from a risk management perspective. We find that, for daily, weekly, and ten-day equity log-returns, MSGARCH models yield more accurate Value-at-Risk,...

Persistent link: https://www.econbiz.de/10012902294

Flight to Safety in Volatility Forecasting

Ruzzi, Dario - 2018

The benefits of using flight-to-safety (FTS) in volatility forecasting are assessed within a multivariate GARCH framework. In particular, we propose realized semi-covariance between falling equity and rising safe haven returns as a proxy of FTS and we use it to model the conditional distribution...

Persistent link: https://www.econbiz.de/10012916710

Censored Posterior and Predictive Likelihood in Bayesian Left-Tail Prediction for Accurate Value at Risk Estimation

Gatarek, Lukasz T. - 2014

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

Persistent link: https://www.econbiz.de/10013064150

Censored posterior and predictive likelihood in Bayesian left-tail prediction for accurate value at risk estimation

Gatarek, Lukasz; Hoogerheide, Lennart; Hooning, Koen; … - 2013

Persistent link: https://www.econbiz.de/10009756308

Multivariate dynamic Copula models : parameter estimation and forecast evaluation

Aepli, Matthias Daniel; Frauendorfer, Karl; Füss, Roland; … - 2015 - This version: June 2015

dynamic conditional correlation model (DCC) to multivariate elliptical copulas. The most suitable dynamic dependence model in …

Persistent link: https://www.econbiz.de/10011344180

An Empirical Investigation of Asymmetric Volatility, Trading Volume and Risk-Return Relationship in the Indian Stock Market

Naik, Pramod Kumar - 2013

The objective of this article is to investigate the volatility asymmetry, volatility-volume relationship by considering trading volume as a mixing variable, and the risk-return relationship in the Indian stock market. Daily data from January 2, 1997 to May 30, 2013 for S&P CNX Nifty are used for...

Persistent link: https://www.econbiz.de/10013078205

Media attention vs. sentiment as drivers of conditional volatility predictions : an application to Brexit

Guidolin, Massimo; Pedio, Manuela - 2020

Using data on international, on-line media coverage and tone of the Brexit referendum, we test whether it is media coverage or tone to provide the largest forecasting performance improvements in the prediction of the conditional variance of weekly FTSE 100 stock returns. We find that versions of...

Persistent link: https://www.econbiz.de/10012487265

Value-at-risk predictive performance : a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets

Serrano Bautista, Ramona; Núñez Mora, José Antonio - In: Journal of economics, finance & administrative science 26 (2021) 52, pp. 197-221

Purpose - This paper tests the accuracies of the models that predict the Value-at-Risk (VaR) for the Market Integrated Latin America (MILA) and Association of Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods. Design/methodology/approach - Many VaR estimation models...

Persistent link: https://www.econbiz.de/10012813839