Yacine Aït-Sahalia (born 1966 in Algeria) is the Otto Hack 1903 Professor of Finance and Economics at Princeton University.

[8] Aït-Sahalia developed series expansions based on Hermite polynomials to represent in closed-form the transition density of arbitrary continuous-time diffusion models.

His series expansion, which represents the transition density as a power series in the time interval starting from a base density, makes it possible to accurately implement maximum-likelihood estimation of an arbitrary parametric continuous-time model using only discretely sampled data.

He has made numerous advances in the estimation and testing of models using high frequency data, with a particular focus on understanding the role and importance of jumps in joint work with Jean Jacod.

His work has shown how distinguishing jumps from volatility is possible, how to analyze the finer structure or spectrum of asset returns[12] including testing whether jumps are present and estimating their degree of activity, and how to implement principal component analysis in a high frequency setting.

[13] He also developed various methods to estimate volatility in situations where the high frequency data is noisy in joint work with Per Mykland and Lan Zhang.