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Non-linear exchange rate forecasting: The role of market microstructure variables (Canada, United States).

机译：非线性汇率预测：市场微观结构变量的作用（加拿大，美国）。

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摘要

In this dissertation, we conduct a study of exchange rate models for the Canada/U.S. exchange rate. More specifically, we focus on their intra-day (high-frequency) and, subsequently, weekly forecast performances. All attempts to explain equilibrium exchange rates suffer from various problems: structural (macroeconomic) models used for out-of-sample forecasting produce poor forecasts. Given that different market participants trade based on private as well as public information sets, it is natural to assume that equilibrium exchange rate expectations are formed from a combination of macroeconomic fundamentals and market microstructure variables.; Chapter 1 motivates research in the area of non-linear microstructure exchange rate modeling, reviews the recent literature and introduces the general ideas behind this thesis.; Chapter 2 outlines Artificial Neural Networks (ANNs) and other non-linear modeling approaches used in this research.; Chapter 3 introduces a non-linear Canada/U.S. exchange rate microstructure model and provides a strong evidence for the microstructure effects. Our horse race for forecast performance results in a non-linear ANN model as the winner. ANN models outperform random walk and linear models in a number of recursive out-of-sample forecasts. The daily forecasts produced by ANN models are statistically significant according to Diebold and Mariano (1995) statistics. Apart from the nearest neighbours model, other linear and non-linear models are unable to generate significant predictions. The inclusion of a microstructure variable, order flow, substantially improves the predictive power of both the linear and non-linear models. Our findings also indicate the necessity of embodying (in a non-linear sense) information not only from interbank order flows, but also from commercial client and foreign institution transactions. No matter which non-linear model is used, there is always a slight forecast gain when dealer's private order flows are included into a set of explanatory variables.; Chapter 4 describes fuzzy logic technology in the form of approximate reasoning as a method that can be used in economics when dealing with continuous and imprecise economic variables, insufficient data for analysis and when a mathematical model of the process is unknown.; Chapter 5 develops an original and novel approach to generating trading strategies in the foreign exchange (FX) market based on forecasts from the ANN. Neuro-fuzzy (NF) decision-making technology is designed and implemented to obtain the optimal daily currency trading rule. We find that a non-linear ANN exchange rate microstructure model combined with a fuzzy logic controller (FLC) generates a set of trading strategies that, on average, earn a higher rate of return compared to the simple buy-and-hold strategy. We also find that after including transaction costs, the gains from the NF technology do not decline and increase on some periods. Finally, we successfully apply the NF model to the problem of determining the FX market's sentiment as reflected by the chartists' trading signals during periods of strong depreciation.
机译：在本文中，我们对加拿大/美国的汇率模型进行了研究。汇率。更具体地说，我们专注于其日内（高频）以及随后的每周预测表现。试图解释均衡汇率的所有尝试都遇到各种问题：用于样本外预测的结构（宏观经济）模型产生的预测很差。假定不同的市场参与者基于私人和公共信息集进行交易，自然就可以假设均衡汇率预期是由宏观经济基本面和市场微观结构变量共同形成的。第1章激发了非线性微观结构汇率建模领域的研究，回顾了最近的文献并介绍了本文的总体思路。第2章概述了本研究中使用的人工神经网络（ANN）和其他非线性建模方法。第3章介绍了非线性的加拿大/美国。汇率微观结构模型，并为微观结构效应提供了有力的证据。我们为预测性能而进行的竞赛使非线性ANN模型成为获胜者。在许多递归样本外预测中，人工神经网络模型的表现优于随机游动和线性模型。根据Diebold和Mariano（1995）的统计，由ANN模型产生的每日预报具有统计意义。除了最近的邻居模型，其他线性和非线性模型都无法生成重要的预测。包含微观结构变量，顺序流，可以大大提高线性和非线性模型的预测能力。我们的发现还表明，不仅要从银行间订单流中体现出信息（在非线性意义上），而且还要从商业客户和外国机构交易中体现出信息的必要性。无论使用哪种非线性模型，当经销商的私人订单流都包含在一组解释变量中时，总会有少量的预测收益。第4章以近似推理的形式描述了模糊逻辑技术，该方法可用于经济学中，用于处理连续和不精确的经济变量，分析数据不足以及过程的数学模型未知的情况。第5章根据ANN的预测，开发了一种新颖新颖的方法来生成外汇（FX）市场中的交易策略。设计并实现了神经模糊（NF）决策技术，以获取最佳的每日货币交易规则。我们发现，非线性ANN汇率微观结构模型与模糊逻辑控制器（FLC）相结合，生成了一套交易策略，与简单的买入并持有策略相比，平均而言，它们可以获得更高的回报率。我们还发现，在计入交易成本后，NF技术的收益在某些时期内不会下降或增加。最后，我们成功地将NF模型应用于确定汇率市场情绪的问题，这一点在强势贬值时期被特许人的交易信号所反映。

著录项

  • 作者

    Gradojevic, Nikola.;

  • 作者单位

    The University of British Columbia (Canada).;

  • 授予单位 The University of British Columbia (Canada).;
  • 学科 Economics Finance.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 147 p.
  • 总页数 147
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 财政、金融;
  • 关键词

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