Multifactor Asset Pricing Models Research Articles

Trade-Offs Between Efficiency and Robustness in the Empirical Evaluation of Asset Pricing Models

Even though we can formally express an asset pricing model in a classical Beta or in the relatively new stochastic discount factor representation, their key empirical features – notably, efficiency and robustness – may differ when estimated by the generalized method of moments. In particular, we find that there appears to be a degree of trade-off between these features, which are linked to the asset pricing representation. Here, we investigate this issue on single and multi-factor asset pricing models using US and UK data. In this setting, our results show that the SDF approach is more likely to be less efficient but more robust than Beta method. We show that the main drivers of this trade-off are the higher order moments of the factors, in which skewness plays an important role, and especially the covariance between returns and factors.

The Role of Realised Volatility in the Athens Stock Exchange

Using a newly developed dataset of daily, value-weighted market returns we construct and analyze the monthly realized volatility of the Athens Stock Exchange (A.S.E.) from 1985 to 2003. Our analysis focuses on the distributional and time series properties of the realized volatility series and on assessing the connection between realized volatility and returns through a multi-factor asset pricing model. In particular, we find strong evidence on the existence of a volatility feedback effect and a leverage effect, and on the existence of asymmetries between lagged returns and volatility. Furthermore, we examine the cross-sectional distribution of unconditional loadings on the realized risk factor(s) for different sets of characteristics-sorted common stock portfolios. We find that realized risk is a significantly priced factor in A.S.E. and its high explanatory power for the cross-section of portfolio average returns is independent of any return variation related to the market (CAPM) or size and book-to-market (Fama-French) factors. We discuss our findings in the context of the recent literature on realized volatility and feedback effects, as well as the literature on the pricing power of realized risk.

Performance evaluation of mutual fund investments: The impact of non-normality and time-varying volatility

Extending previous work on mutual fund pricing, this article introduces the idea of modeling the conditional distribution of mutual fund returns using a fat tailed density and a time-varying conditional variance. This approach takes into account the stylized facts of mutual fund return series, that is heteroscedasticity and deviations from normality. We evaluate mutual fund performance using multifactor asset pricing models, with the relevant risk factors being identified through standard model selection techniques. We explore potential impacts of our approach by analyzing individual mutual funds and show that it can be economically important.

An Empirical Evaluation of the Black-Litterman Approach to Portfolio Choice

We evaluate the Black-Litterman equilibrium model approach to portfolio choice. We quantify the improvement in portfolio performance of a privately informed investor who learns from market prices over an equally informed, but dogmatic investor who only uses private information. We extend the approach to any linear multi-factor asset pricing model (e.g. ICAPM) to examine how learning from prices using different equilibrium models affects portfolio performance. We find that even a misspecified asset-pricing model can improve portfolio performance when private signals are not extremely precise. As we increase the noise in private information, learning from prices is initially harmful and gradually becomes more beneficial.

Risk Premiums in the Cross-Section of Commodity Convenience Yields

In this paper we investigate risk premiums in commodity convenience yields. The analysis consists of two steps. First, we use a three-factor model to extract monthly convenience yields from a broad sample of commodity futures. Second, we estimate multi-factor asset pricing models with conditional and unconditional betas and determine risk premiums embedded in those convenience yields. By analyzing monthly cross-sections of 22 commodities in the period between December 1990 and December 2007 (corresponding to a total of 28,877 traded futures prices) we provide supportive evidence of significant premiums in convenience yields for systematic risk factors associated to stock and bond investments. These risk premiums are found to be predictable by a set of economic instrumental variables.

European capital market integration: An empirical study based on a European asset pricing model

This paper investigates the integration between the capital markets of 15 European countries, all of which are members of the European Union. Integration is tested under the joint hypothesis of a European multifactor asset pricing model. A European portfolio is constructed from which common factors are extracted using maximum likelihood factor analysis. Empirical tests are undertaken to determine whether these European factors are not only priced, but also equally priced across the European capital markets. The results show that a number of common factors are extracted from the European portfolio and a degree of capital market integration is shown to exist across the European capital markets.

Financial risk of the Biotech Industry versus the Pharmaceutical Industry

The biotech industry now accounts for a substantial and growing proportion of total R&D spending on new medicines. However, compared with the pharmaceutical industry, the biotech industry is financially fragile. This article illustrates the financial fragility of the biotech and pharmaceutical industries in the US and the implications of this fragility for the effects that government regulation could have on biotech firms. Graphical analysis and statistical tests were used to show how the biotech industry differs from the pharmaceutical industry. The two industries' characteristics were measured and compared, along with various measures of firms' financial risk and sensitivity to government regulation. Data from firms' financial statements provided accounting-based measures and firms' stock returns applied to a multifactor asset pricing model provided financial market measures. The biotech industry was by far the most research-intensive industry in the US, averaging 38% R&D intensity (ratio of R&D spending to total firm assets) over the past 25 years, compared with an average of 25% for the pharmaceutical industry and 3% for all other industries. Biotech firms exhibited lower and more volatile profits and higher market-related and size-related risk, and they suffered more negative stock returns in response to threatened government price regulation. Biotech firms' financial risks increase their costs of capital and make them more sensitive to government regulations that affect their financial prospects. As biotech products grow to represent a larger share of new medicines, general stock market conditions and government regulations could have a greater impact on the level of innovation of new medicines.

Capital market integration: evidence from the G7 countries

This article examines whether the capital markets of the G7 countries are integrated. Capital market integration is examined under the joint hypothesis of an international multifactor asset pricing model. International factors are extracted from a world portfolio using both maximum likelihood analysis and principal component analysis. Results show that international common factors exist, some of which are priced and equal across some countries, however, the international pricing model does not hold for all G7 countries. The price of risk is not found to be the same across all countries and the hypothesis of full capital market integration is not supported.

Exchange rate regimes, globalisation, and the cost of capital in emerging markets

This paper presents a multifactor asset pricing model for currency, bond, and stock returns for ten emerging markets to investigate the effect of the exchange rate regime on the cost of capital and the integration of emerging financial markets. Our results suggest that a fixed exchange rate regime system can help reduce the cost of capital in emerging markets by reducing the currency risk premia demanded by foreign investors.

Uniform testing and portfolio strategies for single and multifactor asset pricing models in the Pacific Basin markets

We test and implement portfolio strategies for three major asset pricing models, under uniform diagnostic measures using the PACAP data set containing all current listing and de-listing of firms for the local stock exchange in several Pacific Basin countries. Compared to the often used MSCI database that include only a subset of the (large) firms in the local markets, the more complete coverage of our database allows for more robust testing of current multifactor asset pricing models since the possible effects of additional factors such as size and book to market may not show up correctly using less comprehensive data sets. Our data set also provides a natural packet of nonUS data for addressing the issue of whether the results of recent asset pricing research are sample specific. Our overall results provide multi-country (sample nonspecific) support for the additional asset pricing risk factors of the Fama-French three-factor model but not for the momentum factor of the Carhart model. We additionally find that the size risk factor is more prominent than value risk factor in the Pacific Basin markets. Finally, we find strong evidence that portfolio strategies implemented to capture value and size effects are profitable in the Pacific Basin stock markets.

Performance Evaluation of Mutual Fund Investments: The Impact of Non-Normality and Time-Varying Volatility

Extending previous work on mutual fund pricing, this paper introduces the idea of modeling the conditional distribution of mutual fund returns using a fat tailed density and a time-varying conditional variance. This approach takes into account the stylized facts of mutual fund return series, that is heteroscedasticity and deviations from normality. We evaluate mutual fund performance using multifactor asset pricing models, with the relevant risk factors being identified through standard model selection techniques. We explore potential impacts of our approach by analyzing individual mutual funds and show that it can be economically important.

The Efficiency of the SDF and Beta Methods at Evaluating Multi-Factor Asset-Pricing Models

The Efficiency of the SDF and Beta Methods at Evaluating Multi-Factor Asset-Pricing Models

Is the Arbitrage Pricing Theory Dead?

Is the Arbitrage Pricing Theory dead? This paper addresses this question by deriving a multibeta representation theorem, which can price assets using arbitrary reference variables that are not the true factors. Under this theorem, the upper bound on pricing deviations depends upon the correlations not only between the reference variables and the factors but also between the reference variables and the residual risks. A new concept of a well-diversified variable is introduced, which though free of residual risk, may be less than perfectly correlated with the true factors. Well-diversified variables correlated with the factors play a key role in the pricing of assets, since these variables can replace the factors without any loss in pricing accuracy under all linear asset pricing theories. A set of corollaries to the multibeta representation theorem are derived, which are fatal for both the APT as well as the equilibrium APT. Both these theories lead to pricing of arbitrary reference variables, which allows rejection of these theories based on casual empiricism. Since Merton's ICAPM does not suffer from such arbitrary pricing, it represents a viable theoretical framework for the empirical multifactor asset pricing models, such as the 3-factor Fama and French model.

The Introduction of the Euro and the Currency Risk Premium

Exchange rates arrangements aim at reducing uncertainty attached to currency fluctuations hence a reduction in systematic risks. This paper analyzes the behaviour of risk premiums in major equity markets, following the introduction of the euro. Using a multifactor asset pricing model, we find exchange rate risk premium in the largest eurozone markets (Germany and France) rose sharply after 1999, unlike in the markets (Italy and the Netherlands). Market risk premium declined in the eurozone markets except Germany. It appears the euro resulted in systematic risk reduction in the smaller eurozone markets at the expense of their larger partners. This challenges an important rationale for the euro.

Small Firm Effect, Liquidity and Security Returns

Standard asset pricing models ignore the costs of liquidity. In this study we advance the ongoing debate on empirical asset pricing and test if liquidity costs (as proxied by turnover rate, turnover ratio and bid-ask spread) affect stock returns for Australian stocks. Our tests use the factor portfolio mimicking approach of Fama and French (1993, 1996). We find small and less liquid firms generate positive risk premia after controlling for market returns and firm size. We find no evidence of any seasonal effects that can explain our multifactor asset pricing model findings. In summary, our study provides support for a broader asset pricing model with multiple risk factors.

A critical investigation of the explanatory role of factor mimicking portfolios in multifactor asset pricing models

The common approach for constructing factor mimicking portfolios is to go long in assets with high loadings and to short-sell those with low loadings on some background factors. As a result portfolios containing stocks with low loading on the background factor receive negative betas against the corresponding mimicking portfolio. Thus, such portfolios appear as hedges against the background risk and may in tests of asset pricing models receive significant positive intercepts. The final result regarding acceptance or rejection of an asset pricing model may therefore to some extent be understood as a random outcome.

Choosing Factors in a Multifactor Asset Pricing Model when Returns are Nonnormal

Capital Asset Pricing Model (CAPM) is the most widely used model in asset pricing. This model evaluates the asset return in relation to the market return and the sensitivity of the security to the market. However, the evidence supporting the CAPM is mixed. Alternatives to the CAPM in determining the expected rate of return on portfolios and stocks was introduced through the Arbitrage Pricing Theory and through the Intertemporal CAPM. The introduction of these more general models raised the following important question: how should the risk factors in a multifactor pricing model be specified? Since the multifactor model theory is not very explicit regarding the number or nature of the factors the selection of factors has, to a large extent, become an empirical issue. In the first and the second chapters, we conduct an exhaustive evaluation of multifactor asset pricing models based on observable factors. In the first chapter we find strong evidence that a multifactor pricing model should include the market excess return, the size- , and the value premium. In the second chapter we relax the assumption of normal distributed returns. Even if this new setup does not alter the selected factors, we found strong evidence of deviation from normality which makes our approach more appropriate. In contrast to the first two chapters, the third chapter takes the approach of using latent factors. Using data from the US market, 4 to 6 pervasive factor were generally found. Furthermore, the data speaks in favor of an approximate factor structure with time series dependence across assets. In the final chapter, we examine if a momentum strategy, is superior to a benchmark model once the effects of data-snooping have been accounted for. Data snooping occurs when a given set of data is used more than once for inference or model selection. The result shows that data-snooping bias can be very substantial. In this study, neglecting the problem would lead to very different conclusions. For the US data there is strong evidence of a momentum effect and we reject the hypothesis of weak market efficiency. For the Swedish data the results indicates that momentum strategies based on individual stocks generate positive and significant profits. Interestingly, a very weak or none at all, momentum effect can be found when stocks are sorted by size, book-to-market and industry.

Are Price Limits Priced? Evidence from the Taiwan Stock Exchange

In this article, a multifactor asset pricing model incorporating a price limit factor is developed to explain the cross section of asset returns following closely the mimicking portfolio methodology of Fama and French (1996). Differing regulatory environments in the Asian region suggest that empirical studies consider the features of each market. Price limits on the daily movement of stock prices are common in the emerging markets of Asia; however, research on the sensitivity of asset prices to price limits has been lacking. Prior research suggests that price limits are a significant institutional feature of the Taiwan Stock Exchange and this market is used for empirical analysis. Our findings show that the overall market factor, firm size and price limits capture the cross section of average stock returns in a meaningful manner. However, caution is needed as the relationship between excess returns, firm size and price limits remains primarily at an empirical level. Opinion also remains divided as to whether explanatory factors in addition to the market are in fact a premium for risk, or are simply associated with firm characteristics.

Currency risk in excess equity returns: a multi time-varying beta approach

This paper proposes a multi time-varying beta multivariate generalised autoregressive conditional heteroskedastic (MGARCH) framework for estimating and testing conditional multi-factor asset pricing models. The framework nests a number of asset pricing models, and is especially useful when the betas and the factors themselves are of interest. The empirical study is concerned with the significance of a currency risk factor in the returns to a UK share price index—the FT Industrial Ordinary. Results are presented for models with time-varying multi-betas for the risk factors associated with the market, exchange rate volatility and inflation-differentials.

An unobserved component model of asset pricing across financial markets

Our research focuses on multifactor asset pricing models that investigate the importance of economic factors in the pricing of assets beyond the scope of the stock market. We present a Bayesian learning model of asset pricing across financial markets in which unobserved components are estimated using a Kalman filter (KF). Economic factors serve to drive the pricing of risk in the market, and agents update expectations recursively, as new information becomes available. We generally find that the Kalman filter provides superior performance and that economic factors like industrial production and unanticipated inflation provide consistent implications across financial markets.