運用市場輪廓理論與分群分類 分析於台指期市場之行為發現

Abstract

本研究以一分鐘K線圖為基礎，搭配市場輪廓理論以及成交量輪廓圖 ，將一天當中每分鐘所發生的交易裡面隱含的訊息抽出，得到整個市場在不同的時間、不同的價格中所隱含的情緒、行為，並進一步地利用分類方法(Decision Tree、Supervised Self Organized Map) 或者分群方法(K-means、Supervised Self Organized Map)將前處理過後資料進行歸納，經過分群或分類後的資料依照各自被分配至的群組給予情緒假設的標籤，將標籤匯出至一文字串流，再利用字頻統計去計算各連續情緒假設標籤所表現出來的行為，測試一市場在連續的情緒衝擊下會展現出來的行為模式，最後再將這些行為模式統計後轉換成交易策略進行實證。 本研究之研究方法內涵時間序列概念，發現出來之連續行為和過往之研究或者技術指標所描繪出來的一瞬間之能量有所區別，發現出市場除了會受到大幅度波動之影響外對於連續出現隻小幅度物理能量衝擊也會有所反應。 實驗結果證明了市場並非如隨機漫步(random walk)理論之說，而是市場具有邏輯並會受到心理因素的影響，並且會經由時間的醞釀將這些情緒反應在價格上。

This research based on one minute time frame candlestick, market profile theory and volume profile. we can get the mood and behavior that generate by market by Extracting the hiding information in every minutes in day trading. Then using the classification(Decision Tree、Supervised Self Organized Map) or clustering analysis(K-means、Supervised Self Organized Map) algorithm to give a label to every one minute time frame candlestick. After we give every candlestick a label and sort them by time, use the stream analysis algorithm to find the relationship between candlesticks then we can get a invest strategy and use the data between 2010 and 2013 to backtest. This research including the time series concept, showing that not only the big, once psychological factors change can the continuous, little psychological factors change can affect the price in the market. Experimental results show that the market is not random walk, the market has a logical and would be affected by psychological factors, the investors mood will be brewing through time, in the end reactions in the price.