Alex Sharpe's Portfolio

Fama and French’s three factor model attempts to explain the variation of stock prices through a multifactor model that includes a size factor and BE/ME factor in addition to the beta risk factor. Fama-French model essentially extended the CAPM (which breaks up cause of variation of stock price into systematic risk which is non-diversifiable and idiosyncratic risk which is diversifiable) by introducing these two additional factors. Fama and French find that stocks with high beta didn’t have consistently higher returns than stocks with low beta and this indicates that beta was not a useful measure under their model. Their model is based on research findings that sensitivity of movements of the size and BE/ME factor constituted risk, and

So according to the Efficient Market Theory it is impossible for any investor to “beat the market” that is earn more profit or get more return than what the market is actually offering. Therefore the investor can only earn greater profits on his investment if the investment portfolio includes a high proportion of risky investments that is those with higher standard deviations and betas but with a good capability of yielding high returns as well (Stephens, C.R., 2010).

STP) and one risky asset (i.e. US Equities) and the expected return and risk are also linearly related to the weight in the risky asset. The highest Sharpe ratio from these risk-return opportunities available is also where 90% of the portfolio is comprised of STP and 10% of US Equities.

The extracted data used includes monthly returns from January 1972 to July 2011. The assets are selected so that the portfolio contains the largest, most liquid, and most tradable assets. The choice of such a variety of assets across several markets was used in order to generate a large cross sectional dispersion in average return. It helped to reveal new factor exposure and define a general framework of the correlated value and momentum effects in various asset classes.

Advisors and investors would do well to pay as much attention to the expected volatility of any portfolio or investment as they do to anticipated returns. Moreover, all things being equal, a new investment should only be added to a portfolio when it either reduces the expected risk for a targeted level of returns, or when it boosts expected portfolio returns without adding additional risk, as measured by the expected standard deviation of those returns. Lesson 2: Don’t assume bonds or international stocks offer adequate portfolio diversification. As the world’s financial markets become more closely correlated, bonds and foreign stocks may not provide adequate portfolio diversification. Instead, advisors may want to recommend that suitable investors add modest exposure to nontraditional investments such as hedge funds, private equity and real assets. Such exposure may bolster portfolio returns, while reducing overall risk, depending on how it is structured. Lesson 3: Be disciplined in adhering to asset allocation targets. The long-term benefits of portfolio diversification will only be realized if investors are disciplined in adhering to asset allocation guidelines. For this reason, it is recommended that advisors regularly revisit portfolio allocations and rebalance

“The Benefits of diversification are clear. Portfolio theory has played a crucial role in explaining the relationship between risk and return where more than one investment is held. It also enables us to identify optimal and efficient portfolios.”

The lower the risk that is associated with an investment, that investment usually has a potential for lower returns. Conversely, if there are high levels of risk associated with an investment, and in turn a potential for a higher return.

If we were only to consider the expected return, then the S&P 500 appears to be the best investments since it has the greatest expected return. 3. The standard deviation provides a measurement of the total risk by examining the tightness of the probability distribution associated with the different possible outcomes whereas the coefficient of variation measures risk per unit. The coefficient of variation is a better

Estimate and compare the returns and variability (i.e. annual standard deviation over the past five years) of Reynolds and Hasbro with that of the S&P 500 Index. Which stock appears to be riskiest?

When we measure risk per unit of return, Collections, with its low expected return, becomes the most risky stock. The CV is a better measure of an asset’s stand-alone risk than because CV considers both the expected value and the dispersion of a distribution—a security with a low expected return and a low standard deviation could have a higher chance of a loss than one with a high but a high .

We use the equation ri=(Pt-Pt-1+Dt)/Pt-1 to calculate the monthly return of stock of Charles Schwab Corp, Quick & Reilly Group and Waterhouse Investor Srvcs. Then we have two methods to calculate the Beta of Equity for each company.

A common practice to determine the firm’s beta is to draw from historical data from published sources or compare numbers to competitors. In this case, Heinz can compare to Kraft, Campbell Soup and Del Monte and use professional judgement in determining the stock’s sensitivity to the market. A stock’s beta can be determined using a formula as well.

By comparing both the stocks, the riskiest stock in this case is Reynolds. It has the highest return as well as higher standard deviation and the higher variance. If we compare both stocks, Reynolds is riskier than Hasbro in this case. The higher variance indicates higher chance that the actual return on Reynolds will deviate from the expected return.

Using time series regression on the monthly returns we have estimated the beta coefficient for each stock. Using the market model of CAPM i.e., regressing each stock’s monthly returns against the market index (Nifty100) we have estimated individual stock beta’s.

The betas (slope of estimated regression equation) for the individual stocks can be obtained from the regression