Standard Deviations In The Business World Case Study
Purpose of the Study The purpose of this study was to test Linneman’s trade rule and the Sharpe ratio. Researchers were trying to identify whether or not negative residuals on property were the result of undervaluation, causing an opportunity to make extra profits. The rationale of the trade rule suggests property price adjustment is a function of the market and is related to the value of the neighborhood’s physical characteristics.
Is there an opportunity to earn excess profits on undervalued properties based on the assumption of inefficiency in the market? …show more content…
Many corporations and mathematicians use all type of research to gather enough evidence to get even close to the infamous swings. “An analysis is made of a variance measure which could improve the predictive validity of a classical historical variance estimate. Latane and Rendleman derived standard deviations implied in actual call option prices (ISDs) after assuming that investors price options according to the Black-Scholes model. Their results indicated that the approach is valuable, at least from a pragmatic viewpoint.” Becker’s, S. (1981). Becker’s refers that the prediction of stock values rely heavily on their reliance to standard deviations and the efficiencies of their historical variance measurements.
Research Question: Can we predict the future price on a stock?
Hypothesis: History has shown us that after a storm there is calm, after a fire there is growth. Historical variances have been accurate when predicting what a stock will do. “Investment, stock prices, GDP, and interest rates. Stock prices are shown to be exogenous to the system, and investment is positively related to the stock prices. Investment and GDP would be significantly lower during the recessions since 1969 if stock prices adjusted immediately. High stock prices cushion the blow of the recession.” McCown, J. R. (2007).
Main Finding: Historical trends tell us that stock prices adjust slowly after a peak of a business cycle.
Abstract: Computing standard deviation: