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on Market Microstructure |
| By: | Peter Kondor (London School of Economics); Gabor Pinter (Bank of England) |
| Abstract: | In government bond markets the number of dealers with whom clients trade changes through time. Our paper shows that this time-variation in clients’ connections serves as a proxy for time-variation in private information. Using proprietary data covering close to all dealer-client transactions in the UK government bond market, we show that clients have systematically better performance when trading with more dealers, and this effect is stronger during macroeconomic announcements. Most of the effect comes from clients’ increased ability to predict future yield changes (anticipation component) rather than these clients facing tighter bid-ask spreads (transaction component). To explore the nature of this private information, we find that clients with increased dealer connections can better predict the fraction of the aggregate order flow that is intermediated by dealers they regularly trade with. Positive trading performance is concentrated in those periods when clients have more dealer connections than usual. |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed019:126&r=all |
| By: | Carlo Campajola; Fabrizio Lillo; Daniele Tantari |
| Abstract: | We propose a method to infer lead-lag networks of traders from the observation of their trade record as well as to reconstruct their state of supply and demand when they do not trade. The method relies on the Kinetic Ising model to describe how information propagates among traders, assigning a positive or negative ``opinion" to all agents about whether the traded asset price will go up or down. This opinion is reflected by their trading behavior, but whenever the trader is not active in a given time window, a missing value will arise. Using a recently developed inference algorithm, we are able to reconstruct a lead-lag network and to estimate the unobserved opinions, giving a clearer picture about the state of supply and demand in the market at all times. We apply our method to a dataset of clients of a major dealer in the Foreign Exchange market at the 5 minutes time scale. We identify leading players in the market and define a herding measure based on the observed and inferred opinions. We show the causal link between herding and liquidity in the inter-dealer market used by dealers to rebalance their inventories. |
| Date: | 2019–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1909.10807&r=all |
| By: | Torben G. Andersen; Martin Thyrsgaard; Viktor Todorov |
| Abstract: | We study the temporal behavior of the cross-sectional distribution of assets' market exposure, or betas, using a large panel of high-frequency returns. The asymptotic setup has the sampling frequency of the returns increasing to infinity, while the time span of the data remains fixed, and the cross-sectional dimension is fixed or increasing. We derive a Central Limit Theorem (CLT) for the cross-sectional beta dispersion at a point in time, enabling us to test whether this quantity varies across the trading day. We further derive a functional CLT for the dispersion statistics, allowing us to test if the beta dispersion, as a function of time-of-day, changes across days. We extend this further by developing inference techniques for the entire cross-sectional beta distribution at fixed points in time. We demonstrate, for constituents of the S&P 500 index, that the beta dispersion is elevated at the market open, gradually declines over the trading day, and is less than half the original value by the market close. The intraday beta dispersion pattern also changes over time and evolves differently on macroeconomic announcement days. Importantly, we find that the intraday variation in market betas is a source of priced risk. |
| JEL: | C51 C52 G12 |
| Date: | 2019–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26329&r=all |
| By: | Angerer, Martin; Neugebauer, Tibor; Shachat, Jason |
| Abstract: | While algorithmic trading robots are a proliferating presence in asset markets, there is no consensus whether their presence improves market quality or benefits individual investors. We examine the impact of robots seeking arbitrage in experimental laboratory markets. We find that the presence of algorithmic arbitrageurs generally enhances market quality. However, the wealth of human traders suffers from the presence of algorithmic traders. These social costs can be mitigated as we find high latency algorithms harm investors less than low latency algorithms; while the improvements in market quality are indistinguishable between algorithm latency levels and whether they provide liquidity or not. |
| Keywords: | asset market experiment, arbitrage, algorithmic trading |
| JEL: | C92 G12 |
| Date: | 2019–06–29 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:96224&r=all |
| By: | Meraj Allahrakha (Office of Financial Research); Jill Cetina (Federal Reserve Bank of Dallas); Benjamin MUnyan (Vanderbilt University, Office of Financial Research); Sumudu Watugala (Cornell University, Office of Financial Research) |
| Abstract: | Using a novel within-dealer, within-security identification strategy, we examine intended and unintended effects of the Volcker rule on covered firms’ corporate bond trading using dealer-identified regulatory data. We use the underwriting exemption to isolate the Volcker rule’s effects separate from other post-crisis changes in bank regulation and broader trends in market liquidity. We find no evidence of the rule’s intended reduction in the riskiness of covered firms’ trading in corporate bonds. We find significant adverse liquidity effects on covered firms’ corporate bond trading with 20-45 basis points higher costs for customers even for roundtrip trades of shorter duration. These effects do not appear to be transitional. The Volcker rule appears to have increased the cost of the liquidity provided by covered firms and has not decreased the liquidity risk exposure of covered firms. Finally, the Volcker rule has decreased the market share of covered firms. Customers appear to be trading more with non-bank dealers, who are exempt from the Volcker rule but also lack access to emergency liquidity support at the Fed’s discount window. |
| Keywords: | banking regulation, Volcker rule, heightened prudential regulation, corporate bonds, market liquidity, regulatory impact analysis |
| Date: | 2019–08–06 |
| URL: | http://d.repec.org/n?u=RePEc:ofr:wpaper:19-02&r=all |
| By: | Vasilios Mavroudis; Hayden Melton |
| Abstract: | While historically, economists have been primarily occupied with analyzing the behaviour of the markets, electronic trading gave rise to a new class of unprecedented problems associated with market fairness, transparency and manipulation. These problems stem from technical shortcomings that are not accounted for in the simple conceptual models used for theoretical market analysis. They, thus, call for more pragmatic market design methodologies that consider the various infrastructure complexities and their potential impact on the market procedures. First, we formally define temporal fairness and then explain why it is very difficult for order-matching policies to ensure it in continuous markets. Subsequently, we introduce a list of system requirements and evaluate existing "fair" market designs in various practical and adversarial scenarios. We conclude that they fail to retain their properties in the presence of infrastructure inefficiencies and sophisticated technical manipulation attacks. Based on these findings, we then introduce Libra, a "fair" policy that is resilient to gaming and tolerant of technical complications. Our security analysis shows that it is significantly more robust than existing designs, while Libra's deployment (in a live foreign currency exchange) validated both its considerably low impact on the operation of the market and its ability to reduce speed-based predatory trading. |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1910.00321&r=all |