Add training workflow, datasets, and runbook

training_data/curated/text/2b51cb6320b56bc634472f1d626e400622df82dd17041fa19e3e678cea0512f1.txt

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+Chapter 28: Mathematical Applications 
+TABLE 28-3. 
+Distance weighting factors. 
+465 
+Option 
+Distonce 
+from 
+Stock Price 
+Distance 
+Weighting Factor 
+January 30 
+January 35 
+April 35 
+April 40 
+TABLE 28-4. 
+Option's implied volatility. 
+.091 (3/33) 
+.061 (2/33) 
+.061 (2/33) 
+.212 (7 /33) 
+.41 
+.57 
+.57 
+.02 
+Volume Distance Option's Implied 
+Option Factor Factor Volotility 
+January 30 .25 .41 .34 
+January 35 .45 .57 .28 
+April 35 .275 .57 .30 
+April40 .025 .02 .38 
+Implied = .25 x .41 x .34 + .45 x .57 x .28 + .275 x .57 x .30 + .025 x .02 x .38 
+volatility. .25 x .41 + .45 x .57 + .275 x .57 + .025 x .02 
+= .298 
+ual option's implied volatilities. Rather, it is a composite figure that gives the most 
+weight to the heavily traded, near-the-money options, and very little weight to the 
+lightly-traded (5 contracts), deeply out-of-the-money April 40 call. This implied 
+volatility is still a form of standard deviation, and can thus be used whenever a stan­
+dard deviation volatility is called for. 
+This method of computing volatility is quite accurate and proves to be sensitive 
+to changes in the volatility of a stock. For example, as markets become bullish or 
+bearish (generating large rallies or declines), most stocks will react in a volatile man­
+ner as well. Option premiums expand rather quickly, and this method of implied 
+volatility is able to pick up the change quickly. One last bit of fine-tuning needs to be 
+done before the final volatility of the stock is arrived at. On a day-to-day basis, the 
+implied volatility for a stock - especially one whose options are not too active may 
+fluctuate more than the strategist would like. A smoothing effect can be obtained by