nep-mst New Economics Papers
on Market Microstructure
Issue of 2017‒01‒01
five papers chosen by
Thanos Verousis

  1. Interactions among High-Frequency Traders By Benes, Evangelos; Brugler, James; Hjalmarsson, Erik; Zikes, Filip
  2. Time-dependent scaling patterns in high frequency financial data By Noemi Nava; Tiziana Di Matteo; Tomaso Aste
  3. Understanding the Impacts of Dark Pools on Price Discovery By Linlin Ye
  4. Private Information in Over-the-Counter Markets By Bethune, Zachary; Sultanum, Bruno; Trachter, Nicholas
  5. Dealer balance sheets and bond liquidity provision By Adrian, Tobias; Boyarchenko, Nina; Shachar, Or

  1. By: Benes, Evangelos (Bank of England); Brugler, James (University of Melbourne, Department of Finance); Hjalmarsson, Erik (Department of Economics, School of Business, Economics and Law, Göteborg University); Zikes, Filip (Division of Financial Stability, Federal Reserve Board)
    Abstract: Using unique transactions data for individual high-frequency trading (HFT)firms in the U.K. equity market, we examine the extent to which the trading activity of individual HFT firms is correlated with each other and the impact on price effciency. We find that HFT order flow, net positions, and total volume exhibit significantly higher commonality than those of a comparison group of investment banks. However, intraday HFT order flow commonality is associated with a permanent price impact, suggesting that commonality in HFT activity is information-based and so does not generally contribute to undue price pressure and price dislocations.
    Keywords: High-Frequency Trading; Correlated Trading Strategies; Price Discovery
    JEL: G10 G12 G14
    Date: 2016–12
  2. By: Noemi Nava; Tiziana Di Matteo; Tomaso Aste
    Abstract: We measure the influence of different time-scales on the intraday dynamics of financial markets. This is obtained by decomposing financial time series into simple oscillations associated with distinct time-scales. We propose two new time-varying measures of complexity: 1) an amplitude scaling exponent and 2) an entropy-like measure. We apply these measures to intraday, 30-second sampled prices of various stock market indices. Our results reveal intraday trends where different time-horizons contribute with variable relative amplitudes over the course of the trading day. Our findings indicate that the time series we analysed have a non-stationary multifractal nature with predominantly persistent behaviour at the middle of the trading session and anti-persistent behaviour at the opening and at the closing of the session. We demonstrate that these patterns are statistically significant, robust, reproducible and characteristic of each stock market. We argue that any modelling, analytics or trading strategy must take into account these non-stationary intraday scaling patterns.
    JEL: F3 G3
    Date: 2016–10–26
  3. By: Linlin Ye
    Abstract: This paper investigates the impact of dark pools on price discovery (the efficiency of prices on stock exchanges to aggregate information). Assets are traded in either an exchange or a dark pool, with the dark pool offering better prices but lower execution rates. Informed traders receive noisy and heterogeneous signals about an asset's fundamental. We find that informed traders use dark pools to mitigate their information risk and there is a sorting effect: in equilibrium, traders with strong signals trade in exchanges, traders with moderate signals trade in dark pools, and traders with weak signals do not trade. As a result, dark pools have an amplification effect on price discovery. That is, when information precision is high (information risk is low), the majority of informed traders trade in the exchange hence adding a dark pool enhances price discovery, whereas when information precision is low (information risk is high), the majority of the informed traders trade in the dark pool hence adding a dark pool impairs price discovery. The paper reconciles the conflicting empirical evidence and produces novel empirical predictions. The paper also provides regulatory suggestions with dark pools on current equity markets and in emerging markets.
    Date: 2016–12
  4. By: Bethune, Zachary (University of Virginia); Sultanum, Bruno (Federal Reserve Bank of Richmond); Trachter, Nicholas (Federal Reserve Bank of Richmond)
    Abstract: We study trading in over-the-counter (OTC) markets where agents have heterogeneous and private valuations for assets. We develop a quantitative model in which assets are issued through a primary market and then traded in a secondary OTC market. Then we use data on the US municipal bond market to calibrate the model. We find that the effects of private information are large, reducing asset supply by 20%, trade volume by 80%, and aggregate welfare by 8%. Using the model, we identify two channels through which the information friction harms the economy. First, the distribution of the existing stock of assets is inefficient because some of the efficient trades, which should occur, do not. Second, the total stock of assets is inefficiently low because resale value and liquidity go down due to the information friction. We investigate how much a simple tax/subsidy scheme that spurs issuance of new assets can help mitigate the cost associated with private information and find that it lowers the welfare cost from 8% to approximately 1%.
    Keywords: Decentralized markets; bilateral trade; asset issuance; liquidity; asymmetric information
    JEL: D53 D82 G14
    Date: 2016–12–21
  5. By: Adrian, Tobias (Federal Reserve Bank of New York); Boyarchenko, Nina (Federal Reserve Bank of New York); Shachar, Or (Federal Reserve Bank of New York)
    Abstract: Do regulations decrease dealer incentives to intermediate trades? Using a unique data set of dealer-bond-level transactions, we construct the dealer-specific market liquidity metrics for the U. S. corporate bond market. Unlike prior studies, the transactions that we observe are uncapped in size and include the identity of dealer counterparties to the transaction. The granular nature of our data allows us to link changes in liquidity of individual corporate bonds to dealer transaction activity. We show that, in the full sample, bond-level liquidity is higher when institutions that are active traders in the bond are more levered, have higher trading revenue, have higher liquidity mismatch, are more vulnerable, have lower risk-weighted assets, are less reliant on repo funding, and hold fewer illiquid assets. In the rule implementation period (post January 2014), bonds traded by more vulnerable institutions and institutions with greater liquidity mismatch are less liquid, suggesting that prudential regulations may be having an effect on bond market liquidity.
    Keywords: bond liquidity; regulation; dealer constraints
    JEL: G12 G18 G21
    Date: 2016–12–01

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