An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model

Article Abstract:

This research highlights the chance that the systematic risk of an asset is stochastic. Theoretically, modeling of this behavior might be achieved through a semblance of the ARIMA type of modeling, but this research sticks with the development of a first-order autoregressive model. Technique considerations in estimation and market model generalizations are highlighted. Findings show strong support for dumping the fixed parameter model in the face of the choice that systematic risk is stochastic. There is not such strong evidence that the autoregressive parameter is not zero. A random coefficient model might be appropriate. Tables of market model test results and maximum likelihood estimates for autoregressive parameters are included. One hundred and twenty monthly observations, on almost five hundred stocks showed strong randomness in systemic risk in market modeling. Findings did not point to the autocorrelation of risk, but should be weighed against the likelihood of model instability through time.

Models, Risk (Economics), Stochastic processes, Numbers, Random, Random numbers

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Market Timing and Mutual Fund Performance: An Empirical Investigation

Article Abstract:

Market timing capacities of one hundred and sixteen open end mutual funds are analyzed with parametric and nonparametric tests of forecasting. Data from 1968 to 1980 was examined. Tests were based on the basic market timing model proposed by Merton, which pits performance against securities risk levels. Since no actual market timing forecasts of mutual fund managers could not be established, the alternatives were to employ a proxy forecast or stipulate to a specific return-generating process. Returns data involved paid dividends. Sample funds, and the goals of individual funds are highlighted in an appendix. Separate contributions for micro application of weighted timing are found through an application of weighted least squares regression analysis, the mathematical formulas of which are furnished. Forms are also provided for heteroscedasticity corrections in parametric tests. Tables of sample and parametric data are included.

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Achieving Representativeness of the Observable Component of the Indirect Utility Function in Logit Choice Models: An Empirical Revelation

Article Abstract:

Probabilistic discrete-choice models (PDCMs) are traditionally derived using single observations on a sample of individuals. The question explored is whether there are any identifiable individual-specific dimensions which might be encompassed in the representative utility (RU) expression to account for individual differences. The procedure for investigating the representative utility assumption is described. Results for group and individual coefficient models are analyzed. The contention is advanced that taste variation within a population is poorly explained by the socioeconomic differences within that population. The use of individual-specific coefficients produces a better model for design and marketing applications. However, for predicting overall market behavior the group model is recommended because its results are equal to the individual-specific models and less costly.

Analysis, Markets (Economics), Statistics, Statistics (Data), Social status

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