This study provides evidence that high-frequency traders (HFTs) identify patterns in past trades and orders that allow them to anticipate and trade ahead of other investors’ order flow. Specifically, ...HFTs’ aggressive purchases and sales lead those of other investors, and this effect is stronger at times when it is more difficult for non-HFTs to disguise their order flow. Consistent with some HFTs being more skilled or more focused on anticipatory strategies, I show that trades from a subset of HFTs consistently predict non-HFT order flow the best. The results are not explained by HFTs reacting faster to news or past returns, by contrarian or trend-chasing behavior by non-HFTs, or by trader misclassification. These findings support the existence of an anticipatory trading channel through which HFTs increase non-HFT trading costs.
This paper was accepted by Karl Diether, finance.
Liquidity suppliers lean against the wind. We analyze whether high-frequency traders (HFTs) lean against large institutional orders that execute through a series of child orders. The alternative is ...HFTs trading with the wind, that is, in the same direction. We find that HFTs initially lean against these orders but eventually change direction and take positions in the same direction for the most informed institutional orders. Our empirical findings are consistent with investors trading strategically on their information. When deciding trade intensity, they seem to trade off higher speculative profits against higher risk of being detected and preyed on by HFTs.
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Smart grids equipped with bi-directional communication flow are expected to provide more sophisticated consumption monitoring and energy trading. However, the issues related to the security and ...privacy of consumption and trading data present serious challenges. In this paper we address the problem of providing transaction security in decentralized smart grid energy trading without reliance on trusted third parties. We have implemented a proof-of-concept for decentralized energy trading system using blockchain technology, multi-signatures, and anonymous encrypted messaging streams, enabling peers to anonymously negotiate energy prices and securely perform trading transactions. We conducted case studies to perform security analysis and performance evaluation within the context of the elicited security and privacy requirements.
This paper proposes bilateral contract networks as a new scalable market design for peer-to-peer energy trading. Coordinating small-scale distributed energy resources to shape overall demand could ...offer significant value to power systems, by alleviating the need for investments in upstream generation and transmission infrastructure, increasing network efficiency and increasing energy security. However, incentivising coordination between the owners of large-scale and small-scale energy resources at different levels of the power system remains an unsolved challenge. This paper introduces real-time and forward markets, consisting of energy contracts offered between generators with fuel-based sources, suppliers acting as intermediaries and consumers with inflexible loads, time-coupled flexible loads and/or renewable sources. For each type of agent, utility-maximising preferences for real-time contracts and forward contracts are derived. It is shown that these preferences satisfy full substitutability conditions essential for establishing the existence of a stable outcome-an agreed network of contracts specifying energy trades and prices, which agents do not wish to mutually deviate from. Important characteristics of energy trading are incorporated, including upstream-downstream energy balance and forward market uncertainty. Full substitutability ensures a distributed price-adjustment process can be used, which only requires local agent decisions and agent-to-agent communication between trading partners.
Markets are different now, transformed by technology and high frequency trading. In this paper, I investigate the implications of these changes for high frequency market microstructure (HFT). I ...describe the new high frequency world, with a particular focus on how HFT affects the strategies of traders and markets. I discuss some of the gaps that arise when thinking about microstructure research issues in the high frequency world. I suggest that, like everything else in the markets, research must also change to reflect the new realities of the high frequency world. I propose some topics for this new research agenda in high frequency market microstructure.
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In response to the flash crashes and market manipulations blamed on high-frequency trading (HFT), algorithms have been brought inside the regulatory perimeter. This paper focuses on the most ...ambitious regulation directed at the practice: the algorithm-tagging rule in the German High-Frequency Trading Act. Fifteen interviews with stakeholders in the Act's implementation serve to reconstruct how regulators defined an algorithm and help pose the question of to what extent regulatory definitions and data need accurately to represent financial practices to be useful. Although tentative in its findings, the research suggests that the algorithm-tagging rule may be providing valuable signals in the noise to trade surveillance officers and having virtuous effects on the cultures of trading firms. The conclusion argues that sociologists of finance should adopt a more balanced approach when evaluating regulatory technologies and heed MacKenzie's 2005 call to open up their black boxes.
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This survey reviews the growing literature on pairs trading frameworks, i.e., relative‐value arbitrage strategies involving two or more securities. Research is categorized into five groups: The ...distance approach uses nonparametric distance metrics to identify pairs trading opportunities. The cointegration approach relies on formal cointegration testing to unveil stationary spread time series. The time‐series approach focuses on finding optimal trading rules for mean‐reverting spreads. The stochastic control approach aims at identifying optimal portfolio holdings in the legs of a pairs trade relative to other available securities. The category “other approaches” contains further relevant pairs trading frameworks with only a limited set of supporting literature. Finally, pairs trading profitability is reviewed in the light of market frictions. Drawing from a large set of research consisting of over 100 references, an in‐depth assessment of each approach is performed, ultimately revealing strengths and weaknesses relevant for further research and for implementation.
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China launched a pilot scheme in March 2010 to lift the ban on short-selling and margin-trading for stocks on a designated list. We find that stocks experience negative returns when added to the ...list. After the ban is lifted, price efficiency increases while stock return volatility decreases. Panel data regressions reveal that intensified short-selling activities are associated with improved price efficiency. Short-sellers trade to eliminate overpricing by selling stocks with higher contemporaneous returns following a downward trend, and their trades predict future returns. In contrast, we find intensified margin-trading activities for stocks with lower contemporaneous returns, and these trades have no return predictive power.
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THE HIGH-FREQUENCY TRADING ARMS RACE Budish, Eric; Cramton, Peter; Shim, John
The Quarterly journal of economics,
11/2015, Volume:
130, Issue:
4
Journal Article
Peer reviewed
Open access
The 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.
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