Rohit Deo, Affiliate

Professor Deo joined NYU Stern in 1995 and teaches MBA and undergraduate courses in data analysis and forecasting time series. His primary research areas include econometric models, financial data modeling, forecasting, stochastic volatility, and time series analysis. His recent research has focused on developing methods for carrying out reliable inference when only a limited amount of data on a highly dependent time series is available. Using the principles of curvature and invariance, Professor Deo has shown that appropriate likelihoods can yield simple and elegant solutions to problems that applied researchers in finance and economics commonly face in such situations. One application of Professor Deo's methodology is that of predictive regressions in finance, where researchers are interested in testing whether returns on assets are related to lagged values of predictor variables such as dividend-price ratios.

Professor Deo is an Associate Editor of the Journal of the American Statistical Association, the flagship journal of the American Statistical Association and also an Associate Editor of The American Statistician. He was ranked amongst the top 100 theoretical econometricians worldwide in 2007.

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