Do arbitrage pricing models explain the predictability of stock returns?

Article Abstract:

A study is conducted to examine the extent to which predictability in US security returns for multiple investment horizons is influenced by premiums for economy-wide risk factors. The standard methods for factor selection, single-beta models and multiple-beta models are compared. The results show that the multiple-beta models perform better than single-beta models, and that the five-principal-component model and the five-economic-factor-model perform comparably in capturing return predictability. Findings also show that models with constant betas and those with one to five factors do not provide a complete explanation for return predictability, but they do capture a sizeable portion of the predictability for all the investment horizons examined.

Prices and rates, Stocks, Pricing, Stock prices, Arbitrage

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Assessing the market timing performance of managed portfolios

Article Abstract:

A number of techniques are available to measure the separate components of portfolio performance, typically security selection and market timing. It is possible, however, to create artificial market timing - obtained at the cost of poorer measured security selectivity - by investing in option-like securities. This provides a possible explanation of previous empirical findings indicating a negative correlation between measured selectivity and timing ability. Two types of specification tests to help distinguish between spurious and true timing ability are suggested.

Analysis, Testing, Return on investment, Investment analysis, Securities analysis, Rate of return

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Correcting for heteroscedasticity in tests for market timing ability

Article Abstract:

This paper examines a parametric test that is designed to analyze the ability of portfolio managers to forecast stock market trends. Simulation models show that heteroscedasticity, or scatter effect in regression analysis, can introduce significant levels of error into judgements about market timing ability. By using covariance matrix estimators in the inference procedures, heteroscedasticity can be corrected.

Methods

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