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Inflation uncertainty and disagreement in bond risk premia

D'Amico, Stefania; Orphanides, Athanasios - 2014

This paper examines the relation between variations in perceived inflation uncertainty and bond premia. Using the subjective probability distributions available in the Survey of Professional Forecasters we construct a quarterly time series of average individual uncertainty about inflation...

Persistent link: https://www.econbiz.de/10010441139

How Good Can Heuristic-Based Forecasts Be? A Comparative Performance of Econometric and Heuristic Models for UK and US Asset Returns

Guidolin, Massimo - 2017

This paper systematically investigates the sources of differential out-of-sample predictive accuracy of heuristic frameworks based on internet search frequencies and a large set of econometric models. The volume of internet searches helps gauge the degree of investors' time-varying interest in...

Persistent link: https://www.econbiz.de/10012972983

Real-Time Macroeconomic Data and Ex Ante Predictability of Stock Returns

Döpke, Jörg - 2016

Persistent link: https://www.econbiz.de/10012991193

Comparing models for forecasting the yield curve

Matsumura, Marco Shinobu; Moreira, Ajax - 2015

The evolution of the yields of different maturities is related and can be described by a reduced number of commom latent factors. Multifactor interest rate models of the finance literature, common factor models of the time series literature and others use this property. Each model has advantages...

Persistent link: https://www.econbiz.de/10012053243

Incorporating Model Uncertainty and Model Instability in Forecasting Bond Risk Premia and Term Structure of Government Bond Yield – A Bayesian Model Averaging Approach

Zhou, Hao (David) - 2012

This research investigates the macro factors for forecasting (1) bond risk premia and (2) term structure of government bond yields by using Bayesian Model Averaging (BMA) based on empirical prior. Different from the traditional variable selection approach which advocates finding an...

Persistent link: https://www.econbiz.de/10013113732

Sparse Multivariate Modeling for Stock Returns Predictability

Bernardi, Mauro; Bianchi, Daniele; Bianco, Nicolas - 2021

We develop a new variational Bayes estimation method for large-dimensional sparse vector autoregressive models with exogenous predictors. Unlike existing Markov chain Monte Carlo (MCMC) and variational Bayes (VB) algorithms, our approach is not based on a structural form representation of the...

Persistent link: https://www.econbiz.de/10013239660

A quantile-boosting approach to forecasting gold returns

Pierdzioch, Christian; Risse, Marian - In: The North American journal of economics and finance : a … 35 (2016), pp. 38-55

Persistent link: https://www.econbiz.de/10011672283

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

Commodity futures return predictability and intertemporal asset pricing

Cotter, John; Eyiah-Donkor, Emmanuel; Potì, Valerio - 2020

We find out-of-sample predictability of commodity futures excess returns using forecast combinations of 28 potential predictors. Such gains in forecast accuracy translate into economically significant improvements in certainty equivalent returns and Sharpe ratios for a mean-variance investor....

Persistent link: https://www.econbiz.de/10012418356

The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk

Dobrev, Dobrislav - 2011

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

Persistent link: https://www.econbiz.de/10013128339

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