for this regression is defined as the value of exercise possibilities (dependent on market price) plus the value of the timestep value which that exercise would result in (defined in the previous step of the process). Secondly, when all states are valued for every timestep, the value of the option is calculated by moving through the timesteps and states by making an optimal decision on option exercise at every step on the hand of a price path and the value of the state that would result in. This second step can be done with multiple price paths to add a stochastic effect to the procedure. Application As can be seen, Monte Carlo Methods are particularly useful in the valuation of options with multiple sources of uncertainty or with complicated features, which would make them difficult to value through a straightforward Black–Scholes-style or lattice based computation. The technique is thus widely used in valuing path dependent structures like lookback- and Asian options and in real options analysis. Additionally, as above, the modeller is not limited as to the probability distribution assumed. Conversely, however, if an analytical technique for valuing the option exists—or even a numeric technique, such as a (modified) pricing tree—Monte Carlo methods will usually be too slow to be competitive. They are, in a sense, a method of last resort; see further under Monte Carlo methods in finance. With faster computing capability this computational constraint is less of a concern. See also Monte Carlo methods in finance Quasi-Monte Carlo methods in finance Stochastic modelling (insurance) Stochastic asset model References Notes Sources Primary references Bibliography External links Online tools Monte Carlo simulated stock price time series and random number generator (allows for choice of distribution), Steven Whitney Discussion papers and documents Monte Carlo Simulation, Prof. Don M. Chance, Louisiana State University Pricing complex options using a simple Monte Carlo Simulation, Peter Fink (reprint at quantnotes.com) MonteCarlo Simulation in Finance, global-derivatives.com Monte Carlo Derivative valuation, contd., Timothy L. Krehbiel, Oklahoma State University–Stillwater Applications of Monte Carlo Methods in Finance: Option Pricing, Y. Lai and J. Spanier, Claremont Graduate University Option pricing by simulation, Bernt Arne Ødegaard, Norwegian School of Management Pricing and Hedging Exotic Options with Monte Carlo Simulations, Augusto Perilla, Diana Oancea, Prof. Michael Rockinger, HEC Lausanne Monte Carlo Method, riskglossary.com Monte Carlo methods in finance Options (finance)