when statistically analyzing positive correlation it is important to understand the dataset s p value p value is the statistical measurement of how statistically significant the findings are in general a higher p value indicates there is greater evidence that two data points are more strongly correlated 6
positive correlation in financea simple example of positive correlation involves the use of an interest bearing savings account with a set interest rate the more money that is added to the account whether through new deposits or earned interest the more interest that can be accrued similarly a rise in the interest rate will correlate with a rise in interest generated while a decrease in the interest rate causes a decrease in actual interest accrued investors and analysts also look at how stock movements correlate with one another and with the broader market most stocks have a correlation between each other s price movements somewhere in the middle of the range with a coefficient of 0 indicating no relationship whatsoever between the two securities 7a stock in the online retail space for example likely has little correlation with the stock of a tire and auto body shop while two similar retail companies will see a higher correlation this is because businesses that have very different operations will produce different products and services using different inputs each of these companies face different risks opportunities and operational challenges modern portfolio theory is heavily rooted in diversification the concept that an investor should hold assets that are widely unrelated to reduce portfolio wide risk this flies in the face of positive correlation investing theory usually states that investors should be wary of widespread positive correlation within their portfolio for most investors an ideal investing strategy is to avoid positive correlation between assets and asset classes though every individual should evaluate their own investing strategy holding assets with positive correlation tends to increase the risk of loss 8beta and correlationbeta is a common measure of how correlated an individual stock s price is with the broader market often using the s p 500 index as a benchmark if a stock has a beta of 1 0 it indicates that its price activity is strongly correlated with the market a stock with a beta of 1 0 has a systematic risk but the beta calculation can t detect any unsystematic risk adding a stock to a portfolio with a beta of 1 0 doesn t add any risk to the portfolio but it also doesn t increase the likelihood that the portfolio will provide an excess return a beta of less than 1 0 means that the security is theoretically less volatile than the market meaning the portfolio is less risky with the stock included than without it for example utility stocks often have low betas because they tend to move more slowly than market averages a beta that is greater than 1 0 indicates that the security s price is theoretically more volatile than the market for example if a stock s beta is 1 2 it is assumed to be 20 more volatile than the market technology stocks and small caps tend to have higher betas than the market benchmark this indicates that adding the stock to a portfolio will increase the portfolio s risk but also increase its expected return some stocks even have negative betas a beta of 1 0 means that the stock is inversely correlated to the market benchmark as if it were an opposite mirror image of the benchmark s trends put options or inverse etfs are designed to have negative betas but there are a few industry groups like gold miners where a negative beta is also common 3a beta of 1 0 indicates a stock that moves in the same direction as the rest of the market a beta of 1 0 indicates that a stock moves opposite to the rest of the market 3positive correlation vs negative correlationnegative correlation is sometimes described as inverse correlation in statistics positive correlation describes the relationship between two variables that change together while an inverse correlation describes the relationship between two variables which change in opposing directions 9examples of positive correlations occur in most people s daily lives the more hours an employee works for instance the larger that employee s paycheck will be at the end of the week the more money is spent on advertising the more customers buy from the company inverse correlations describe two factors that seesaw relative to each other examples include a declining bank balance relative to increased spending habits and reduced gas mileage relative to increased average driving speed one example of an inverse correlation in the world of investments is the relationship between stocks and bonds in theory as stock prices rise the bond market tends to decline just as the bond market does well when stocks are underperforming 9it is important to understand that correlation does not necessarily imply causation variables a and b might rise and fall together or a might rise as b falls but it is not always true that the rise of one factor directly influences the rise or fall of the other both may be caused by an underlying third factor such as commodity prices or the apparent relationship between the variables might be a coincidence 4the number of people connected to the internet for example has been increasing since its inception and the price of oil has generally trended upward over the same period 1011 this is a positive correlation but the two factors almost certainly have no meaningful relationship that both the population of internet users and the price of oil have increased is explainable by a third factor namely general increases due to time passed 