Add training workflow, datasets, and runbook

training_data/curated/text/4fc95efa7f207f3a234b06920e7af99d64cb94e5375609b8e2f8e07be1d49027.txt

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+470 
+where 
+v = annual volatility 
+t = time, in years 
+vt = volatility for time, t. 
+Part IV: Additional Considerations 
+As an example, a 3-month volatility would be equal to one-half of the annual 
+volatility. In this case, t would equal .25 (one fourth of a year), so v_25 = v65 = .5v. 
+The necessary groundwork has been laid for the computation of the probabili­
+ty necessary in the expected return calculation. The following formula gives the prob­
+ability of a stock that is currently at price p being below some other price, q, at the 
+end of the time period. The lognormal distribution is assumed. 
+Probability of stock being below price q at end of time period t: 
+P (below) = N (In~)) 
+where 
+N = cumulative normal distribution 
+p = current price of the stock 
+q = price in question 
+In = natural logarithm for the time period in question. 
+If one is interested in computing the probability of the stock being above the 
+given price, the formula is 
+P (above)= 1- P (below) 
+With this formula, the computation of expected return is quickly accomplished 
+with a computer. One merely has to start at some price - the lower strike in a bull 
+spread, for example - and work his way up to a higher price - the high strike for a 
+bull spread. At each price point in between, the outcome of the spread is multiplied 
+by the probability of being at that price, and a running sum is kept. 
+Simplistically, the following iterative equation would be used. 
+P ( of being at price x) = P (below x) - P (below y) 
+where y is close to but less than x in price. As an example: 
+P (of being at 32.4) = P (below 32.4) - P (below 32.3)