Ricky Alyn Cooper

Whole Distribution Statistical Process Control in High Frequency Trading

High-frequency trading enables real-time control of outputs. However, sampling techniques in traditional statistical process control (SPC) may be too slow to detect rapid changes in market structure. The authors develop statistical tests that examine each event using the generalized lambda distribution. They demonstrate the manner in which this provides a more descriptive and quicker-reacting method of process control than that of traditional SPC.

Phantom Liquidity and High Frequency Quoting

This article examines every NASDAQ ITCH feed message for S&P 500 Index stocks for 2012 and identifies clusters of extremely high and extremely low limit-order cancellation activity. The authors find results consistent with the idea that cancel clusters are the result of high-frequency traders jockeying for queue position and reacting to information to establish a new price level. Furthermore, few trades seem to be executed during cancel clusters or even immediately after them. Low cancellation activity seems to be markedly different, with many level changes all caused by executions. The results are consistent with high-frequency trading firms behaving as agents who bring efficiency to the market without the need to have executions at intermediate prices. The authors also discuss the misconception that investors and low-frequency traders are synonymous and its implications for policy given these results.

Multi-Scale Capability: A Better Approach to Performance Measurement for Algorithmic Trading

This paper develops a new performance measurement methodology for algorithmic trading. By adapting capability from the quality control literature, we present new criteria for assessing control, expected tail loss and risk-adjusted performance in a single framework. The multi-scale capability measure we present is more descriptive and more appropriate for algorithmic trading than the traditional measure used in finance. It is robust to non-normality and the multiple time horizon decision processes inherent in algorithmic trading. We also argue that an algorithmic trading strategy, indeed any investment strategy, which satisfies the criteria to be multi-scale capable also satisfies any definition of prudence. It will be unlikely to harm the investor or external market participants in the event of its failure, while providing a high likelihood of satisfactory risk-adjusted performance.

Expected Return in High Frequency Trading

Defining a in high-frequency trading is more complicated than in low-frequency trading since not all strategies are based on price forecasts. More components are required, as is an understanding of the interactions between them. In this article, we develop the a attribution model for high-frequency trading by explicating its components and the trading tactics used to implement high-frequency strategies. The results show why high-frequency traders need to be fast in order to generate positive expected returns and why they are better at providing liquidity. We provide an example implementation, using a sample of high-frequency equity data.

High-frequency trading and conflict in the financial markets

The last few decades has seen an ever-increasing growth in the way activities are productized and associated with a financial cost. This phenomenon, termed financialization, spans all areas including government, finance, health and manufacturing. Recent developments within finance over that past decade have radically altered the way trading occurs. This paper analyses high-frequency trading (HFT) as a necessary component of the infrastructure that makes financialization possible. Through interviews with HFT firms, a software vendor, regulators and banks, the effects of HFT on market efficiency, and its impact on costs to long-term investors are explored. This paper contributes to the literature by exploring the conflict that exists between HFT and traditional market makers in today’s fragmented markets. This paper argues that society should be unconcerned with this conflict and should instead focus on the effects these participants have on the long-term investors, for whom the markets ultimately exist. In order to facilitate the best outcomes, regulation should be simple, aimed at keeping participants’ behavior stable, and the interactions among them transparent and straightforward. Financialization and HFT are inextricably linked, and society is best served by ensuring that the creative energy of these market participants is directed on providing liquidity and removing inefficiencies.

Black–Litterman, exotic beta and varying efficient portfolios: an integrated approach

This paper brings together Black-Litterman optimization, exotic betas, and varying starting portfolios into one complete, symbiotic framework. The approach is unique because these techniques are often viewed as alternatives, and not as complements to each other. The paper is comprised of two main sections. The first section demonstrates using exotic beta as the “views” in the Black-Litterman optimization. This approach benefits investors who already utilize the classic Black-Litterman approach and appreciate advances in the exotic beta research, and also those who focus on practical implementation of exotic betas. The second section explores using the risk parity portfolio as an efficient starting portfolio for Black-Litterman optimization on both theoretical and practical grounds. This paper demonstrates that risk parity is a highly effective starting point in many situations. Finally, as part of our discussion, we derive conditions under which almost any completely diversified portfolio may be used as a starting portfolio in the Black-Litterman process. The integrated methodology developed is robust, flexible, and easily implemented, which means that a wide range of investors can benefit from this framework.