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Forecasting aggregate productivity using information from firm-level data

Bartelsman, Eric J.; Wolf, Zoltán - 2009

This paper contributes to the productivity literature by using results from firm-level productivity studies to improve forecasts of macro-level productivity growth. The paper employs current research methods on estimating firm-level productivity to build times-series components that capture the...

Persistent link: https://www.econbiz.de/10011378362

Forecasting Aggregate Productivity Using Information from Firm-Level Data

Bartelsman, Eric J. - 2017

Persistent link: https://www.econbiz.de/10012976846

Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices

Gatarek, Lukasz T. - 2014

risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one … uncertainty with risk and return of stock trading. In terms of methodology, we show the effect that using an encompassing prior … better results in terms of profit per capital engagement and risk than using a standard linear normalization …

Persistent link: https://www.econbiz.de/10013056713

Bayesian risk forecasting for long horizons

Borowska, Agnieszka; Hoogerheide, Lennart; Koopman, Siem Jan - 2019

risk. The key insight behind our importance sampling based approach is the sequential construction of marginal and …We present an accurate and efficient method for Bayesian forecasting of two financial risk measures, Value-at-Risk and … Expected Shortfall, for a given volatility model. We obtain precise forecasts of the tail of the distribution of returns not …

Persistent link: https://www.econbiz.de/10011979983

Bayesian Forecasting with Highly Correlated Predictors

Korobilis, Dimitris - 2012

This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms

Persistent link: https://www.econbiz.de/10013099177

A Bayesian infinite hidden Markov vector autoregressive model

Nibbering, Didier; Paap, Richard; Wel, Michel van der - 2016

We propose a Bayesian infinite hidden Markov model to estimate time- varying parameters in a vector autoregressive model. The Markov structure allows for heterogeneity over time while accounting for state-persistence. By modelling the transition distribution as a Dirichlet process mixture model,...

Persistent link: https://www.econbiz.de/10011569148