股票是投資人常用投資方式，股票受到金融環境影響使得股價變化快速，找出買入賣出股票的時間點為提高獲利的重要關鍵，因此學者提出技術分析提供投資者找尋合適的進出場時機此為擇時策略，但各種技術指標常常彼此相互矛盾，在相同的時間點不同技術指標常出現不同的擇時訊號。
本研究從基本分析角度利用財會模型Ohlson Model做為擇時依據來分析股票真實價值做為投資買賣的擇時策略，並加入不同的公司治理變數組合，研究不同變數組合之下Ohlson Model的擇時能力，在不同公司治理變數組合下有何差異，並結合模型利用其強大學習能力的類神經網路學習Ohlson Model模型中變數的關係，並在學習完成後來預測真實股價為投資的時間點，最後使用Henriksson ＆ Merton模型檢定本研究方法的擇時能力效果。
研究結果發現股票市場將當多變，使用Ohlson Model預測出的真實價值與市場價值之間的關係後進行的投資，在使用因素分析組合的投資具有顯著擇時能力，但不具有選股能力，全變數的投資組合具有普通的選股能力但不具有擇時能力，另外研究中也發現在多頭市場時的投資報酬率較不理想，空頭市場的投資報酬率較好，投資人需要評估出的真實價值建立一套投資策略來投資股票市場。

Most people invest in stocks. Stocks and its prices usually influenced by financial environments, buying and selling stock is a key issue for raise profit, therefore researchers proposed a technical analysis for investors to seek appropriate time to get entry or exit. Technical indicators sometimes conflicts to others, some different technical indicators shows different timing signals at the same time. 
This study uses Ohlson Model to do timing and analyses for real values of stocks for buying and selling decision. It also combines variables of corporate governance, then do research about that what the difference is between combinations of governance variables, incorporating strongly learning artificial neural networks to learn the relationship of variables of Ohlson Model, and predict real stock value and invest time, finally Henriksson & Metron model will be used to test the result of timing ability, it is found that the total effect increased while deviation multiples added into the model.
Investment in the stock market after studies found that when changing the use of the relationship Ohlson Model predicted between the true value and market value carried in the use of factor analysis when combined with a significant investment timing ability, but do not have stock-picking ability, portfolio is full of variables with a common stock-picking ability, but do not have the timing ability, while the study also found that the return on investment when compared to the bull market is not satisfactory, return on investment is better bear market, investors need to assess the the real value of the investment strategy to invest in the establishment of a stock market.

目錄
壹、緒論1
第一節、研究動機與背景1
第二節、研究流程3
第三節、論文架構4
貳、文獻探討5
第一節、投資策略與人工智慧5
第二節、公司治理5
第三節、公司治理定義與公司治理變數6
第四節、Ohlson評價模型11
第五節、類神經網路12
第六節、Henriksson ＆ Merton 模型14
參、研究方法16
第一節、研究架構16
第二節、實例說明19
第三節、擇時能力Henriksson & Merton模型21
肆、實驗分析25
第一節、實驗資料來源與參數設定25
第二節、敘述統計27
第三節、公司治理因素分析35
第四節、類神經網路實驗分析43
第五節、投資策略正確率43
第六節、投資組合報酬率45
第七節、選股擇時能力檢定49
伍、結論與未來展望51
參考文獻53
圖目錄
圖1研究流程4
圖2倒傳遞類神經網路模型13
圖3研究架構圖17
圖4類神經網路架構圖18
圖5實例說明圖19
圖6擇時模型說明22
表目錄
表1實例說明買賣股價方式21
表2選股擇時能力實例說明使用三個月訓練全變數(2008年)23
表3選股擇時能力實例說明使三個月全變數檢定結果(2008年)23
表4定存利率24
表5水泥窯製敘述統計27
表6食品飲料敘述統計28
表7塑膠石化敘述統計29
表8紡織人織敘述統計30
表9電機重纜敘述統計31
表10造紙工業敘述統計32
表11營造建材敘述統計33
表12金融保險敘述統計34
表13水泥窯製公司治理變數因素分析結果35
表14食品飲料公司治理變數因素分析結果36
表15塑膠石化公司治理變數因素分析結果37
表16紡織人織公司治理變數因素分析結果38
表17電機重纜公司治理變數因素分析結果39
表18造紙工業公司治理變數因素分析結果40
表19營造建材公司治理變數因素分析結果41
表20金融保險公司治理變數因素分析結果42
表21投資正確率水泥窯製與食品飲料44
表22投資正確率塑膠石化與紡織人織45
表23投資正確率電機重纜與造紙工業46
表24投資正確率營造建材與金融保險47
表252008/01~2008/12投資結果48
表262009/01~2009/12投資結果49
表272010/01~2010/12投資結果49
表282011/01~2011/12投資結果50
表292012/01~2012/12投資結果50
表302013/01~2013/12投資結果51
表31選股擇時檢定52

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