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Chemistry is often a place where Markov chains and continuous-time Markov processes are especially useful, because these simple physical systems tend to satisfy the Markov property quite well. The classical model of enzyme activity, Michaelis-Menten kinetics, can be viewed as a Markov chain, where at each time step the reaction proceeds in some direction. While Michaelis-Menten is fairly straightforward, far more complicated reaction networks can also be modeled with Markov chains. Markov chains are used in Finance and Economics to model a variety of different phenomena, including asset prices and market crashes. The first financial model to use a Markov chain was from Prasad et al in 1974.[9] Another was the regime-switching model of James D. Hamilton (1989), in which a Markov chain is used to model switches between periods of high volatility and low volatility of asset returns.[10] A more recent example is the Markov Switching Multifractal asset pricing model, which builds upon the convenience of earlier regime-switching models.[11] It uses an arbitrarily large Markov chain to drive the level of volatility of asset returns.