Add training workflow, datasets, and runbook
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886 Part VI: Measuring and Trading Volatility
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that is somewhat variable. But, for the purposes of such a projection, it is acceptable
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to use the current volatility. The results of as many as 9 stock prices might be dis
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played: every one-half standard deviation from -2 through + 2 (-2.0, -1.5, -1.0,
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-0.5, 0, 0.5, 1.0, 1.5, 2.0).
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Example: XYZ is at 60 and has a volatility of 35%. A distribution of stock prices 7
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days into the future would be determined using the equation:
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Future Price = Current Price x eav-ft
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where
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a corresponds to the constants in the following table: (-2.0 ... 2.0):
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# Standard Deviations
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-2.0
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- 1.5
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- 1.0
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-0.5
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0
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0.5
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1.0
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1.5
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2.0
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Projected Stack Price
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54.46
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55.79
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57.16
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58.56
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60.00
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61.47
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62.98
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64.52
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66.11
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Again, refer to Chapter 28 on mathematical applications for a more in-depth
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discussion of this price determination equation.
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Note that the formula used to project prices has time as one of its components.
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This means that as we look further out in time, the range of possible stock prices will
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expand - a necessary and logical component of this analysis. For example, if the
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prices were being determined 14 days into the future, the range of prices would be
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from 52.31 to 68.82. That is, XYZ has the same probability of being at 54.46 in 7 days
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that it has of being at 52.31 in 14 days. At expiration, some 90 days hence, the range
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would be quite a bit wider still. Do not make the mistake of trying to evaluate the
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position at the same prices for each time period (7 days, 14 days, 1 rnonth, expiration,
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etc.). Such an analysis would be wrong.
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Once the appropriate stock prices have been determined, the following quanti
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ties would be calculated for each stock price: profit or loss, position delta, position
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gamma, position theta, and position vega. (Position rho is generally a less important
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risk measure for stock and futures short-term options.) Armed with this information,
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the strategist can be prepared to face the future. An important item to note: A model
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