Calculation and Interpretation of the ...
The standard error (SE) of the sample mean refers to the standard deviation... Read More
Financial assets are primarily defined based on their return-risk characteristics. This definition approach helps when building a portfolio from all the assets available. It’s noteworthy that there are different ways of measuring returns.
Financial market assets generate two types of returns: Income from cash dividends or interest payments and capital gains or losses from changes in the prices of financial assets.
Some financial assets give only one stream of return. For instance, headline stock market indices typically only report on price appreciation. They do not include the dividend income unless the index clarifies that it is a “total return” series.
A holding period return is earned from holding an asset for a specified period, such as a day, month, or ten years.
The general formula of the holding period return is given by:
$$R=\frac{\left(P_1-P_0\right)+I_1}{P_0}$$
\(P_0\) = Price of an asset at the beginning of the period (t=0).
\(P_1\) = Price of an asset at the end of the period (t=1).
\(I_1\) = Income received at the end of the period (t=1).
Example: Calculating Holding Period Return
An investor purchased 100 shares of a stock at $50 per share and held the investment for one year. During that period, the stock paid dividends of $2 per share. At the end of the year, the investor sold all the shares for $60 per share.
The holding period return is closest to:
Solution
In this case, we have:
$$\begin{align}P_0&=100 \text{ shares} \times \$50\ \text{per share} =\$5,000\\ I_1&=100\ \text{shares} \times\$2\ \text{per share} =\$200\\ P_1&=100 \text{ shares} \times \$60\ \text{per share} =\$6,000\end{align}$$
Therefore,
$$R=\frac{\left(P_1-P_0\right)+I_1}{P_0}=\frac{6,000-5,000+200}{5,000}=24\%$$
Holding period returns can also be calculated for periods longer than a year. For instance, if we need to calculate the holding period return for a five-year period, we should compound the five annual returns as follows:
$$R=\frac{\left(P_5-P_0\right)+I_{(1-5)}}{P_0}$$
When we have assets with multiple holding periods, we must aggregate the returns into one overall return.
Denoted by \({\bar{R}}_i\) arithmetic mean for an asset \(i\) is a simple process of finding the average holding period returns. It is given by:
$${\bar{R}}_i=\frac{R_{i,1}+R_{i,2}+\ldots+R_{i,T-1}+R_{iT}}{T}=\frac{1}{T}\sum_{t=1}^{T}R_{it}$$
Where:
\(R_{it}\) = Return of asset \(i\) in period \(t\).
\(T\) = Total number of periods.
For example, if a share has returned 15%, 10%, 12%, and 3% over the last four years, then the arithmetic mean is computed as follows:
$${\bar{R}}_i=\frac{1}{T}\sum_{t=1}^{T}R_{it}=\frac{1}{4}\left(15\%+10\%+12\%+3\%\right)=10\%$$
Computing a geometric mean follows a principle similar to the one used to compute compound interest. It involves compounding returns from the previous year to the initial investment’s value at the start of the new period, allowing you to earn returns on your returns.
A geometric return provides a more accurate representation of the portfolio value growth than an arithmetic return.
Denoted by \({\bar{R}}_{Gi}\) the geometric return for asset \(i\) is given by:
$$\begin{align}{\bar{R}}_{Gi}&=\sqrt[T]{\left(1+R_{i,1}\right)\times\left(1+R_{i2}\right)\times\ldots\times\left(1+R_{i,T-1}\right)\times\left(1+R_{iT}\right)}-1\\ &=\sqrt[T]{\prod_{t=1}^{T}{(1+R_t)}}-1\end{align}$$
Using the same annual returns of 15%, 10%, 12%, and 3% as shown above, we compute the geometric mean as follows:
$$\begin{align}\text{Geometric mean} &=\ \left[\left(1+15\%\right)\times\ \left(1+10\%\right)\times\ \left(1+12\%\right)\times\ \left(1+3\%\right)\right]^\frac{1}{4}\ -1\\&=\ 9.9\%\end{align}$$
Note that the geometric return is slightly less than the arithmetic return. Arithmetic returns tend to be biased upwards unless the holding period returns are all equal.
The harmonic mean measures central tendency. It’s especially useful for rates or ratios such as P/E ratios. The harmonic mean’s formula is derived from the harmonic series, a specific mathematical sequence.
$${\bar{X}}_H=\frac{n}{\sum_{i=1}^{n}\frac{1}{X_i}},\ X_i>0 \text{ for all } i=1,2,\ldots,n$$
The above formula is interpreted as the “harmonic mean of observations \(X_1,\ X_2,\ldots,\ X_n\).”
The harmonic mean is handy for averaging ratios when those ratios are consistently applied to a fixed quantity, resulting in varying unit numbers. For instance, it’s applied in cost-averaging strategies where you invest a fixed amount of money at regular intervals.
An investor practices cost averaging by investing in a particular stock over a three-month period. The investor decides to allocate different amounts of money each month. In the first month, the investor invests $2,000; in the second month, $3,000; and in the third month, $4,000. The share prices of the stock for these three months are $10, $12, and $15, respectively.
Calculate the average price paid per share for the three-month period.
Solution
Using the harmonic mean formula,
$${\bar{X}}_H=\frac{n}{\sum_{i=1}^{n}\frac{1}{X_i}}=\frac{3}{\frac{1}{10}+\frac{1}{12}+\frac{1}{15}}=12$$
Trimmed and Winsorized means seek to lower the effect of outliers in a data set.
The trimmed mean is a measure of central tendency. We calculate it after excluding a small percentage of the lowest and highest values from a dataset.
For example, a data set consists of 10 observations: 12, 15, 18, 20, 22, 25, 27, 30, 35, and 40. We can calculate the trimmed mean after removing the highest and lowest values.
After removing these values, the remaining data set is 15, 18, 20, 22, 25, 27, 30, and 35.
Now, let’s calculate the trimmed mean by taking the average of these remaining values:
$$\frac{15+18+20+22+25+27+30+35}{8}\ =\frac{192}{8}\ \ =\ 24$$
Therefore, the trimmed mean of the given data set is 24.
The Winsorized mean is a central tendency measure. It works by replacing extreme values at both ends of the data with the values of their closest observations. This process is similar to the trimmed mean. Essentially, it helps eliminate outliers in a dataset.
For example, consider a dataset of 12 observations: 8, 12, 15, 18, 20, 22, 25, 27, 30, 35, 40, and 50. We can calculate the Winsorized mean by replacing the lowest and highest values with those closest to the 10th and 90th percentiles, respectively. As such, the new values are 10, 12, 15, 18, 20, 22, 25, 27, 30, 35, 37.5, and 40, and the winsorized mean is:
$$\frac{10 +12+15+ 18 + 20 +22 + 25 +27 +30+35+37.5+40}{12} \approx 24.46$$
Question 2
What are the arithmetic mean and geometric mean, respectively, of an investment that returns 8%, -2%, and 6% each year for three years?
A. Arithmetic mean = 5.3%; Geometric mean = 5.2%.
B. Arithmetic mean = 4.0%; Geometric mean = 3.6%.
C. Arithmentic mean = 4.0%; Geometric mean = 3.9%.
Solution
The correct answer is C.
$$ \text{Arithmetic mean} = \frac {8\% + (-2\%) + 6\%} {3} = 4\% $$
$$ \text{Geometric mean} = [(1+8\%) × (1+(-2\%)) × (1+6\%)]^{1/3} – 1 = 3.9\% $$