India's Race to the Top: An Analysis of Stability of Indian Infra-Stocks

India's Race to the Top: An Analysis of Stability of Indian Infra-Stocks

Chitrakalpa Sen (BML Munjal University, India) and Gagari Chakrabarti (Presidency University, India)
DOI: 10.4018/978-1-5225-2361-1.ch019
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Abstract

This study analyses the underlying stability and therefore investment worthiness of infrastructure stocks in India. For that purpose, it has chosen NSE INFRA for the time period 2010-2016. To compare with a market index, NIFTY has been chosen. An examination of underlying volatility dynamics using ARCH models reveal that NSE INFRA is characterized by less volatility, especially during instable times. Both the series turns out to have significant long-term dependence. An investigation into the inherent chaotic dynamics indicates that NSE INFRA has a relatively less chaotic signature than NIFTY, reinforcing the stability and investment worthiness of infrastructure stocks.
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Introduction

… infrastructure is the big elephant in the room…once these measures are implemented, the elephant would start dancing, and with it the overall economy. - Vinayak Chatterjee, Feedback Infra (Economic Times, 2015).

At the threshold of the second decade of the millennium, India has found itself at a very interesting crossroad, maybe one of the most exciting one since its independence. India seems to be the flavor of the season, with all global giant multinationals look at India as their prime destination. With over 40% of the Indian population below the age of 20(First post, 2016), India faces a massive demographic dividend like no other nation. India has been the centre of attraction, more so after the Indian growth rate (7.4%) surpassed the Chinese growth rate in the third quarter of 2015(Worstall, 2015). Although continuously compared with China, the Indian growth story however, has largely been different than the Chinese growth story. Indian growth has been powered largely by its buoying services sector. In 2014-15, the services sector’s contribution to GDP has been 52.97%, while the manufacturing sector has a contribution of 17.18%, which is even lesser than its contribution the previous year, 17.26% (www.statisticstimes.com, 2015). On the other hand China, the biggest export led economy in the world has used the industrial sector as its engine of growth. In 2015, the Chinese manufacturing sector contributed to 34% of its GDP (Wildau, 2015).

Although services sector has so far been proved to be a propagator of growth for India, the full potential of the services sector will really be limited for India, if its backward linkages are not developed properly. It’s time to provide a “big push” to India’s slowing manufacturing sector otherwise the services sector will eventually saturate and experience a diminishing returns. To achieve that, a strong infrastructure and communications framework across the nations is of utmost need. And this is where India lags behind its close competitors. For example, in 2013 India had 18 internet users per 100 people compared to 49.3 in China, in 2013, 78.7% people in India had access to electricity while China had 100%, India has 66460 km of rail lines, compared to 66298 km in China, in 2011 India had 79116 km of paved expressways compared to 84946 km in China, in 2011, 53.8% of the roads in India were paved compared to 63.7% in China (Bloomberg, 2015).By 2015, India has 7000kms of four lane roads, while China has 34,000 kms, India has 66.590km of National Highway while China has 1,900,000 kms of National Highway, The turnaround time at Indian ports on an average is 84 hours, while that in Hong Kong and Singapore is only 7 hours(Niggl, 2015).

This is reflected from Global Innovation Index, India is significantly behind China in infrastructure (Table 1).

Table 1.
Comparison of Infrastructure between China and India (www.globalinnovationindex.org, 2015)
Indicator NameIndiaChina
Infrastructure34.650.5
Information and communication technologies (ICT)38.651.6
General infrastructure38.965.1
Ecological sustainability26.335

Key Terms in this Chapter

NSE Infra: NSE Infrastructure index of National Stock Exchange.

Long Memory: Long-term memory is said to exist if a random process is an autocorrelation function which is not integrable and the autocorrelation decays asymptotically over time, following a power law (Lillo, Farmer, 2004 AU112: The in-text citation "Lillo, Farmer, 2004" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).

Non-Linear Deterministic Chaos: For a system to be chaotic, it must be nonlinear, deterministic and sensitive to initial condition.

NIFTY: NIFTY 50 is one of the two major Indian stock market index, the other being SENSEX.

Structural Breaks: A structural break is said to exit when a series jumps for a period characterized by low values of its parameters to a period characterized by low values of its parameters.

Infrastructure: According to Merriam Webster dictionary, infrastructure can be defined as “the basic equipment and structures (such as roads and bridges) that are needed for a country, region, or organization to function properly”.

Conditional Heteroscedasticity: Conditional heteroscedasticity is said to exist when the variance of current error term is dependent or conditional, i.e. a function of past factors (such as past volatility, information shock etc).

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