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This study examines changes in volume and transaction on volatility over the past three decades and tests two theoretical models, namely competitive and strategic models, using intraday quotes and trade data spanning from January 01, 1993 to December 31, 2019. We use 30-minute, 10-minute and 5-minute intervals. The sample period is carefully selected to encompass our analysis for various trading eras with different tick sizes. We find that volume is highly significant in both pre- and post-decimalization eras in explaining the volatility of returns. We also find that a strong positive relationship between volume and volatility exists, even after controlling for frequency of trades and before algorithmic trading came to dominate the market. We do, however, find a reduced ability of trading volume and frequency to explain volatility patterns in the recent period, coincident with the rise of algorithmic and high-frequency trading. We also document a shift in market relationships through time. JEL Classification: C02, D52, D53, G14, G15 Key Words: Volatility, GMM, Volume, Flash Crash, Liquidity, Volatility Smile, I. Introduction Is it volume or frequency of trades that transmits information to the market and drives volatility, and how does the relative contribution of each change over time? The [...]

This paper demonstrates that the ability of fund managers to create value depends on market liquidity conditions, which in turn introduces a liquidity risk exposure (beta) for skilled managers. We document an annual liquidity beta performance spread of 4% in the cross section of mutual funds over the period 1983-2014. Liquidity risk premia explain an insubstantial fraction of this spread; instead, the spread can be attributed to the differential ability of high liquidity beta funds to outperform across high and low market liquidity states, due to a differential rate of either mispricing correction or intensity of informed trading. Tests based on mispricing, proxied by a comprehensive set of 68 anomalies, and tick-by-tick trades, from a large proprietary institutional trading data set, corroborate the contribution of these channels. The results highlight the interaction between informed investors, mispricing, and liquidity beta. History: Accepted by Neng Wang, finance. Supplemental Material: The Internet appendix is available at https://doi.org/10.1287/mnsc.2017.2851. Keywords: liquidity risk * mutual funds * active management * mispricing * investment skill * anomaly, 1. Introduction Systematic liquidity risk has been a focus of recent literature, especially in light of the financial crisis. Prior studies demonstrate the pricing of liquidity risk exposure (beta) in [...]

Abstract. We show that an equity pairs trading strategy generates large and significant abnormal returns. We find that two components of the trading signal (i.e., short-term reversal and pairs momentum) [...]

We examine the make-take structure, which compensates liquidity suppliers and charges liquidity demanders, in the options markets where it competes with a traditional structure that uses payments for order flow. Using the introduction of the make-take structure as an event, we find that execution costs (including fees) for liquidity demanders decline after the event for the affected options, that the make-take structure encourages market makers to improve quoted prices, and that brokers change their routing behavior to include fees in the routing decision. The decline in execution costs is consistent with the benefits of the increased quote competition from the make-take structure prevailing over the fees the structure charges to liquidity demanders. Keywords: securities; open markets; microstructure; maker-taker pricing History : Received May 28, 2013; accepted May 30, 2015, by Wei Jiang, finance. Published online in Articles in Advance January 6, 2016., 1. Introduction Make-take pricing marks a significant recent innovation in securities market structure. In the typical implementation of make-take pricing, the exchange charges a fee to the liquidity demander in [...]

Market surveillance systems (MSSs) are increasingly used to monitor trading activities in financial markets to maintain market integrity. Existing MSSs primarily focus on statistical analysis of market activity data and [...]

Abstract We investigate the trading of benchmark Exchange traded funds (ETFs), leveraged ETFs, and leveraged inverse ETFs that are matched based on their tracking index or sector. We find that [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jimonfin.2009.11.001 Byline: Charles Chang Abstract: I compare the performance of buy/hold/sell recommendations from foreign, local, and expatriate (foreigners with local operations) analysts in an emerging market. Location appears to be important: expatriate analysts significantly outperform foreign analysts. Expatriates also significantly outperform locals, implying that other factors such as global resources also play a role, and a variety of controls for the characteristics of the recommending firm does not alter findings. Trading based on expatriate recommendations generates significantly positive risk-adjusted returns. Furthermore, foreign and local institutional investors appear to trade on the superior information of expatriate analysts, even when it contradicts their own information. Author Affiliation: Cornell University, 435 Statler Hall, Ithaca, NY 14853, USA

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1467-9957.2010.02204.x Byline: SAYAT R. BARONYAN (1), L. LLKAY BODUROĞLU (2), EMRAH SENER (3) Abstract: We investigate several market-neutral trading strategies and find empirical evidence that market-neutral equity trading outperforms in 2008, the first full year of the global financial meltdown. In our experiments we use 14 distinct market-neutral trading strategies, using the combination of seven trading methods and two selection methods of pairs trading. Author Affiliation: (1)Informatics Institute, Computational Science & Engineering Graduate Program, Istanbul Technical University (2)Namik Kemal University (3)Center for Computational Finance, Ozyegin University

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1475-6803.2009.01261.x Byline: Wing Lon Ng (*) Keywords: C22; C32; C41; G14 Abstract: Abstract I analyze the dynamic trading behavior of market participants by developing a bivariate modeling framework for describing the arrival process of buy and sell orders in a limit order book. The model contains an extended autoregressive conditional duration model with a flexible generalized Beta distribution to explain the duration process, combined with a dynamic logit model to capture the traders' order submission strategy. I find that the state of the order book as well as the speed of the order arrival have a significant influence on the order placement, inducing temporal asymmetric market movements. Author Affiliation: (*)University of Essex

Abstract In this project, our topic pertains to examination of market efficiency, employing data from closed-end funds (CEFs) trading in the American stock market. Employing both aggregate and individual data, [...]