Asymmetric Behavior of Inflation Uncertainty and Friedman-Ball Hypothesis: Evidence from Pakistan

This paper is first attempt to measure and analyze inflation uncertainty in Pakistan and it provides several contributions. Using quarterly data from 1976:01 to 2008:02, at first stage we model inflation uncertainty as time varying process through GARCH framework. At second stage asymmetric behavior of inflation uncertainty is analyzed by using GJR-GARCH and EGARCH models, for further analysis of asymmetry and leverage effects, we developed news impact curves proposed by Pagan and Schwert (1990). Finally we investigate the causality and its direction between inflation and inflation uncertainty by using bivariate Granger-Causality test to know which inflation uncertainty hypothesis (Friedman-Ball or Cukierman- Meltzer) holds true for Pakistani data. We get two important results. First, GJR-GARCH and EGARCH models are more successful in capturing inflation uncertainty and its asymmetric behavior as compared to simple GARCH model. This can also be seen from news impact curves. Second, there is strong evidence that Friedman-Ball inflation uncertainty hypothesis holds true for Pakistan.Inflation, Uncertainty, GJR-GARCH, EGARCH

Inflation Targeting Framework: Is the story different for Asian Economies?

This paper aims to measure and compare the economic performance of four Asian economies who adopted Inflation Targeting (Indonesia, Philippines, South Korea and Thailand) against their six neighboring Asian non-targeting economies (China, Hong Kong, India, Malaysia, Singapore and Pakistan). Using the methodology of Ball and Sheridan, firstly, behavior of inflation, output growth and short term interest rate has been measured for both groups (Targeters vs. Non-Targeters) in pre and post IT adoption period in order to see whether performance has improved in targeting countries after the adoption of IT. Secondly, we try to find out whether Inflation Targeting has played any significant role in the changed behavior of these variables. Thirdly, we measure the effect of output gap and supply shock on inflation and see whether economic structure of these countries has changed between pre and post targeting period; and then we measure the role of IT in the structural change of these economies if there is any. The results force us to believe that economic performance has improved in all Asian economies in post targeting period. However, IT does not seem to play any significant role in this improvement of targeting countries. In addition to this, we find strong evidence that all variables showed strong reversion to mean suggesting that improved performance of variables today is in fact the outcome of poor economic performance in the past.Inflation Targeting, Asian countries, Output gap, Targeters vs Non Targeters, Economic Performance

What Does Pakistan Have to Join Inflation Targeters Club, A Royal Flush or A Seven-Deuce Offsuit?

The economic and institutional structure required for successful adoption and implementation of Inflation Targeting (IT) framework is often lacking in Emerging economies. In this paper, we evaluate these structures for the economy of Pakistan both qualitatively and quantitatively. Although our comprehensive assessment identifies non-realization of many core requirements but as literature and real time experience pointed out that IT can be a framework for emerging economies even in the absence of these conditions, we go further by investigating that if State Bank of Pakistan (SBP) decides to adopt IT, does there exist a stable and significant relationship between policy rate (monetary tool) and inflation measure (objective)? This bivariate relationship is important to be analyzed given the important role of interest rate in mitigating the deviations between actual and target inflation while working within the IT framework. To illustrate this relationship, we use Granger Causality test and our estimates fail to find any significant link between interest rate and inflation. On the basis of overall findings, this study suggests that Pakistan, due to the absence of most fundamental requirements of IT, is perhaps not ready for Inflation Targeting yet.Inflation Targeting, Pakistan, Monetary policy

Oil market volatility: comparison of COVID-19 crisis with the SARS outbreak of 2002 and the global financial crisis of 2008

During the recent COVID-19 outbreak, the crude oil market experienced enormous price fluctuations. A large number of researchers contended the volatility observed in oil market as unprecedented and it was immediately attributed to the pandemic owing to its globally devastating nature. Whether or not this attribution is justified, is the major question we have raised in this paper. We perform the comparative analysis of the volatility spasms of oil market during the COVID-19 pandemic (COVID19), the Global financial crisis of 2008 (GFC) and the SARS outbreak of 2002–2004 (SARS). Preliminary investigation is conducted using two proxies of market sentiment which are oil price returns and oil price spread. For further investigations we apply symmetric GARCH (1,1) and the asymmetric GJR-GARCH (1,1) models. Our results based on skewness and kurtosis, indicate an extremely high degree of fat tail risk implying COVID-19 crisis as low probability yet high severity event a.k.a. black swan event. Our results further confirm the presence of volatility clustering (GARCH effect) along with the highest degree of asymmetry during COVID-19. These facts collectively make COVID-19 crisis more uncertain and pessimistic compared to the GFC and SARS

Do fear indices help predict stock returns

This study investigates the forecasting power of implied volatility indices on forward looking returns. Prior studies document that negative innovations to returns are associated with increasing implied volatility of the underlying indices; thus, suggesting a possible relationship between extremely high levels of implied volatility and positive short term returns. We investigate this issue by examining the predictive power of three implied volatility indices, VIX, VXN and VDAX, on the underlying index returns. We extend previous research by also focusing on characterised selected stocks and examine the relationship between implied volatility indices and future returns across different sectors and classified portfolios. Our findings suggest that implied volatility indices are good predictors of 20-days and 60-days forward looking returns and illustrate insignificant predictive power for very short term (1-day and 5-days) returns

A Study on Volatility Dynamics and Inter-Sectoral Spillovers Originating from Banking Sector: The Case of Karachi Stock Exchange

The study was conducted to investigate the spillover effects originating from the Banking sector and directionality of these effects on various sectors of Pakistan. The sectors under study were Banks, Oil and Gas, Construction, Chemical, Food Producer, Fixed Line Telecommunication, Electricity sector and Personal Goods sector. Daily data of 251 companies was considered and the time period studied was from 2008 to 2012. We investigated the spillover effects originating from Banking sector and whether they differ across different sector but also examined whether correlation of Banking sector with other sector varies over time. We used BEKK parameterization as used by  (Engle & Kroner, 1995) to detect volatiltity transmission among Banking and all other sectors. We also conducted Granger Causality test on weekly portfolio returns, volatility and conditional standard deviation to have a better understanding. The results of daily data showed returns of banking sector significantly impacted returns in Oil and Gas sector, Chemical and Electricity Sector Returns in Construction and Chemical sector impacted return in banking sector. We tested Granger Causality, on weekly portfolio returns, volatility and conditional standard deviation and then ran the GARCH model on weekly and monthly data set. We concluded that banking sector did play a crucial role in impacting various sectors of the economy but it was also evident from the results that few sectors did impact the Banking sector too. Keywords: Volatility, GARCH Model, Portfolio returns, Banking Secto

COVID-19, Lockdowns and Herding Towards Cryptocurrency Market Specific Implied Volatility Index

This study investigates herds effect in more than 100 cryptocurrencies during the period from January 2015 to June 2020. The results document a significant evidence of herding behavior in the cryptocurrency market. My findings show that herding asymmetry is present during bullish and bearish regimes of cryptocurrency market, where the herds investing is dominantly visible during extremely bullish percentile regimes of cryptocurrency market. Although the study finds no evidence of correlated trading when cryptocurrency specific fear prevails in the market, yet crypto investors mimic trading decisions of others during the times of COVID-19 except for the period of lockdowns

Do fear indices help predict stock returns?

This study investigates the forecasting power of implied volatility indices on forward looking returns. Prior studies document that negative innovations to returns are associated with increasing implied volatility of the underlying indices; thus, suggesting a possible relationship between extremely high levels of implied volatility and positive short term returns. We investigate this issue by examining the predictive power of three implied volatility indices, VIX, VXN and VDAX, on the underlying index returns. We extend previous research by also focusing on characterised selected stocks and examine the relationship between implied volatility indices and future returns across different sectors and classified portfolios. Our findings suggest that implied volatility indices are good predictors of 20-days and 60-days forward looking returns and illustrate insignificant predictive power for very short term (1-day and 5-days) returns. © 2014 © 2014 Taylor & Francis

Covid-19, Lockdowns And Herding Towards A Cryptocurrency Market-Specific Implied Volatility Index

This study investigates herd effects in 101 cryptocurrencies during the period from January 2015 to June 2020. Our results confirm the existence of herding behavior in the cryptocurrency market for the entire sample and show that herding asymmetry is present during both bullish and bearish regimes. The asymmetry in correlated trading is particularly visible in extreme return percentile regimes (1% and 5%) of cryptocurrency market Although our study finds no evidence of correlated trading when cryptocurrency specific fear prevails in the market, crypto investors seem to mimic the trading decisions of others during the COVID-19 pandemic, outside the lockdown periods. (C) 2021 Elsevier B.V. All rights reserved