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In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in …
Persistent link: https://www.econbiz.de/10012127861
autocorrelations. We also show that shifting ER implies biased cross-autocorrelation, and find supporting evidence for this phenomenon …
Persistent link: https://www.econbiz.de/10013405361
We perform a comprehensive examination of the recursive, comparative predictive performance of a number of linear and non-linear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STR) regime switching models,...
Persistent link: https://www.econbiz.de/10008990694
We develop an exact and distribution-free procedure to test for quantile predictability at several quantile levels jointly, while allowing for an endogenous predictive regressor with any degree of persistence. The approach proceeds by combining together the quantile regression t-statistics from...
Persistent link: https://www.econbiz.de/10012946689
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...
Persistent link: https://www.econbiz.de/10012487589
This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous autoregressive model (HAR) framework. We show that periodicity inflates the variance of the realized volatility and biases jump estimators. This combined effect adversely affects...
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