Impact of Us Volatility on Indian Bond Market
Autor: Rachel • February 2, 2018 • 1,240 Words (5 Pages) • 728 Views
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This paper has included only the effect of large scale asset purchases by the Federal Reserve on the emerging economies’ bond market. It has missed to include other macroeconomic factors that affect the emerging economies’ financial market.
2. Nair, K.S. and Thenmozhi. M. (2012) ‘Macroeconomic factors and conditional bond volatility: evidence from emerging and developed bond markets’, American J. Finance and Accounting, Vol. 2, No. 4, pp.326–345: This study investigates the effect of macroeconomic factors on the conditional volatility of developed and emerging bond markets using ARMAGARCH mode. The findings show that the macroeconomic factors exhibit a significant relationship with volatility in all the bond markets, more specifically in the emerging bond markets. It is found that past lags explain bond volatility in India, Brazil, USA, UK and Japan, which reasserts that the assumptions of random walk hypothesis does not hold true and bond markets are predictable in the long run. The predictive power of macroeconomic variables and ARMA terms is high in the Indian and Brazilian bond market compared to the developed bond markets. The study shows that, similar to the equity market, the bond market too incorporates information on economic activity and it is more significant in emerging markets.
This paper has missed the effect of US policies on emerging market’s volatilities in financial sector.
3. Yogendra Singh Rajavatb(Associate Professor Prestige Institute of Management Dewas)
The author tries to explain the behavior of Indian Bond market and number of factors that have an effect on it. This paper examines s studied conducted with respect to Indian and International context. This paper tries to find out the important factors those are affecting the Indian Bond Return directly or indirectly. Long term cointegration is calculated for identifying the factors which affect the IBR. The Trace test as well as Max Eigen value test shows that there are at most three factors which affect the IBR. The long term cointgrating Equation is also suggested taking into the test results. The results draw some concluding observations that the UKB and USB and BSE have positive impact on IBR.
4. Interdependence of International Financial Markets: The Case of India and U.S.
Pami Dua and Divya Tuteja (Department of Economics, Delhi School of Economics, University of Delhi): This paper examines the nexus between domestic and foreign financial markets viz. Indian and U.S. The study reveals that volatility in all the markets surges post the global financial crisis of 2008-09. Spillovers in volatility across the markets are found to be present due to both innovations effects as well as volatility persistence. In particular, findings for the lagged volatility persistence effects suggest existence of significant bi-directional spillovers across the two stock markets and the currency market. Further, we observe the conditional correlations across assets to be time-varying.
Objective and Data:
The primary objective of this study aims to analyze the impact on Indian Gsec bond yield with respect to volatility in US and UK bonds.
The hypothesis: No correlation (impact) of Gsec with UK and US bonds
The sample comprises India, among the emerging bond markets and USA, UK, among the developed bond markets. The data constitutes monthly data and the sample period of the study spans from 2001 to 2016. The bond indices used for the study are Gsecs bond index for India, Treasury bill for US and 10 year Gilt bond for UK.
The variables used for the study were tested for stationarity using Augmented Dickey–Fuller test and all the variables are stationary. Pearson’s correlation analysis has been done to identify whether multicollinearity exists among the independent variables. The data has been collected from n.investing.com.
Methodology:
STATA is used for descriptive analysis (Regression), R is used for cointegration and stationarity check, line graph and plot. Johansen cointegration is used.
Empirical findings:
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