Our work on refining the Least Squares Monte Carlo (LSMC) algorithm was accepted for publication in "Quantitative Finance". The latest version of the paper is available on my SSRN page. In this paper we propose a methodology to reduce the bias of the original method. LSMC is preferred to other numerical methods is the case of complex options with multiple sources of risk. Although LSMC converges in theory, we show how challenging it can be to get precise results even with not so complex optio. We combine a simple technique to impose constraints in the regressions and we show it reduces the bias significantly. Efficient algorithms are available to solve the constrained regressions, making our refined method competitive compared to the original LSMC.

Great news! We just received our response after submitting our revised version of "Refining the Least Square Monte Carlo method by imposing structure": we have one single comment and we should be able to send a final version shortly.