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This study empirically explores the intraday price discovery mechanism and volatility transmission effect between the dual-listed Indian Nifty index futures traded simultaneously on the onshore Indian exchange, National Stock Exchange (NSE) and offshore Singapore Exchange (SGX) and its spot market by using high-frequency data.

This study applies the vector error correction model to analyze the lead-lag relationship in price discovery among three markets. The contributions of individual markets in assimilating new information into prices are measured using various measures, Hasbrouck's (1995) information share, Lien and Shrestha's (2009) modified information share and Gonzalo and Granger's (1995) component share. Additionally, the Granger causality test is conducted to determine the causal relationship. Lastly, the BEKK-GARCH specification is employed to analyze the volatility transmission.

This study provides robust evidence that Nifty futures lead the spot in price discovery. The offshore SGX Nifty futures consistently ranked first in contributing to price discovery, followed by onshore NSE Nifty futures and finally by the spot. Empirical results also show unidirectional causality and volatility transmission from Nifty futures to spot, as well as bidirectional causal relationship and volatility spillovers between NSE and SGX Nifty futures. These novel findings provide fresh insights into the informational efficiency of the dual-listed Indian Nifty futures, which is distinct from previous literature.

These findings can potentially help market participants, policymakers, stock exchanges and regulators.

Unlike previous studies in this area, this is the first study that empirically examines the intraday price discovery mechanism and volatility spillover between the dual-listed futures markets and its spot market using 5-min overlapping price data and trivariate econometric models.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.

This chapter examines the use of signaling mechanism to identify promising acquisition targets. It draws on the importance of inter-organizational relationships of target firms and their relevance as signals of firm quality. It takes into account two types of inter-organizational relationships, alliances and corporate venture capital (CVC) investments. It further identifies the boundary conditions that are most likely to influence the acquisition decision of the acquirer. These are based on the characteristics of target firms and their partners. By considering the role of CVC investments and alliances as signals of firm quality, the study draws a connection between how the different types of equity and non-equity relationships of firms influence the acquirer’s choice of potential takeover target.

The theoretical frame based on the signaling perspective provides fresh and valuable insights to evaluate the quality of target firms. The research provides directions for future opportunities to examine the value of signals and whether such signals create synergies in mergers and acquisitions (M&A) deals. The author identifies new avenues of research that would help to move forward the signaling perspective in the literature on M&A.

The purpose of this study was to identify if and how K–6 teachers perceive that their literacy instructional coaches influence their writing teaching.

The authors employed a parallel convergent mixed-methods design with survey data. The authors used thematic analysis to identify patterns within short-answer responses.

K–6 teachers receive little literacy coaching specific to writing. However, when they do receive coaching, they believe it benefits their writing instruction. Sustained coaching through the coaching cycle, frequent collaborations, and support with writing instructional resources and strategies were reported as the most influential writing coaching practices.

Sample size was a limitation to this study. Of the 66 participants, 41 (62%) completed the entire survey.

This research provides coaches with valuable insights about coaching practices that teachers find to be the most effective in influencing their writing instruction. The increase in teachers' competence in writing instruction due to coaching provides evidence to administrators and stakeholders that coaching in writing is an area in need of attention.

This study adds to research specific to the coaching of writing within the K–6 context, which currently is sparse.

This study focused on unpacking the instructional coaching process, addressing key questions about what happens during a coaching session and what coaching elements predict teacher outcomes.

Using coaching observational data, the research examined critical coaching processes described in the literature: coaching practices (observation, feedback, reflective discussion and planning), the coach–teacher relationship, coaching strategies and coaching duration. The study also developed a path model documenting how coaching behaviors predicted teacher instruction.

Results showed that the coach talked more than the teacher and that most coaching time was spent in reflective discussion. The coach–teacher relationship was promoted by building rapport and reciprocal trust, with use of “we” language demonstrating that coach and teacher were working as a partnership. Most common coaching strategies were clarifying and the coach prompting the teacher to attend to teacher or student behaviors. Path model analysis showed that (a) the coach–teacher relationship quality predicted the level of teacher engagement in coaching and their instructional reflection and (b) the quality of coaching strategies predicted the overall quality of the classroom instruction.

The study provides empirical evidence about the active ingredients of coaching – those underlying processes that impact and improve teacher practice.

The purpose of this study is to examine the impact of a recent innovation in the uranium market, the Global X Uranium Exchange-Traded Fund (URA), on the trading characteristics of constituent and non-constituent stocks.

The authors analyse bid-ask spread measures, relative effective spreads and adverse selection costs to assess changes in information asymmetry among uranium stocks. The authors also study abnormal returns to assess the impact of URA on the market.

Over a three-month period, following the introduction of URA, the authors find uranium stocks display decreased bid-ask spread measures, driven by reductions in information asymmetry. Relative effective spreads decrease by 36% after the introduction of URA, and adverse selection costs decline by 24% over the same period. Uranium stocks experience a significant positive abnormal return of 5.0% the day after the introduction of URA with subsequent price reversals. These suggest that the introduction of URA prompted uninformed traders to rebalance portfolios and migrate to the less information-sensitive Exchange-Traded Fund (ETF), causing temporary deviations in trading characteristics.

The authors demonstrate that the introduction of new financial securities to the market can have a significant impact on the trading characteristics of related equities. As URA is the only ETF in the uranium sector, the authors thereby avoid the influence of multiple ETFs that may have impacted previous studies.

The purpose of this study is to compare market reactions to the change in the demand by index funds between large and small company stocks by examining the transition of the S&P 500, S&P 400 MidCap and S&P 600 SmallCap indexes from market capitalization to free-float weighting. This unique information-free event allows not only avoiding confounding information signaling and investor awareness effects but also comparing the effect of the decrease in demand on stocks of different sizes.

This study uses the event study methodology to calculate abnormal returns and trading volume around the full-float adjustment day. It also tests for significant changes in institutional ownership and liquidity. Multivariate regressions are used to examine the relation of liquidity changes and price elasticity of demand to the cumulative abnormal returns around the full-float adjustment day.

This study finds significant decreases in stock price accompanied with significant increases in trading volume on the full-float adjustment day, and significant gains in quasi-indexer institutional ownership and liquidity. The main finding is that cumulative abnormal returns around the event period are related to changes in the number of quasi-indexer and transient institutional shareholders, not to changes in liquidity or price elasticity of demand.

This study provides the first comprehensive comparison analysis of stock market reactions to the decline in demand between large and small company stocks. As an important implication for future studies of the index effect, changes in institutional ownership should be considered in the analysis.

This paper aims to explore the epistemic connections between three instructional coaches and a first-year in-service teacher during remote planning and debrief meetings. Prior evidence suggests that remote instructional coaching leads to better teaching practices and identifies the instructional coaching moves used to prompt teacher reflection.

In this study, the authors utilized quantitative ethnography and epistemic network analysis (ENA) approaches to explore the epistemic frames of three remote university-based instructional coaches as they supported a first-year in-service teacher.

Quantitative ENA findings shed light on the network connections between instructional coaches and teachers, as well as the epistemic frames observed during planning and debrief meetings. Additionally, the authors provide qualitative findings that complement and reinforce the quantitative results.

All data collection occurred via Zoom, and the class was in a hybrid modality, with some students attending class in person and some attending remotely via Zoom. This unique context could have impacted the epistemic connections surrounding technology and logistics.

This study provides a practical codebook for use in future studies that explores instructional coaching. Findings from this study can be used to inform instructional coaching decisions.

The ENA findings helped deepen the authors' understanding of how instructional coaches can support a first-year in-service teacher during planning and debrief meetings in several ways. Additionally, this study presents a unique context given the COVID-19 pandemic and the remote model of instructional coaching.

This study aims to systematically review the literature in the fields of liquidity, informational efficiency and default risk. The authors outline the key research streams and provide possible pathways for future research.

The study adopts bibliographic mapping to identify the most influential studies in the research fields of liquidity, informational efficiency and default risk from 1984 to 2021.

The study identifies four key research themes that include efficiency and transparency of markets; corporate yield spreads; market interactions: bonds, stocks and cryptocurrencies; and corporate governance. By assessing publications published from 2018 to 2021, the authors also document seven key emerging research trends: cross markets, managerial learning and corporate governance, state ownership and government subsidies, international evidence, machine learning (FinTech approaches), environmental themes and financial crisis. Drawing on these emerging trends, the authors highlight the opportunities for future research.

Keyword searches have limitations since some studies might be overlooked if they do not match the specified search criteria, even though their relevance to the topic is under investigation. Adopt the R project to expand this review by incorporating more literature from other databases, such as the Scopus database could be a possible solution.

The four key research streams contribute to a comprehensive understanding of liquidity, informational efficiency and default risk. The emerging trends integrate existing knowledge and leave the chance for innovative research to expand the research frontier.

This study fulfills the systematic literature review streams in the fields of liquidity, informational efficiency and default risk, and provides fruitful opportunities for future research.

The purpose of this study is to ascertain how foreign and domestic Exchange Traded Funds (ETFs) investing in Indian equities affect their return volatility and pricing efficiency. Further, we investigate how the difference in market timings affect the impact of ETFs on their constituents. Lastly, we examine how these effects vary during tranquil and turmoil periods in the ETF markets.

The study is based on quarterly data for stocks comprising the CNX Nifty 50 Index from 2009Q1 to 2019Q3. The data on holdings of 45 domestic and 196 foreign ETFs in the sample stocks were obtained from Thomson Reuters' Eikon. The paper employs a panel-regression methodology with stock and time fixed effects and robust standard errors.

Foreign ETFs from North America and the Asia Pacific largely have an adverse impact on stocks' return volatility. In times of turmoil, stocks with higher coverage of European, North American and Domestic funds are susceptible to volatility shocks emanating from these regions. European and Asia Pacific ETFs are associated with improved price discovery while North American funds impound a mean-reverting component in stock prices. However, in turbulent markets, both positive and negative impacts of ETFs on pricing efficiency coexist.

To the best of the authors' knowledge, this is the first study that examines the impact of domestic as well as foreign ETFs on the equities of an emerging market. Furthermore, the study is unique as we investigate how the effects of ETFs vary in turbulent and tranquil markets. Moreover, the paper examines the role of asynchronous market timings in determining the ETF impact. The paper adds to the growing literature on the unintended consequences of index-linked products.