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  • 學位論文

整合隱藏式馬可夫模型與演化策略於股市交易策略最佳化

Integrated Hidden Markov Model and Evolution Strategies to Optimize Stock Trading Strategies

指導教授 : 張應華

摘要


銀行低利率時代來臨,日本甚至已進入負利率的時代,因此愈來愈多人另尋其他管道投資。其中股票是投資者熟悉的一種投資理財工具,舉凡電視、報章雜誌和網際網路,皆有不少人在熱烈討論。一般投資者常根據技術指標來進行股票擇時的操作,如利用KD值、MA指標、RSI…等來決定股票的買賣時機,但經常出現各指標間互相矛盾的買賣訊號,或是預測訊號與股票實際漲跌狀況差異甚大。 本研究整合隱藏式馬可夫模型與演化策略,建立一股市投資決策最佳化系統。利用隱藏式馬可夫模型,透過觀測值的變化來預測股票漲跌狀態。使用風險每變動一單位,投資人獲利程度的累積變化做為進場時機的依據,亦即做為何時該重新調整投資人手上投資組合的判斷,買賣交易策略則透過三個常用的技術指標:KD、MA和RSI來預測股票是否該買或該賣。結合進場訊號、買賣訊號與演化策略,共同演化出最佳資金配置與選股策略以幫助投資人做出正確的決策,以獲取優渥的超額報酬。

並列摘要


The low interest rate has come, and Japan has even entered the era of negative interest rates, so there is getting more people looking for other ways to invest. One of investment and financial instruments is stocks, there are many discussions from TV to internet. General investors use technical indicator to make stock timing decision, for example: KD, MA, and RSI. However, the signals from technical indicator are different from indicator to indicator. This paper integrated Hidden Markov Model and Evolution Strategies to build a stock investment strategies system. By Hidden Markov Model, it can observe the observation sequence to forecast the stock will rise or fall, which is the hidden state. In the timing part, this paper use cumulative “changes in return of per change in risk” to forecast when to adjust the portfolio. This paper use three common technical indicator, KD, MA, and RSI to make the trading decision. Finally, combing the signal of adjusting portfolio, the signal of trading signal and genetic algorithm, the best capital allocation will be evolved, and that is helpful to investors make correct decision.

參考文獻


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