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One-Time Binary Search Tree Balancing - Size
One-Time Binary Search Tree Balancing - Size

Abnormal Returns, Risk, and Options in Large Data Sets
Abnormal Returns, Risk, and Options in Large Data Sets

... have periods of quiescence and turbulence. A popular model for this feature is the class of ARCH processes, see Engle (1982). The ARCH model relates current variance to the past squared realizations. Kearns and Pagan (1997) considered how this second moment dependence might in uence the properties o ...
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CPS 214: Networks and Distributed Systems Lecture 4
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... See Calvo (1979) for a more detailed analysis of monetary models with perfect foresight. Using similar techniques, one can show that the present model boils down to two differential equations (in m and p), with no initial conditions. The linear approximation at the steady state displays two positive ...
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... are given k sorted lists L1 , . . . , Lk each of length n, and you want to find the successor of x in each of them. One could trivially solve this problem with k separate binary searches, resulting in a runtime of O(k log n). Fractional cascading allows this problem to be solved in O(k + log n). To ...
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Lattice model (finance)



For other meanings, see lattice model (disambiguation)In finance, a lattice model [1] is a technique applied to the valuation of derivatives, where, because of path dependence in the payoff, 1) a discretized model is required and 2) Monte Carlo methods fail to account for optimal decisions to terminate the derivative by early exercise. For equity options, a typical example would be pricing an American option, where a decision as to option exercise is required at ""all"" times (any time) before and including maturity. A continuous model, on the other hand, such as Black Scholes, would only allow for the valuation of European options, where exercise is on the option's maturity date. For interest rate derivatives lattices are additionally useful in that they address many of the issues encountered with continuous models, such as pull to par.
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