Modelling the Riskiness in Country Risk Ratings

This book presents an econometric analysis of riskiness in country risk ratings. Country risk and its associated risk ratings for 120 countries covering eight geographic regions is analysed by using the univariate and multivariate volatility models

Modelling the Riskiness in Country Risk Ratings

This book presents an econometric analysis of riskiness in country risk ratings. Country risk and its associated risk ratings for 120 countries covering eight geographic regions is analysed by using the univariate and multivariate volatility models

Impact of International Trade and Trade Duties on Current Account Balance of the Balance of Payment: A study of N-11 Countries

This study is aimed to investigate the impact of international trade and trade duties upon the current account balance of the balance of payment of N-11 countries. Two constituents of each factor have been considered for the purpose of analysis. For International trade, import (IMPT) and export (EXPT) of goods and services have been considered whereas, for trade duties, taxes on international trade (TOIT) and customs and other import duties (CID) have been taken as the research variables whereas, current account balance (CAB) has been taken as the dependent variable. For the purpose of analysis panel data of N-11 countries for 27 years from 1990 to 2016 has been tested using different econometric technique such as Panel unit root test, Panel co-integration test, Hausman test, Panel regression analysis and Panel causality analysis. The results demonstrate that overall research variables are co-integrated and having long term relationship and affecting each other in the conventional manner. Notably, it is observed via results that in case of N-11 countries the CAB itself is the regulating factor and all other factors are adjusted according to the movement of CAB. The study provides recommendations for the rectification of current account deficit position and also provides scope for future research as well

Terrorism and Stock Market Linkages: An Empirical Study from Pakistan

This paper investigated the impact of prolonged terrorist activities on stock prices of different sectors listed in Karachi Stock Exchange by using newly developed terrorism impact factor index with lingering effect (TIFL) and monthly time series data from 2002(Jan) to 2011(Dec). Johansen and Jeuselius cointegration revealed long run relationship between terrorism and stock price. Normalized cointegration vectors are used to test the effect of terrorism on stock price. Results demonstrated significantly mixed positive and negative impact of prolonged terrorism on stock prices of different sectors and have shown that market has not become insensitive to the prolonged terrorist attacks

Long-Run Movement and Predictability of Bond Spread for BRICS and PIIGS: The Role of Economic, Financial and Political Risks#

We examine co-movement and predictability of Bond Spread of BRICS and PIIGS with respect to political risk (PR), financial risk (FR), and economic risk (ER). Our linear Granger causality findings imply that PR is the most important risk in predicting bond spread, followed by ER in both BRICS and in PIIGS, while FR is useful in predicting bond spread in BRICS only. Our nonlinear individual causality results infer that ER is the most important risk in predicting bond spread, followed by FR, and PR. We make a conjecture that linear and nonlinear causality are independent and our findings support this

Does country risks predict stock returns and volatility? Evidence from a nonparametric approach

We use the k-th order nonparametric causality test at monthly frequency over the period of 1984:1–2015:12 to analyze whether aggregate country risk, and its components (economic, financial and political) can predict movements in stock returns and volatility of eighty-three developed and developing economies. The nonparametric approach controls for the existing misspecification of a linear framework of causality, and hence, the weak evidence of causality obtained under the standard Granger tests cannot be relied upon. When we apply the nonparametric test, we find that, while there is no evidence of predictability of squared stock returns barring one case, at times, there are nearly 50 percent of the countries where the aggregate risks and its components tend to predict stock returns and realized volatility.http://www.elsevier.com/locate/ribaf2018-12-30hj2018Economic

Time-varying rare disaster risks, oil returns and volatility

© 2018 Elsevier B.V. This paper provides a novel perspective to the predictive ability of rare disaster risks for West Texas Intermediate (WTI) oil market returns and volatility using a nonparametric quantile-based methodology over the monthly period of 1918:01–2013:12. We show that a nonlinear relationship and structural breaks exists between oil returns and various rare disaster risks; hence, linear Granger causality tests are misspecified and the linear model results of non-predictability are unreliable. However, the quantile-causality test shows that rare disaster-risks strongly affect both WTI returns and volatility, with stronger evidence of predictability observed at lower quantiles of the respective conditional distributions. Our results are robust to alternative specification of volatility (based on a GARCH model), and measure of rare disaster risks (based on the number of crises)

Exchange rate returns and volatility : the role of time-varying rare disaster risks

This paper provides empirical evidence to the theoretical claim that rare disaster risks have predictability for exchange rate returns and volatility using a nonparametric quantile-based methodology. Using dollar-based exchange rates for Brazil, Russia, India, China, and South Africa, the quantile-causality test shows that indeed rare disaster-risks affects both returns and volatility over the majority of their respective conditional distributions. In addition, these effects are much stronger when compared to those using the British pound, especially in terms of currency returns.http://www.tandfonline.com/loi/rejf202020-04-15hj2018Economic

Pilot Placement Schemes for Channel Estimation of Proposed 5G-GFDM System

Orthogonal Frequency Division Multiplexing (OFDM) is a highly regarded technique used in the 4G mobile communication systems to provide reliable communication and high data rates due to the orthogonality between its sub carriers. However, it cannot be used in the next generation cellular system i.e. 5G. Thus, a new technique Generalized Frequency Division Multiplexing (GFDM) has been proposed to meet the demands of the next generation systems, which are higher data rates than 4G, minimum response time, lower power consumption etc. GFDM is a non-orthogonal, multicarrier scheme, which seems to fulfil the requirements of the new wireless communication system. The aim of this paper is to use the pilot symbols and their optimum placements within the data for the channel estimation of the GFDM system. It is shown that the optimum arrangement of the pilot symbols is to place them uniformly on equal intervals within the data and to cluster them in the middle of the data