Since the beta systematic risk coefficient and the standard deviation are both important statistics in the received capital market theory [22] and the received option theory [1], considerabe effort has been expended on obtaining empirical estimates of these statistics [30]. The ordinary least squares (OLS) technique is typically utilized to estimate beta as the regression coefficient of a simple linear regression. However, the OLS betas for common stocks were found to be disconcertingly unstable over time [5, 6, 13, 15, 25]. But, whether the OLS beta or an adjusted beta were used, the regression statistics could still only explain less than half of the variability of most New York Stock Exchange (NYSE) stocks' returns (more specifically, R2

Part 1: The characteristics of securities: risk and return debt securities equity and asset-backed securities. Part 2: The market place: security markets security markets indexes regulation of the securities markets taxes. Part 3: Introduction to financial analysis: sources of financial information analysis of financial statements the interest-rate risk factor the default risk factor bond selection. Part 5: Investing in stocks: common stock analysis earnings analysis. Part 6: Other risk factors: the market risk factor the purchasing power risk factor and the industry risk factor the management risk factor and other risk factors. Part 7: Pulling things together and making decisions with APT: making buy-sell decisions arbitrage pricing theory (APT). Part 8 The behaviour of stock prices technical analysis choosing between technical analysis or fundamental analysis. Part 9: Other investments: options, warrants and convertibles futures contracts investing in real assets. Part 10: Portfolio management: capital market theory international diversification investments performance evaluation.

Includes traditional institutional material and newer, more abstract risk-return theories. The book contains examples, applications and appendices outlining the mathematics of the theories.

Monthly returns are used to estimate the single-index market model (SIMM). Binary variables are used to determine if the alpha intercept and beta slope coefficients are stable through alternating bull markets and bear markets. The results suggest that some investment analysts have fallen into the trap of misapplying econometric models and, as a result, are purveying erroneous information. Neither the alpha nor the beta statistics in the SIMM appear to be significantly affected by the alternating forces of bull and bear markets. Of course, the SIMM, the alpha, the beta and the statistics from all econometric models change from sample to sample. But, the question addressed here was whether or not these normal sampling errors were more than would occur in the classic stability tests. Such instability would tend to depreciate the value of the received risk-return theories. However, the SIMM was found to be unaffected by the three different bull and bear market conditions which were delineated.