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Forecasting USD/EUR FX Rate Volatilities
Park, Jungjun - 2022
risk management purposes. We estimate GARCH models to capture the behavior of the conditional volatility. The expected …
Persistent link: https://www.econbiz.de/10014236565
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Forecasting Exchange Rates : An Investor Perspective
Melvin, Michael - 2013
rates approach forecasting from a different perspective. Rather than focus on forecast errors for bilateral exchange rates … perspective, a particular approach to quantitative modeling is presented that incorporates return forecasts, a risk model, and a …
Persistent link: https://www.econbiz.de/10013081705
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Forecasting Foreign Exchange Rate Assuming PPP Conditions : Empirical Evidence Using VAR
Fayad, Catherine - 2010
data) between the PPP-based forecast models, and the Vector Autoregresive (VAR) ones. The VAR method has a better …
Persistent link: https://www.econbiz.de/10013152799
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Can We Beat the Random Walk? The Case of Survey-Based Exchange Rate Forecasts in Chile
Pincheira, Pablo M. - 2018
We examine the accuracy of survey-based expectations of the Chilean exchange rate relative to the US dollar. Our out-of-sample analysis reveals that survey-based forecasts outperform the Driftless Random Walk (DRW) in terms of Mean Squared Prediction Error at several forecasting horizons. This...
Persistent link: https://www.econbiz.de/10012906841
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The Role of Technical Indicators in Exchange Rate Forecasting
Panopoulou, Ekaterini - 2017
Forecasting exchange rates is a subject of wide interest to both academics and practitioners. We aim at contributing to this vivid research area by highlighting the role of both technical indicators and macroeconomic predictors in forecasting exchange rates. Employing monthly data ranging from...
Persistent link: https://www.econbiz.de/10012945988
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Forecasting Realized Volatility with wavelet decomposition
Souropanis, Ioannis; Vivian, Andrew - 2021
Forecasting Realized Volatility (RV) is of paramount importance for both academics andpractitioners. During recent decades, academic literature has made substantial progressboth in terms of methods and predictors under consideration. Despite the popularity oftechnical indicators, there has been...
Persistent link: https://www.econbiz.de/10013244692
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An application of deep learning for exchange rate forecasting
Claveria, Oscar; Monte, Enric; Sorić, Petar; Torra, … - 2022
This paper examines the performance of several state-of-the-art deep learning techniques for exchange rate forecasting (deep feedforward network, convolutional network and a long short-term memory). On the one hand, the configuration of the different architectures is clearly detailed, as well as...
Persistent link: https://www.econbiz.de/10013296645
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Modeling and Forecasting Realized Portfolio Weights
Golosnoy, Vasyl; Gribisch, Bastian - 2020
We propose direct multiple time series models for predicting high dimensional vectors of observable realized global minimum variance portfolio (GMVP) weights computed based on high-frequency intraday returns. We apply Lasso regression techniques, develop a class of multiple AR(FI)MA models for...
Persistent link: https://www.econbiz.de/10014352129
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Analysts versus the random walk in financial forecasting : evidence from the Czech National Bank's Financial Market Inflation Expectations Survey
Kladívko, Kamil; Österholm, Pär - 2022
Inflation Expectations survey perform relative to the random-walk forecast when it comes to predicting five financial variables …-walk forecast for the repo rate and Prague Interbank Offered Rate at the onemonth forecasting horizon. For the five-year and ten … horizons. For the CZE/EUR exchange rate, no statistically significant differences in forecast precision were found. …
Persistent link: https://www.econbiz.de/10013469611
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Graph Neural Networks for Forecasting Realized Volatility with Nonlinear Spillover Effects
Zhang, Chao; Pu, Xingyue (Stacy); Cucuringu, Mihai; … - 2023
We propose a novel methodology for modeling and forecasting multivariate realized volatilities using graph neural networks. This approach extends the work of Zhang et al. [2022] (Graph-based methods for forecasting realized covariances) and explicitly incorporates the spillover effects from...
Persistent link: https://www.econbiz.de/10014265206