The behaviour of style anomalies on the Australian Stock Exchange : a univariate and multivariate analysis

Recent attempts to empirically verify the Sharpe ( 1964), Lintner ( 1965), Moss in (1966), and Black ( 1972) Capital Asset Pricing Model (CAPM) have identified numerous inconsistencies with the model ' s predictions. A number of variables have displayed evidence of the ability to explain the cross-sectional variation in share returns beyond that explained by beta. These anomalous effect have become known as "style effects" or "style characteristics". This thesis sets out to examine the existence and behaviour of these style-characteristics over the period June 1994 to May 2004. A data set of 207 firm-specific attributes is created for all Australian Stock Exchange (ASX) All Ordinaries stocks listed on I September 2004. The data are adjusted for both thin trading and look-ahead bias. The study largely follows the tests of van Rensburg and Robertson (2003) who adopt the characteristic-based approach of Fama and Macbeth ( 1973). Attributes are tested for the ability to explain the cross-sectional variation in ASX share returns beyond that explained by the CAPM and a principalcomponents-derived APT model. Similar significant characteristics are found when unadjusted and both risk-adjusted returns sets are examined. The set of significant characteristics derived from the unadjusted returns test is then simplified using correlation analysis and an agglomerative hierarchical clustering algorithm, resulting in a list of 27 variables that are not highly correlated with each other. These characteristics are divided into nine interpretation groups or combinations thereof, namely: (1) Liquidity; (2) Momentum; (3) Performance; (4) Size; (5) Value; (6) Change in Liquidity; (7) Change in Performance; (8) Change in Size; and (9) Change in Value. While the existence of the anomalies found in prior Australian literature (size, price-per-share, M/B, cashflow-to-price, and shortto mediumterm momentum) is confirmed, the PIE effect is not found to be significant in this study. As these previously documented anomalies only cover five of the final 27 characteristics, this paper identifies 22 new Australian anomalies. Six style-timing models are evaluated for the ability to forecast the monthly payoffs to the 27 characteristics. A twelve-lag autoregressive model convincingly displays the best performance against moving average and historic mean models. Parametric and nonparametric tests find inconclusive evidence of seasonality in the monthly payoffs to the attributes. The 27 significant style characteristics are then used to construct a multifactor stylecharacteristics model which comprises a set of factors that are significant when simultaneously cross-sectionally regressed on share returns. The employed construction method yields a five-factor style model for the ASX and comprises: (1) prior twelve-month momentum; (2) book-to-market value; (3) two-year percentage change in dividends paid; (4) cashflow-to-price; and (5) two-year percentage change in market-to-book value. Finally, a stepwise procedure is performed using six style-timing models. Five dynamic multifactor expected return models are created and contrast with a static multifactor expected return model similar to that used in van Rensburg and Robertson (2003). The derived expected return models have between three and thirteen factors . While all six models display good forecasting ability, the dynamic (trailing moving average) models all perform better than the static (historic mean) model. This is convincing evidence that the asset pricing relationship foll ows a dynamic model.