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Article
Publication date: 5 June 2017

Ajay K. Dhamija, Surendra S. Yadav and P.K. Jain

Certified emission reduction (CER) survey studies in the literature are quite restrictive in scope. These studies are based on convenience sampling and, therefore, cannot…

Abstract

Purpose

Certified emission reduction (CER) survey studies in the literature are quite restrictive in scope. These studies are based on convenience sampling and, therefore, cannot be relied upon. The current study comprehensively surveys the strengths, weaknesses and suggestive measures for clean development mechanism (CDM). This paper systematically aims to conduct the survey on top 50 companies in terms of CER volume.

Design/methodology/approach

The survey is aimed to target top 50 companies which account for 55 per cent of total number of CERs of all the Indian projects. The online survey link was sent to all 50 companies, and the finance managers were followed up regularly over a period of one year. Finally, 37 responses (a response rate of 72 per cent) have been received.

Findings

“CER is cheaper than EUA for Emission Compliance” is rated as topmost strength and “Methodology of Financial Additionality is Subjective” is rated as topmost weakness of CER mechanism. Removal of Quantitative Restrictions on CERs is rated as the topmost suggestive measure for stabilization of CER. Companies overwhelmingly favored continuation of banking and inclusion of carbon emission cost as one of the internal cost of business.

Practical implications

The current study throws light on future policy interventions for minimization of carbon footprint and efficient energy management.

Social implications

This study gives vital reflections for stabilization of CDM. This will help sustainable development, generation of green energy, mitigation of carbon emission at the least cost and employment generation in developing countries because of CDM project development.

Originality/value

This study differs from earlier studies because it comprehensively surveys the pertinent issues relating to strengths, weaknesses and suggestive measures for CDM. It also differs from them because it is not based on convenience sampling. It conducts the survey systematically on top 50 companies in terms of CER volume. Therefore, unlike previous studies of questionable validities, the findings of this study can be safely considered for policy interventions

Details

International Journal of Energy Sector Management, vol. 11 no. 2
Type: Research Article
ISSN: 1750-6220

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Article
Publication date: 7 October 2021

Vikas Gupta, Shveta Singh and Surendra S. Yadav

In initial public offerings (IPOs), the media plays a pivotal role by disseminating the information to the investors who generally lack the expertise to understand the…

Abstract

Purpose

In initial public offerings (IPOs), the media plays a pivotal role by disseminating the information to the investors who generally lack the expertise to understand the information through the prospectus. Thus, media coverage can impact the investment decision of the investors and the IPO performance. Media typically covers the IPO before listing, suggesting that it may play an important role in explaining the opening price rather than the closing price on the day of listing. Therefore, this study aims to disaggregate the traditional IPO underpricing into three categories: voluntary, pre-market and post-market and provides a comparative analysis of the media sentiments impact on the traditional and disaggregated IPO underpricing. The authors’ disaggregated IPO underpricing analysis will facilitate the investors in making an effective investment strategy based on media sentiments.

Design/methodology/approach

The study deploys sentiment analysis using bags of n (2) grams approach to gauge the sentiments on 2,891 media articles and uses “robust-regression” technique to analyze them on a sample of 222 Indian IPOs during 2009–2018.

Findings

The study reports that the sentiment score is positively related to the traditional underpricing; the sentiment score is positively associated with the pre-market underpricing and does not have any significant relationship with the post-market underpricing; the number of media articles does not play a significant role in explaining the IPO underpricing. The findings highlight the presence of a semi-strong form of efficiency in the Indian IPO market.

Originality/value

Existing literature focuses that the role of media on IPO performance is based on the developed countries. IPO laws differ based on the countries. For instance, in India, investors can check the demand by the other categories of investors on a real-time basis. Thus, it is interesting to study whether, with such a high level of transparency, media can explain IPO performance in the Indian market. Media generally covers IPO before listing; therefore, the present study disaggregates the IPO underpricing to evaluate the role of media on the primary and secondary market separately. It will help the investors to decide when to enter and exit the market.

Details

Journal of Asia Business Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1558-7894

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Article
Publication date: 2 October 2017

Ajay Kumar Dhamija, Surendra S. Yadav and P.K. Jain

The purpose of this paper is to find out the best method for forecasting European Union Allowance (EUA) returns and determine its price determinants. The previous studies…

Abstract

Purpose

The purpose of this paper is to find out the best method for forecasting European Union Allowance (EUA) returns and determine its price determinants. The previous studies in this area have focused on a particular subset of EUA data and do not take care of the multicollinearities. The authors take EUA data from all three phases and the continuous series, adopt the principal component analysis (PCA) to eliminate multicollinearities and fit seven different homoscedastic models for a comprehensive analysis.

Design/methodology/approach

PCA is adopted to extract independent factors. Seven different linear regression and auto regressive integrated moving average (ARIMA) models are employed for forecasting EUA returns and isolating their price determinants. The seven models are then compared and the one with minimum (root mean square error is adjudged as the best model.

Findings

The best model for forecasting the EUA returns of all three phases is dynamic linear regression with lagged predictors and that for forecasting EUA continuous series is ARIMA errors. The latent factors such as switch to gas (STG) and clean spread (capturing the effects of the clean dark spread, clean spark spread, switching price and natural gas price), National Allocation Plan announcements events, energy variables, German Stock Exchange index and extreme temperature events have been isolated as the price determinants of EUA returns.

Practical implications

The current study contributes to effective carbon management by providing a quantitative framework for analyzing cap-and-trade schemes.

Originality/value

This study differs from earlier studies mainly in three aspects. First, instead of focusing on a particular subset of EUA data, it comprehensively analyses the data of all the three phases of EUA along with the EUA continuous series. Second, it expressly adopts PCA to eliminate multicollinearities, thereby reducing the error variance. Finally, it evaluates both linear and non-linear homoscedastic models incorporating lags of predictor variables to isolate the price determinants of EUA.

Details

Journal of Advances in Management Research, vol. 14 no. 4
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 14 August 2017

Dhanya Jothimani, Ravi Shankar and Surendra S. Yadav

Portfolio optimization is the process of making an investment decision on a set of assets to realize high returns with low risk. It has three major stages: asset…

Abstract

Purpose

Portfolio optimization is the process of making an investment decision on a set of assets to realize high returns with low risk. It has three major stages: asset selection, asset weighting and asset management. Asset selection is an important phase because it influences asset allocation and ultimately affects the returns of a portfolio. Today, there is an increase in the number of listings on a stock exchange. Therefore, it is important for an investor to screen and select stocks for investment. This study focuses on the first stage of the portfolio optimization problem, namely, asset selection. The purpose of this study is to evaluate and select profitable stocks quoted on National Stock Exchange (NSE) for portfolio optimization.

Design/methodology/approach

Financial ratios are considered as the input and output parameters for evaluating the financial performance of the firms. This study adopts a hybrid principal component analysis (PCA) and data envelopment analysis (DEA) approach to evaluate the efficiency of the firms. Based on the efficiency scores, the firms are selected for the investment process.

Findings

The model helps to determine the relative efficiencies of the firms. The efficient firms are considered to be the potential stocks for investment. It helps the investors to screen the stocks from a large number of stocks quoted on NSE.

Research limitations/implications

One of the limitations of the standard DEA model is that it fails to discriminate the firms when the number of input and output parameters are larger than the number of firms. To overcome this problem, either a parameter can be ignored or weight-restricted DEA can be applied. When an input/output parameter is dropped, the information in that variable is lost. Weight-restricted DEA model uses expert opinion for measuring the relative importance of input and output parameters. Expert opinion is subjective and might be biased. The PCA-DEA model helps to identify the efficient firms by improving the discriminatory power of standard DEA without any loss of information and without the need for expert opinion, which might be biased.

Practical implications

Asset selection is an important stage in the investment process. Selection of stocks based on the efficiency score is an easier option available to the investors. But the misclassification of firms either due to biased expert opinion or discrimination inability of DEA can be costly to an investor. The PCA-DEA model overcomes both these limitations. Investors can select the potential candidates for asset allocation based on the efficiency scores obtained using the PCA-DEA model. Further, the relative efficiencies obtained can help the firms to benchmark their performance against the best performing firms within their industry.

Originality/value

This paper is one of few papers to adopt the PCA-DEA framework to select stocks in the Indian stock market.

Details

Journal of Modelling in Management, vol. 12 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 25 July 2018

Surendra S. Yadav and Ravi Shankar

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Journal of Advances in Management Research, vol. 15 no. 3
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 6 February 2017

Surendra S. Yadav and Ravi Shankar

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360

Abstract

Details

Journal of Advances in Management Research, vol. 14 no. 1
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 7 August 2017

Surendra S. Yadav and Ravi Shankar

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650

Abstract

Details

Journal of Advances in Management Research, vol. 14 no. 3
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 24 January 2019

Surendra S. Yadav and Ravi Shankar

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384

Abstract

Details

Journal of Advances in Management Research, vol. 16 no. 1
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 7 August 2017

Nisha Mary Thomas, Smita Kashiramka and Surendra S. Yadav

The purpose of this paper is to investigate the long-run equilibrium relationship between developed, emerging and frontier markets of the Asia-Pacific region during…

Abstract

Purpose

The purpose of this paper is to investigate the long-run equilibrium relationship between developed, emerging and frontier markets of the Asia-Pacific region during January 2000 to June 2016.

Design/methodology/approach

Zivot and Andrews’ unit root test is used to examine the existence of unit root in index series in the presence of a structural break. Gregory and Hansen’s test of cointegration is employed to examine the stable long-run relationship between the indices under study.

Findings

The results suggest that the emerging markets of China and Thailand and the frontier markets of Sri Lanka and Pakistan are fairly segmented from most of the markets in the Asia-Pacific region. Hence, these markets provide good diversification opportunities to global investors. Bidirectional cointegration analysis indicates that emerging and frontier markets influence developed markets. Hence, it can be inferred that the de facto position that only bigger markets influence small markets no longer holds true in the current environment.

Practical implications

The findings of this study will provide valuable inputs to global investors for creating an optimal investment portfolio.

Originality/value

This study does a comprehensive examination of market integration in the Asia-Pacific region. It also contributes to the thin body of work done on frontier markets. Unlike past studies, this paper analyzes the bidirectional cointegration relationship to examine if the notion that only bigger markets influence smaller markets holds true or not. Finally, this study employs advanced techniques of unit root test and cointegration test that consider structural breaks in the models.

Details

Journal of Advances in Management Research, vol. 14 no. 3
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 5 February 2018

Harshita Harshita, Shveta Singh and Surendra S. Yadav

The purpose of this paper is to ascertain the monthly seasonality in the Indian stock market after taking into consideration the market features of leptokurtosis…

Abstract

Purpose

The purpose of this paper is to ascertain the monthly seasonality in the Indian stock market after taking into consideration the market features of leptokurtosis, volatility clustering and the leverage effect.

Design/methodology/approach

Augmented Dickey-Fuller, Phillips-Perron and Kwaitkowski-Phillips-Schmidt-Shin tests are deployed to check stationarity of the series. Autocorrelation function, partial autocorrelation function and Ljung-Box statistics are employed to check the applicability of volatility models. An exponential generalized auto regressive conditionally heteroskedastic model is deployed to test the seasonality, where the conditional mean equation is a switching model with dummy variables for each month of the year.

Findings

Though the financial year in India stretches from April to March, the stock market exhibits a November effect (returns in November are the highest). Cultural factors, misattribution bias and liquidity hypothesis seem to explain the phenomenon.

Research limitations/implications

The paper endeavors to provide a review of possible explanations behind month-of-the-year effect documented in literature in the past four decades. Further, the unique evidence from the Indian stock market supports the argument in the literature that monthly seasonality, by nature, may not be a consistent/robust phenomenon. Therefore, it needs to be examined from time to time.

Originality/value

As the seasonality in the stock market and resultant anomalies are dynamic phenomena, the paper reports the current seasonality/anomalies prevalent in the Indian market. This would aid investors in designing short-term investment portfolios (based on anomalies present) in order to earn abnormal returns.

Details

Journal of Advances in Management Research, vol. 15 no. 1
Type: Research Article
ISSN: 0972-7981

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