High Probability Trading Strategies: Entry to Exit Tactics by Robert C. Miner

By Robert C. Miner

In High chance buying and selling Strategies, writer and famous buying and selling educator Robert Miner skillfully outlines each point of a pragmatic buying and selling plan–from access to exit–that he has built over the process his distinctive twenty-plus-year occupation. the result's a whole method of buying and selling that might let you exchange with a bit of luck in numerous markets and time frames. Written with the intense dealer in brain, this trustworthy source information a confirmed method of interpreting industry habit, opting for ecocnomic alternate setups, and executing and handling trades–from access to exit.

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Extra info for High Probability Trading Strategies: Entry to Exit Tactics for the Forex, Futures, and Stock Markets

Example text

8 for subsequent values of ti builds a tree with node values Suj dk 18 Chapter 1 Modeling Tools for Financial Options and j+k = i. In this way, specific discrete values Sj,i of Si and the nodes of the tree are defined. Since the same constant factors u and d underlie all meshes and since Sud = Sdu holds, after the time period 2Δt the asset price can only take three values rather than four: The tree is recombining. It does not matter which of the two possible paths we take to reach Sud. This property extends to more than two time periods.

From the continuous model we apply the relation 2 E(Si+1 ) = Si2 e(2r+σ 2 )Δt . 12). Recall that the variance satisfies Var(S) = E(S 2 ) − (E(S))2 (−→ Appendix B1). 8) combine to Var(Si+1 ) = Si2 e2rΔt (eσ 2 Δt − 1) . On the other hand the discrete model satisfies 2 ) − (E(Si+1 ))2 Var(Si+1 ) = E(Si+1 = p(Si u)2 + (1 − p)(Si d)2 − Si2 (pu + (1 − p)d)2 . 9) constitute two relations for the three unknowns u, d, p. We are free to impose an arbitrary third equation. 10) which reflects a symmetry between upward and downward movement of the asset price.

4 Mean Reversion The assumptions of a constant interest rate r and a constant volatility σ are quite restrictive. To overcome this simplification, SDEs for rt and σt have been constructed that control rt or σt stochastically. 40) again with driving force Wt as Wiener process. 40) is positive for rt < R and negative for rt > R, which causes a pull to R. This effect is called mean reversion. A frequency parameter α influences the strength of the reversion. The parameter R, which may depend on t, corresponds to a long-run mean of the interest rate over time.

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