nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒08‒13
ten papers chosen by
Thanos Verousis

  1. Directed Continuous-Time Random Walk with memory By Jaros{\l}aw Klamut; Tomasz Gubiec
  2. First to "Read" the News: New Analytics and Algorithmic Trading By Bastian von Beschwitz; Donald B. Keim; Massimo Massa
  3. Market-making with Search and Information Frictions By Lester, Benjamin; Shourideh, Ali; Venkateswaran, Venky; Zetlin-Jones, Ariel
  4. Trading Cointegrated Assets with Price Impact By Alvaro Cartea; Luhui Gan; Sebastian Jaimungal
  5. Discriminatory Pricing of Over-the-Counter Derivatives By Harald Hau; Peter Hoffmann; Sam Langfield; Yannick Timmer
  6. Algorithmic Trading and Liquidity: Long Term Evidence from Austria By Roland Mestel; Michael Murg; Erik Theissen
  7. Fragmentation and Strategic Market-Making By Laurence Daures Lescourret; Sophie Moinas
  8. Decentralized Exchange By Semyon Malamud; Marzena J. Rostek
  9. Banks’ Trading after the Lehman Crisis – The Role of Unconventional Monetary Policy By Isabel Schnabel; Johannes Tischer
  10. Optimal Portfolio in Intraday Electricity Markets Modelled by L\'evy-Ornstein-Uhlenbeck Processes By Marco Piccirilli; Tiziano Vargiolu

  1. By: Jaros{\l}aw Klamut; Tomasz Gubiec
    Abstract: We propose a new Directed Continuous-Time Random Walk (CTRW) model with memory. As CTRW trajectory consists of spatial jumps preceded by waiting times, in Directed CTRW, we consider the case with only positive spatial jumps. Moreover, we consider the memory in the model as each spatial jump depends on the previous one. Our model is motivated by the financial application of the CTRW presented in [Phys. Rev. E 82:046119][Eur. Phys. J. B 90:50]. As CTRW can successfully describe the short term negative autocorrelation of returns in high-frequency financial data (caused by the bid-ask bounce phenomena), we asked ourselves to what extent the observed long-term autocorrelation of absolute values of returns can be explained by the same phenomena. It turned out that the bid-ask bounce can be responsible only for the small fraction of the memory observed in the high-frequency financial data.
    Date: 2018–07
  2. By: Bastian von Beschwitz; Donald B. Keim; Massimo Massa
    Abstract: Exploiting a unique identification strategy based on inaccurate news analytics, we document a causal effect of news analytics on the market irrespective of the informational content of the news. We show that news analytics speed up the stock price and trading volume response to articles, but reduce liquidity. Inaccurate news analytics lead to small price distortions that are corrected quickly. The market impact of news analytics is greatest for press releases, which are timelier and easier to interpret algorithmically. Furthermore, we provide evidence that high frequency traders rely on the information from news analytics for directional trading on company-specific news.
    Keywords: Stock Price Reaction ; News Analytics ; High Frequency Trading ; Press Releases
    JEL: G10 G12 G14
    Date: 2018–07
  3. By: Lester, Benjamin (Federal Reserve Bank of Philadelphia); Shourideh, Ali (Carnegie Mellon University); Venkateswaran, Venky (NYU Stern School of Business); Zetlin-Jones, Ariel (Federal Reserve Bank of Philadelphia)
    Abstract: We develop a dynamic model of trading through market-makers that incorporates two canonical sources of illiquidity: trading (or search) frictions, which imply that market-makers have some amount of market power; and information frictions, which imply that market-makers face some degree of adverse selection. We use this model to study the effects of various technological innovations and regulatory initiatives that have reduced trading frictions in over-the-counter markets. Our main result is that reducing trading frictions can lead to less liquidity, as measured by bid-ask spreads. The key insight is that more frequent trading—or more competition among dealers—makes traders’ behavior less dependent on asset quality. As a result, dealers learn about asset quality more slowly and set wider bid-ask spreads to compensate for this increase in uncertainty.
    Keywords: Adverse selection; trading frictions; bid-ask spreads; liquidity; learning
    Date: 2018–07–19
  4. By: Alvaro Cartea; Luhui Gan; Sebastian Jaimungal
    Abstract: Executing a basket of co-integrated assets is an important task facing investors. Here, we show how to do this accounting for the informational advantage gained from assets within and outside the basket, as well as for the permanent price impact of market orders (MOs) from all market participants, and the temporary impact that the agent's MOs have on prices. The execution problem is posed as an optimal stochastic control problem and we demonstrate that, under some mild conditions, the value function admits a closed-form solution, and prove a verification theorem. Furthermore, we use data of five stocks traded in the Nasdaq exchange to estimate the model parameters and use simulations to illustrate the performance of the strategy. As an example, the agent liquidates a portfolio consisting of shares in Intel Corporation (INTC) and Market Vectors Semiconductor ETF (SMH). We show that including the information provided by three additional assets, FARO Technologies (FARO), NetApp (NTAP) and Oracle Corporation (ORCL), considerably improves the strategy's performance; for the portfolio we execute, it outperforms the multi-asset version of Almgren-Chriss by approximately 4 to 4.5 basis points.
    Date: 2018–07
  5. By: Harald Hau (University of Geneva, Swiss Finance Institute, Centre for Economic Policy Research (CEPR), and CESifo (Center for Economic Studies and Ifo Institute)); Peter Hoffmann (European Central Bank (ECB); Sam Langfield (European Central Bank); Yannick Timmer (Trinity College (Dublin))
    Abstract: New regulatory data reveal extensive discriminatory pricing in the foreign exchange derivatives market, in which dealer-banks and their non-financial clients trade over-the-counter. After controlling for contract characteristics, dealer fixed effects, and market conditions, we find that the client at the 75th percentile of the spread distribution pays an average of 30 pips over the market mid-price, compared to competitive spreads of less than 2.5 pips paid by the bottom 25% of clients. Higher spreads are paid by less sophisticated clients. However, trades on multi-dealer request-for-quote platforms exhibit competitive spreads regardless of client sophistication, thereby eliminating discriminatory pricing.
    Keywords: Dealer spreads, information rents, RFQ platforms, corporate hedging
    JEL: G14 G18 D4
    Date: 2018–01
  6. By: Roland Mestel (Institute of Banking and Finance, Karl-Franzens-University Graz); Michael Murg (Institute of Banking and Insurance, University of Applied Sciences FH Joanneum); Erik Theissen (Institute of Banking and Finance, University of Graz; Finance Area, University of Mannheim)
    Abstract: We analyze the relation between algorithmic trading and liquidity using a novel data set from the Austrian equity market. Our sample covers almost 4.5 years, it identifies the market share of algorithmic trading at the stock-day level, and it comes from a market that has hitherto not been analyzed. We address the endogeneity problem using an instrumental variables approach. Our results indicate that an increase in the market share of algorithmic trading causes a reduction in quoted and effective spreads while quoted depth and price impacts are unaffected. They are consistent with algorithmic traders on average acting as market makers.
    Date: 2018–01–04
  7. By: Laurence Daures Lescourret; Sophie Moinas
    Abstract: Information technology, infrastructure enhancement, and arbitrage strategies all contributeto link trading venues in fragmented markets. Our paper highlights a new cross-market linking channel: the interdependence of liquidity providers' inventory costs. We use a two-venue duopoly model involving strategic risk-averse market-makers. Costs to provide immediacy depend on market-makers' inventory aggregated across venues, implying that absorbing a shock in one venue simultaneously changes marginal costs in all other venues. Moreover, market-makers strategically choose which shock(s) to absorb. These two forces may lead to competitive prices and enhanced liquidity. Using Euronext proprietary data, we uncover evidence for these crossmarket inventory cost linkages.
    Date: 2018
  8. By: Semyon Malamud (Ecole Polytechnique Federale de Lausanne, Centre for Economic Policy Research (CEPR), and Swiss Finance Institute); Marzena J. Rostek (University of Wisconsin)
    Abstract: Most assets are traded in multiple interconnected trading venues. This paper develops an equilibrium model of decentralized markets that accommodates general market structures with coexisting exchanges. Decentralized markets can allocate risk among traders with different risk preferences more efficiently, thus realizing gains from trade that cannot be reproduced in centralized markets. Market decentralization always increases price impact. Yet, markets in which assets are traded in multiple exchanges, whether they are disjoint or intermediated, can give higher welfare than the centralized market with the same traders and assets. In decentralized markets, demand substitutability across assets is endogenous and heterogeneous among traders.
    JEL: D43 D44 D85 G11 G12
    Date: 2018–03
  9. By: Isabel Schnabel; Johannes Tischer
    Abstract: Based on a unique trade-level dataset, we analyze the proprietary trading reaction of German banks to the Lehman collapse and the subsequent unconventional monetary policy measures in 2008. After the Lehman collapse, we observe that market liquidity tightened. However, there is no evidence of broad-based fire sales in the German banking sector. Instead, we observe a flight to liquidity. The European Central Bank’s unconventional measures had a strong impact on banks’ trading behavior by inducing shifts towards eligible securities and reducing pressure on market liquidity. This suggests that the unconventional measures helped stabilizing the financial system after the Lehman collapse.
    Keywords: Proprietary trading, fire sales, flight to liquidity, Lehman crisis, market liquidity, unconventional monetary policy
    JEL: E44 E50 G01 G11 G21
    Date: 2018–08
  10. By: Marco Piccirilli; Tiziano Vargiolu
    Abstract: We study an optimal portfolio problem designed for an agent operating in intraday electricity markets. The investor is allowed to trade in a single risky asset modelling the continuously traded power and aims to maximize the expected terminal utility of his wealth. We assume a mean-reverting additive process to drive the power prices. In the case of logarithmic utility, we reduce the fully non-linear Hamilton-Jacobi-Bellman equation to a linear parabolic integro-differential equation, for which we explicitly exhibit a classical solution in two cases of modelling interest. The optimal strategy is given implicitly as the solution of an integral equation, which is possible to solve numerically as well as to describe analytically. An analysis of two different approximations for the optimal policy is provided. Finally, we perform a numerical test by adapting the parameters of a popular electricity spot price model.
    Date: 2018–07

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