Please use this identifier to cite or link to this item: http://prr.hec.gov.pk/jspui/handle/123456789/16862
Title: Modeling Analysis and Managing Risk of Stock Markets Using Multifactor Econometric Approach Under Extend Inflationary and Deflationary Pressures
Authors: Ashraf, Muhammad Ather
Keywords: Business Education
Accounting and Finance
Issue Date: 2019
Publisher: The University of Lahore, Lahore.
Abstract: For more than one century we know that hyper inflation and full blown deflation are once a while kind of incidents like the times of the 1930s, hyper inflation in Germany and around same time frame in the USA was dealing with deflation and inflation in the USA in the 1970s. Even these incidents are country specific, sometimes one country or area is under inflation and other country or area is under deflation. Most of the times there is inflationary and deflationary pressures which central banks try to control and minimize its impact on the economy. Portfolio theory basically studies that how efficiently unsystematic risk can be minimized in the stock market by diversification, because even with simple diversification systematic risk cannot be avoided. Other theories which have been worked for the valuation of asset prices like stock market are Rational Expectation Theory, Arbitrage Pricing Theory (APT) and also the Efficient Market Hypothesis (EMH). When we call all these concepts into one theory then that can be considered as Joint Hypothesis theory. Based on EMH prices capture all relevant information at that time and based on newer version based on the “No Arbitrage” assumption only information affects the prices and the information which is already available does not matter. Major economies of USA, China, Japan and England were selected based on the portion of these economies as GDP and market cap is concerned. All these economies share more than 50% of GDP and market cap. Main time frames selected for this study based on two incidents one September 2001 and other Financial Crises. Based on this these time periods were split as 2002 to 2008 and 2008 to 2016. All this means if we take relevant technical, micro and macro variables then we should be able to establish a model which can show significance of these variables for the performance of stock markets. Basically after selecting the variables and in the light of wealth effect of stock market on economy and Efficient Market hypothesis by using Arbitrage Pricing Theory (APT) Approach we worked on the Econometric Model. APT was selected because this approach has been used for factor and variable analysis and also this can be used to calculate returns. To develop these Econometric Models we used Autoregressive Distributed Lag (ARDL) technique with Error Correction Models both for short and long run aspects of the results. We found out which variables are statistically significant and which markets are weak and which are not efficient. Based on the current literature and results of the proposed models in this study Japan economy is still under deflationary pressure and susceptible to deflation she saw for couple of decades. Models for other countries are selected such that we can see statistical significance of Japan performance for other countries. Based on this we can see impact of Japan economy on other selected countries. This relationship does not bode well for the USA markets based on this study. The findings from this study how market performance in inflationary and deflationary periods behave give us some idea from these models and this way we can reduce our risk by analyzing these behaviors of the markets. It seems like that even though Federal Reserve has started increasing rates all major Central Banks need to be keeping loose monetary policies in place for longer than expected time frame in the future. Keywords: Technical, Micro and Macro variables, ZIRP, SPY, ARDL, Error Correction Model, Wealth Effect, APT and EMH
Gov't Doc #: 21716
URI: http://prr.hec.gov.pk/jspui/handle/123456789/16862
Appears in Collections:PhD Thesis of All Public / Private Sector Universities / DAIs.

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