Suppose that the price (S) of a stock has an expected return of 12% per annum and a volatility of 24% per annum. The stock price is currently $88. (a) Calculate the expected stock price at the end of the next day. (b) Calculate the standard deviation of the stock price at the end of the next day. (c) Find the 95% confidence limits for the stock price at the end of the next day. (d) If you are to do the same for the stock price at the end of the month, assuming that it is the beginning of a month now, is it appropriate to use the same method as above? Explain.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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