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Changing Risk Appetite and Price Dynamics of Gold Vis-a-Vis Real and Financial Assets: Perspective from the Indian Market

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Abstract

Motivated by the changing dynamics of gold prices on account of the prevalent uncertainty amidst the COVID-19 pandemic coupled with the proactive policy interventions by the central bank and the government, this paper studies the linkages between gold, other precious metals (silver and platinum), industrial metals, and financial assets, including equity and debt, in the Indian context. The paper finds that gold is largely a commodity-market follower in terms of price dynamics. In terms of inflation volatility and real returns, gold is not only less volatile, but it also records higher real returns. The paper develops a risk appetite index for India, termed as the Composite Risk Appetite Index (CRAI), using ten indicators measuring different aspects of financial market uncertainty and analyses the effect of CRAI on returns and returns’ volatility of select commodities/assets including gold. The paper finds evidence of gold providing higher returns during periods of low risk appetite and thus, establishing itself as a safe haven asset, albeit with higher volatility of returns.

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Fig. 1

Sources: World Bank Commodity Price Data (The Pink Sheet)

Fig. 2

Sources: World Bank Commodity Price Data (The Pink Sheet); and authors’ calculations

Fig. 3

Sources: World Bank Commodity Price Data (The Pink Sheet); and authors’ calculations

Fig. 4

Sources: MCX; Bloomberg; NSE, BSE; and authors’ calculations

Fig. 5

Sources: MCX; Bloomberg; BSE and authors’ calculations

Fig. 6

Sources: MCX; Bloomberg, BSE; FIMMDA and authors’ calculations

Fig. 7

Sources: Bloomberg; NSE; BSE; FIMMDA; Financial Benchmark India Pvt. Ltd. (FBIL); and authors’ calculations

Fig. 8

Sources: MCX; Bloomberg; BSE; FIMMDA; FBIL and authors’ calculations

Fig. 9

Source: Authors’ estimates

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Data availability

Data used in the paper are in public domain. If required, authors may be contacted for the data.

Notes

  1. Literature defines a hedge as a security that is uncorrelated with stocks or bonds on average, while a safe haven as a security that is uncorrelated with stocks and bonds during times when financial markets experience stress.

  2. The NIFTY 50 is a benchmark Indian stock market index that represents the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange (NSE). The BSE SENSEX is a free-float market-weighted stock market index of 30 well-established and financially sound companies listed on Bombay Stock Exchange (BSE).

  3. PCA is a dimension reduction method and is used to separate out the idiosyncratic components of the considered components from the common factors. As noted by Coudert and Gex (2006), PCA allows for the extraction of a list of k new uncorrelated variables from a set of p correlated quantitative variables (The correlation coefficients between the various risk appetite indicators are provided in “Appendix”).

  4. Component ARCH(1,1) model has been used to compute the fitted values of CRAI. See, for instance, Bekaert et al., (2009) which models uncertainty and risk aversion as simple univariate but heteroskedastic autoregressive processes.

  5. Similar types of methods are found in the literature. See, for instance, Domanski et al., (2016); Fuhrer and Moore, (1995); Sbordone (2002).

  6. Separate OLS regressions were conducted to study the impact of CRAI on liquidity of gold, silver and SENSEX (proxied by average daily turnover), after controlling for banking system liquidity (average daily net liquidity adjustment facility), FII flows, IIP growth and inflation volatility. The regression coefficients for CRAI were found to be negative and significant, suggesting an increase in trading activity in these segments during episodes of low-risk appetite.

  7. Based on data available from the World Gold Council.

  8. Based on data available in the Database on Indian Economy, RBI.

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Acknowledgements

The first version of the paper was presented in the Annual Conference on Gold and Gold Markets, 2021 hosted by the India Gold Policy Centre (IGPC) at the Indian Institute of Management, Ahmedabad. The authors express sincere thanks to the panelists and participants in the conference as well as two anonymous referees for their valuable suggestions and feedback which helped improve the paper. The work is not funded by any organization.

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Authors and Affiliations

  1. Department of Economic and Policy Research, Central Office Building, Reserve Bank of India, Shahid Bhagat Singh Road, Fort, Mumbai, Maharashtra, 400 001, India

    Sujata Kundu

  2. Department of Statistics and Information Management, Reserve Bank of India, Bandra Kurla Complex, Bandra (East), Mumbai, Maharashtra, 400 051, India

    Archana Dilip

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Appendix

Appendix

See Table 8

Table 8 Correlation matrix of risk appetite indicators
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Kundu, S., Dilip, A. Changing Risk Appetite and Price Dynamics of Gold Vis-a-Vis Real and Financial Assets: Perspective from the Indian Market. J. Quant. Econ. 21, 899–923 (2023). https://doi.org/10.1007/s40953-023-00359-6

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