本研究主要在探討價平買賣權隱含波動率與買賣權隱含波動率差的時間序列關係，對於樣本進行一系列的檢定以判斷樣本為何種性質的時間序列，在本研究中主要是使用AR-GARCH模型對隱含波動率進行相關的分析，經過ACF與PACF的判斷，買權與買賣權隱含波動率差落遲期數均為4期，賣權隱含波動率的落後期數為5期，透過時間序列模型對於買權隱含波動率與賣權隱含波動率進行樣本外的預測方式，再透過所預測的買權、賣權隱含波動率進行模擬操作。

透過四種交易方式，為買低賣高、估計明日大盤變動進行買進買權賣出賣權或是賣出買權買進賣權的動作、估計明日大盤變動進行跨式交易、及預測隱含波動率的 進行跨式交易，基於這四種交易方式，可發現在計入交易成本之後為負值或是利潤極低，再將損益進行T檢定發現利潤不顯著，而呈現無法透過四種交易方式賺取超額報酬，雖然模型的配適度良好，但是仍然無法對於交易成本所產生侵蝕利潤的狀況有任何的助益，當計入交易成本後即使本來有顯著正利潤的交易策略，即產生虧損無法有顯著的利潤產生，若能夠有日內資料對於隱含波動率時間序列更正確的估計的話，或許可以找出主要的關鍵點，對於交易策略設定一限制值，如此一來不需要每日交易，可以避免因為每日交易侵蝕利潤。

This studies is research of time series relationship of at the money option implied volatility and implied volatility spread, in this research is using AR-GARCH model analysis relationship about implied volatility, when data after ACF and PACF judgment, Call and implied volatility spread order of lag are both 4, Put order of lag is 5. After determine time series models this studies will predict implied volatility and implied volatility spread, then using predict data for trading simulation.

This studies are using four different trading strategy, base on four different trading strategy, when trading include transaction cost the trading profit is negative or few, then use T test to test profit dose it significant? Although time series models are good of fit. After T test doesn’t discovery any trading strategy has significant profit. If this studies has intraday data maybe could find critical value. The critical value can avoid trading every day. Avoid transaction cost corrode profit.

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