overview

  • My research interests span econometrics (time series analysis), macroeconomics (business cycles), and finance (asset pricing).

    One line of research that I have pursued is the application of signal extraction techniques in analyzing macroeconomic issues. In this context, I have applied non-Gaussian state space models in a series of papers to uncover market expectations of inflation rates and to examine whether predictable components exist in stock returns. These models also adapt rapidly to abrupt changes in the behavior of time series; therefore I have compared their performance with the popularly used Markov switching models.

    In a second line of research I have examined whether or not economic expansions and contractions are statistically dissimilar. If they were indeed dissimilar then one would need to use non-linear models rather than simple linear models in order to characterize business cycle dynamics. I have provided robust statistical evidence on this issue using business cycle data in a series of articles.

    A third line of research examines the impact of fat tails in the driving processes of theoretical asset pricing models on their equilibrium implications. In a couple of articles I have sought to characterize in quantitative economic terms what is to be gained by taking fat tails into account.

    My current work aims to integrate these three strands of research, seeking to embed signal extraction into standard asset pricing models and to characterize the effects of non-linearities on the equilibrium dynamic implications of such models.

selected publications

research interests

  • Econometrics

full name

  • Prasad Bidarkota

visualizations

Recent publications and grants in Scholars@FIU

publication subject areas

Citation index-derived subject areas the researcher has published in