Sequential Tests of the Arbitrage Pricing Theory: A Comparison of Principal Components and Maximum Likelihood Factors

Shukla, Ravi; Trzcinka, Charles

doi:10.1111/j.1540-6261.1990.tb03727.x

Cited by 35 publications

(13 citation statements)

References 24 publications

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“…I then run cross‐sectional regressions of the five‐year mean excess returns on the estimated factor loadings to obtain unconditional means of risk premiums. This two‐pass regression approach makes my results comparable to those of Shukla and Trzcinka (1990) and other previous studies. I estimate similar regressions for the CAPM, using two market portfolios.…”

Section: Empirical Implementation Of the Semiautoregressive Approachsupporting

confidence: 84%

“…This result is similar to those in recent studies by Connor and Korajczyk (1988), and Lehmann and Modest (1988), and Shukla and Trzcinka (1990), who find that the APT better describes expected returns on individual stocks than the CAPM.…”

supporting

confidence: 91%

“…11Recent studies include Connor and Korajczyk (1988), Lehmann and Modest (1988), and Shukla and Trzcinka (1990).…”

mentioning

confidence: 99%

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A Semiautoregression Approach to the Arbitrage Pricing Theory

Mei¹

1993

The Journal of Finance

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This paper developes a semiautoregression (SAR) approach to estimate factors of the arbitrage pricing theory (APT) that has the advantage of providing a simple asymptotic variance‐covariance matrix for the factor estimates, which makes it easy to adjust for measurement errors. Using the extracted factors, I confirm the finding that the APT describes asset returns slightly better than the CAPM, although there is still some mispricing in the APT model. I find that not only are the factors “priced” by the market, but the factor premiums move over time in relation to business cycle variables.

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Section: Empirical Implementation Of the Semiautoregressive Approachsupporting

confidence: 84%

supporting

confidence: 91%

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A Semiautoregression Approach to the Arbitrage Pricing Theory

Mei¹

1993

The Journal of Finance

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“…Other eigenvalues appear to be important, but they seem to grow at a much slower rate. The evidence on whether the additional factors are actually priced appears mixed (Shukla and Trzcinka (1990)). The following corollary to Theorem 3 gives an explicit expression for the speed at which they can grow, although we show by example below that for specific covariance matrices, faster rates of growth may be permissible.…”

Section: Factors and Diversificationmentioning

confidence: 99%

When Will Mean‐Variance Efficient Portfolios Be Well Diversified?

Green

Hollifield

1992

The Journal of Finance

289

145

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We characterize the conditions under which efficient portfolios put small weights on individual assets. These conditions bound mean returns with measures of average absolute covariability between assets. The bounds clarify the relationship between linear asset pricing models and well-diversified efficient portfolios. We argue that the extreme weightings in sample efficient portfolios are due to the dominance of a single factor in equity returns. This makes it easy to diversify on subsets to reduce residual risk, while weighting the subsets to reduce factor risk simultaneously. The latter involves taking extreme positions. This behavior seems unlikely to be attributable to sampling error. THE MEAN-VARIANCE EFFICIENT frontier plays an important role in pedagogy and applications in finance. The properties of efficient portfolios are also central in both static and dynamic asset pricing.1 For all its simplicity and intuitive appeal, however, practical implementation of mean-variance analysis has proved problematic. Portfolios constructed using sample moments of returns often involve very extreme positions. As the number of assets grow, the weights on individual assets do not approach zero as quickly as suggested by naive notions of "diversification."Admittedly, the theoretical links between "diversification," in the sense of putting small weight on any asset, and variance minimization are tenuous. The Arbitrage Pricing Theory (APT) implies that efficient portfolios are well diversified, but the mean-variance Capital Asset Pricing Model (CAPM) requires this only insofar as the value weighted market portfolio is diversified. In applications, however, the connection between mean-variance efficiency and diversification is central. Black and Litterman (1990), for example, point to the inconsistency between naive diversification and the weights generated by asset allocation models as a major obstacle to their implementation. Practitioners are suspicious of portfolios that are not naively * Green is from Carnegie Mellon University and Hollifield is from the University of British Columbia. We wish to thank seminar participants at Carnegie The Journal of Finance diversified, so mean-variance methods are generally implemented with extensive sets of constraints that enforce such diversification. Numerous academic researchers have also documented problems in employing the weights that result from calculating efficient frontiers using sample moments.2 This paperstudies the question of when mean-variance efficiency and "well diversified" coincide, and when they do not. First, we provide a theoretical answer to this question. Then, we use more specialized examples to advance possible explanations for the "poorly diversified" weights found in efficient portfolios calculated using sample return data.Through duality theory, we provide simple and intuitive characterizations of conditions under which minimum-variance portfolios will be well diversified. These characterizations involve bounds on the means of portfolio returns in terms of...

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“…Arbitrage pricing models have been examined using factor‐analytic techniques by a number of authors for the US (Roll & Ross, 1980; Chen, 1983; Dhrymes, Friend, & Gultekin, 1985a,b; Shukla & Trzcinka, 1990) and the UK (Beenstock & Chan, 1986; Abeysekera & Mahajan, 1987; Cheng, 1996).…”

Section: Risk Factors In Stock Markets and Principal Components Analysismentioning

confidence: 99%

Changes in the risk structure of stock returns: Consumer Confidence and the dotcom bubble

Leger

Leone²

2007

Rev Financ Econ

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• This is a working paper. AbstractChanges in the risk structure of stock returns may sometimes be very revealing.We examine economic variables that help explain principal components in UK Consumer Confidence variable in a pre-bubble period only. We observe apparently systematic changes in the structure of risk, and conjecture that Consumer Confidence captures a change in market sentiment that could be a signal for the evolution of stock prices.

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Sequential Tests of the Arbitrage Pricing Theory: A Comparison of Principal Components and Maximum Likelihood Factors

Cited by 35 publications

References 24 publications

A Semiautoregression Approach to the Arbitrage Pricing Theory

A Semiautoregression Approach to the Arbitrage Pricing Theory

When Will Mean‐Variance Efficient Portfolios Be Well Diversified?

Changes in the risk structure of stock returns: Consumer Confidence and the dotcom bubble

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