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risk management purposes. We estimate GARCH models to capture the behavior of the conditional volatility. The expected …
Persistent link: https://www.econbiz.de/10014236565
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
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
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
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
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
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
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
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
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