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Do inflation expectations improve model-based inflation forecasts?

Bánbura, Marta; Leiva León, Danilo; Menz, Jan-Oliver

Las expectativas de inflación de los pronosticadores profesionales ayudan a mejorar las previsiones de inflación basadas en modelos. Para una amplia gama de modelos de series de tiempo para el área del euro y sus Estados miembros, encontramos una mayor precisión de pronóstico en los modelos...

Persistent link: https://www.econbiz.de/10012670001

Meese-Rogoff Redux: Micro-Based Exchange Rate Forecasting

Evans, Martin D.; Lyons, Richard K. - 2005

This paper compares the true, ex-ante forecasting performance of a micro-based model against both a standard macro … model and a random walk. In contrast to existing literature, which is focused on longer horizon forecasting, we examine … forecasting over horizons from one day to one month (the one-month horizon being where micro and macro analysis begin to overlap …

Persistent link: https://www.econbiz.de/10009440722

"Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange"

Bollerslev, T.; Andersen, T.G.; Diebold, F. X.; Vega, C. - 2003

Using a new dataset consisting of six years of real-time exchange rate quotations, macroeconomicexpectations, and macroeconomic realizations (announcements), we characterize the conditional means of U.S. dollar spot exchange rates versus German Mark, British Pound, Japanese Yen, Swiss Franc, and...

Persistent link: https://www.econbiz.de/10009475485

Are Exchange Rates Really Random Walks? Some Evidence Robust To Parameter Instability

Rossi, Barbara - 2006

Many authors have documented that it is challenging to explain exchange rate fluctuations with macroeconomic fundamentals: a random walk forecasts future exchange rates better than existing macroeconomic models. This paper applies newly developed tests for nested model that are robust to the...

Persistent link: https://www.econbiz.de/10009475539

A closed-form filter for binary time series

Fasano, Augusto; Rebaudo, Giovanni; Durante, Daniele; … - 2021

Non-Gaussian state-space models arise in several applications, and within this framework the binary time series setting provides a relevant example. However, unlike for Gaussian state-space models — where filtering, predictive and smoothing distributions are available in closed form — binary...

Persistent link: https://www.econbiz.de/10015214276

Beyond Conditional Second Moments: Does Nonparametric Density Modelling Matter to Portfolio Allocation?

Li, Chenxing; Maheu, John M - 2023

This paper investigates the economic importance of nonparametrically/semiparametrically modelling the shape and the change in the unknown distribution of returns in portfolio allocation problems from a Bayesian perspective. Besides parametric multivariate GARCH (MGARCH) benchmark models for...

Persistent link: https://www.econbiz.de/10015214743

An Infinite Hidden Markov Model with GARCH for Short-Term Interest Rates

Li, Chenxing; Yang, Qiao - 2025

This paper introduces a novel Bayesian time series model that combines the nonparametric features of an infinite hidden Markov model with the volatility persistence captured by the GARCH framework, to effectively model and forecast short-term interest rates. When applied to US 3-month Treasury...

Persistent link: https://www.econbiz.de/10015214745

Forecasting inflation in Mongolia: A dynamic model averaging approach

Doojav, Gan-Ochir; Luvsannyam, Davaajargal - 2017

This paper investigates the use of DMA approach for identifying good inflation predictors and forecasting inflation in … important role in forecasting inflation and change considerably over time and over forecast horizons. Second, among domestic …

Persistent link: https://www.econbiz.de/10015217259

Forecasting economy with Bayesian autoregressive distributed lag model: choosing optimal prior in economic downturn

Bušs, Ginters - 2009

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag (ADL) model is chosen. The results show that a...

Persistent link: https://www.econbiz.de/10015218160

Economic forecasts with Bayesian autoregressive distributed lag model: choosing optimal prior in economic downturn

Bušs, Ginters - 2009

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal Litterman prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag model is chosen. The results show that a...

Persistent link: https://www.econbiz.de/10015218632