本文在檢定管理期貨績效的真實性，檢定時為了避免產生資料探勘(data snooping bias)的問題，故採用Kosowski , Timmermann , Wermers , and White（2006，此後簡稱KTWW）所提出控制資料探勘偏誤的檢定方法，來檢定CTAs經理人究竟是否具有異常報酬的操作能力。並根據CISDM數據資料庫，CTAs可分為全權策略 CTAs和系統性策略 CTAs二類來探討。透過KTWW檢定後，本文實證結果顯示，表現好的Discretionary CTAs和Systematic CTAs，相對於單因子、四因子、五因子基準模型的t_α ̂ 值，大部分都顯著為正，代表二者CTAs都具有能產生正異常報酬的操作能力。反之，表現差的Discretionary CTAs在單因子、四因子、五因子、十因子模型下，t_α ̂ 值都無法被證明在統計上顯著為負值，代表績效差的Discretionary CTAs不是因操作能力不佳而產生負報酬，僅是統計上的抽樣變異使然。而表現較差的Systematic CTAs在同樣四個模型下，部分產生顯著為負的t_α ̂ 。代表部份的Systematic CTAs表現不佳不是一群同儕基金同時被比較之下，資料探勘造成的結果，而有可能是因基金經理人的確具有較差的操盤能力。

In this study we aim to test the performance of CTA Funds. In order to avoid the data- snooping-bias problem, we use the Kosowski, Timmermann, Wermers, and White (called KTWW for short) approach to examine if the CTA fund managers have a genuine ability to gain abnormal returns. According to our database, CISDM, the CTAs are divided into discretionary CTAs and systematic CTAs. Based up on the KTWW test, our empirical results show that discretionary CTAs and systematic CTAs tend to show a significant, positive t_α ̂ value with respect to the single-factor, four-factor, and five-factor models. This result shows that both types CTAs that perform well have a genuine ability to gain risk-adjusted abnormal returns. As to CTAs that perform badly, discretionary CTAs tend to show a negative but statistically insignificant t_α ̂ with respect to the single factor, four-factor, five-factor, and ten-factor models. This finding shows that the poor performance of discretionary CTAs is not due to their fund managers’ poor skill but rather a result of sampling variation. However, some systematic CTAs do show a negative and statistically significant t_α ̂ with the four factor models, indicating the genuinely bad management ability of these fund managers.

參考文獻
Brorsen, B. W., and J. P. Townsend., 2002 . Performance Persistence for Managed Futures. Journal of Alternative Investments, 4, 57-61.
Carhart, M. M., 1997. On Persistence in Mutual Fund Performance, The Journal of Finance 52, 57-82.
Efron, B., 1979. Bootstrap Methods: Another Look at the Jackknife, The Annals of Statistics 7, 1-26.
Fung, W., and David H., 1997. Empirical Characteristics of Dynamic Trading
Strategies: The Case of Hedge Funds, Review of Financial Studies 10, 275-302.
Fung, W., and David H., 2001. The Risk in Hedge Fund Strategies: Theory and
Evidence from Trend Followers, Review of Financial Studies 14, 313-341
Fama, E. F., and K. R. French, 1993. Common Risk Factors in the Returns on Stocks and Bonds, Journal of Financial Economics 33, 3-56.
Hsu, P.-H., Y.-C. Hsu, and C.-M. Kuan, 2010. Testing the Predictive Ability of Technical Analysis Using a New Stepwise Test without Data Snooping Bias, Journal of Empirical Finance 17, 471-484.
Hansen, P. R., 2005. A Test for Superior Predictive Ability, Journal of Business and Economic Statistics 23, 365-380.
Henriksson, R., & Merton, R. 1981. On Market Timing and Investment Performance
II. Statistical Procedures for Evaluating Forecasting Skills. Journal of Business, 54,513–533.
Jensen, M. C., 1968. The Performance of Mutual Funds in the Period 1945-1964, The Journal of Finance 23, 389-416.
Kazemi, H., & Li, Y., 2008. Market Timing of CTAs：An Examinationof Systematic CTAs VS. Discretionary CTAs,The Journal of Futures Markets,29,1067-1099
Kosowski, R., A. Timmermann, R. Wermers and H. White, 2006. Can Mutual Fund “Stars” Really Pick Stocks? New Evidence from a Bootstrap Analysis, Journal of Finance 61, 2551-2595.
Lintner, J. K., 1983. The Potential Role of Managed Commodity — Financial Futures Accounts in Portfolios of Stocks and Bonds, Annual Conference of the Financial Analysts Federation, Toronto, Canada
Markowitz, H., 1952. Portfolio Selection, Journal of Finance, 7, 77-91
Politis, D. N., and J. P. Romano, 1994. The Stationary Bootstrap, Journal of the American Statistical Association 89, 1303-1313.
Schneeweis T. and Spurgin R., 2000. Quantitative Analysis of Hedge Fund and Managed Futures Return and Risk Characteristics”, Working Paper, CISDM, University of Massachusetts, Amherst
Schneeweis T. and Spurgin R., 1996 . Multi-Factor Models in Managed Futures, Hedge Fund and Mutual Fund Return Estimation. Working paper, CISDM, University of Armhest
Sharpe, W. F., 1966. Mutual Fund Performance, The Journal of Business 39, 119-138.
Treynor, J., & Mazuy, K. ,1966. Can Mutual Funds Outguess the Market? Harvard
Business Review, 44, 131–136.
Treynor, J. L., 1965. How to Rate Management of Investment Fund, Harvard Business Review 13, 131-136.
White, H., 2000. A Reality Check for Data Snooping, Econometrica 68, 1097-1126