Phase Transition in a Log-Normal Markov Functional Model

We derive the exact solution of a one-dimensional Markov functional model with log-normally distributed interest rates and constant volatility in the terminal measure. The model is shown to have two distinct limiting states, corresponding to small and asymptotically large volatilities, respectively. These volatility regimes are separated by a phase transition at some critical value of the volatility, at which certain expectation values display non-analytical behavior as a function of volatility. We investigate the conditions under which this phase transition occurs, and show that it is related to the position of the zeros of an appropriately defined generating function in the complex plane, in analogy with the Lee-Yang theory of the phase transitions in condensed matter physics