nep-mst New Economics Papers
on Market Microstructure
Issue of 2023‒06‒19
eight papers chosen by
Thanos Verousis

  1. The Effects of Volatility on Liquidity in the Treasury Market By Andrew C. Meldrum; Oleg Sokolinskiy
  2. Optimal liquidation under indirect price impact with propagator By Dupret, Jean-Loup; Hainaut, Donatien
  3. The effect of funding liquidity regulation and ESG promotion on market liquidity By Judit Hevér; Péter Csóka
  4. Competing for Dark Trades By Paul J. Irvine; Egle Karmaziene
  5. Why Fixed-Price Policy Prevails: The Effect of Trade Frictions and Competition By Selcuk, Cemil
  6. Retail Investors’ Disposition Effect and Order Choices By De Winne, Rudy; Luong, Nhung; Palan, Stefan
  7. Trade among moral agents with information asymmetries By José Ignacio Rivero Wildemauwe
  8. Algorithmic trading and investment-to-price sensitivity By Aliyev, Nihad; Huseynov, Fariz; Rzayev, Khaladdin

  1. By: Andrew C. Meldrum; Oleg Sokolinskiy
    Abstract: We study the relationship between volatility and liquidity in the market for on-the-run Treasury securities using a novel framework for quantifying price impact. We show that at times of relatively low volatility, marginal trades that go with the flow of existing trades tend to have a smaller price impact than trades that go against the flow. However, this difference tends to diminish at times of high volatility, indicating that the perceived information content of going against the flow is less when volatility is high. We also show that market participants executing trades aggressively using market orders will experience larger increases in price impact than those executing trades passively using limit orders as volatility increases. And times of low market depth are associated with increased risk of high price impact and high sensitivity to volatility in future, perhaps because liquidity is more reliant on high-speed quote replenishment and is therefore more fragile.
    Keywords: Liquidity; Treasury market; Market depth; Volatility; Order execution; Hidden Markov model
    JEL: G01 G10 G12 C51 C58
    Date: 2023–05–05
  2. By: Dupret, Jean-Loup (Université catholique de Louvain, LIDAM/ISBA, Belgium); Hainaut, Donatien (Université catholique de Louvain, LIDAM/ISBA, Belgium)
    Abstract: We propose in this paper a new framework of optimal liquidation strategies for a trader seeking to liquidate his large inventory based on a jump-dependent price impact model with propagator. This new jump-dependent price impact model allows to best reproduce the empirical direct and indirect effects of market orders on the transaction price. More precisely, different choices of propagators are proposed and their implications in terms of temporary, permanent and transient impacts on the transaction price are discussed. For each choice of such kernels, we formulate the most relevant optimal liquidation problem faced by the trader, derive explicitly the related Hamilton-Jacobi-Bellman equation and solve it numerically. Moreover, we show how to extend our price impact model so to include the possibility for the trader to also use limit orders. We hence manage in this paper to propose an alternative more realistic and flexible description of the order book’s dynamic and to make a bridge between high-frequency price models and optimal liquidation problems.
    Keywords: Optimal liquidation ; HJB equation ; Price impact model ; Market impact ; High-frequency trading
    Date: 2023–04–05
  3. By: Judit Hevér (Central Bank of Hungary); Péter Csóka (Institute of Finance, Corvinus University of Budapest, Centre for Economic and Regional Studies)
    Abstract: Liquidity is a key consideration in financial markets, especially in times of financial crises. For this reason, regulatory attention to and measures in this field have been on the rise for the past years. Based on practical experience, regulations aiming at ensuring funding liquidity or, in general, reducing certain risky positions have the side effect of reducing market liquidity. To understand this effect, we extend a standard general equilibrium model with transaction costs of trading, endogenous market liquidity, and the modeling of regulation. We prove that funding liquidity regulation or divesting bad ESG assets reduces market liquidity.
    Keywords: market liquidity, funding liquidity, general equilibrium model, regulatory requirement, ESG related assets
    JEL: G11
    Date: 2023–03
  4. By: Paul J. Irvine (Egle Karmaziene); Egle Karmaziene (Vrije Universiteit Amsterdam)
    Abstract: We use recent European restrictions to evaluate how traders substitute across available dark pools. Our findings suggest that restricting dark trading at the most prominent platform has a detrimental effect on dark trading activity. Annual dark trading in a restricted stock decreases by more than 50% over the six-month restriction period. Consistent with investors’ sticky relationships with specific dark pools, our results suggest that substitution across dark pools is remarkably low. Despite the availability of alternative dark pools, traders are unwilling to trade elsewhere. Our study provides evidence that dark trading is not a market of exchanges, but rather a collection of independent silos. This fact has implications for the vulnerability of dark trading to the introduction of an HFT into the pool, and sharpens our understanding of how the pecking order theory of trading actually functions.
    Keywords: MiFID II, dark pool trading, competition
    JEL: G12 G14 G18 D47
    Date: 2023–04–25
  5. By: Selcuk, Cemil (Cardiff Business School)
    Abstract: Fixed-price selling is common in todayís markets. While previous research in marketing and economics literatures provide several intuitive reasons for the emergence of fixed-price selling (e.g. clarity and simplicity of managing the fixed-price process, reduced coordination and information costs) our study offers an entirely different rationale —— based on market competition and trade frictionsó that explains the prevalence of fiixed-price selling. Using a market equilibrium approach, and employing a novel competitive search framework to account for a fully competitive and dynamic market, we offer a new and micro-founded account for the widespread use of fixed pricing policy. Considering three important market characteristics—— customer risk aversion, the degree of trade frictions and the level of market competition —— we explore the strategic choice between the fixed-price, best-offer, and over-the-sticker pricing policies. Unlike the standard models in the literature, which are based Hotelling, Cournot, Bertrand frameworks, the competitive search framework enables us to model competition with a large number of buyers and sellers, and to vary the degree of competition accordingly. We find that fixed pricing emerges as the unique or the de-facto selling rule in most parameter regions. Indeed, the only region where haggling matters is the case in which customers are risk neutral and trade frictions are significant and market competition is moderate
    Keywords: fixed-price selling, haggling, risk aversion, trade friction, competition
    Date: 2023–05
  6. By: De Winne, Rudy (Université catholique de Louvain, LIDAM/LFIN, Belgium); Luong, Nhung (Université catholique de Louvain, LIDAM/LFIN, Belgium); Palan, Stefan (University of Graz)
    Abstract: Retail investors are prone to the disposition effect and submit many more limit orders than market orders. Mechanical effects stemming from the price-contingency conditions for order executions can lead these limit orders to inflate an investor’s measured disposition effect (Linnainmaa 2010). Our paper is the first to demonstrate that the relationship between the disposition effect and order choices is bi-directional. Using a controlled experiment on the one hand and empirical trading data of thousands of investors on the other hand, we show that investors who are prone to the disposition effect differ from others in their use of limit orders and in their choice of limit prices.
    Keywords: Disposition effect ; order choice ; limit orders ; retail investors ; behavioral finance
    Date: 2022–05–14
  7. By: José Ignacio Rivero Wildemauwe (Université de Cergy-Pontoise, THEMA)
    Abstract: This research builds an integrated chain of models to compute the economic costs of population Two agents trade an item in a simultaneous offer setting, where the exchange takes place if and only if the buyer’s bid price weakly exceeds the seller’s ask price. Each agent is randomly assigned the buyer or seller role. Both agents are characterized by a certain degree of Kantian morality, whereby they pick their bidding strategy behind a veil of ignorance, taking into account how the outcome would be affected if their trading partner were adopting their strategy. I consider two variants with asymmetric information, respectively allowing buyers to have private information about their valuation or sellers to be privately informed about the item’s quality. I show that when all trades are socially desirable, even the slightest degree of morality guarantees that the outcome is fully efficient. In turn, when quality is uncertain and some exchanges are socially undesirable, full efficiency is only achieved with sufficiently high moral standards. Moral concerns also ensure equal ex-ante treatment of the two agents in equilibrium. Finally, I show that if agents are altruistic rather than moral, inefficiencies persist even with a substantial degree of altruism.
    Keywords: bilateral trade; altruism; homo moralis.
    JEL: D03 D82 D91 C78
    Date: 2023
  8. By: Aliyev, Nihad; Huseynov, Fariz; Rzayev, Khaladdin
    Abstract: Does the increased prevalence of algorithmic trading (AT) produce real economic effects? We find that AT contributes to managerial learning by fostering the production of new information and thereby increases firms' investment-to-price sensitivity. We link AT's impact on the investment-to-price sensitivity to the revelatory price efficiency - extent to which stock prices reveal information for real efficiency. AT-driven investment-to-price sensitivity helps managers make better investment decisions, leading to improved firm performance. While in aggregate AT contributes positively to managerial learning, we also show that there is a subset of AT strategies, namely opportunistic AT that is harmful to managerial learning.
    Keywords: algorithmic trading; real effects of algorithmic trading; revelatory price efficiency; investment-to-price sensitivity
    JEL: G20 G30
    Date: 2022–09–02

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