交易策略、股價走勢和石油價格是否有助於匯率預測?

Are trading strategies, stock price, and oil price helpful in exchange rate forecasting?

葉修為(Hsiu-Wei Yeh)

指導教授 ： 林靜儀

國立清華大學/科技管理學院/經濟學系所/碩士(2018年)

摘要

為了提升匯率預測能力，本論文利用 Bayesian Treed Gaussian Process 模，調整交易策略的計算方式，並在解釋變數中加入經濟指標進行匯率預測。本文研究方向分為兩大部分，第一部分是探討在國家分類標準不同的情況下，利用計算取得的交易策略進行匯率預測，匯率預測能力有沒有差異；第二部分是研究經濟指標作為解釋變數，是否有助於提升匯率預測能力。本研究之主要解釋變數為交易策略和經濟指標，並利用 Directional Accuracy、Excess Predictability、Annual Percentage Rate 和 Sharpe Ratio 四種檢驗方法衡量匯率預測能力。研究結果發現，國家分類標準不同並不影響匯率預測能力，然而經濟指標皆有助於提升匯率預測能力。本模型的預測結果優於 Random Walk 和 Random Walk with Drift，尤其在交易策略、股價和石油價格同時作為解釋變數時，其匯率預測能力最佳。

關鍵字

股價 ； 石油價格 ； 貝氏決策樹高斯迴歸模型 ； 隨機漫步 ； 匯率預測

並列摘要

In order to improve the exchange rate forecasting ability, we use the Bayesian Treed Gaussian Process model with different methods to obtain different trading strategies, and employ some kinds of economic variables as fundamentals for exchange rate forecasting. Therefore, the aspects of our research is divided into two parts. The first part is whether there is any difference in exchange rate forecasting ability when the trading strategies obtained by the different classification standards of countries. The second part is whether economic variables as fundamentals will help increase the exchange rate forecasting ability. Directional Accuracy、Excess Predictability、 Annual Percentage Rate and Sharpe Ratio are used to measure the exchange rate forecasting ability. The paper finds that different classification standards of countries does not affect the exchange rate forecasting ability; economic variables all help to improve the exchange rate forecasting ability. We also find that t he forecasting results of the Bayesian Treed Gaussian Process model dominate those of Random Walk and Random Walk with Drift. In particular, the exchange rate forecasting ability is the best when we employ trading strategies, stock prices and oil prices as fundamentals.

並列關鍵字

stock price ； oil price ； Bayesian Treed Gaussian Process model ； Random Walk ； exchange rate forecasting

參考文獻

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