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Keywords:out-of-sample forecasting OR Out-of-sample forecasting 

Working Paper
Forecasts of inflation and interest rates in no-arbitrage affine models

In this paper, we examine the forecasting ability of an affine term structure framework that jointly models the markets for Treasuries, inflation-protected securities, inflation derivatives, and oil future prices based on no-arbitrage restrictions across these markets. On the methodological side, we propose a novel way of incorporating information from these markets into an affine model. On the empirical side, two main findings emerge from our analysis. First, incorporating information from inflation options can often produce more accurate inflation forecasts than those based on the Survey of ...
FRB Atlanta Working Paper , Paper 2016-3

Working Paper
Trend-Cycle Decomposition and Forecasting Using Bayesian Multivariate Unobserved Components

We propose a generalized multivariate unobserved components model to decompose macroeconomic data into trend and cyclical components. We then forecast the series using Bayesian methods. We document that a fully Bayesian estimation, that accounts for state and parameter uncertainty, consistently dominates out-of-sample forecasts produced by alternative multivariate and univariate models. In addition, allowing for stochastic volatility components in variables improves forecasts. To address data limitations, we exploit cross-sectional information, use the commonalities across variables, and ...
Finance and Economics Discussion Series , Paper 2024-100

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C32 2 items

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