本研究利用貝氏模型將總經因子代入條件變數中衡量管理期貨基金績效。過往研究在探討管理期貨基金績效時，皆採用傳統評價方法，本研究選擇了貝氏條件模型，透過五大投資人特性分析經理人績效。
本研究結合TASS及BarclayHedge資料庫，採1994年至2012年管理期貨基金為樣本。實證結果發現，五大投資人績效皆較巴克萊管理期貨基金指數佳，其中，相信基金經理人有創造超額報酬能力的投資者相較於不相信經理人有此能力的投資者擁有較高的顯著正超額報酬。此外，本研究亦發現全權決策管理期貨基金表現較系統化交易管理期貨基金佳，而相信基金經理人有創造超額報酬能力的投資者平均會投資較高比重於全權決策基金。本文推測此為造成其績效較佳的主要原因。最後，本文實證結果亦指出貝氏模型採用愈短期樣本內期間的預測表現會愈佳，與貝氏估計模型特性相符。

In this thesis, we measure CTAs performance by conditioning managerial skill on macroeconomic variables. Most of previous studies, those considering CTAs performance, adopted traditional models. This thesis is the first study, which applies conditional model to CTAs, analyzing manager skills under five types of investors with different prior beliefs and restrictions.
This study combines TASS and BarclayHedge databases, from which we collect CTAs data during the sample period from 1994 to 2012. Empirical results show that all five Bayesian investors investigated outperform the Barclay CTA Index. Investors who believe in active managerial skills tend to have significantly larger alpha than those who don't. In addition, our results suggest that Discretionary CTAs outperform Systematic CTAs. We find people who believe in management skills will choose to invest in more Discretionary CTAs than in Systematic CTAs under an equal-weight scheme; this would be the key reason for their remarkable significant abnormal return. Finally, our results point out that Bayesian models will perform better with a shorter prior period, a finding consistent with the characteristics of Bayesian models.

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