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Neglecting Parameter Changes In Garch Option Pricing Models And Var, Burak Hurmeydan
Neglecting Parameter Changes In Garch Option Pricing Models And Var, Burak Hurmeydan
LSU Doctoral Dissertations
In GARCH models, neglecting parameter changes in the conditional volatility process results in biased estimation. The estimated sum of the autoregressive parameters of the conditional volatility converges to one. In Chapter 2, I analyze the effect of changes in the parameters of conditional volatility on European call option prices when these parameters are estimated ignoring the change-points. Simulation studies show that ignoring parameter changes in the conditional variance process of GARCH(1,1) models leads to biased estimates of option prices. The bias, measured in percentages, is most pronounced for out-of-the-money options, substantial for at-the-money options, and vanishes as options move deep-in-the-money. …
Technology Diffusion And Total Factor Productivity Growth, Subaran Roy
Technology Diffusion And Total Factor Productivity Growth, Subaran Roy
LSU Doctoral Dissertations
I investigate the effects of two important channels of technology diffusion (i) Foreign Direct Investment (FDI) and (ii) import of capital goods, on the total factor productivity (TFP) growth. My first essay contributes to the literature by empirically investigating the role of initial distance of a country from the technology frontier in determining the net effect of FDI on TFP growth. In this essay, I find that the net effect of FDI on TFP growth decreases with the increase in distance. In order to take this research a step further, I implement the recently developed threshold regression technique to explore …
Essays On Models For Financial Volatility, Mihaela Oana Craioveanu
Essays On Models For Financial Volatility, Mihaela Oana Craioveanu
LSU Doctoral Dissertations
This research is focused on models for volatility. After the introduction of realized volatility as a consistent estimator for daily volatility, time series models without latent variables have been used to model and forecast volatility. The first part of this research provides a critical review of some of the commonly used realized volatility models and addresses the problem of stationarity and lag selection. In the empirical part we apply our methodology to thirty Dow Jones Industrial Average stocks from the NYSE TAQ dataset. We address the lag selection problem for each of the stocks considered. We find that models based …