Investigating impact of financial stress on FII flows in Indian equity market

Singh, Amanjot; Singh, Manjit

doi:10.1080/23311975.2016.1190263

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…The study further discusses work carried out to understand the role of macroeconomic variables in determining FPIs and it revealed that currency risk had a negative influence (Garg & Dua, 2014), while Kaur and Dhillon (2010) evidenced that turnover of the stock market and market capitalisation imposed a positive influence on FPIs. Furthermore, negative impact of financial stress in US markets was seen on FPIs investment decisions towards India (Singh & Singh, 2016). Singhania and Saini (2018) identified factors such as freedom index, trade openness of the country, differential of the rate of interest, performance of the stock market, and US market have substantial effect on investments of FPIs.…”

Section: Category 1: Sovereign and International Entitiesmentioning

confidence: 99%

Analysis of Variation in Foreign Inflows by Different Categories of Foreign Portfolio Investors

Gupta,

Kumar

2024

The Indian Economic Journal

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The liberalisation of Indian financial markets has smoothened the capital flows of international institutional investors, resulting in rising foreign investor participation in the domestic equity and debt markets. Since the reforms of the 1990s, India has become one of the favourite investment hubs of foreign institutional investors (FIIs) across the globe. The research aims to analyse the variation in contribution to foreign inflows by the three different categories of foreign portfolio investments (FPIs) and the determinants of inflows of the categories of FPIs. The study is based on the use of secondary data collected from the National Securities Depository Limited and the Securities Exchange Board of India. One-way ANOVA has been employed to examine the variation in inflows by different categories of FIIs. Autor regressive distributed lag model has been used to understand the factors determining the inflows of FPIs. The results of the study revealed that there exists variation in the inflows of investments among the different categories of FIIs. The variation in inflows by different categories into equity instruments was significant, while the inflows into debt instruments were not significant. Furthermore, the highest inflows were seen from the second category of FIIs. JEL Codes: C32, G2

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Section: Category 1: Sovereign and International Entitiesmentioning

confidence: 99%

Analysis of Variation in Foreign Inflows by Different Categories of Foreign Portfolio Investors

Gupta,

Kumar

2024

The Indian Economic Journal

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“…The value 1 denotes existence of a condition ( P ), whereas the value 0 denotes absence of a condition (1– P ). The logistic regression equation is expressed as follows (Chauhan, 2015; Singh & Singh, 2016a):…”

Section: Empirical Frameworkmentioning

confidence: 99%

“…Growing integration among the international economies has further made the domestic stock markets to witness co-movement with foreign stock markets. These dynamic co-movement effects also embody spillover effects, interdependencies and the contagion phenomenon that catalyze information transmissions from one economy to another (Singh & Singh, 2016b). Above all, these cross-country dynamic interactions have an impact on the overall risk–return relationship prevalent in the respective equity markets owing to increasing sensitivity towards external shocks (Harvey, 1995).…”

Section: Introductionmentioning

confidence: 99%

Does US Financial Stress Explain Risk–Return Dynamics in Indian Equity Market? A Logistic Regression Approach

Singh

Kaur

2017

Vision

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The present study attempts to capture the impact of the US financial stress on the risk–return dynamics in the Indian equity market by employing Markov regime switching and binary logistic regression model. The span of data ranges from 2004 to 2013. The study uses weekly closing local values of benchmark equity indices ‘CNX Nifty 50 and S&P 500’ and St. Louis Fed Financial Stress Index (SFSI). The said index captures stress in the US financial system on a weekly basis. The Markov results support the existence of ‘Bull’ regime as well as ‘Bear’ regime in the Indian equity market. Corresponding to this, the logistic regression model indicates a positive impact of the US financial stress on the probability for the existence of bear regime. Particularly, the probability for the existence of bull regime approaches zero, when the stress in the US financial system crosses the level of two. The results support strong implications for the investors in the Indian equity market against the stress in the US financial system.

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“…It is this threat of reversal in capital flows and adverse exchange rate movements that channelize monetary policy actions in emerging markets against external imbalances in addition to the domestic cycles. For instance, overall financial stress in the US financial system has an impact not only on FII flows in the Indian equity market but on risk-return regimes as well (Singh and Singh, 2016a; Singh and Kaur, 2017). As a response to these adverse market scenarios, fiscal policy initiatives are also adjusted in the respective economies.…”

Section: Introductionmentioning

confidence: 99%

A revisit to how linkages fuel dependent economic policy initiatives

Singh

2017

IJLMA

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Purpose The authors aim to report empirical linkages between the US and Brazil, Russia, India and China (BRIC) financial stress indices catalyzing catalyzing dependent economic policy initiatives (an extended version of Singh and Singh, 2017a). Design/methodology/approach Initially, the study develops financial stress indices for the respective BRIC financial markets. Later, it captures linkages among the said US-BRIC indices by using Johansen cointegration, vector autoregression/vector error correction models (VECM), generalized impulse response functions, Toda–Yamamoto Granger causality, variance decomposition analyses and bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model under constant conditional correlation framework, in general. Markov regime switching and efficient causality tests proposed by Hill (2007) are also used. Findings Overall, there are both short-run and long-run dynamic interactions observed between the US and Indian financial stress indices. For rest of the markets, only short-run interactions are found to be in existence. The time-varying co-movement coefficients report financial contagion impact of the US financial crisis on Russian and Indian financial systems only. Contrary to this, Brazilian and Chinese financial systems are largely exhibiting interdependence with the US financial system. Efficient causality tests report indirect impact of the Russian financial system on Brazilian via auxiliary Indian financial system. Originality/value The present study is the first of its kind capturing linkages among the US-BRIC financial stress indices by using diverse econometric models. The results support different market participants and policymakers in understanding effectiveness and implementation of economic policies while considering their cross-market interactions as well.

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Investigating impact of financial stress on FII flows in Indian equity market

Cited by 6 publications

References 5 publications

Analysis of Variation in Foreign Inflows by Different Categories of Foreign Portfolio Investors

Analysis of Variation in Foreign Inflows by Different Categories of Foreign Portfolio Investors

Does US Financial Stress Explain Risk–Return Dynamics in Indian Equity Market? A Logistic Regression Approach

A revisit to how linkages fuel dependent economic policy initiatives

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