What Do Fund Flows Reveal about Asset Pricing Models and Investor Sophistication?

2020 ◽  
Vol 34 (1) ◽  
pp. 108-148
Author(s):  
Narasimhan Jegadeesh ◽  
Chandra Sekhar Mangipudi
Keyword(s):  
Asset Pricing ◽  
Mutual Fund ◽  
Market Model ◽  
Fund Flows ◽  
Pricing Model ◽  
Pricing Models ◽  
Asset Pricing Model ◽  
Asset Pricing Models ◽  
Investor Sophistication ◽  
Mutual Fund Flows

Abstract Recent evidence indicates that market model alphas are stronger predictors of mutual fund flows than alphas with other models. Some recent papers have interpreted this evidence to mean that CAPM is the best asset pricing model, but some others have interpreted it as evidence against investor sophistication. We evaluate the merits of these mutually exclusive interpretations. We show that no tenable inference about the validity of any asset pricing model can be drawn from this evidence. Rejecting the investor sophistication hypothesis is tenable, but the appropriate benchmark to judge sophistication is different from that used in this literature.

Examining Asset Pricing Anomalies: Evidence from Europe

2021 ◽  
pp. 227853372110257
Author(s):  
Asheesh Pandey ◽  
Rajni Joshi
Keyword(s):  
Asset Pricing ◽  
Pricing Model ◽  
Pricing Models ◽  
Investment Rate ◽  
Asset Pricing Model ◽  
Fund Managers ◽  
Asset Pricing Models ◽  
Asset Pricing Anomalies ◽  
Pricing Anomalies ◽  
Portfolio Managers

We examine five important asset pricing anomalies, namely, size, value, momentum, profitability, and investment rate to evaluate their efficacy in major West European economies, that is, France, Germany, Italy, and Spain. We employ four prominent asset pricing models, namely Capital Asset Pricing Model (CAPM), Fama–French three-factor (FF3) model, Carhart model and Fama–French five-factor (FF5) model to evaluate whether portfolio managers can create trading strategies to generate risk-adjusted extra normal returns for their investors. We also examine the prominent anomalies which pass the test of asset pricing in our sample countries and evaluate the best performing asset pricing model in explaining returns in each of these countries. We find that in spite of being matured markets, these countries provide portfolio managers with opportunities to exploit these strategies to generate extra normal returns for their investors. Momentum anomaly for Germany and profitability anomaly for Italy can be exploited by fund managers for generating risk-adjusted returns. For France, except for net investment rate anomaly, all the other anomalies remained unexplained by asset pricing models. We also find CAPM to be the better model in explaining returns of Italy and Spain. While FF3 factor and FF5 factor models explain returns in Germany, our sample asset pricing models failed to work for France. Our study has implications for portfolio managers, academia, and policymakers.

scholarly journals Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression

2008 ◽  
Vol 43 (2) ◽  
pp. 331-353 ◽  
Author(s):  
Wayne E. Ferson ◽  
Sergei Sarkissian ◽  
Timothy Simin
Keyword(s):  
Asset Pricing ◽  
Time Varying ◽  
Pricing Model ◽  
Data Snooping ◽  
Pricing Models ◽  
Asset Pricing Model ◽  
Spurious Regression ◽  
Predictive Regressions ◽  
Asset Pricing Models ◽  
Conditional Betas

AbstractThis paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become biased. Previous studies overstate the significance of time-varying alphas.

scholarly journals Optimisation of Time-Varying Asset Pricing Models with Penetration of Value at Risk and Expected Shortfall

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 394
Author(s):  
Adeel Nasir ◽  
Kanwal Iqbal Khan ◽  
Mário Nuno Mata ◽  
Pedro Neves Mata ◽  
Jéssica Nunes Martins
Keyword(s):  
At Risk ◽  
Asset Pricing ◽  
Stock Returns ◽  
Value At Risk ◽  
Expected Shortfall ◽  
Time Varying ◽  
Pricing Models ◽  
Asset Pricing Model ◽  
Asset Pricing Models ◽  
Market Beta

This study aims to apply value at risk (VaR) and expected shortfall (ES) as time-varying systematic and idiosyncratic risk factors to address the downside risk anomaly of various asset pricing models currently existing in the Pakistan stock exchange. The study analyses the significance of high minus low VaR and ES portfolios as a systematic risk factor in one factor, three-factor, and five-factor asset pricing model. Furthermore, the study introduced the six-factor model, deploying VaR and ES as the idiosyncratic risk factor. The theoretical and empirical alteration of traditional asset pricing models is the study’s contributions. This study reported a strong positive relationship of traditional market beta, value at risk, and expected shortfall. Market beta pertains its superiority in estimating the time-varying stock returns. Furthermore, value at risk and expected shortfall strengthen the effects of traditional beta impact on stock returns, signifying the proposed six-factor asset pricing model. Investment and profitability factors are redundant in conventional asset pricing models.

Evaluating alternative performance benchmarks for Indian mutual fund industry

2017 ◽  
Vol 14 (2) ◽  
pp. 222-250 ◽  
Author(s):  
Sanjay Sehgal ◽  
Sonal Babbar
Keyword(s):  
Asset Pricing ◽  
Mutual Fund ◽  
Factor Model ◽  
Five Factor Model ◽  
Content Type ◽  
Asset Pricing Model ◽  
Fund Managers ◽  
Asset Pricing Models ◽  
Performance Benchmarks ◽  
Fama And French

Purpose The purpose of this paper is to perform a relative assessment of performance benchmarks based on alternative asset pricing models to evaluate performance of mutual funds and suggest the best approach in Indian context. Design/methodology/approach Sample of 237 open-ended Indian equity (growth) schemes from April 2003 to March 2013 is used. Both unconditional and conditional versions of eight performance models are employed, namely, Jensen (1968) measure, three-moment asset pricing model, four-moment asset pricing model, Fama and French (1993) three-factor model, Carhart (1997) four-factor model, Elton et al. (1999) five-index model, Fama and French (2015) five-factor model and firm quality five-factor model. Findings Conditional version of Carhart (1997) model is found to be the most appropriate performance benchmark in the Indian context. Success of conditional models over unconditional models highlights that fund managers dynamically manage their portfolios. Practical implications A significant α generated over and above the return estimated using Carhart’s (1997) model reflects true stock-picking skills of fund managers and it is, therefore, worth paying an active management fee. Stock exchanges and credit rating agencies in India should construct indices incorporating size, value and momentum factors to be used for purpose of benchmarking. Originality/value The study adds new evidence as to applicability of established asset pricing models as performance benchmarks in emerging market India. It examines role of higher order moments in explaining mutual fund returns which is an under researched area.

Linear Beta Pricing with Inefficient Benchmarks

2013 ◽  
Vol 03 (01) ◽  
pp. 1350004 ◽  
Author(s):  
George Diacogiannis ◽  
David Feldman
Keyword(s):  
Asset Pricing ◽  
Market Risk ◽  
Expected Returns ◽  
Pricing Model ◽  
Pricing Models ◽  
Expected Return ◽  
Risk Premiums ◽  
Asset Pricing Models ◽  
Current Asset ◽  
Mean Variance

Current asset pricing models require mean-variance efficient benchmarks, which are generally unavailable because of partial securitization and free float restrictions. We provide a pricing model that uses inefficient benchmarks, a two-beta model, one induced by the benchmark and one adjusting for its inefficiency. While efficient benchmarks induce zero-beta portfolios of the same expected return, any inefficient benchmark induces infinitely many zero-beta portfolios at all expected returns. These make market risk premiums empirically unidentifiable and explain empirically found dead betas and negative market risk premiums. We characterize other misspecifications that arise when using inefficient benchmarks with models that require efficient ones. We provide a space geometry description and analysis of the specifications and misspecifications. We enhance Roll (1980), Roll and Ross's (1994), and Kandel and Stambaugh's (1995) results by offering a "Two Fund Theorem," and by showing the existence of strict theoretical "zero relations" everywhere inside the portfolio frontier.

scholarly journals THE SEARCH FOR TIME-SERIES PREDICTABILITY-BASED ANOMALIES

2021 ◽  
Vol 0 (0) ◽  
pp. 1-19
Author(s):  
Javier Humberto Ospina-Holguín ◽  
Ana Milena Padilla-Ospina
Keyword(s):  
Time Series ◽  
Asset Pricing ◽  
Market Timing ◽  
The United States ◽  
Trading Rule ◽  
Optimal Parameters ◽  
Pricing Models ◽  
Asset Pricing Model ◽  
Asset Pricing Models ◽  
Out Of Sample

This paper introduces a new algorithm for exploiting time-series predictability-based patterns to obtain an abnormal return, or alpha, with respect to a given benchmark asset pricing model. The algorithm proposes a deterministic daily market timing strategy that decides between being fully invested in a risky asset or in a risk-free asset, with the trading rule represented by a parametric perceptron. The optimal parameters are sought in-sample via differential evolution to directly maximize the alpha. Successively using two modern asset pricing models and two different portfolio weighting schemes, the algorithm was able to discover an undocumented anomaly in the United States stock market cross-section, both out-of-sample and using small transaction costs. The new algorithm represents a simple and flexible alternative to technical analysis and forecast-based trading rules, neither of which necessarily maximizes the alpha. This new algorithm was inspired by recent insights into representing reinforcement learning as evolutionary computation.

Sign in / Sign up

Export Citation Format

Share Document