ISSN (Print) - 0012-9976 | ISSN (Online) - 2349-8846

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Empirical Evidences from India

Monetary Policy Transmission in Financial Markets

In the Indian context, a key question is addressed: What has been the influence of monetary policy on different segments of the financial markets? Constructing a structural vector autoregressive model with the monetary policy rate, the pattern of monetary transmission to financial markets is examined over three distinct periods of regime changes in the Indian monetary policy and liquidity management framework. The empirical evidence indicates that there is sufficient period-specific transmission of monetary policy across the different segments of the financial markets. While the transmission of monetary policy to the money and bond markets is found to be fast and efficient, the impact of the policy rates on the forex and stock markets is limited.

It is well known that transmission of monetary policy, to begin with, takes place via the financial markets. This paper looks into the impact of monetary policy across various segments of the financial markets. Specifically, four markets are being probed, namely money, bond (both government and corporate), forex, and the stock markets. Often these markets are interlinked by the virtue of the commonality of market players as well as the general sentiment across the different segments of the financial markets. In this context, the current paper seeks to address the questions—what has been the influence of monetary policy on different segments of the financial markets?

There are three discerning features of the study. First, it uses the daily data over a period from April 2005 to December 2018, to decipher the extent of monetary policy transmission across the money, government securities (G-secs), corporate debt, forex, and the equity segments of the Indian financial market.1 Second, the study also seeks to probe the transition of monetary policy transmission in three different periods of regime changes. Third, given the short run nature of the data (notwithstanding the number of observations), it uses structural vector autoregressive (svar) models to discern econometrically robust conclusions.2

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Updated On : 29th Mar, 2019

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