Jamshed Y. Uppal

Evidence of nonlinear speculative bubbles in pacific-rim stock markets

Abstract Increased volatility of many stock markets in recent years has sometimes been associated with rapid increases or decreases in asset values that may contain elements of speculative bubbles not justified by the underlying fundamentals. This paper studies the behavior of daily stock returns from ten pacific-rim countries by using a regime switching model to detect trends. Residuals from a VAR model of daily stock indices and presumed fundamentals like exchange rates, Far East and the World stock indices used in a regime switching model point to the existence of bubbles. The ARCH and BDS statistics also indicate strong evidence of non-linearities in all of these countries.

Emerging Markets and Stock Market Bubbles: Nonlinear Speculation?

Daily returns of stock markets in emerging markets in Asia, Africa, South America, and Eastern Europe from the early 1990s through 2006 are analyzed for the possible presence of nonlinear speculative bubbles. The absence of these is tested for by studying residuals of vector autoregressive-based fundamentals, using the Hamilton regimeswitching model and the rescaled range analysis of Hurst. For the first test, absence of bubbles is rejected for twenty-four countries (except Mexico, Sri Lanka, and Taiwan); for the second test, it is rejected for twenty-six countries (except Malaysia). BDS testing on these residuals after autoregressive conditional heteroskedasticity (ARCH) effects are removed fails to reject further nonlinearity (except for Israel). Policy issues are discussed, noting that what is appropriate varies from country to country and time period to time period.

Stock return volatility in an emerging market: a case study of the Karachi Stock Exchange

Reports concerns that the lifting of restrictions on portfolio investment by foreigners would lead to overheating or excessive volatility in the capital markets of developing countries. Describes the abrupt lifting of restrictions on the Karachi Stock Exchange in Pakistan, given six notable developments in 1991. Examines the homogeneity of variance on weekly returns on the market index from 1988 to 1993 (over the period of liberalization). Finds that stock market volatility will reflect economic variables in the long run, while the market is shown to be information‐efficient.

Extreme loss risk in financial turbulence – evidence from the global financial crisis

Purpose - This study aims to examine the stock returns distributions in ten countries in the periods before and after the global financial crisis (GFC) to evaluate how well the empirical distributions conformed to the extreme value theory (EVT) which underlies a family of risk management models. Design/methodology/approach - The authors’ sample consists of the G5 countries and the five leading emerging economies. Parameters of the General Pareto Distribution (GPD) for each country are estimated for the pre- and the crisis period. The authors follow a two-step procedure: a GARCH(1,1) model is fitted to the historical return data by pseudo maximum likelihood method; Hills GPD tail estimation procedure is employed on the residuals from the first step. Goodness-of-fit is evaluated for the empirical distributions. Findings - The authors find that the EVT explains the observed distributions well in both the pre-GFC and the GFC periods, with the important exceptions of the US and the UK markets in the crisis period. Moreover, the estimated distribution parameters are quite different for the two periods. The results underscore the inadequacy of the quantitative risk models in times of financial turbulence, and the need for prudential exercise of judgment in risk management. Originality/value - The global financial crisis (GFC) provides a unique and historical experiment to evaluate the models of tail distributions. Although the EVT provides a sound basis for modeling extreme risks, the study highlights the fundamental problem of dealing with uncertainty.

Are there nonlinear speculative bubbles in commodities prices

Daily price movements of seventeen commodities are tested for the possible presence of nonlinear speculative bubbles during 1991-2012. A VAR model for logarithmic first differences of each is estimated with one-year Treasury bill rates, U.S. dollar value, a world stock market index, and an overall commodities price index using Hamilton regime switching and Hurst rescaled range tests. Residuals after removing ARCH for all seventeen commodity price series are tested for remaining nonlinearity using the BDS test. These tests fail to reject the presence of bubble-like trends and nonlinearity beyond ARCH for all seventeen commodity series. However, we note that we are unable to overcome the misspecified fundamentals problem, which means we cannot argue that we have definitely found speculative bubbles. At most we can argue that our results indicate that these markets appear to exhibit excess volatility and unexplained trends.

Challenges in the Application of Extreme Value Theory in Emerging Markets: A Case Study of Pakistan

Abstract Application of financial risk models in the emerging markets poses special challenges. A fundamental challenge is to accurately model the return distributions which are particularly fat tailed and skewed. Value-at-Risk (VaR) measures based on the Extreme Value Theory (EVT) have been suggested, but typically data histories are limited, making it hard to test and apply EVT. The chapter addresses issues in (i) modeling the VaR measure in the presence of structural breaks in an economy, (ii) the choice of stable innovation distribution with volatility clustering effects, (iii) modeling the tails of the empirical distribution, and (iv) fixing the cut-off point for isolating extreme observations. Pakistan offers an instructive case since its equity market exhibits high volatility and incidence of extreme returns. The recent Global Financial Crisis has been another source of extreme returns. The confluence of the two sources of volatility provides us with a rich data set to test the VaR/EVT model rigorously and examine practical challenges in its application in an emerging market.