Exchange Rate Forecasting via a Machine Learning Approach
نویسندگان
چکیده
This paper attempts to forecast exchange rates by applying a machine learning approach. More specifically, in this study, we attempt the dynamic evolutions of four Canadian dollars, Australian Great Britain pounds, and euros, which are all against US dollar, using random forest methodology. Evaluating effectiveness, find that predictive performance approach rate forecasting is rather high.
منابع مشابه
A hybrid computational intelligence model for foreign exchange rate forecasting
Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...
متن کاملWavelet Based Exchange Rate Forecasting with Improved Instance Based Learning
In this paper we present a novel wavelet based exchange rate forecast model integrating wavelet filters for denoising and Improved Instance Based Learning(IIBL) approach. The proposed model implements a novel technique that extends the nearest neighbor algorithm to include the concept of pattern matching so as to identify similar instances thus implementing a nonparametric regression approach.T...
متن کاملA Machine Learning Approach for Virtual Flow Metering and Forecasting
We are concerned with robust and accurate forecasting of multiphase flow rates in wells and pipelines during oil and gas production. In practice, the possibility to physically measure the rates is often limited; besides, it is desirable to estimate future values of multiphase rates based on the previous behavior of the system. In this work, we demonstrate that a Long Short-Term Memory (LSTM) re...
متن کاملA Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health
Drought threatens food and water security around the world, and this threat is likely to become more severe under climate change. High resolution predictive information can help farmers, water managers, and others to manage the effects of drought. We have created an open source tool to produce short-term forecasts of vegetation health at high spatial resolution, using data that are global in co...
متن کاملFinancial Time Series Forecasting – a Machine Learning Approach
The Stock Market is known for its volatile and unstable nature. A particular stock could be thriving in one period and declining in the next. Stock traders make money from buying equity when they are at their lowest and selling when they are at their highest. The logical question would be: "What Causes Stock Prices To Change?". At the most fundamental level, the answer to this would be the dema...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Ibusiness
سال: 2022
ISSN: ['2150-4075', '2150-4083']
DOI: https://doi.org/10.4236/ib.2022.143009