Whole Distribution Statistical Process Control in High Frequency Trading

Cooper, Ricky; Vliet, Ben Van

doi:10.2139/ssrn.2327252

Cited by 6 publications

(8 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Where KNV assumes normality by way of sampling and the central limit theorem, our measure explores capability using non-normal return distributions. Similarly, where KNV uses sampling and normality for stability assessment and control monitoring (which is is inherently slow 4 ), we examine each outcome and assess its conformance to non-normal expected behavior, building on the methodology of Cooper and Van Vliet (2012) (henceforth CV). In our example implementations of capability, we consider a non-normal case and provide 5 the necessary tests and statistics, including a new algorithm for deriving the distribution of the mean.…”

Section: Introductionmentioning

confidence: 99%

Multi-scale capability: A better approach to performance measurement for algorithmic trading

Cooper

Ong²,

Vliet

2015

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

Multi-scale capability: A better approach to performance measurement for algorithmic trading

Cooper

Ong²,

Vliet

2015

Self Cite

View full text Add to dashboard Cite

show abstract

“…SPC should be of particular interest to the financial services industry, especially when daily numbers of transactions are high (see Bilson et al. , Cooper and Van Vliet , Kumiega et al. ).…”

Section: Process Risk Managementmentioning

confidence: 99%

Operational Risk in Financial Services: A Review and New Research Opportunities

Mei

2017

Production and Operations Management

View full text Add to dashboard Cite

We present a framework to describe and analyze operational risk in financial services from an operations management perspective, focusing in particular on process design, process management, and human behavior aspects. The financial services industry differs from other service industries in ways that affect the nature of the operational risks it is subject to. In recent decades, many books and papers have focused on operational risk in financial services; however, this literature has focused mainly on the conceptual and statistical aspects of operational risk management and not on its operational aspects. Operational risk in financial services has not received much attention from the operations management community. The framework presented here is based on the premise that operational risk in financial services can reap significant benefits from research done in the theory and practice of operations management in manufacturing industries as well as in other services industries. The objective of this study is to propose particular challenges and questions raised in the practice of operational risk management that may stimulate future research in this particular area of operations management.

show abstract

“…The second step involves monitoring activity continuously, to determine the likelihood that the system running is currently performing as expected. Such a system is outlined in Cooper and Van Vliet (2012), but a sophisticated methodology may not even be necessary. The point is to have a sense of the important control variables: profit and loss, number of messages (add, cancels, executes) expected per minute, etc., and a sense of whether the current activity is likely consistent with those expectations.…”

Section: The Language Of Price Discoverymentioning

confidence: 99%

High-Frequency Trading and Conflict in the Financial Markets

Cooper

Seddon

Vliet

2017

Journal of Information Technology

Self Cite

View full text Add to dashboard Cite

International audienceThe 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

show abstract

Whole Distribution Statistical Process Control in High Frequency Trading

Cited by 6 publications

References 20 publications

Multi-scale capability: A better approach to performance measurement for algorithmic trading

Multi-scale capability: A better approach to performance measurement for algorithmic trading

Operational Risk in Financial Services: A Review and New Research Opportunities

High-Frequency Trading and Conflict in the Financial Markets

Contact Info

Product

Resources

About