Information spillover and cross-predictability of currency returns: An analysis via Machine Learning

IF 3.6 2区经济学 Q1 BUSINESS, FINANCE

Journal of Banking & Finance Pub Date : 2024-09-26 DOI:10.1016/j.jbankfin.2024.107313

Yuecheng Jia , Yuzheng Liu , Yangru Wu , Shu Yan

引用次数: 0

Abstract

This paper documents significant cross-return predictability of news variables, derived from textual analysis of news articles, for a broad cross-section of currencies. By employing forecasts based on the Least Absolute Shrinkage and Selection Operator (LASSO) that incorporate both news variables and forward discounts, we develop a notably profitable trading strategy. This strategy proves robust against transaction costs, risk adjustments, and controls for currency characteristics. Further analyses indicate that both risks and market frictions contribute to the profitability of the trading strategy, highlighting the crucial role of news in financial markets.

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信息溢出和货币回报的交叉可预测性：机器学习分析

本文记录了从新闻文章文本分析中得出的新闻变量对多种货币的交叉收益预测能力。通过采用基于最小绝对缩水和选择操作器（LASSO）的预测，并结合新闻变量和远期贴水，我们开发出了一种显著盈利的交易策略。事实证明，该策略在交易成本、风险调整和货币特性控制方面都很稳健。进一步的分析表明，风险和市场摩擦都有助于提高交易策略的盈利能力，凸显了新闻在金融市场中的关键作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Banking & Finance Multiple-

CiteScore

6.40

自引率

5.40%

发文量

262

期刊介绍： The Journal of Banking and Finance (JBF) publishes theoretical and empirical research papers spanning all the major research fields in finance and banking. The aim of the Journal of Banking and Finance is to provide an outlet for the increasing flow of scholarly research concerning financial institutions and the money and capital markets within which they function. The Journal''s emphasis is on theoretical developments and their implementation, empirical, applied, and policy-oriented research in banking and other domestic and international financial institutions and markets. The Journal''s purpose is to improve communications between, and within, the academic and other research communities and policymakers and operational decision makers at financial institutions - private and public, national and international, and their regulators. The Journal is one of the largest Finance journals, with approximately 1500 new submissions per year, mainly in the following areas: Asset Management; Asset Pricing; Banking (Efficiency, Regulation, Risk Management, Solvency); Behavioural Finance; Capital Structure; Corporate Finance; Corporate Governance; Derivative Pricing and Hedging; Distribution Forecasting with Financial Applications; Entrepreneurial Finance; Empirical Finance; Financial Economics; Financial Markets (Alternative, Bonds, Currency, Commodity, Derivatives, Equity, Energy, Real Estate); FinTech; Fund Management; General Equilibrium Models; High-Frequency Trading; Intermediation; International Finance; Hedge Funds; Investments; Liquidity; Market Efficiency; Market Microstructure; Mergers and Acquisitions; Networks; Performance Analysis; Political Risk; Portfolio Optimization; Regulation of Financial Markets and Institutions; Risk Management and Analysis; Systemic Risk; Term Structure Models; Venture Capital.