Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/14061
Title: Exploring the impact of Integration in Corporate Bond Markets using Multiple Regression with Error Correction
Authors: Panda, Ruchira
Bag, Dinabandhu
Keywords: Integration;Yield;Price Measures;Markets
Issue Date: 2015
Publisher: Indian Institute of Management, Ahmedabad
Citation: Panda, R., & Bag, D.. (2015). Exploring the impact of Integration in Corporate Bond Markets using Multiple Regression with Error Correction. 4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence. Indian Institute of Management, Ahmedabad
Series/Report no.: IC 15;101
Abstract: This paper relates to study of bond market integration by using yield based measures of integration. It also provides insight into the impact of variation in yield which caused by developments in related markets and indicators of financial development multiple regression. Although the broader issue of financial markets integration have been examined in the literature with greater attention to stock markets and more in the global context. There are few empirical works on bond markets integration and fewer works in India. The measures proposed here are also indicative of the money and credit markets. The objective is to assess the current level of integration using multiple regressions and error correction. For fixed-income securities, yield based measures are more suitable to check the law of one price. Such measures could be based on either nominal or real yields and nominal yields may be preferred since purchasing power parity (PPP) may not hold in the event of capital flow restrictions, trade barriers and transaction costs. The data includes daily traded bonds reported in FIMMDA and NSE archives during ten year period from January 1999 to December 2010. We find significant of bond yield with instruments of other markets such as domestic credit markets, money markets, and external credit markets. We also find relatively lower degree with forex markets and no relationship with any of the commodity or economic indicators.
URI: http://hdl.handle.net/11718/14061
Appears in Collections:4th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence

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