On the filtering of stochastically non-linear economic time series: An application to stock prices.

Title: On the filtering of stochastically non-linear economic time series: An application to stock prices.
Identifier: AAI9130320
identifier: 9130320
Creator: Han, Sangwan.
Contributor: Adviser: Salih N. Neftci
Date: 1991
Language: English
Publisher: City University of New York.
Subject: Economics, General | Economics, Finance
Abstract: The aim of this paper is to contribute to an understanding of the filtering theory of stochastically non-linear economic time series. Both the linear and non-linear filters are derived and applied to three different stock price indices (Standard & Poor's, Korean Composite Stock Price Index and Dow Jones Industrial Average) under the assumption that stock prices follow a two-state, first-order markov process. The results will show that, under fairly general condition, the non-linear filter outperforms the linear filter. However, if cost effectiveness is a source of major concern, the linear filter is preferable.
Type: dissertation
Source: PQT Legacy CUNY.xlsx
degree: Ph.D.

Media: On the filtering of stochastically non-linear economic time series: An application to stock prices.