本研究採用Hodrick-Prescott 濾波器優化傳統移動平均法，藉由HPF 產生去除雜訊 波動之價格趨勢，以降低雜訊對判斷買賣交易訊號的影響。檢視過去研究，HPF 普 遍應用於低頻率經濟數據分析，甚少研究將HPF 應用在高頻率之交易資料，以做為 建立操作交易策略之依據。此外，HPF 建立的價格趨勢取決於平滑參數λ 值之設 定，由λ 值決定資訊漏損及雜訊消除之扺換關係，進而影響HPF 之操作績效。因此 本研究將HPF 應用於高頻率外匯價格之動能交易策略，以檢視HPF 應用在高頻資 料之妥適性，並藉由調整λ 參數，找出適合運用於高頻率數據分析之λ 值。

Using the Hodrick-Prescott filter, this study extracts the price trend from an observed price series for advancing the directional accuracy of the traditional moving average rule (MA) which usually is noised by the short-term component of price variation. Hodrick-Prescott filter have been widely-used to generate the business cycle using low-frequency economic data, however, less study examined its fitness for using high-frequency trading price. In addition, the performance of HPF is sensitive to the smoothing parameter of HPF’s λ. This study aims to detect the validity of HPF for using high-frequency exchange price. Secondly, an appropriate smoothing parameter of HPF’s λ is determined by investigating the performance of the high frequency momentum trading strategy.