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PREDICITING BULL AND BEAR IN THE SWEDISH STOCK MARKET

Saleh Tabari, Arash LU (2016) NEKN01 20161
Department of Economics
Abstract (Swedish)
Very little if any previous research has been done on the potential predictability of bear and bull regimes in the Swedish stock market. In this study my aim is to predict OMXS30 bull and bear regimes with dynamic binary time series models. After using a nonparametric approach to identify the regimes of bull and bear periods in the market I looked at both an in sample and out of sample test. Based on monthly data I found different predictive variables, with the variables with highest predictive power being, the term spread and market liquidity deviation. Further variables with statistically significant results and predictive power are, the federal fund rate, purchasing manager index and the nominal return. The result can be improved using... (More)
Very little if any previous research has been done on the potential predictability of bear and bull regimes in the Swedish stock market. In this study my aim is to predict OMXS30 bull and bear regimes with dynamic binary time series models. After using a nonparametric approach to identify the regimes of bull and bear periods in the market I looked at both an in sample and out of sample test. Based on monthly data I found different predictive variables, with the variables with highest predictive power being, the term spread and market liquidity deviation. Further variables with statistically significant results and predictive power are, the federal fund rate, purchasing manager index and the nominal return. The result can be improved using the dynamic structure in the binary response model. Using multivariate dynamic binary time series I found that the model yield higher returns than the buy and hold strategy. (Less)
Please use this url to cite or link to this publication:
author
Saleh Tabari, Arash LU
supervisor
organization
course
NEKN01 20161
year
type
H1 - Master's Degree (One Year)
subject
keywords
Dynamic, Binary, State, Conditional probability, Probit model
language
English
id
8890582
date added to LUP
2016-09-09 14:02:21
date last changed
2016-09-09 14:02:21
@misc{8890582,
  abstract     = {Very little if any previous research has been done on the potential predictability of bear and bull regimes in the Swedish stock market. In this study my aim is to predict OMXS30 bull and bear regimes with dynamic binary time series models. After using a nonparametric approach to identify the regimes of bull and bear periods in the market I looked at both an in sample and out of sample test. Based on monthly data I found different predictive variables, with the variables with highest predictive power being, the term spread and market liquidity deviation. Further variables with statistically significant results and predictive power are, the federal fund rate, purchasing manager index and the nominal return. The result can be improved using the dynamic structure in the binary response model. Using multivariate dynamic binary time series I found that the model yield higher returns than the buy and hold strategy.},
  author       = {Saleh Tabari, Arash},
  keyword      = {Dynamic,Binary,State,Conditional probability,Probit model},
  language     = {eng},
  note         = {Student Paper},
  title        = {PREDICITING BULL AND BEAR IN THE SWEDISH STOCK MARKET},
  year         = {2016},
}