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Let s examine the use of the Cookie module..

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where we have dropped the time subscript for ease of notation. Here, m and are the constant instantaneous expected rate of return on the stock (drift rate) and volatility of the stock price, respectively. It turns out that this choice of constant volatility, although not entirely realistic, as we will see, is very robust and leads to a tractable model. The process is called geometric Brownian motion (geometric refers to the multiplicative nature of uctuations). The assumption of constant volatility is reasonable as a rst approximation. It means that the variance of the percentage return in a short period of time, dt, is the same regardless of the stock price. Then 2dt is the variance of the proportional change in the stock price in time dt, and 2S2dt is the variance of the actual change in the stock price, S, during dt. The SDE in equation (1.12) can be integrated in closed form. Indeed, suppose we know the stock price S at time t, St, and we are interested in the price ST at time T. We will solve the SDE subject to this initial condition by rst introducing a new variable, x: x = f(S) = lnS (1.13)

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N Round it up to the nearest penny. N Round it down to the nearest penny. N Round it to the nearest penny (the rounding may be up or down).

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