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The regulatory design of Indian stock market provides us with the opportunity to disaggregate initial returns into two categories, i.e. voluntary premarket underpricing and post market mispricing. This study explores the impact of investor attention on the disaggregated short-run returns and long-run performance of initial public offerings (IPOs).

The study employs regression techniques on the sample of IPOs listed from 2005 to 2019. It measures investor attention with the help of the Google Search Volume Index (GSVI) extracted from Google Trends. Along with GSVI, the subscription rate is used as a proxy to measure investor attention.

The empirical results suggest a positive and significant relationship between initial returns and investor attention, thus validating the attention theory for Indian IPOs. Furthermore, when the returns are analysed for a more extended period using buy-and-hold abnormal returns (BHARs), it was found that price reversal holds in the long run.

This study highlights the importance of information diffusion in the market. It emphasizes the behavioural tendency of the investors in the pre-market, which reduces the market efficiency. Hence, along with fundamentals, investor attention also plays an essential role in deciding the returns for an IPO.

According to the best of the authors’ knowledge, this is one of the first studies that has attempted to explore the influence of investor attention and its interplay with underpricing and long-run performance for IPOs of Indian markets.

The main purpose of this paper is to analyze the role of information and communication technology (ICT) diffusion in women empowerment and in fostering the process of achieving the Sustainable Development Goals (SDGs) in South Asian Association for Regional Cooperation (SAARC) countries using panel data from 2005 to 2020.

An ICT diffusion index was constructed using principal component analysis (PCA). Further, the study uses econometric techniques robust to cross-sectional dependence (CSD) which include Pesaran's CSD tests, second-generation unit root test, Pedroni, Kao, Westerlund cointegration test, FMOLS, DCCE, Driscoll–Kraay (DK) regression, and D&H causality tests.

ICT diffusion and economic growth have a significant and favorable impact on women's empowerment. However, fertility rates and trade openness harm women's empowerment. In addition, the causality test results depict a bidirectional causal relationship between ICT and women empowerment and between growth and women empowerment. In addition, unidirectional causality is detected between education and women's empowerment. Overall, the findings indicate that expanding ICT and bridging the digital divide, particularly among women, can be effective in achieving empowerment-related SDGs.

To date, there are hardly any studies in SAARC context that empirically evaluate the link between ICT, women empowerment, and the issue of sustainability in a unified framework. Therefore, this study is unique in terms of conceptualization and methodological robustness in this context. The study will benefit policymakers and regulatory bodies to formulate appropriate policies to empower women and thereby attain the SDGs by 2030.

The main purpose of the present research is to analyze the relationship between technological development, financial development and economic growth in India in a non-linear and asymmetric framework.

The study employs the nonlinear autoregressive distributed lags model (NARDL) and Hetemi J asymmetric causality tests to explore nonlinearities in the dynamic interaction among the variables. The stationarity properties of data are checked by using Ng–Perron and ADF structural break unit root tests. The unit root test confirms that the variables are non-stationarity in level and are differenced stationary.

The study finds that there is a cointegrating relationship between technological development, financial development and economic growth in the long run. The findings suggest that a positive shock in technological development increases economic growth (coefficient value 1.497 at 1% significance level) and a negative shock will harm economic performance (coefficient value −0.519 at 1% significance level). A long-term positives shock in financial development boosts the economy (coefficient value 1.08 at 5% significance level) and negative shock hampers the economic performance (coefficient value −1.09 at 5% significance level). The asymmetric causality test result confirms bi-directional causality between technological development and economic growth and unidirectional causality from negative economic growth to negative technological development and bi-directional causality between economic growth and financial development, unidirectional negative financial development to economic growth.

The results of this research can significantly facilitate stakeholders and policymakers in devising short-term as well as long-term policies for financial development and technological innovation to achieve sustainable long-run economic growth in India.

This paper is the first of its kind to empirically examine the cointegrating and causal relationship between technology, financial development and economic growth in India using non-linear asymmetric cointegration and causality tests.

This paper aims to study the underpricing phenomenon of initial public offerings (IPOs) of 355 Indian companies issued from 2007 to 2019. The research question this paper empirically examines is whether Indian corporate executives deliberately underprice IPOs from its fair value to attract investors, thereby causing an abnormal spike in the prices on the listing day. The findings of this study challenge a commonly held notion of leaving money on the table by IPO issuing companies. Of the overall average listing day returns of 17%, the deliberate premarket underpricing component is found to be mere 5.3%, while the remaining price fluctuation is, inter alia, a result of market momentum along with the unmet demands of impatient investors.

Following Koop and Li (2001), this study uses Stochastic frontier model (SFM) to study a routine anomaly of disparity between the primary market price (i.e. IPO issue price) and the secondary market price (listing price). The jump in the issue price observed on a listing day is decomposed into deliberate premarket underpricing component that reflects the extent of managerial manipulation and the after-market misvaluation component attributable to information asymmetry and prevailing market volatility.

This paper uses SFM to bifurcate initial returns into deliberate underpricing by managers and after-market mispricing by noise traders. This study finds that a significant part of the initial return is explained through after-market mispricing. This study finds that average initial returns are 17%, deliberate premarket underpricing is 5.3% and after-market mispricing averages 11.9%.

This study can isolate underpricing done at the premarket by estimating a systematic one-sided error term that measures the maximum predicted issue price deviation from the offered price. Consequentially, the disaggregation of initial returns may be especially informative for retail investors in planning their exit strategy from an IPO by separating the strength of the firm's fundamentals and its causal relationship with the initial returns. Substantial proportion of after-market mispricing implies that future research should focus on factors causing after-market mispricing. As underlying causes are identified, tailor-made policy responses can be formulated to benefit investors.

This paper has empirically validated that initial return is a mix of both components, i.e. deliberate underpricing and aftermarket mispricing. This disaggregation of initial returns can prove helpful for investors in planning their exit strategy. This study can help investors to become more aware of the importance of the fundamentals of the firm and its causal relation with the initial returns. This information in turn can help reduce the information asymmetry amongst investors and help them lessen the costs of adverse selection.

A large number of research studies on IPO pricing find overwhelming evidence of underpricing in public issues. This research attempts to decompose the extent of underpricing into deliberate underpricing and after-market mispricing, thereby supplementing the existing literature on the IPO pricing puzzle. To the best of the authors’ knowledge, this study is the first contribution to the literature on initial return decomposition for the Indian capital markets.

This study aims to examine the relationship between pandemic sentiment (PS) and stock market returns in an emerging order-driven stock market like India.

This study uses nonlinear causality and wavelet coherence techniques to analyze the sentiment-returns nexus. The analysis is conducted on the full sample period from January to December 2020 and further extended to two subperiods from January to June and July to December to investigate whether the associations between sentiment and market returns persist even several months after the outbreak.

This study constructs two novel measures of PS: one using Google Search Volume Intensity and the other using Textual Analysis of newspaper headlines. The empirical findings suggest a high degree of interrelationship between PS and stock returns in all time-frequency domains across the full sample period. This interrelationship is found to be further heightened during the initial months of the crisis but reduces significantly during the later months. This could be because a considerable amount of uncertainty regarding the crisis is already accounted for and priced into the markets in the initial months.

The ongoing coronavirus pandemic has resulted in sharp volatility and frequent crashes in the global equity indices. This study is an endeavor to shed light on the ongoing debate on the COVID-19 pandemic, investors’ sentiment and stock market behavior.

This study aims to examine the relationship between economic policy uncertainty and stock market liquidity in an order-driven emerging stock market.

Empirical estimates are based on vector autoregressive Granger-causality tests, impulse response functions and variance decomposition analysis.

The empirical findings suggest that economic policy uncertainty moderately influences stock market liquidity during normal market conditions. However, the role of economic policy uncertainty for determining stock market liquidity is significant in times of financial crises. The authors have also observed a significant portion of variation in stock market liquidity that is attributed to investor sentiments during financial crises.

This study is original in nature and provides evidence to consider economic policy uncertainty as a possible source of commonality in liquidity in the context of an emerging market.