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    1. 【95周年校慶系列講座】Evaluation of Asset Pricing Models: Optimal Risk Premia and Goodness-of-Fit Measures

      時間:2020-07-22         閱讀:

      光華講壇——社會名流與企業家論壇第 5761 期

      (線上講座)

      主題Evaluation of Asset Pricing Models: Optimal Risk Premia and Goodness-of-Fit Measures

      主講人新加坡南洋理工大學  Robert L.Kimmel兼職教授

      主持人金融研究院  Philip H. Dybvig教授

      時間2020年7月24日(周五)9:00-10:30

      直播平臺及會議ID騰訊會議

      主辦單位:金融研究院 科研處

      主講人簡介:

      Robert L. Kimmel received his PhD from the University of Chicago, and has held various positions at Princeton University, Ohio State University, EDHEC Business School, and the National University of Singapore. Since leaving NUS last year, he has been an adjunct lecturer at Nanyang Technological University in Singapore, and a freelance consultant. His research focuses on continuous-time modelling of stochastic volatility and interest rate processes, and methods for estimation and evaluation of asset pricing models.

      Robert L. Kimmel在芝加哥大學獲得博士學位,曾就職過普林斯頓大學、俄亥俄州立大學、EDHEC商學院和新加坡國立大學。自去年離開新加坡國立大學后,他一直是新加坡南洋理工大學的兼職教授和自由職業顧問。他的研究重點是隨機波動率和利率過程的連續時間建模,以及資產定價模型的估計和評估方法。

      內容提要:

      We consider linear factor models, in which expected returns are linear functions of beta coefficients on explanatory factors. Such models have been in common use in finance for decades, and many methods for assignment of risk premia to the factors and evaluation of the model's fit have appeared in the literature. We show that there is essentially a unique method for assigning risk premia, and a unique method for assessing the fit of the model, based on only two assumptions: the fit of the model is judged solely by its predictions of the assets' expected returns, and the fit improves when the prediction error for an asset decreases, holding the prediction error of all uncorrelated assets fixed. The unique (to within monotonic transformation and additional “tie-breaking” criteria) goodness-of-fit is based on the maximum Sharpe ratio that can be achieved using the factor mimicking portfolios, and the unique risk premia assigned to factors that are themselves excess returns are simply the expected excess returns of the factors.

      本文考慮預期收益是因子β系數的線性函數的因子模型,該類模型在金融學中已被廣泛使用了幾十年,文獻中出現了許多將風險溢價分配給因子和評估模型擬合度的方法。我們發現,本質上存在一種分配風險溢價的獨特方法,以及一種評估模型擬合度的唯一方法,僅基于兩個假設:模型的擬合度僅由其對資產預期收益率的預測來判斷,此外,當對資產收益的預測誤差減小,保持對所有不相關資產收益的預測誤差不變的情況下,擬合度會提高。擬合優度(在單調變換和附加的“加時決勝”標準內)是基于因子模擬投資組合可以實現的最大夏普比率,而分配給因子獨特的風險溢價就是這些因子的預期超額收益,這些因子自身就是超額收益。

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