Browsing by Subject ",Business Finance"

The past decade has witnessed high volatility in the global macroeconomic conditions and has shown how the banking system is exposed to a variety of risks which can assume systemic dimensions and can affect the financial stability of a country adversely. Given the importance of financial stability, organizations like International Monetary Fund (IMF), World Bank, Bank for International Settlements(BIS) and the Central banks across the globe are striving to evolve a robust Macro Prudential and Systemic risk assessment framework. Macro stress testing is an integral element of this exercise. In the Indian context also, Macro stress testing has evolved over the last few years; however, given the advancements in this area across the globe, the research is still in a very nascent stage. Against this backdrop, our study is an attempt to contribute to the ongoing research efforts in this area and provide a reference point for reassessing and reviewing the existing macro stress testing practices in the Indian context. We propose to modify the existing macro stress testing model for credit risk as developed by Reserve Bank of India in terms of endogenous variable selection, calibration of stress testing scenarios and modification of the macro stress testing model. In the dissertation, Top-down approach of stress testing has been adopted for the Indian banks using quarterly data pertaining to the time period 1996Q2 to 2016Q4. The macroeconomic variables employed for the study are GDP, CPI, Exchange rate, Oil, Market Capitalisation of NSE, Short-term interest rate and Long term interest rate. For the empirical analysis, Vector Error Correction Model (VECM) technique has been employed to investigate the dynamic impact of changes in the macroeconomic variables on the Default Ratio which has been taken as a Credit Risk indicator. Wald Test, Granger Causality and Toda Yamamoto test have been employed to investigate the short term relationship between the variables...

A key challenge for emerging economies is their interdependence with the developed economies. To reduce this interdependence and to progress towards self-reliance, it is necessary to understand the emerging markets dependence in terms of macroeconomic integration, financial market spillovers, co-movements and correlations. Understanding the dependence provides valuable inputs to the investors, risk managers and to the policy makers. In this context, this study investigates the interaction effect between selected implied volatility indices and its time varying conditional correlations among developed and emerging economies. This study employs daily data from March 2009 to October 2015. The study uses implied volatility indices data from developed markets like US, Germany, Switzerland, Euronext, Hong Kong, Japan and India from the emerging markets list. Macroeconomic variables like gold, oil and federal fund rate are used to understand the volatility transmission from the macroeconomic environment to financial markets. The paper employs various econometric models like ARCH, EGARCH, Threshold GARCH, Vector autoregressive model (VAR) model and Markov Switching dynamic regression model for the analysis. The results found an asymmetric risk return relationship between Nifty 50 returns and the Indian implied volatility index (IVIX). The study found evidence of regime switching behavior of the Indian implied volatility index and is characterized by two states. There exists a high degree of synchronicity between IVIX and VIX of developed markets during the bear market situation. Hence, there are very limited opportunities to hedge the risk by diversifying the investments to these markets during high volatility state. The VAR results found unidirectional spillover from oil to IVIX. The financial analysts, risk managers and the investors should observe external economic environment very closely to protect their portfolios from potential spillovers. The policy of oil price deregulation has to be carefully monitored.

This dissertation aims at understanding the dynamic interactions between financial deepening and economic growth for the OECD (The Organization for Economic Cooperation and Development) nations. Numerous researchers have analyzed the causal relationships between financial deepening and economic growth. The results produced by the causality studies conducted in the past differ based on the country used for analysis, time periods selected and the variables used in the estimation system. However recent research indicates that there exists a non-linear relationship between financial deepening and economic growth. The relationship between economic growth and financial deepening is an inverted U-shaped curve according to a few researches. This inverted parabola is checked on the high income nations using an ARDL PGM model and the results are positive. The dissertation analyses the non-monotonicity between financial depth indicators and the economic growth indicator using a Threshold Auto Regression (TAR) model. Time Series data for a period of 57 years (1960-2016) were collected on the 21 OECD nations. The TAR model checks for the non-linearity in the data and the obtained results reveal that there exists a nonmonotonic relationship between financial deepening and economic growth. In order to study the problems of excess finance in the high income nations, the OECD nations are ranked based on absolute GDP in an ascending order. They are divided into four quartiles with absolute GDP values with the lowest range in the first quartile and so on. The main aim of dividing the countries into different quartiles is to check if the relationship between economic growth and financial deepening differs based on the stages of economic development of the high income nations. Each quartile is studied under a VAR environment after performing panel unit root tests and panel cointegration tests. The results are interpreted using the impulse response functions...