Oct' 19
The IUP Journal of Applied Economics
Focus
the
author, Payal Goel, has made an attempt to investigate the herding behavior of the investors, with special emphasis on the two most prominent phases of the market, i.e., the bull market and the bear market, using two most extensively time-honored regression models on monthly data for the period April 2000 to March 2018. The author opines that the policymakers have to understand the phenomenon behind the irrational investment behavior of the market participants. Although the results of the study indicate significant positive herding in the rising market conditions, due to presence of nonlinearity the study concludes the absence of herding behavior in the Indian stock market.
In the second paper, �Price Discovery Behavior of Spot and Futures: Evidence from Pre- and Post-Crisis Periods�, the authors, VDMV Lakshmi and Medha Joshi, have made an attempt to examine if there is any shift in the behavior of the stocks in price discovery process in pre-crisis, crisis and post-crisis periods using Johansen�s cointegration and vector error correction model for the period November 9, 2001 to December 31, 2018. The results indicate that there is evidence of futures market leading spot market during pre-crisis period. The study also reveals that there is clear evidence of the dominant role of spot market in price discovery in India even after 18 years from the launch of futures trading. The authors opine that SEBI may have to undertake necessary steps to bring in more institutional participation to ensure better price discovery mechanism and to improve the quality of the market as a whole.
In the third paper, �Pattern and Determinants of Household Savings in Odisha: An Empirical Analysis of Censored Data Using a Tobit Model�, the authors, Amaresh Samantaraya and Suresh Kumar Patra, have examined the pattern of household savings in Odisha and assessed the role of its various determinants using Tobit model or censored regression model for analyzing the saving behavior of the sample households. The study finds that family income, attainment of education and adoption of nuclear family structure are favorable for savings, while working-age dependency and old age are detrimental. The authors opine that expansion of secondary and graduate level education needs to be promoted, and a larger proportion of young household is conducive for generating saving and this advantage will continue with larger proportion of this segment overall.
In the last paper, �The Impact of Demonetization on Indian Stock Market: A Sectoral Analysis of Bombay Stock Exchange�, the authors, Surya Dev and Pranati Mohapatra, have attempted to examine the impact of demonetization on the stock market using the event study methodology on 19 sectoral indices of Bombay Stock Exchange for the period from April 1, 2015 to November 24, 2016. The results indicate that the sectors that are mostly dependent on liquid cash are the ones whose share prices are adversely affected and the sectors that depend on government initiatives are found to benefit directly from demonetization and the indices reflect the same. The study reveals that there is no leak about the event to the market as the Cumulative Abnormal Return (CAR) for the pre-event period is not significant for any sector.
Consulting Editor
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| Article | Price (₹) | ||
| Herding Behavior and Market Conditions: Empirical Evidence from Bombay Stock Exchange, India |
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| Price Discovery Behavior of Spot and Futures: Evidence from Pre- and Post-Crisis Periods |
100
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| Pattern and Determinants of Household Savings in Odisha: An Empirical Analysis of Censored Data Using a Tobit Model |
100
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| The Impact of Demonetization on Indian Stock Market: A Sectoral Analysis of Bombay Stock Exchange |
100
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Herding Behavior and Market Conditions: Empirical Evidence from Bombay Stock Exchange, India
The study seeks to investigate how market participants behave, with special reference to herd behavior wherein investors imitate the investment patterns of their fellow investors. It further explores the magnitude of such behavior not only during normal circumstances, but also during severe upswings and intense downturns, with special focus on the Indian stock market. Two most extensively time-honored models given by Christie and Huang (1995) and Chang et al. (2000) have been applied to examine the herding component by scrutinizing the wide dispersions of the security returns as regards the standard market model on a large dataset of monthly returns of BSE 500 index for a period of 18 years, i.e., from April, 2000 to March, 2018. The study found absence of herding behavior in the Indian stock market.
Price Discovery Behavior of Spot and Futures: Evidence from Pre- and Post-Crisis Periods
The study attempts to examine if there is any shift in the price discovery behavior of spot and futures markets between pre-crisis period and post-crisis period. All those stocks which are available for trading in futures segment since the launch of futures trading on November 9, 2001 to December 31, 2018 have been considered for the purpose of the study so as to understand the behavior of the stocks in price discovery process in pre-crisis, crisis and post-crisis periods. To measure the price discovery effects, the study uses Johansen�s cointegration and Vector Error Correction Model (VECM), as it helps in investigating which market (spot or futures) leads in discounting the potential value of the information. The study also applies Hasbrouck�s information share approach to investigate the proportion of contribution of each market to price discovery. The results indicate that there is evidence of futures market leading spot market during pre-crisis period. However, the leading role of futures disappeared during the crisis period. It may be attributed to the fear of market participants to trade in high levered instruments. Rather, there is evidence of leading of spot market during the crisis period and also after the crisis period. On the whole, it is observed that spot market plays a dominant role in price discovery as against the general premise that futures being low-cost instruments lead in price discovery. This phenomenon may be attributed to relatively low participation of informed institutional investors in Indian futures segment.
Pattern and Determinants of Household Savings in Odisha: An Empirical Analysis of Censored Data Using a Tobit Model
The virtuous cycle of higher savings, capital formation, output expansion and higher income generation underscores the role of higher savings in achieving and sustaining higher economic growth. This becomes more relevant for an economically weaker state like Odisha, which needs to sustain high economic growth, having important implications for poverty reduction and improving inter-state economic disparity in the entire country. In this context, empirical analysis of the pattern of household savings in Odisha and the role of its various socioeconomic-demographic determinants become important. In the absence of reliable official data on household savings in Odisha, the present study undertook a household survey to understand the pattern of household savings in Odisha and assess the role of its various determinants. The study employed Tobit model which is most suitable to analyze the saving behavior of the sample households, as some of them reported �nil� savings. The estimated results revealed that along with household income, factors such as education, and nuclear family structure were statistically significant in promoting household savings. Based on the empirical analysis, relevant policy implications are derived, which will be critical for improving household savings in particular and promoting overall economic welfare in general.
The Impact of Demonetization on Indian Stock Market: A Sectoral Analysis of Bombay Stock Exchange
In 2016, the Indian government demonetized the ?500 and ?1,000 notes, the two highest denomination currencies in the system. This was a rare event that affected the entire Indian economy. The present study aims to find out the impact of the demonetization on the stock market by applying the event study methodology on 19 sectoral indices of Bombay Stock Exchange. The period of study spans from April 1, 2015 to November 24, 2016. The estimation period is from April 1, 2015 to September 30, 2016. The Cumulative Abnormal Returns (CAR) are calculated for 25 trading days before the event day to 10 days after it, with November 9, 2016 considered as the event date. The results of the study show that demonetization had a positive impact on indices like the public sector enterprise (CPSE), power (SIPOWE), infrastructure (Infra), banks (SIBANKEX), healthcare (SI0800), metals (SI1200) and utilities (SPBSUTIP), and negative impact on indices like auto (SI1900), FMCG (SI0600), consumer discretionary goods (SPBSCDIP), realty (SIREAL), basic materials (SPBSBMIP), and tech (SIBTEC), while capital goods (BISO200), oil and gas (SI1400), energy (SPBSENIP), industrials (SPBSIDIP), and telecom (SPBSTLIP) indices were not affected. The findings also reveal that there is no leak about the event to the market as the CAR for the pre-event period is not significant for any sector.