nep-mst New Economics Papers
on Market Microstructure
Issue of 2020‒06‒22
seven papers chosen by
Thanos Verousis

  1. A Theory of 'Auction as a Search' in speculative markets By Sudhanshu Pani
  2. Trading on Long-term Information By Corey Garriot; Ryan Riordan
  3. Stock Return Comovement when Investors are Distracted: More, and More Homogeneous By Ehrmann, Michael; Jansen, David-Jan
  4. Trading for Bailouts By Toni Ahnert; Caio Machado; Ana Elisa Pereira
  5. Market Fragmentation By Chen, Daniel; Duffie, Darrell
  6. Generating Realistic Stock Market Order Streams By Junyi Li; Xitong Wang; Yaoyang Lin; Arunesh Sinha; Micheal P. Wellman
  7. Market Making and Proprietary Trading in the US Corporate Bond Market By Hugues Dastarac

  1. By: Sudhanshu Pani
    Abstract: The tatonnement process in high frequency order driven markets is modeled as a search by buyers for sellers and vice-versa. We propose a total order book model, comprising limit orders and latent orders, in the absence of a market maker. A zero intelligence approach of agents is employed using a diffusion-drift-reaction model, to explain the trading through continuous auctions (price and volume). The search (levy or brownian) for transaction price is the primary diffusion mechanism with other behavioural dynamics in the model inspired from foraging, chemotaxis and robotic search. Analytic and asymptotic analysis is provided for several scenarios and examples. Numerical simulation of the model extends our understanding of the relative performance between brownian, superdiffusive and ballistic search in the model.
    Date: 2020–06
  2. By: Corey Garriot; Ryan Riordan
    Abstract: Predatory trading discourages informed investors from gathering information and trading on it. However, using 11 years of equity trading data, we do not find evidence that informed investors are being discouraged. They have roughly constant volumes and profits through the sample. They are sophisticated, trading patiently over weeks and timing their trading to achieve negative price impacts, leaving price efficiency unchanged. We identify shorter-term traders and, in contrast to theory, find that they supply liquidity by trading in the opposite direction of the informed. Inefficient prices may be the result of informed investors' sophisticated trading and not of predatory short-term trading.
    Keywords: Financial institutions; Financial markets; Market structure and pricing
    JEL: G20 L1
    Date: 2020–06
  3. By: Ehrmann, Michael; Jansen, David-Jan
    Abstract: This paper tests whether fluctuations in investors' attention affect stock return comovement with national and global markets, and which stocks are most affected. We measure fluctuations in investor attention using 59 high-profile soccer matches played during stock market trading hours at the three editions of the FIFA World Cup between 2010 and 2018. Using intraday data for more than 750 firms in 19 countries, we find that distracted investors shift attention away from firm-specific and from global news. When movements in global stock markets are large, the pricing of global news reverts back to normal, but firm-specific news keep being priced less, leading to increased comovement of stock returns with the national stock market. This increase is economically large, and particularly strong for those stocks that typically comove little with the national market, thereby leading to a convergence in betas across stocks.
    Keywords: comovement; investor attention; Stock returns
    JEL: G12 G15
    Date: 2020–05
  4. By: Toni Ahnert; Caio Machado; Ana Elisa Pereira
    Abstract: Government interventions such as bailouts are often implemented in times of high uncertainty. Policymakers may therefore rely on information from financial markets to guide their decisions. We propose a model in which a policymaker learns from market activity and where market participants have high stakes in the intervention. We study how the strategic behavior of informed traders affects market informativeness, the probability and efficiency of bailouts, and stock prices. We apply the model to study the liquidity support of distressed banks and derive implications for market informativeness and policy design. Commitment to a minimum liquidity support can increase market informativeness and welfare.
    Keywords: Financial institutions, Financial markets, Financial system regulation and policies, Lender of last resort
    JEL: D83 G18
    Date: 2020–06
  5. By: Chen, Daniel (Stanford U); Duffie, Darrell (Stanford U)
    Abstract: We model a simple market setting in which fragmentation of trade of the same asset across multiple exchanges improves allocative efficiency. Fragmentation reduces the inhibiting effect of price-impact avoidance on order submission. Although fragmentation reduces market depth on each exchange, it also isolates cross-exchange price impacts, leading to more aggressive overall order submission and better rebalancing of unwanted positions across traders. Fragmentation also has implications for the extent to which prices reveal traders' private information. While a given exchange price is less informative in more fragmented markets, all exchange prices taken together are more informative.
    JEL: D47 D82 G14
    Date: 2020–02
  6. By: Junyi Li; Xitong Wang; Yaoyang Lin; Arunesh Sinha; Micheal P. Wellman
    Abstract: We propose an approach to generate realistic and high-fidelity stock market data based on generative adversarial networks (GANs). Our Stock-GAN model employs a conditional Wasserstein GAN to capture history dependence of orders. The generator design includes specially crafted aspects including components that approximate the market's auction mechanism, augmenting the order history with order-book constructions to improve the generation task. We perform an ablation study to verify the usefulness of aspects of our network structure. We provide a mathematical characterization of distribution learned by the generator. We also propose statistics to measure the quality of generated orders. We test our approach with synthetic and actual market data, compare to many baseline generative models, and find the generated data to be close to real data.
    Date: 2020–06
  7. By: Hugues Dastarac
    Abstract: I study broker-dealers' trading activity in the US corporate bond market. I find evidence of broker-dealer market making when customers both buy and sell a bond in a day, which happens half of the time: as predicted by market making theories with adverse selection or inventory costs, prices go down (up) as customers sell (buy). Otherwise, evidence is in favor of proprietary trading as in limits of arbitrage theories: prices go up (down) when customers sell (buy), and dealers buy (sell) bonds that are relatively cheap (expensive). Proprietary trading is reduced after the crisis. Relatedly I show that before the crisis, large broker-dealers borrowed and sold Treasury bonds in amounts similar to their corporate bond holding, but not after. I give suggestive evidence that they were subject to a severe tightening of their margin constraints as early as July 2007, in particular following increased Treasury bond volatility.
    Keywords: : Credit Spreads, Dealer behavior, corporate bonds, limits of arbitrage, Volcker rule.
    JEL: G20
    Date: 2020

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