Add training workflow, datasets, and runbook

training_data/relevant/text/4265d318ab59a70724df029d7e12ec8b4c7f64d76a332aed913695663d23a49c.txt

@@ -0,0 +1,20 @@
+Vega
+Over the past decade or so, computers have revolutionized option trading.
+Options traded through an online broker are filled faster than you can say,
+“Oops! I meant to click on puts.” Now trading is facilitated almost entirely
+online by professional and retail traders alike. Market and trading
+information is disseminated worldwide in subseconds, making markets all
+the more efficient. And the tools now available to the common retail trader
+are very powerful as well. Many online brokers and other web sites offer
+high-powered tools like screeners, which allow traders to sift through
+thousands of options to find those that fit certain parameters.
+Using a screener to find ATM calls on same-priced stocks—say, stocks
+trading at $40 a share—can yield a result worth talking about here. One $40
+stock can have a 40-strike call trading at around 0.50, while a different $40
+stock can have a 40 call with the same time to expiration trading at more
+like 2.00. Why? The model doesn’t know the name of the company, what
+industry it’s in, or what its price-to-earnings ratio is. It is a mathematical
+equation with six inputs. If five of the inputs—the stock price, strike price,
+time to expiration, interest rate, and dividends—are identical for two
+different options but they’re trading at different prices, the difference must
+be the sixth variable, which is volatility.