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The present study seeks to investigate the relative edge between the market microstructure of the two leading stock exchanges of the Indian capital market, that is BSE and NSE with a focus on analysing their trading mechanism, efficiency, liquidity and volatility.

We analyse the microstructure of BSE and NSE on the basis of: (1) trading mechanism – ownership structure, listing of securities, trading system and settlement and clearing process; (2) information efficiency using unit root test, serial correlation, runs test, variance ratio and the ARIMA model; (3) liquidity using trading statistics no. of listed Companies, market capitalisation, no. of trades etc. and (4) volatility using standard deviation and GARCH(1,1) model.

A comprehensive scrutiny on microstructure of BSE and NSE makes it evident that the two leading stock exchanges of India are mostly similar and leave no scope to choose between them. Both the exchanges are demutualised corporate entities with a fully automated trading system in an order-driven market, informationally inefficient as evidenced by the predictability of returns, have shown tremendously growing trading statistics and by and large a declining trend in volatility over the years.

Understanding the components of the microstructure black-box will provide the regulatory bodies with an intellectual framework to strengthen the market architecture. Both the exchanges will get aware of the dynamics of trading, can grow to be more competitive and attract more firms for listing and investors for trading of securities. Also, investors, portfolio managers and equity analysts will be able to make better investment strategies by understanding how the market works.

Research in the area of market microstructure has been severely neglected, especially in the context of the Indian market. India is the world's fastest growing economies and we have witnessed tremendous reforms in the capital market. The past two and a half decades have brought about several innovations via demutualisation, screen-based trading, emergence of clearing corporations, innovative financial products and intense use of IT in the Indian stock market. A spurt of reforms and the emerging environment make it crucial to deeply analyse the market structure and design of two premier stock exchanges of India – BSE and NSE.

This study examines the semi-strong market efficiency of the Indian agricultural commodity market in light of market reforms and policies. This study investigates whether the market reforms have boosted the speed of price adjustment and influenced the market quality.

The study used the daily data of nine agricultural commodities. To precisely capture the effects of market microstructure changes, this study split the whole data into pre- and post-ban and pre- and post-reform eras. To ascertain the velocity of price adjustment, the authors used the ARMA (1,1) model, and the ADD VRatio was employed to identify the price movement on a specific day.

This study found that full incorporation of information happens sometimes. The authors noticed no gradual progress in the quickness of price adjustment. Since both methods suggested the same result for the period, the authors confirm that market microstructure changes do not enhance market quality.

This research has implications for academicians, policymakers and market players.

The paper has twofold novelty. First, this is a contemporary topic, and very few studies have been done in the Indian agriculture context. Second, the study has implications for policymakers and government because it highlights the effects of structural changes on market quality and market efficiency.

This study aims to provide a systematic literature review of the research study in the area of limit order book (LOB) mechanism of trading and its implications for market efficiency. The study attempts to document the recent theoretical developments and empirical findings from the literature exhaustively and identifies the research gaps for future research.

The study uses seven reputable databases to select 2,514 research studies spanning over 1981-2018 (finally compressed to a pool of 103 articles, based on relevance and impact). The study uses bibliometric network visualization and text analytics to categorize and examine the literature. The chosen articles are compiled and analyzed to provide a comprehensive account of the current research on LOBs.

The recent LOB literature is summarized on various criteria as follows: sub-areas, the types of economies and markets, methodologies and the LOB measures. The review identifies a dearth of studies on the LOBs in emerging markets. It suggests the potential research areas as intraday studies in emerging LOB markets; application of market indicators based on deeper levels of LOB, beyond the best prices; market fragmentation, order routing decision and its impact on order execution quality; optimal display of LOB levels; liquidity dynamics in quote-driven markets vis-à-vis LOB markets; effect of high-frequency trading on market microstructure; application of advanced techniques (e.g. machine learning models, zero-intelligent models); relationship between the trading speed, order aggressiveness, shape and resilience of the order book and informed trading; and information content of the auxiliary order submission strategies, including cancellation, amendments and hidden orders.

For the past 15 years, to the best of the knowledge, a comprehensive review of the literature on LOBs has not been published. The financial markets have transformed significantly over this period, driven by the adoption of LOBs, low latency trading and technological advancements in information dissemination. This article provides an extensive collection and classification of the literature on LOBs. This would be useful for the practitioners, future researchers and academics in the area of financial markets.

The purpose of this paper is to examine market microstructure differences in stock market quality for hospitality real estate investment trusts (REITs) during the pre- and post-financial crisis eras. It provides insight on different trading strategies based on the underlying liquidity and volatility of hospitality REITs as compared traditional REITs and the broader market.

The paper uses established microstructure measures for liquidity, trading volumes and risk assessment and compares daily and intraday trading patterns of REITs, hospitality REITs and the broad market.

The results suggest a quicker recovery of performance for hospitality REITs and some fundamental increases in liquidity measures post-crisis. The results of the study highlight the differences in trading volumes, liquidity and risk profile of hospitality REITs compared to traditional REITs both in the pre- and post-financial crisis periods.

The quicker recovery of hospitality REITs in key trading measures may suggest flight to quality during periods of high volatility.

This study fills the gap in the literature relative to microstructure studies and provides information to help hotel firms and portfolio managers choose an appropriate organizational structure and investment vehicle, respectively.

This paper is aimed to investigate the impact of different categories of traders on price and volume durations at Euronext Paris. The two series are respectively related to the instantaneous volatility and the market liquidity; hence, they are particularly suited to test microstructure hypotheses.

A Log-autoregressive conditional duration model was adopted to include the information on the traders’ identity at the transaction level. High-frequency data were used and how the informed traders and the liquidity provider affect the arrival of market events was studied. The robustness of our results was also checked by testing different distributions and controlling for microstructure effects.

It was found that informed traders and the liquidity provider exert a dominant role in accelerating the market activity. This result depends on the state of the market, i.e. it is effective only during periods of high frequency of transactions. The estimates for price durations show that a high instantaneous volatility can be mainly ascribed to a great concentration of informed traders. Informed traders are also found to shorten volume durations by clustering small-size orders to disguise their private signal. For both durations, the liquidity provider is also found to foster the market activity, likely because of his contractual duties.

The article is of interest for researchers in the field of market microstructure, as well as for specialists in the high-frequency trading. Results provide an empirical confirmation of information models which theorize an accelerating effect for informed trading. To the best of the authors’ knowledge, this is the first contribution to study the impact of traders’categories at the transaction level and with different definitions of durations.

This study investigates the impact of simultaneously replacing both midday single-price call auction and lunch break with multi-price continuous trading on intraday volatility–volume patterns as well as the intraday volatility–volume nexus.

The analysis utilises 150 m tick-by-tick transaction data related to 333 stocks traded on Borsa Istanbul Equity Market covering a period of 2 months prior to and following the change. In addition to graphic comparisons, the study uses difference in mean tests, panel-fixed generalized least squares (GLS), panel-random GLS and random-effects linear models with AR(1) disturbance regression estimations.

The results show that intraday volatility and trading volume form an inverse J-shape and are positively correlated. It is observed that the implementation of the regulation change decreased intraday volatility and increased trading volume. Additionally, the results indicate a negative volatility–liquidity and a positive volume–liquidity relationship, supporting the mixture of distribution hypothesis.

Enhanced market efficiency provides greater opportunity for investment and risk management. Investors can benefit from the findings on the intraday volatility–volume nexus, which is an indicator of informed trading, and regulatory authorities can use volume to oversight volatility.

This very rare regulation change of the simultaneous replacement of the lunch break and midday call auction with continuous trading is investigated in the context of intraday volume and volatility. This study also expands upon some important findings on the volume–volatility nexus for the Turkish Stock Market.

The purpose of this paper is to investigate and compare the impact of order imbalance on returns, liquidity and price volatility in agricultural futures markets on an intraday basis. The authors examine whether order imbalance is more powerful to explain variations in asset prices compared to other indicators of trading activity, particularly trading volume.

Using Chicago Mercantile Exchange best bid best offer data, the impact of order imbalance is analyzed via regression analyses. The analyses are carried out for corn, wheat, soy, live cattle and lean hogs in March 2008 and March 2016.

Results confirm the positive relation between order imbalance and returns as well as between order imbalance and price volatility as suggested by market microstructure models. Order imbalance, however, does not generally outperform trading volume as an explanatory variable.

For some contracts, returns can be predicted using lagged order imbalance. This offers the opportunity to derive profitable trading strategies.

This paper is one of the first attempts to explore the relationship between order imbalance and returns, liquidity and volatility for agricultural commodity futures on an intraday basis, accounting for the increased trading volume and for the high speed at which new information enters the market in an electronic trading environment.

Intraday volatility characteristics throughout the trading week are examined at the emerging Borsa Istanbul (BIST) stock exchange. Using five-minute (and 15-minute) intervals, accentuated intraday volatility patterns at the microstructure level are examined during the stock market open and close in the morning and in the afternoon sessions. Volatility is highest when markets open in the morning. The second highest is during the afternoon open. The third highest is before the market closes for the day. Volatility before the market close has increased in recent years. These characteristics are seen every trading day. There are also differences: Monday returns are lowest, Friday returns are highest, and Monday morning volatility is highest of the entire trading week. Day-of-the-week and intraday accentuated volatility smile anomalies are jointly investigated using the longest intraday sample period in the emerging country stock exchange literature. Investment companies and professionals can utilize the results for risk management and hedging by avoiding highly volatile opening and closing periods. Arbitrageurs, speculators, and risk takers should trade during these highly volatile periods. Heightened volatility is increased difficulty in price discovery, thus inefficiency. Market participants, exchanges, and public prefer efficient markets. The research presents evidence of trading days, and periods during the trading day, when the exchange becomes more efficient. This is the first research that explores day-of-the-week effect from intraday volatility perspective in an emerging market, and provides useful recommendations in designing risk management strategies at market microstructure level.

The purpose of this study is to systematically review and analyze the literature in the area of liquidity of financial markets. The study summarizes the key findings and approaches and highlights the research gaps in the extant literature.

A variety of reputed databases are utilized to select 100 research papers, from a large pool of nearly 3,000 research papers spanning between 1972 and 2018 using systematic literature review methodology. The selected research papers are organized to provide an in-depth analysis and an account of the ongoing research in the area of liquidity. The study uses bibliometric network visualization and word-cloud analyses to compile and analyze the literature.

The study summarizes the recent approaches in the liquidity research on aspects such as methodologies followed, variables applied, sub-areas covered, and the types of economies and markets covered. The article shows that the literature on liquidity in the emerging markets (e.g. China and India) is deficient. Overall, the following research areas related to liquidity need further exploration in the context of emerging markets: liquidity beyond the best bid-ask quotes, intraday return predictability using microstructure variables (e.g. order imbalances), impact of algorithmic-trading and volatility of liquidity.

To the best of authors’ knowledge, in the recent past, a detailed account of the literature on liquidity has not been published. It provides a comprehensive collection and classification of the literature on the liquidity of financial markets. This would be helpful to the future researchers, academics and practitioners in the area of financial markets.