Machine learning based forecasting of significant daily returns in foreign exchange markets

09/21/2020
by   Firuz Kamalov, et al.
14

Asset value forecasting has always attracted an enormous amount of interest among researchers in quantitative analysis. The advent of modern machine learning models has introduced new tools to tackle this classical problem. In this paper, we apply machine learning algorithms to hitherto unexplored question of forecasting instances of significant fluctuations in currency exchange rates. We perform analysis of nine modern machine learning algorithms using data on four major currency pairs over a 10 year period. A key contribution is the novel use of outlier detection methods for this purpose. Numerical experiments show that outlier detection methods substantially outperform traditional machine learning and finance techniques. In addition, we show that a recently proposed new outlier detection method PKDE produces best overall results. Our findings hold across different currency pairs, significance levels, and time horizons indicating the robustness of the proposed method.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 12

page 16

page 17

page 18

page 19

page 20

page 21

page 22

04/02/2021

A Survey on Semi-parametric Machine Learning Technique for Time Series Forecasting

Artificial Intelligence (AI) has recently shown its capabilities for alm...
03/31/2020

Machine Learning Algorithms for Financial Asset Price Forecasting

This research paper explores the performance of Machine Learning (ML) al...
12/25/2021

A comparative study on machine learning models combining with outlier detection and balanced sampling methods for credit scoring

Peer-to-peer (P2P) lending platforms have grown rapidly over the past de...
10/07/2019

PyODDS: An End-to-End Outlier Detection System

PyODDS is an end-to end Python system for outlier detection with databas...
09/09/2019

Super learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms

Daily streamflow forecasting through data-driven approaches is tradition...
04/27/2021

Yield forecasting with machine learning and small data: what gains for grains?

Forecasting crop yields is important for food security, in particular to...
09/30/2021

Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation

Detection of Out-of-Distribution (OOD) samples in real time is a crucial...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.