Summary of a research paper - Essay Example

It would be therefore be interesting to review findings of such study which presents contradicting results and concludes from the perspective of investors that there are substantial variances in annualized stock returns in the long run. The journal article refers to previous studies including Siegel (2008) and Campbell and Viceira (2002, 2005) that have concluded that both unconditional and conditional variances in stock returns are greater in the shorter time frame as compared to the longer investment horizon.

The study by Pastor & Stambaugh is carried out from investors’ perspective and suggests that stock returns have greater volatility in the long run mainly due to two conditions which investors face. These include inability of investors to know the drivers of conditional expected return from stocks and also investors are of the view that even observable factors influencing stock returns forecasts do not sufficiently predict changes in conditional expected return. . The study adopted vector autoregression (VAR) model with assumptions that predictors are imperfect, which is a different approach as compared to previous studies by Stambaugh (1999), Barberis (2000), Hoevenaars et al. (2007). The study reflects that on the basis of imperfect predictors there are significant direct and indirect values in the long run.

The study considered five components of variances observed in the long run including the uncertainty pertaining to independent and identical distribution of returns over the term of analysis i.e. true variance, mean reversion, uncertainty of future and current expected stock return, and estimation risk. The study reveals that there is a positive relationship between long term variances and these components of variances except mean reversion. This implies that higher values of these components result in higher volatility of stock returns Mean reversion, which is an assumption that current negative shocks in the stock return are offset by positive return shocks in the future, has a negative impact on variances.

This does apply in the long run but its relevance is offset by other four components of long term variance. It is suggested in the research article that investors are not able to observe the variances and instead they rely on historical data of returns to predict future returns. Therefore, in the presence of imperfect predictors of returns there is a high degree of predictability which leads to greater volatility in the long term stock returns. The analysis of data in the report is divided into nine sections.

Expressions for five components of long term variations are developed using VAR and then using a predictive system conditional expected returns