Add training workflow, datasets, and runbook

training_data/curated/text/45ce4c210a56f7693046d9e591d213a50ace7c33481e3175c345b2886f5219bc.txt

@@ -0,0 +1,36 @@
+798 Part VI: Measuring and Trading Volatility 
+model, for example, uses a lognormal distribution. Personally, this author believes 
+that the Black-Scholes model is an excellent tool for analyzing options and option 
+strategies, but one must understand that it may not be affording enough probability 
+to large moves by the underlying. 
+Does this mean that most options are underpriced, since traders and market­
+makers are using the Black-Scholes model (or similar models) to price them? 
+Without getting too technical, the answer is that yes, some options - particularly out­
+of-the-money options - are probably underpriced. However, one must understand 
+that it is still a relatively rare occurrence to experience one of these big moves - ifs 
+just not as rare as the lognormal distribution would indicate. So, an out-of-the-money 
+option might be slightly underpriced, but often not enough to make any real differ­
+ence. 
+In fact, futures options in grains, gold, oil, and other markets that often experi­
+ence large and sudden rallies display a distinct volatility skew. That is, out-of-the-money 
+call options trade at significantly higher implied volatilities than do at-the-money 
+options. Ironically, there is far less chance of one of these hyper-standard-deviation 
+moves occurring in commodities than there is in stocks, at least if history is a guide. So, 
+the fact that some out-of-the-money futures options are expensive is probably an incor­
+rect overadjustment for the possibility of large moves. 
+THE PROBABILITY OF STOCK PRICE MOVEMENT 
+The distribution information introduced in this chapter can be incorporated into 
+somewhat rigorous methods of determining probabilities. That is, one can attempt to 
+assess the chances of a stock, futures contract, or index moving by a given distance, 
+and those chances can incorporate the fat tails or other non-lognormal behavior of 
+prices. 
+The software that calculates such probabilities is typically named a "probability 
+calculator." There are many such software programs available in the marketplace. 
+They range from free calculators to completely overpriced ones selling for more than 
+$1,000. In reality, high-level probability calculation software can be created by some­
+one with a good understanding of statistics, or a program can be purchased for a 
+rather nominal fee - perhaps $100 or so. 
+Before getting into these various methods of probability estimation, it should be 
+noted that all of them require the trader to input a volatility estimate. There are only 
+a few other inputs, usually the stock price, target price(s), and length of time of the 
+study. The volatility one inputs is, of course, an estimate of future volatility - some-