Add training workflow, datasets, and runbook

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+828 Part VI: Measuring and Trading Volatility 
+make the move to profitability (or not make the move into loss territory, if you're sell­
+ing options). This is where historical volatility plays a big part, for it is the input into 
+the probability calculator. In fact, no probability calculator will give reasonable pre­
+dictions without a good estimate of volatility. Please refer to the previous chapter for 
+a more in-depth discussion of probability calculators and stock price distributions. 
+The use of probability analysis also mitigates some of the problems inherent in 
+the method of selection that compares implied and historical volatilities. If the prob­
+abilities are good for success, then we might not care so much whether the options 
+are currently in a low percentile of implied volatility or not (although we still would 
+not want to buy volatility when the options were in a high percentile of implied 
+volatility and we would not want to sell options that are in a low percentile). 
+In using the probability calculator, one first selects a strategy (straddle buying, 
+for example, if options are cheap) and then calculates the break-even points as 
+demonstrated in the previous section. Then the probability calculator is used to 
+determine what the chances are of the underlying instrument ever trading at one or 
+the other of those break-even prices at any time during the life of the option position. 
+It was shown in the previous chapter that a Monte Carlo simulation using the fat tail 
+distribution is best used for this process. 
+An attractive volatility buying situation should have probabilities in excess of 
+80% of the underlying ever exceeding the break-even point, while an attractive 
+volatility selling situation should have probabilities of less than 25% of ever trading 
+at prices that would cause losses. The volatility seller can, of course, heavily influence 
+those probabilities by choosing options that are well out-of-the-money. As noted 
+above, the volatility seller should, in fact, calculate the probabilities on several dif­
+ferent striking prices, striving to find a balance between high probability of success 
+and the ability to take in enough premium to make the risk worthwhile. 
+Example: The OEX Index is trading at 650. Suppose that one has determined that 
+volatilities are too high and wants to analyze the sale of some naked options. 
+Furthermore, suppose that the choices have been narrowed down to selling the 
+September options, which expire in about five weeks. The main choices under con­
+sideration are those in Table 39-2. The option prices in this example, being index 
+options, reflect a volatility skew (to be discussed later) to make the example realistic. 
+The two right-hand columns should be rejected because the probabilities of 
+the stock hitting one or the other of the striking prices prior to expiration are too 
+high well in excess of the 25% guideline mentioned earlier. That leaves the 
+September 500-800 strangle or the September 550-750 strangle to consider. The 
+probabilities are best for the farthest out-of-the-money options (September 500-
+800 strangle), but the options are selling at such small prices that they will not pro-