Explicit-Factor-Model-The-Results明确的因子模型的的的结果课件.ppt
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- Explicit Factor Model The Results 明确 因子 模型 结果 课件
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1、Lionel MartelliniRisk and Asset Management Research Center,EDHEC Graduate School of Businesslionel.martelliniedhec.eduConfrence Gestion Alternative2 Avril 2019The Alpha and Omega of Hedge Fund Performance EvaluationJoint work with Nol Amenc(EDHEC)and Susan Curtis(USC)Outline IntroductionStandard CAP
2、M ModelAdjusting CAPM for the Presence of Stale PricesPayoff Distribution ModelMulti-Factor Models Implicit Factor ModelExplicit Factor ModelExplicit Index ModelPeer BenchmarkingComparative Performance AnalysisImpact on Attributes on Funds PerformanceConclusionIntroductionPapers on MF and HF Perform
3、ance There is ample evidence that portfolio managers following traditional active strategies on average under-perform passive investment strategies Examples are:Jensen(1968),Sharpe(1966),Treynor(1966),Grinblatt and Titman(1992),Hendricks,Patel and Zeckhauser(1993),Elton,Gruber,Das and Hlavka(1993),B
4、rown and Goeztman(2019),Malkiel(2019),Elton,Gruber and Blake(2019),or Carhart(2019),among many othersRecently,many papers have focused on hedge fund performance evaluationExamples are:Ackermann,McEnally,and Ravenscraft(2019),Amin and Kat(2019),Agarwal and Naik(2000a,2000b),Brown,Goetzmann and Ibbots
5、on(2019),Edwards and Caglayan(2019),Fung and Hsieh(2019,2019a,2019b),Gatev,Goetzmann and Rouwenhorst(2019),Liang(2000),Lhabitant(2019),Lo(2019),Mitchell and Pulvino(2019),Schneeweis and Spurgin(2019,2000)Because these studies are based on a variety of models for risk-adjustment,and also differ in te
6、rms of data used and time period under consideration,they yield very contrasted resultsThe present paper can be viewed as an attempt to provide an unified picture of hedge fund managers to generate superior performanceTo alleviate the concern of model risk on the results of performance measurement,w
7、e consider an almost exhaustive set of pricing models that can be used for assessing the risk-adjusted performance of hedge fund managers.IntroductionModelsWhile we find significantly positive alphas for a sub-set of hedge funds across all possible models,our main finding is perhaps that the dispers
8、ion of alphas across models is very largeHedge funds appear to have significantly positive alphas on average when normal returns are measured by an explicit factor model,even when multiple factors serving as proxies for credit or liquidity risks are accounted forHowever,hedge funds on average do not
9、 have significantly positive alphas once the entire distribution is considered or implicit factors are includedOn the other hand,all pairs of models have probabilities of agreement greater than.50In other words,while different models strongly disagree on the absolute risk-adjusted performance of hed
10、ge funds,they largely agree on their relative performance in the sense that they tend to rank order the funds in the same wayIntroductionPreview of the ResultsOur analysis is conducted on a proprietary data base of 1,500 individual hedge fund managers(MAR-CISDM data base)We use the 581 hedge funds i
11、n the MAR database that have performance data as early as January 2019The data base contains monthly returns and alsoFund size(asset under management)Fund type(MAR classification system)Fund age(defined as the length of time in operation prior to the beginning of our study)Location(US versus non US)
12、Incentive feesManagement feesMinimum purchase amountIntroductionDataStandard CAPM ModelNormal and Abnormal ReturnsFactor models allow us to decompose managers (excess)returns intoNormal returns(risk premium)Abnormal returns(investment opportunity)Statistical noise(illusion)Normal returns are generat
13、ed as a fair reward for the risk(s)taken by fund managersAbnormal returns are generated managers unique ability to“beat the market”in a risk-adjusted sense,generated through superior access to information or better ability to process commonly available informationNeed some model to understand what a
14、“normal”return is;benchmark model is the CAPM(Sharpe(1964)Standard CAPM Model ResultsThe average alpha across all funds is significantly positiveThe majority of hedge funds have positive alphas,and about a third are statistically significantVery few funds have significantly negative alphasStatisticV
15、alue under CAPMAlpha(average fund)5.83%Std.Err.Alpha(average fund)2.85%p-value(for average alpha not 0)0.045St.Dev.Alpha(across funds)10.02%of funds with alpha significantly031.3%of funds with alpha significantly00.7%Standard CAPM Model Distribution of CAPM AlphasDistribution of CAPM Alphas0%2%4%6%8
16、%10%12%14%16%-15-13-11-9-7-5-3-1135791113151719212325Alpha Value(annual%,midpoint of bin)PercentofFundsStandard CAPM Model Distribution of CAPM BetasDistribution of CAPM Betas0%5%10%15%20%25%-1-0.8-0.6-0.4-0.200.20.40.60.811.21.41.61.82Beta Value(midpoint of range)PercentofFundsAdjusting CAPM for St
17、ale Prices The Presence of Stale PricesIt has been documented(Asness,Krail and Liew(2019)that a fair number of hedge funds hold illiquid securitiesFor monthly reporting purposes,they typically price these securities using either the last available traded price or estimates of current market pricesSu
18、ch non-synchronous return data can lead to understated estimates of actual market exposure,and therefore to mismeasurement of hedge fund risk-adjusted performanceIn that context,some adjustment must be performed to account for the presence of stale pricesAdjusting CAPM for Stale Prices Model and Res
19、ultsModel:run regressions of returns on both contemporaneous and lagged market returnsResults:the number of funds with alpha values significantly greater than zero has been cut in halfri,trf,tik 0KikrM,t krf,t ki,tStatisticValue under CAPMValue under Lagged CAPMAlpha(average fund)5.83%2.14%Std.Err.A
20、lpha(average fund)2.85%3.21%p-value(average fund alpha not 0)0.0450.51%of funds with alpha significantly031.3%16.9%of funds with alpha significantly00.7%2.8%Adjusting CAPM for Stale Prices Model and ResultsCAPM has more funds with alphas near 10%,and lagged CAPM model has more funds with alphas betw
21、een-10%and 0Comparison of Alphas under CAPM and Lagged CAPM0%2%4%6%8%10%12%14%16%-23-21-19-17-15-13-11-9-7-5-3-11357911131517192123Alpha Values(bin midpoints)PercentofFundsCAPMLagged CAPMPayoff Distribution Function ApproachNon-Linear Exposure to Standard Asset ClassesHedge fund returns exhibit non-
22、linear option-like exposures to standard asset classes becauseThey can use derivativesThey follow dynamic trading strategiesFurthermore,the explicit sharing of the upside profits under the form of incentive fees implies that post-fee returns have option-like element even if pre-fee returns do notIn
23、this context,mean-variance CAPM based performance measures will fail to account for non trivial preferences about skewness and kurtosisThere exists a method allowing an investor to account for the whole distribution of returnsPayoff Distribution Function ApproachMethodologyMethodology introduced by
24、Dybvig(see Dybvig(1988a,1988b),applied to hedge fund performance evaluation by Amin and Kat(2019)First step:recover the cumulative probability distribution of the monthly hedge fund payoffs as well as the S&P 500 from the available data set assuming$100 are invested at the beginning of the period A
25、normal distribution is assumed for the S&P 500(i.e.,we only need to estimate the mean and standard deviation of the monthly return on the S&P 500 over the period),but not for the hedge fundsSecond step:generate payoff functions for each hedge fundA payoff function is a function f that maps the retur
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