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Under this part, we present an informal discussion of the moving average of the logarithm of return on capital. We first look at the trend in the raw data, and then carry out a simple regression analysis to see whether the slope of the line is different from zero. An important consideration is the possibility of the auto correlation of a series being different from zero. This is important because the volatility of the series may also be a function of its past values. For example, if one investment fund generally outperforms another fund, its volatility may also be larger than the volatility of the other. The series that we are looking at may have a correlation of one. This means that the returns of this series will be correlated to its previous values, a fact that must be taken into account when we calculate the moving average. In the example, we will assume that this auto correlation is one. The end is to look at the standard deviation and see if it is different from zero. Some volatility in the series is a good thing in terms of the risk in the series. An investment portfolio, which is likely to go up and down, should have a high volatility. This would make the portfolio a more risky investment and reduce the risk in the portfolio. An investment portfolio, however, should have a low standard deviation. This means that it should be very stable. Many investment managers want a standard deviation of less than 0.3. The end result is that a portfolio, which has a standard deviation of 0.3, is most likely a poor investment. Assume that the risk level in the raw series is important, and we wish to reduce the risk to a minimum. If we were to identify a series of high volatility, we would be unable to define the risk. We would be unable to reduce the risk in the series. This idea may be carried out in practice using the following process. First, we would take the logarithm of the series and look at the volatility in the series. The reason for looking at the logarithm is that we know the volatility. If the volatility is high, we want to look at the logarithm of this volatility. It may be that the logarithm of the volatility is high, but the volatility is low, and thus the logarithm of the volatility is low. This will give us a measure of the volatility in the series. We also know that the volatility in the series is proportional to the absolute temperature and to the specific gravity

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