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Before you can use an adaptive parameter, you must come up with a function or adaptive engine that automatically changes the value of the once static parameter The input of this adaptive engine should be some form of market statistic In the case of the Dynamic Break Out II, we used market volatility When market volatility expands, so does the number of look back days in our break out calculation Increased market volatility usually equates to market indecisiveness By increasing the number of look back days when market volatility increases, we make it more difficult for the system to initiate a trade When market volatility decreases, we reduce the number of look back days Low market volatility equates to a trending market By decreasing the number of look back days, we encourage the system to initiate a trade.

3 5 12 12 T Score 45 35 41 35 35 40 35 45 40 45 50 40 55 Standard Score 127 96 109 95 97 99 116 112 91 (continued)

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Axiom 2 (Independence) If the utility of X is no worse than that of Y, U(X) U(Y), there is a fraction 1 > q > 0, and an additional choice Z, then U[qX + (1 - q)Z] U[qY + (1 - q)Z] If X is equivalent to Y in utility, U(X) = U(Y), then U(X) = U[qX + (1 - q)Y] Axiom 2 ensures that the combinations of risky investments do not affect the expected utility of each Otherwise, an investor would have to continually revalue the same stock depending on what other stocks are held in the portfolio For example, the utility function U(X) = ln X matches Samuelson s axioms The marginal utility MU = U(X)/ X = (1/X) is diminishing, since as X increases, MU diminishes Therefore the function is concave, and evaluating the utility regardless of other choices assumes independence.

This helps the Dynamic Break Out II to lock into long-term profits and be on the look out for a change in the long-term trend We used market volatility to fuel our adaptive engine, but you could use any market characteristic We can visualize an engine that uses a market s overbought/oversold state If we had a long position in a market, and it became overbought, we could use an overbought/ oversold indicator to adapt the parameter that determines the sell point Once an adaptive engine is dreamed up and it is pumping out values, you must maintain the values in an acceptable range The Dynamic Break Out II system will not let the look back days go above 60 or below 20 Through optimization, we discovered that look back lengths that fell beyond these bound-.

Zoey is an 11-year 10-month-old repeating fourth grader who is being followed by her pediatric neurologist for a history of complex partial seizure disorder that began at approximately 1 to 2 years of age Initially, Zoey s seizures were febrile in nature; however, at approximately 2 to 3 years of age, she began having seizures without fever The seizures were characterized by an aura described by Zoey as It feels like it s coming up from my stomach This was followed by staring, loss of consciousness, right arm posturing, and lip smacking, after which Zoey might fall to the oor if she was not seated The seizures typically lasted 10 to 15 seconds, and she was averaging three to four every 2 weeks with multiple anti-epileptic medications (carbamazepine [Tegretol] and topiramate [Topamax]).

We will start at a wealth of $1 M Taking natural logarithms, the starting utility is ln(1) = 0 Now let us move to our choice The safe investment (a) would give a nal wealth of $105 M, or a utility of ln(105) = 00488 The risky investment (b) has a 50% chance of a utility of ln(115) = 01398 and a 50% chance of a utility ln(95) = -00513 Choice (b) gives an expected utility of E(U) = 05(01398) + 05(-00513) = 00443 Since 00488 > 00443, the commonsense choice in favor of the choice (a) can be justi ed simply by choosing a (nonlinear concave) logarithmic functional form of the utility function.

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