Averaged-Calibration-Length Prediction for Currency Exchange Rates by a Time-Dependent Vasicek Model

Machine Learning Vasicek Model Calibration with Gaussian Processes

In this paper we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The ma...

SVM Based Models for Predicting Foreign Currency Exchange Rates

Support vector machine (SVM) has appeared as a powerful tool for forecasting forex market and demonstrated better performance over other methods, e.g., neural network or ARIMA based model. SVM-based forecasting model necessitates the selection of appropriate kernel function and values of free parameters: regularization parameter and ε– insensitive loss function. In this paper, we investigate th...

Foreign Currency Exchange Rates Prediction Using CGP and Recurrent Neural Network

Neural Network Based Forecasting of Foreign Currency Exchange Rates

The foreign currency exchange market is the highest and most liquid of the financial markets, with an estimated $1 trillion traded every day. Foreign exchange rates are the most important economic indices in the international financial markets. The prediction of them poses many theoretical and experimental challenges. This paper reports empirical proof that a neural network model is applicable ...

Can currency-based risk factors help forecast exchange rates?

This paper examines the time series predictability of bilateral exchange rates from linear factormodels that utilize the unconditional and conditional expectations of three currencybased risk factors. Exploiting a comprehensive set of statistical criteria, we find that all versions of the linear factor models largely fail to outperform the benchmark random walk with drift model for the out-of-s...