Batch Auctions Research Articles

Experiments in High-Frequency Trading: Testing the Frequent Batch Auction

We implement a laboratory financial market where traders can access costly technology that reduces communication latency with a remote exchange. In this environment, we conduct a market design study on high-frequency trading: we contrast the performance of the newly proposed Frequent Batch Auction (FBA) against the Continuous Double Auction (CDA), which organizes trades in most exchanges worldwide. Our evidence suggests that, relative to the CDA, the FBA exhibits (1) less predatory trading behavior, (2) lower investments in low-latency communication technology, (3) lower transaction costs, and (4) lower volatility in market spreads and liquidity. We also find that transitory shocks in the environment have substantially greater impact on market dynamics in the CDA than in the FBA.

Too fast or too slow? Determining the optimal speed of financial markets

Market quality is maximized at intermediate batch auction intervals of a few seconds when markets are neither too fast nor too slow and clearing price is near equilibrium

Toward a fully continuous exchange

We propose a new market design for a securities exchange that matches ‘continuous scaled limit orders’. This new order type differs from standard limit orders in two ways. First, orders to buy and sell represent flows of shares over time rather than stocks of shares available for immediate purchase or sale. Second, orders are expressed as continuous piecewise linear functions relating price to quantity rather than step functions defined on a discrete grid of prices and quantities. Continuous scaled limit orders implement Fischer Black’s vision of traders limiting temporary price impact by trading gradually over time. They dramatically lessen the rents high-frequency traders earn from the current market design. The proposal is compatible with frequent batch auctions and random time delays.

A Markov Model of a Limit Order Book: Thresholds, Recurrence, and Trading Strategies

We analyze a tractable model of a limit order book on short time scales, where the dynamics are driven by stochastic fluctuations between supply and demand. We establish the existence of a limiting distribution for the highest bid, and for the lowest ask, where the limiting distributions are confined between two thresholds. We make extensive use of fluid limits to establish recurrence properties of the model. We use the model to analyze various high-frequency trading strategies, and comment on the Nash equilibria that emerge between high-frequency traders when a market in continuous time is replaced by frequent batch auctions.

Front‐Running Scalping Strategies and Market Manipulation: Why Does High‐Frequency Trading Need Stricter Regulation?

AbstractRegulators continue to debate whether high‐frequency trading (HFT) is beneficial to market quality. Using Strongly Typed Genetic Programming (STGP) trading algorithm, we develop several artificial stock markets populated with HFT scalpers and strategic informed traders. We simulate real‐life trading in the millisecond time frame by applying STGP to real‐time and historical data from Apple, Exxon Mobil, and Google. We observe that HFT scalpers front‐run the order flow, resulting in damage to market quality and long‐term investors. To mitigate these negative implications, we propose batch auctions every 30 milliseconds of trading.

A note on the relationship between high-frequency trading and latency arbitrage

We develop three artificial stock markets populated with two types of market participants — HFT scalpers and aggressive high frequency traders (HFTrs). We simulate real-life trading at the millisecond interval by applying Strongly Typed Genetic Programming (STGP) to real-time data from Cisco Systems, Intel and Microsoft. We observe that HFT scalpers are able to calculate NASDAQ NBBO (National Best Bid and Offer) at least 1.5ms ahead of the NASDAQ SIP (Security Information Processor), resulting in a large number of latency arbitrage opportunities. We also demonstrate that market efficiency is negatively affected by the latency arbitrage activity of HFT scalpers, with no countervailing benefit in volatility or any other measured variable. To improve market quality, and eliminate the socially wasteful arms race for speed, we propose batch auctions in every 70ms of trading.

A New Approach to Stock Market Execution

The Financial Markets Group of the Federal Reserve Bank of Chicago has a keen interest in frequent batch auctions as a potential tool to diminish the utility of raw speed in executing trades on electronic financial markets. The Chicago Stock Exchange has received approval from the Securities and Exchange Commission to launch an innovative variant of batch auctions, the CHX SNAP auction. This article describes the CHX SNAP auction concept in great detail. If commercially successful, the CHX SNAP auction would allow institutional traders to leave hidden resting equity orders at the CHX out of the vision of digital traders who might otherwise attempt to profit from such knowledge.

Discrete or Continuous Trading? HFT Competition and Liquidity on Batch Auction Markets

Frequent batch auction (FBA) markets do not necessarily improve liquidity relative to continuous-time trading. HFTs submit quotes that become stale if the market clears before new information becomes public, and may be sniped by other privately-informed HFTs. Less frequent auctions enhance learning by allowing for more public news: liquidity improves. For infrequent enough auctions, a frequency wall emerges as lower adverse selection is offset by lower liquidity demand by impatient traders. Beyond this wall, longer auction intervals do not improve liquidity anymore. However, higher HFT speed stimulates price competition between arbitrageurs, allowing for a lower spread.

The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response *

AbstractThe high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed in a batch auction instead of serially. Our argument has three parts. First, we use millisecond-level direct-feed data from exchanges to document a series of stylized facts about how the continuous market works at high-frequency time horizons: (i) correlations completely break down; which (ii) leads to obvious mechanical arbitrage opportunities; and (iii) competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them. Second, we introduce a simple theory model which is motivated by and helps explain the empirical facts. The key insight is that obvious mechanical arbitrage opportunities, like those observed in the data, are built into the market design—continuous-time serial-processing implies that even symmetrically observed public information creates arbitrage rents. These rents harm liquidity provision and induce a never-ending socially wasteful arms race for speed. Last, we show that frequent batch auctions directly address the flaws of the continuous limit order book. Discrete time reduces the value of tiny speed advantages, and the auction transforms competition on speed into competition on price. Consequently, frequent batch auctions eliminate the mechanical arbitrage rents, enhance liquidity for investors, and stop the high-frequency trading arms race.

Low-Latency Trading and Price Discovery Without Trading: Evidence from The Tokyo Stock Exchange Pre-Opening Period

We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to price discovery in the subsequent opening call auction and the continuous trading session. Our analysis evokes shades of the debate on the switch from the current continuous auction in many markets to a periodic auction, affecting the speed advantage of low-latency traders. We empirically investigate these questions using a unique dataset based on server IDs provided by the Tokyo Stock Exchange (TSE), one of the largest stock markets in the world. Our data allow us to develop a more comprehensive classification of traders than in the prior literature, and to investigate the behavior of the different categories of traders, based on their capability for low-latency trading. We find that, perhaps due to the lack of immediate execution, about three quarters of the low-latency traders do not participate in the pre-opening period, but do participate in and dominate the continuous trading session. Furthermore, we find that the larger presence of low-latency traders in the trading of a stock in the pre-opening period as well as in the continuous session improves the price discovery process. Our results suggest that HFTs may not participate in trading in the periodic batch auction because of a lack of immediate execution, and that this large reduction in HFT participation may impede the quality of price discovery.

Implementation Details for Frequent Batch Auctions: Slowing Down Markets to the Blink of an Eye

Our recent research (Budish, Cramton, and Shim 2013) proposes frequent batch auctions - uniform-price sealed-bid double auctions conducted at frequent but discrete time intervals - as a market design alternative to continuous-time trading in financial markets. This short paper discusses the implementation details of frequent batch auctions. We outline the process flow for frequent batch auctions, discuss a modification to the market design that accommodates market fragmentation and Reg NMS, and discuss the engineering and economic considerations relevant for determining the batch interval. Open questions are discussed throughout.

Liquidity Risk, Speculative Trade, and the Optimal Latency of Financial Markets

How fast should a security trade? To answer this question, we model the trading of a security via periodic batch auctions and study how market quality depends on the clearing frequency of the auctions. In our model, the optimal clearing frequency is determined by four factors: (1) the volatility of the security’s value; (2) the dispersion of investors’ reservation prices; (3) the intensity of trading in the security; and (4) the correlation of the security’s value with other securities. We find that for most parameter values, market quality is maximized at intermediate auction intervals, when markets are neither too fast nor too slow. Based on simulations, we demonstrate that an analogous intermediate time delay is also optimal for order placements in continuous double auction markets. Finally, using proxies of the model parameters, we estimate that the ideal clearing interval for a typical S&P 500 stock is on the order of a few seconds currently, compared with several minutes in the 1990s.

The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response

The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book (CLOB) that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, e.g., every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed in a batch auction instead of serially. Our argument has three parts. First, we use millisecond-level direct-feed data from exchanges to document a series of stylized facts about how the CLOB market design works at high-frequency time horizons: (i) correlations completely break down; which (ii) leads to obvious mechanical arbitrage opportunities; and (iii) competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them. Second, we introduce a simple theory model which is motivated by, and helps explain, the empirical facts. The key insight is that obvious mechanical arbitrage opportunities, like those observed in the data, are built into the CLOB market design – continuous-time serialprocessing implies that even symmetrically observed public information creates arbitrage rents. These rents harm liquidity provision and induce a never-ending socially-wasteful arms race for speed. Last, we show that frequent batch auctions directly address the problems caused by the CLOB. Discrete time reduces the value of tiny speed advantages, and the auction transforms competition on speed into competition on price. Consequently, frequent batch auctions eliminate the mechanical arbitrage rents, enhance liquidity for investors, and stop the high-frequency trading arms race.

Simple market protocols for efficient risk sharing

This paper studies the performance of four market protocols with regard to allocative efficiency and other performance criteria such as volume or volatility. We examine batch auctions, continuous double auctions, specialist dealerships, and a hybrid of these last two. All protocols are practically implementable because the messages that traders need to use are simple. We test the protocols by running (computerized) experiments in an environment that controls for traders’ behavior and rules out any informational effect. We find that all protocols generically converge to the efficient allocation in finite time. An extended comparison over other performance criteria produces no clear winner, but the presence of a specialist is associated with the best all-round performance.

A comparison of different trading protocols in an agent-based market

We compare price dynamics of different market protocols (batch auction, continuous double auction and dealership) in an agent-based artificial exchange. In order to distinguish the effects of market architectures alone, we use a controlled environment where allocative and informational issues are neglected and agents do not optimize or learn. Hence, we rule out the possibility that the behavior of traders drives the price dynamics. Aiming to compare price stability and execution quality in broad sense, we analyze standard deviation, excess kurtosis, tail exponent of returns, volume, perceived gain by traders and bid-ask spread. Overall, a dealership market appears to be the best candidate, generating low volume and volatility, virtually no excess kurtosis and high perceived gain.

Institutional architectures and behavioral ecologies in the dynamics of financial markets

The paper examines the properties of financial market dynamics, under different trading protocols. We start with an empirical analysis of the statistical properties of daily data from the world’s major Stock Exchanges, comparing the behavior of different market phases characterized by different trading protocols. The evidence lends support to the importance of investigating the outcome of alternative market mechanisms. Motivated by this finding, we present an agent-based model allowing the consistent treatment of agents’ behavior under three different trading set-ups, namely a Walrasian auction, a batch auction and an ‘order-book’ mechanism. The results highlight the importance of the institutional setting in shaping the dynamics of the market but also suggest that the latter can become the outcome of a complicated interaction between the trading protocol and the ecology of traders behaviors. In particular, we show that market architectures bear a central influence upon the time series properties of market dynamics. Conversely, the revealed allocative efficiency of different market settings is strongly influenced by the trading behavior of agents.

A Theoretical Analysis of Institutional Investors’ Trading Costs in Auction and Dealer Markets

This paper compares trading costs for institutional investors subject to liquidity shocks, in auction and dealer markets. The batch auction restricts the institutions’ ability to exploit informational advantages because of competition between institutions when they simultaneously submit orders. This competition lowers aggregate trading costs. In the dealership market, competition between traders is absent but private information is revealed by observing the flow of successive orders and so reduces aggregate trading costs. We analyse the relative effects on trading costs of competition and information revelation in the two systems and derive a parameter inequality which determines which system has lower costs.

Strategic Market Making in a Batch Auction

Strategic Market Making in a Batch Auction

Trading Systems in European Stock Exchanges: Current Performance and Policy Options

Stock markets Marco Pagano and Ailsa Roell The deregulation of financial markets and the liberalization of international capital flows raises a number of challenging issues. Market participants and policy-makers are treading largely uncharted territories. This article offers some markers, exploring the implications of economic principles and producing new evidence on European stock exchanges. One vast set of issues concerns the design of market operations. The article compares the merits, both in theory and in practice, of auctions versus market-making, of concentration versus fragmentation of trading, of batch auctions versus continuous markets and of single- versus dual-capacity dealers. Policy conclusions are grounded on a detailed analysis of the experience accumulated on European and North American exchanges. Another theme runs through this article: the implications for the relative competitiveness of European financial markets. Rapid changes have already occurred in the late 1980s: while much wholesale trade has moved to London, continental exchanges have grown at an accelerated pace. We examine whether this is connected to innovations in trading systems and regulation. The paper also attempts to foresee the geographical structure of Europe's integrated stock markets. At stake is the hierarchy of financial centres, the potentially dangerous drift towards competitive deregulation and the scope for wholly computerized trading where market location becomes irrelevant.