A MULTIVARIATE TEST OF THE GENERALISED MEAN-LOWER PARTIAL MOMENT ASSET PRICING MODEL: AUSTRALIAN EVIDENCE

This paper tests the Mean-Lower Partial Moment (MLPM) model of asset pricing, using the Gibbons (1982) multivariate methodology, as developed by Hariow and Rao (1989). The MLPM model specifies risk to be a measure of the downside deviations of return relative to a prespecified and exogenous target rate of return. The MLPM model of Hariow and Rao is a new model which has only been tested once, using US data. Therefore, further tests using independent data will help to assess whether the model deserves more serious consideration as a possible alternative to the Capital Asset Pricing Model (CAPM). In general, tests in this paper using Australian data confirm the results of Hariow and Rao (1989). The MLPM model cannot be rejected against an unspecified alternative, nor can it be rejected against the zero-beta CAPM. Conditional on the MLPM model's validity, the optimal target rate appears to be more closely related to mean market returns than either to a risk-free return or to a zero return. In addition, there is some evidence to support an intertemporally constant target rate of around 3 percent per month, over the 30 year period examined.     

A note on the geometry of Shanken's CSR T2 test for mean/variance efficiency

Shanken (1985) derives a test for the zero-beta capital asset pricing model (CAPM) which, as he points out, is equivalent to a test of the mean/variance efficiency of the market portfolio. This note illustrates the geometry of Shanken's test in the mean/variance space.     

A mean-variance framework for tests of asset pricing models

This article presents a mean-variance framework for likelihood-ratiotests of asset pricing models. A pricing model is tested byexamining the position of one or more reference portfolios insample mean-standard-deviation space. Included are tests ofboth single-beta and multiple-beta relations, with or withouta riskless asset, using either a general or a specific alternativehypothesis. Tests with a factor that is not a portfolio returnare also included. The mean-variance framework is illustratedby testing the zero-beta CAPM, a two-beta pricing model, andthe consumption-beta model.     

Temporal Aggregation and the Continuous-Time Capital Asset Pricing Model

We examine how the empirical implications of the Capital Asset Pricing Model (CAPM) are affected by the length of the period over which returns are measured. We show that the continuous-time CAPM becomes a multifactor model when the asset pricing relation is aggregated temporally. We use Hansen's Generalized Method of Moments (GMM) approach to test the continuous-time CAPM at an unconditional level using size portfolio returns. The results indicate that the continuous-time CAPM cannot be rejected. In contrast, the discrete-time CAPM is easily rejected by the tests. These results have a number of important implications for the interpretation of tests of the CAPM which have appeared in the literature.     

On the power of cross-sectional and multivariate tests of the CAPM

This paper examines the power of the cross-sectional and multivariate tests of the CAPM under ideal conditions. When the CAPM is true the positively weighted market portfolio is MV-efficient and securities plot on the security market line. When the CAPM is false an alternative asset pricing model determines prices. An examination of the population intercepts, slopes and R² from cross-sectional regressions of expected returns on betas indicates that all three are unreliable indicators of whether the CAPM holds. Simulation analysis of the power of the cross-sectional tests expands on and reinforces the analysis based on the population values. The Gibbons et al. (1989) multivariate test fares much better.     

Alternative beta risk estimators and asset pricing tests in emerging markets: The case of Pakistan

This paper tests and compares the applicability of two asset pricing models specifically, the CAPM and the Fama–French three factor models for an emerging stock market namely, Pakistan. The paper analyses a number of beta risk estimators, including OLS, the Dimson thin trading estimator, a trade-to-trade estimator and a sample selectivity estimator. To uncover any possible influence of the return interval and the type of the market index, the analysis is carried out on three data frequencies namely daily, weekly and monthly as well as for a value and an equally weighted market index. The alternative beta estimators appear to correct thin trading bias but their effects on asset pricing tests are not visible. Moreover contrary to the expectations the test results for monthly and weekly frequencies are not promising. Instead for daily data the cross-section of returns are explained by a number of risk factors and trading volume.     

Tests of the CAPM with Time-Varying Covariances: A Multivariate GARCH Approach

This paper examines an asset pricing model in which the Sharpe-Lintner CAPM and the zero-beta CAPM are special cases. The model allows the ratio of expected market risk premium to market variance, the conditional expected excess returns, and the risks to change over time. The results are found to be sensitive to the choice of the portfolio formation techniques. Significant time variability is shown in the conditional expected excess asset returns and risks and also in the reward-to-risk ratio.     

Return Distributions and Improved Tests of Asset Pricing Models

We compare and contrast some existing ordinary least squares(OLS)- and generalized method of moments (GMM)-based tests ofasset pricing models with a new more general test. This newtest is valid under the assumption that returns are ellipticallydistributed, a necessary and sufficient assumption of the linearcapital asset pricing model (CAPM). This new test fails to rejectthe CAPM on a dataset of stocks sorted by market valuations,whereas similar tests constructed from OLS and GMM estimationmethods reject the linear CAPM. We also find that outliers reducethe OLS-estimated mispricing of the linear CAPM on monthly returnssorted by previous performance, that is, momentum. Monte Carloevidence supports superior size and power properties of thenew test relative to OLS- and GMM-based tests.     

The conditional CAPM does not explain asset-pricing anomalies

Recent studies suggest that the conditional CAPM holds, period by period, and that time-variation in risk and expected returns can explain why the unconditional CAPM fails. In contrast, we argue that variation in betas and the equity premium would have to be implausibly large to explain important asset-pricing anomalies like momentum and the value premium. We also provide a simple new test of the conditional CAPM using direct estimates of conditional alphas and betas from short-window regressions, avoiding the need to specify conditioning information. The tests show that the conditional CAPM performs nearly as poorly as the unconditional CAPM, consistent with our analytical results.     

Tests of conditional asset pricing models in the Brazilian stock market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976–1992. We also test a conditional APT model by using the difference between the 30-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.     

Sensitivity of Multivariate Tests of the Capital Asset-Pricing Model to the Return Measurement Interval

The capital asset-pricing model's (CAPM) primary empirical implication is a positively sloped linear relation between a security's expected rate of return and its relative risk (beta). Recent research indicates that inferences about the risk-return relation are sensitive to the choice of the return measurement interval. We perform multivariate tests of the Sharpe-Lintner CAPM using monthly and annual returns on market-value-ranked portfolios. The CAPM is rejected using monthly returns, a result consistent with previous research. In contrast, we fail to reject the CAPM when annual holding period returns are used.     

Testing the CAPM with broader market indexes: A problem of mean-deficiency

This study addresses a problem that can arise when a broader market index is used to test the CAPM: a return series used in the index can exclude part of an asset's return. If the excluded return is constant, then a test of mean-variance efficiency can be constructed, but an additional parameter must be estimated. This point is illustrated in tests with both broader market indexes and stocks-only indexes. The broader indexes exclude the rental return on real estate and durables. The excluded rental return is estimated under the assumption that the index portfolio is mean-variance efficient.     

NONNESTED PROCEDURES IN ECONOMETRIC TESTS OF ASSET PRICING THEORIES

In this paper nonnested tests are used to contrast the performance of the capital asset pricing (CAPM) and consumption capital asset pricing (CCAPM) theories in describing the U.S. stock market. The procedures employed include the N‐test, the NT‐test, the W‐test, the J‐test, and the Encompassing test. The tests are carried out using data on firms as well as portfolios based on beta, capitalization, and Standard Industrial Classification codes. The findings indicate that although during 1973–82 the CAPM dominates the CCAPM, during 1978–87 the results are mixed, and during 1983–92 the CCAPM dominates. The finding in favor of the CCAPM in 1983–92 conflicts with much of the existing literature, which favors the CAPM.     

Testing the CAPM revisited

This paper re-examines the tests of the Sharpe–Lintner Capital Asset Pricing Model (CAPM). The null that the CAPM intercepts are zero is tested for ten size-based stock portfolios and for twenty five book-to-market sorted portfolios using five-year, ten-year and longer sub-periods during 1965–2004. The paper shows that the evidence for rejecting the CAPM on statistical grounds is weaker than the consensus view suggests, and highlights the pitfalls of testing multiple hypotheses with the conventional heteroskedasticity and autocorrelation robust (HAR) test with asymptotic P-values. The conventional test rejects the null for almost all sub-periods, which is consistent with the evidence in the literature. By contrast, the null is not rejected for most of the sub-periods by the new HAR tests developed by Kiefer et al. (2000), Kiefer and Vogelsang (2005), and Sun et al. (2008).     

Capital Asset Pricing Model and Stochastic Volatility: A Case Study of India

The existing literature demonstrates that under a general equilibrium model, the performance of the Capital Asset Pricing Model (CAPM) can be improved significantly by using conditional consumption and market return volatilities as factors. This article tests the validity of these factors explaining stock return differences using a less developed country (India) as a case study. While the earlier studies used panel data to test CAPM, we use portfolios sorted by size and book-to-market equity (BE/ME) ratio. We found that conditional volatility has a limited effect on firms with large capitalization but a significant impact on small-growth and small-value firms.     

Does Money Explain Asset Returns? Theory and Empirical Analysis

A cash-in-advance model of a monetary economy is used to derive a money-based CAPM (M-CAPM), which allows us to implement tests of asset pricing restrictions without consumption data. A test as in Fama and MacBeth of the model suggests that the money betas have some explanatory power for the cross-sectional variation of expected returns; however, the model is rejected using conditional information. Consistent with our predictions, estimates of the curvature parameter are lower than those of the consumption CAPM (C-CAPM) and pricing errors of the M-CAPM tend to be smaller than those of the C-CAPM.     

What causes mean reversion in corporate bond index spreads? The impact of survival

Previous studies document that the spread between the yield on commonly used corporate bond indexes (e.g., Moody’s Baa index) and a comparable maturity treasury bond exhibits mean reversion. An analytical model shows that a part of the observed negative relationship between changes in the spread and the level of spreads is a natural consequence of ratings based classification of bonds included in the index and the related effects of survival. Using data on individual corporate bonds over the period January 1985 to December 1996, I corroborate the analysis and illustrate the effects of survival. The result has several implications for parametric specifications of spread dynamics in the pricing of contingent claims, for the application of spreads in tests of asset pricing models (such as the conditional version of the CAPM) and for the use of spreads in business cycle forecasts.     

Multifactor Asset Pricing Models

Since the early 1960s, the mean-variance Capital Asset Pricing Model (CAPM) has been a dominant paradigm in modern finance. Recently, the accumulation of anomalous evidence, and a realisation that empirical tests of the model are tautologically related to the efficiency of the market index, have pushed that paradigm to a point of crisis. This paper reviews alternative asset pricing models which coexisted with the CAPM and may provide plausible substitutes. The major distinguishing feature of these models is that they predict multiple risk factors and, with the exception of the Arbitrage Pricing Theory (APT), are extensions of the CAPM.     

Pension benefits, wealth accumulation, and capital market equilibrium: a life cycle hypothesis-based dynamic model

This paper examines the impacts of pension benefits on capital asset pricing in conjunction with wealth accumulation and retirement, and derives and tests a dynamic capital asset pricing model (CAPM) within the framework of a life cycle hypothesis-based dynamic model. The life cycle hypothesis-based dynamic model maximizes the expected utility of the individual's lifetime wealth in a continuous time process. An optimal solution of the individual's wealth path, incorporating the ages of retirement and death, is obtained and, based on the optimal wealth path, an analysis of comparative dynamics is pursued. The dynamic CAPM is then derived from the optimal wealth path; simulation and nonparametric tests are undertaken to evaluate the performance of the dynamic CAPM as compared to the traditional model which does not consider the impacts of pension benefits and the static model that incorporates the effects of pension benefits. The test results suggest that the proposed dynamic CAPM closely states the expected rate of return for a capital asset; that the new dynamic CAPM is preferable over the static model that is preferable over the traditional model; and that the three models considered are statistically distinguishable from one another.     

Possible explanations of no-synergy mergers and small firm effect by the Generalized Capital Asset Pricing Model

The Sharpe-Lintner Capital Asset Pricing Model (CAPM) and the General Capital Asset Pricing Model (GCAPM) suggested by Levy (1978), Merton (1987), and Markowitz (1989) are compared and analyzed. Under the GCAPM we obtain the following main results: 1) the value additivity principle breaks down, which explains mergers and acquisitions; 2) beyond a certain limit, the profit from additional merger is negative; and 3) in a GCAPM equilibrium, small firms earn an abnormal profit in comparison to what is predicted by the CAPM. These results, which are indeed observed in the market, are fully consistent with the GCAPM, but are in contradiction to the CAPM.