美股 S&P500 之交易策略及其績效分析

S&P500 Investment Strategy and Performance Analysis

周威(Chou, Wei)

指導教授 ： 丁承

國立交通大學/管理學院/經營管理研究所/碩士(2020年)

摘要

本研究以美國 S&P500 大盤指數為投資標的，開發投資交易策略提供投資 人做投資建議參考。本投資交易策略能產生買進訊號與非買進訊號基於本文之 參考指標做判斷依據，其參考指標包含 S&P500 之動能條件、VIX 恐慌指數之 黃金死亡區間判斷、花旗銀行全球風險指標條件與美國 10 年期與 2 年期公債利 差之條件。將上述 4 條件建構出完整投資交易策略之買進與非買進判斷訊號機 制為本文最後之研究結果。本文最後也針對 1999 年 12 月 31 日起至 2020 年 2 月 28 日計算並分析回測績效結果，而其績效結果也較大盤優勢。除此之外，也 計算其買進訊號與非買進訊號正確率做分析，並利用相同參考指標做為虛擬變 數建構羅吉斯迴歸之買進訊號與非買進訊號，並與本投資策略做比較。而其結 果為本投資交易策略之買進訊號正確率與整體訊號正確率較羅吉斯迴歸表現優 異。

關鍵字

資產配置 ； 交易訊號 ； 動能 ； 恐慌指數 ； 羅吉斯迴歸

並列摘要

This paper explores a self-design investment strategy based on S&P500, which generates the investment recommendation for investors reference. The investment strategy is able to generate buy-in and none buy-in signal according the indicators in this paper. The indicators including S&P500 momentum factor, VIX moving average range factor, Citi Global Market Risk Indicator factor and the spread between 10-year US treasury yield and 2-year US treasury yield factor. This paper combines all 4 factor together and designs the mechanism of the investment buy-in and none buy-in signal, which is this paper final research results. This paper also includes the back-test and performance analysis for the investment strategy in the time frame of 1999/12/31 to 2020/2/28. And the performance of the investment strategy is outperformed over the benchmark S&P500. Besides, this paper also calculates and analysis the prediction correction rate for buy-in and none buy-in signal. We also use the 4 factors of the indicators in the investment strategy as 4 dummy variables to build the logistic regression, and build the cross table of the prediction correction rate for buy-in and none buy-in signal. And the final result of the comparison of the prediction correction rate is investment strategy has more advantages over the logistic regression.

並列關鍵字

Asset Allocation ； Trading Signals ； VIX ； Momentum ； Logistic Regression

參考文獻

Corrado, C. J., & Miller, Jr, T. W. (2005). The forecast quality of CBOE implied volatility indexes. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 25(4), 339-373.

Dotsey, M. (1998). The predictive content of the interest rate term spread for future economic growth. FRB Richmond Economic Quarterly, 84(3), 31-51.

Dueker, M. J. (1997). Strengthening the Case for the Yield Curve as a Predictor of US Recessions. Federal Reserve Bank of St. Louis Review, 79(2), 2-41.

Estrella, A., & Hardouvelis, G. A. (1991). The term structure as a predictor of real economic activity. The Journal of Finance, 46(2), 555-576.

Estrella, A., & Mishkin, F. S. (1997). The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank. European Economic Review, 41(7), 1375-1401.