Here is some great information on dividend valuation models and statistical analysis to help you pass your series 65 exam
Dividend Valuation models
A fundamental analysts may use a dividend valuation model to determine a fair valuation for an equity security and to determine if an investment is warranted The two dividend valuation models most often use are the dividend discount model and the dividend growth model.
The Dividend Discount Model – The dividend discount model takes the sum of all future dividends to be received and discounts them into a net present value. The model states that the market price of the stock should be equal to the net present value of all future cash flows. A simple way to estimate the value based on this method would be to take the annual dividend and divide it by the prevailing rate paid by other similar investments. If a utility stock is paying a $2 annual dividend and other similar utilities are yielding 5% the market price can be estimated to be $40 . Found as follows: $ 2 / .05 =$40
The dividend discount model may be used for issues that have both fixed and variable dividends over time
The Dividend Growth Model - The Dividend Growth Model values the stock based on the net present value of the cash flow to be generated by a dividend that is expected to grow over time. It is unlikely that you will have to calculate the value of a stock based on the dividend growth model. It is important to know that the present value is significantly higher for an equity with a dividend that is predicted to grow. The higher the growth rate the higher the net present value.
Some analysts will employ statistical analysis or the study of mathematical data in security evaluation models. Analyst will plot the price points at which a security has traded under a standardized bell curve to determine the potential pricing outcomes for a security. The wider the distribution of the price points the wider the range. The range is the difference between the lowest price and highest price at which a security has traded over a given period. The wider the range the higher the standard deviation and therefore the higher the risk associated with the security and its potential return. Analysts will review the price points plotted underneath the bell curve distribution to determine various measures of central tendency. There are several measures that can be used to determine the midpoint of the range all distributions, these are the arithmetic mean, median and mode.
The arithmetic mean – the arithmetic mean is found by adding all of the price observations together and dividing the total by the number of price observation. The arithmetic mean can be thought of as the average price at which the security traded over the observation period.
The Median- the median is the exact middle of all price observations and is the price point on the bell curve that separates the higher prices from the lower prices. The median is found by listing all of the prices numerically from lowest to highest and picking the price in the exact middle. If there is an even number of price observations there will be no single median value therefore the median value will be the average of the two middle values.
The Mode – the mode is the price observation that appears most frequently on the price distribution curve. Simply put the mode is the price at which the security has most frequently traded. While the mode will have a significant impact on the mean and median as a result of the frequency of its occurrences it tends to be a price that is not like the price calculated by the mean and the median
Statistical analysis may be applied to individual equities or to the returns generated by portfolios containing a number of securities. When comparing portfolios any portfolio with the highest mean relative to the median and mode contains investments that have significantly outperformed the other investments . Statistical analysis in finance is part of the broad school of quantitative analysis. Simply put quantitative analysis is based on the study of quantities ( the number of occurrences and observations ) analyst who employ quantitative analysis are known as “quants”
Beta measures systematic risk in the price volatility of a security relative to the market as whole. Standard deviation measures both systematic and unsystematic risk in the volatility of the return of a security versus its expected return