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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

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

Equity Premium Predictions with Adaptive Macro Indexes

Bai, Jennie - 2014

Fundamental economic conditions are crucial determinants of equity premia. However, commonly used predictors do not adequately capture the changing nature of economic conditions and hence have limited power in forecasting equity returns. To address the inadequacy, this paper constructs macro...

Persistent link: https://www.econbiz.de/10013069149

Time-frequency Forecast of the Equity Premium

Faria, Gonçalo - 2020

Any time series can be decomposed into cyclical components fluctuating at different frequencies. Accordingly, in this paper we propose a method to forecast the stock market's equity premium which exploits the frequency relationship between the equity premium and several predictor variables. We...

Persistent link: https://www.econbiz.de/10012835434

Forecasting the Equity Premium with Frequency-Decomposed Technical Indicators

Stein, Tobias - 2020

Technical trading rules are widely used by practitioners to forecast the U.S. equity premium. I decompose technical indicators into components with frequency-specific information, showing that the predictive power comes from medium-frequency variation in buy and sell signals, without much...

Persistent link: https://www.econbiz.de/10012839601

The Variance Risk Premium and Fundamental Uncertainty

Conrad, Christian - 2015

We propose a new measure of the expected variance risk premium that is based on a forecast of the conditional variance from a GARCH-MIDAS model. We find that the new measure has strong predictive ability for future U.S. aggregate stock market returns and rationalize this result by showing that...

Persistent link: https://www.econbiz.de/10013027179

Machine Learning Predictions of Credit and Equity Risk Premia

Kita, Arben - 2021

The emergence of algorithmic high-frequency trading in the market for credit risk affords accurate inference of new risk measures. When combined with machine learning predictive methods, these measures forecast substantial future changes in firms' credit and equity risk premiums in...

Persistent link: https://www.econbiz.de/10013240829

Equity premium prediction : The role of information from the options market

Alexandridis, Antonios; Apergis, Iraklis; Panopoulou, … - 2022

This paper examines the role of information from the options market in forecasting the equity premium. We provide empirical evidence that the equity premium is predictable out-of-sample using a set of CBOE strategy benchmark indices as predictors. We use a range of econometric approaches to...

Persistent link: https://www.econbiz.de/10013289582

Time-frequency forecast of the equity premium

Faria, Gonçalo; Verona, Fabio - 2020

Persistent link: https://www.econbiz.de/10012208225

Diverging roads: theory-based vs. machine learning-implied stock risk premia

Grammig, Joachim; Hanenberg, Constantin; Schlag, Christian - 2020

We assess financial theory-based and machine learning-implied measurements of stock risk premia by comparing the … preferable to rely on a theory-based approach instead of engaging in the computerintensive hyper-parameter tuning of statistical … models. The theory-based approach also delivers a solid performance at the one year horizon, at which only one machine …

Persistent link: https://www.econbiz.de/10012163064

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