Portfolio Management and Measurements Flashcards
Modern Portfolio Theory
According to Markowitz, the investor should view the rate of return associated with any one of these portfolios as a random variable; such variables can be “described” by their moments, two of which are:
Expected (or mean) value - measure of the potential reward associated with any portfolio
Standard deviation - measure of the risk associated with any portfolio
Measures of Return
Holding Period (Terminal Value - Initial Value) / Initial Value. This method’s major weakness is it fails to take the time value of money into account.
Dollar-Weighted Return (Internal Rate of Return) Breaks up the holding period so that the market value of the account after a change will be compounded by the amount of time it was earning the interest. It is the best way to measure an individual investor’s results.
Time-Weighted Return Calculates the return for the amount prior to a change caused by deposit or withdrawal. The individual returns are added together. It is more accurate than annualized returns.
Annualized Returns Either add the returns of the quarters together, or add 1 to each quarterly return, then multiply the four figures, and finally subtract 1 from the resulting product. This could be misleading because it does not consider how long each dollar was in the investment.
Security Expected Return
This procedure involves calculating the expected return on a portfolio as the weighted average of the expected returns on its component securities. The relative market values of the securities in the portfolio are used as weights. In symbols, the general rule for calculating the expected return on a portfolio consisting of N securities is:
rp= X1r1 + X2r2 + ⋯+ XNrN
where:
rp = the expected return of the portfolio
XI = the proportion of the portfolio’s initial value invested in security I
rI = the expected return of security I
N = the number of securities in the portfolio
Portfolio Standard Deviation
A useful measure of risk should take into account both the probabilities of various bad outcomes and their associated magnitudes. Instead of measuring the probability of a number of different possible outcomes, the measure of risk should estimate the extent to which the actual outcome is likely to diverge from the expected outcome. Standard deviation accomplishes this objective.
How is the standard deviation of a portfolio calculated?
σp= Sqrt (W2iσ2i+W2jσ2j+2WiWjCOVij)
Covariance
Covariance is a statistical measure of the relationship between two random variables. That is, it is a measure of how two random variables, such as the returns on securities i and j, “move together.” A positive value for covariance indicates that the securities’ returns tend to move in the same direction.
The formula sheet for the CFP® certification examination has the following formula for determining covariance:
COV=SDi × SDj × corr. coeff.ij
Correlation
Closely related to covariance is the statistical measure known as correlation coefficient. In fact, when it comes to diversification, the correlation coefficient is the most important statistic. Correlation coefficients always lie between -1.0 and +1.0. A value of -1.0 represents perfect negative correlation, and a value of +1.0 represents perfect positive correlation. In the real world, most financial assets have positive correlation coefficients ranging in value from .4 to .9. However, for purposes of diversification, combining assets with anything other than perfect positive (+1.0) correlation will have diversification benefits. The lower the coefficient (say .4 vs. .7) the better, and negative is much better than positive. If you could ever find perfect negatively correlated assets (in theory anyway), you could have zero risk with just two assets. Your return would be with complete certainty.
Correlation vs covariance
The difference between correlation coefficient and covariance is that covariance is more of a refined statistic, designed to take specific asset risk into account. Correlation coefficients are raw figures, which simply measure the degree of variation between two assets returns from one period to the next.
R squared
The correlation coefficient squared is known as the coefficient of determination in the statistical-world, but commonly known as R squared in the every-day world. The R squared is another extremely important statistic, in that it tells you the degree to which a fund or a portfolio is diversified.
For example, if I have a fund with an R squared of .92, that tells me that 92% of the variation of the fund’s returns are due to systematic forces (non-diversifiable). More importantly, it tells me 8% of the variation of the fund’s returns are due to unsystematic or diversifiable risk.
Negative corelated assets
Negatively correlated assets are NOT “necessary” to reduce risk (low positives are great).
Example
Example
Security A Security B
Expected Return 8% 14%
Standard Deviation 12% 30%
Portfolio Weight 40% 60%
Correlation Coef. = 0.22
Question:
What is the portfolio’s return?
What is the portfolio’s standard deviation?
Answer:
The portfolio weighted return is (40% × 8%) + (60% × 14%) = 11.60%
The portfolio standard deviation is as follows:
Since it is needed as input, calculate covariance between security A and security B first.
12 × 30 × .22 = 79.20
[(SD2i×W2i)+(SD2j×W2j)+2(Wi)(Wj)(COVij)]12
[(12 × 12 × .40 × .40) + (30 x 30 × .60 × .60) + (2 x .40 × .60 × 79.20)] ½
[ 23.04 + 324.00 + 38.02 ]½
[385.06]½
= 19.62 (This is a percent.)
Coefficient of Variation
Coefficient of Variation is a relative measure for determining if the return is worth the risk. Under the CAPM, it is an investment statistic that determines which investment is more efficient. The formula is standard deviation divided by the expected return.
The higher the number the higher the risk we are carrying per unit of return.
Risk of a portfolio
Two kinds of risk can be estimated:
the portfolio’s market (or systematic) risk, measured by its beta, and
the portfolio’s total risk, measured by its standard deviation.
Risk-Adjusted Performance Measures
Each one of these measures provides an estimate of a portfolio’s risk-adjusted performance, thereby allowing the client to see how the portfolio performed relative to other portfolios and relative to the market.
The following are CAPM-based measures of portfolio performance:
Sharpe ratio
Treynor ratio
Jensen ratio
Information ratio
Sharpe Ratio
William F. Sharpe devised the reward-to-variability index of portfolio performance, denoted SHARPEp. This defines a single parameter portfolio performance index that is calculated from both the risk and return statistics.
Treynor Ratio
Jack Treynor conceived an index of portfolio performance that is based on systematic risk, as measured by a portfolio’s beta coefficient. In fact, the only difference between the Sharpe Ratio and the Treynor Ratio, is the different measures of risk in the denominator.