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Forecasting Value-at-Risk and Expected Shortfall of Cryptocurrencies using Combinations based on Jump-Robust and Regime-Switching Models

Trucíos, Carlos; Taylor, James W. - 2021

more than a single regime, have performed substantially better than standard methods in terms of volatility and Value …

Persistent link: https://www.econbiz.de/10013242299

Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios : A General Dynamic Factor Model Approach

Hallin, Marc; Trucíos, Carlos - 2021

Beyond their importance from the regulatory policy point of view, Value-at-Risk (VaR) and Expected Shortfall (ES) play an important role in risk management, portfolio allocation, capital level requirements, trading systems, and hedging strategies. Unfortunately, due to the curse of...

Persistent link: https://www.econbiz.de/10013242339

Multiple-Days-Ahead Value-At-Risk and Expected Shortfall Forecasting for Stock Indices, Commodities and Exchange Rates : Inter-Day Versus Intra-Day Data

Degiannakis, Stavros Antonios - 2018

-day and intra-day volatility models by estimating the AR(1)-GARCH(1,1)-skT and the AR(1)-HAR-RV-skT frameworks, respectively … intra-day volatility model is not as appropriate as it was expected to be for each of the different asset classes; stock … performance of the inter-day and intra-day volatility models across various markets. The inter-day specification predicts and …

Persistent link: https://www.econbiz.de/10012910113

Predicting Tail Risks by a Markov Switching MGARCH Model with Varying Copula Regimes

Fülle, Markus J.; Herwartz, Helmut - 2022

pandemic. We find that the MS-C-MGARCH model outperforms benchmark volatility models (MGARCH, C-MGARCH) in predicting expected …

Persistent link: https://www.econbiz.de/10013405757

The choice of GARCH models to forecast value-at-risk for currencies (euro exchange rates), crypto assets (Bitcoin and Ethereum), gold, silver and crude oil : automated processes, statistical distribution models and the specification of the mean equation

Gohs, Andreas Marcus - 2022

Regular or automated processes require reliable software applications that provide accurate volatility and Value …

Persistent link: https://www.econbiz.de/10013474092

GARCH models for daily stock returns : impact of estimation frequency on value-at-risk and expected shortfall forecasts

Ardia, David; Hoogerheide, Lennart - 2013

Persistent link: https://www.econbiz.de/10010191413

GARCH Models for Daily Stock Returns : Impact of Estimation Frequency on Value-at-Risk and Expected Shortfall Forecasts

Ardia, David - 2020

We analyze the impact of the estimation frequency - updating parameter estimates on a daily, weekly, monthly or quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily returns for constituents of the S&P 500 index. We assess the...

Persistent link: https://www.econbiz.de/10012857089

The Role of High-Frequency Prices, Long Memory and Jumps for Value-at-Risk Prediction

Fuertes, Ana-Maria - 2012

such as the realized volatility and squared overnight returns, are confronted with those from ARFIMA realized volatility …

Persistent link: https://www.econbiz.de/10013105936

Large mixed-frequency VARs with a parsimonious time-varying parameter structure

Götz, Thomas B.; Hauzenberger, Klemens - 2018

To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...

Persistent link: https://www.econbiz.de/10011903709

Assessing the Accuracy of Exponentially Weighted Moving Average Models for Value-at-Risk and Expected Shortfall of Crypto Portfolios

Alexander, Carol; Dakos, Michael - 2022

, provided they capture an asymmetric volatility response and a heavy-tailed returns distribution. Moreover, on ranking each …

Persistent link: https://www.econbiz.de/10013292091