A mixed-frequency approach for exchange rates predictions

06/01/2021
by   Raffaele Mattera, et al.
0

Selecting an appropriate statistical model to forecast exchange rates is still today a relevant issue for policymakers and central bankers. The so-called Meese and Rogoff puzzle assesses that exchange rate fluctuations are unpredictable. In the literature, a lot of studies tried to solve the puzzle finding alternative predictors and statistical models based on temporal aggregation. In this paper, we propose an approach based on mixed frequency models to overcome the lack of information caused by temporal aggregation. We show the effectiveness of our approach in comparison with other proposed methods by performing CAD/USD exchange rate predictions.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/31/2017

Proceedings of the Data For Good Exchange 2017

These are the proceedings of the Data For Good Exchange 2017, which was ...
research
05/19/2020

On the Theoretical Properties of the Exchange Algorithm

Exchange algorithm is one of the most popular extensions of Metropolis-H...
research
08/09/2018

Non-Interfering Concurrent Exchange (NICE) Networks

In studying the statistical frequency of exchange in comparison-exchange...
research
12/31/2022

Wealth Redistribution and Mutual Aid: Comparison using Equivalent/Nonequivalent Exchange Models of Econophysics

Given the wealth inequality worldwide, there is an urgent need to identi...
research
02/10/2022

Semidirect Product Key Exchange: the State of Play

In this report we survey the various proposals of the key exchange proto...
research
06/18/2019

Multiscale cross–correlations and triangular arbitrage opportunities in the Forex

Multifractal Detrended Cross-Correlation methodology is applied to the f...

Please sign up or login with your details

Forgot password? Click here to reset