Algorithmic Trading in Practice

2018 ◽  
Author(s):  
Peter Gomber ◽  
Kai Zimmermann
Keyword(s):  
Financial Markets ◽  
Value Chain ◽  
Trading Strategies ◽  
Algorithmic Trading ◽  
Securities Markets ◽  
Computer Algorithms ◽  
Flash Crash ◽  
Time Savings ◽  
Securities Trading ◽  
The U.S

The use of computer algorithms in securities trading, or algorithmic trading, has become a central factor in modern financial markets. The desire for cost and time savings within the trading industry spurred buy side as well as sell side institutions to implement algorithmic services along the entire securities trading value chain. This chapter encompasses this algorithmic evolution, highlighting key cornerstones in it development discussing main trading strategies, and summarizing implications for overall securities markets quality. In addition, it touches on the contribution of algorithmic trading to the recent market turmoil, the U.S. Flash Crash, including the discussions of potential solutions for assuring market reliability and integrity.

The Regulatory, Technology and Market ‘Dark Arts Trilogy’ of High Frequency Trading: A Research Agenda

2017 ◽  
Vol 32 (2) ◽  
pp. 111-126 ◽  
Author(s):  
Wendy L. Currie ◽  
Jonathan J. M. Seddon
Keyword(s):  
Information Systems ◽  
Financial Markets ◽  
Empirical Data ◽  
High Frequency ◽  
Research Agenda ◽  
High Frequency Trading ◽  
Algorithmic Trading ◽  
Flash Crash ◽  
Financial Trading ◽  
Dow Jones Industrial Average

Computerization has transformed financial markets with high frequency trading displacing human activity with proprietary algorithms to lower latency, reduce intermediary costs, enhance liquidity and increase transaction speed. Following the “Flash Crash” of 2010 which saw the Dow Jones Industrial Average plunge 1000 points within minutes, high frequency trading has come under the radar of multi-jurisdictional regulators. Combining a review of the extant literature on high frequency trading with empirical data from interviews with financial traders, computer experts and regulators, we develop concepts of regulatory adaptation, technology asymmetry and market ambiguity to illustrate the ‘dark art’ of high frequency trading. Findings show high frequency trading is a multi-faceted, complex and secretive practice. It is implicated in market events, but correlation does not imply causation, as isolating causal mechanisms from interconnected automated financial trading is highly challenging for regulators who seek to monitor algorithmic trading across multiple jurisdictions. This article provides information systems researchers with a set of conceptual tools for analysing high frequency trading.

scholarly journals Prudential supervisory disclosure (PSD) with supervisory technology (SupTech): lessons from a FinTech crisis

2021 ◽  
Author(s):  
Stefan Zeranski ◽  
Ibrahim E. Sancak
Keyword(s):  
Financial Markets ◽  
High Frequency ◽  
Market Value ◽  
Financial Supervision ◽  
Algorithmic Trading ◽  
Rapid Decline ◽  
Flash Crash ◽  
Market Participants ◽  
History Of ◽  
Financial Supervisors

AbstractThe U.S. financial markets faced an unprecedented rapid decline and recovery on May 6, 2010, known as the May 6 flash crash. Roughly one trillion $ market value in less than thirty minutes vanished with the biggest one-day point decline in the history of the DJIA at the time. Since the market events took place in electronic markets, and algorithmic trading and high-frequency trading, parts of FinTech, played significant roles, we handle the May 6 flash crash from the FinTech, SupTech, and financial supervision perspectives. With the flashback method, we analyzed the reactions of market participants, media, and two financial supervisors, the SEC, and the CFTC, to the market crash. We find that the technological imbalance between financial markets or institutions and their supervisors drove the markets in uncertainty, hence in a fear and panic environment. Since the imbalance has not diminished yet, the same risks still exist. As a remedy, we introduce a new concept and model with a well-functioning SupTech system to cope with the May 6 type FinTech crises.

scholarly journals Reliable Signals Based on Fisher Transform for Algorithmic Trading

2018 ◽  
Vol 11 (1) ◽  
pp. 87-102
Author(s):  
Cristian Păuna
Keyword(s):  
Financial Markets ◽  
Price Volatility ◽  
Trading Strategies ◽  
Algorithmic Trading ◽  
Market Participant ◽  
Trading Systems ◽  
Functional Parameters ◽  
The Common ◽  
Set Up ◽  
Very High

Abstract Trading and investment on financial markets are common activities today. A very high number of investors, companies, public or private funds are buying and selling every day with a single purpose: the profit. The common questions for any market participant are: when to buy, when to sell and when is better to stay away from the market risk. In order to answer all these questions, many trading strategies are used to establish the best moments to entry or to exit the trades. Due to the large price volatility, a significant part of the trades is set up automatically today by computers using algorithmic trading procedures. For this particular field, special aspects must be met in order to automate the trading process. This paper presents one of these mathematical models used in automated trading systems, a method based on the Fisher transform. A general form of this method will be presented, the functional parameters and the way to optimize them in order to reduce the risk. It will be also suggested a method to build reliable trading signals with the Fisher function in order to be automated. Three different trading signal types will be explained together with the significance of the functional parameters in the price field. A code sample will be included in this paper to prove the simplicity of this method. Real results obtained with the Fisher trading signals will be also presented, compared and analyzed in order to show how this method can be implemented in algorithmic trading.

Information Technology and Financial Markets

2011 ◽  
pp. 1-18
Author(s):  
Donald Crooks ◽  
John Slayton ◽  
John Burbridge
Keyword(s):  
Information Technology ◽  
Financial Crisis ◽  
Financial Markets ◽  
Information And Communication Technologies ◽  
Communication Technologies ◽  
Mortgage Loan ◽  
Flash Crash ◽  
The World ◽  
Information And Communication ◽  
The U.S

Much has been written about information technology and its role in reinventing financial markets. Today’s markets are truly global, and the interconnectedness is the result of information and communication technologies (ICT) providing the necessary infrastructure. A financial crisis in any part of the world can cause widespread disruptions due to this interconnectedness. Clearly, the Asian crisis in the late 1990s, the sub-prime mortgage loan issues in 2006 and 2007, and the problems occurring in Greece and the U.S. “Flash Crash” in 2010 were exacerbated by the ability of technology to allow financial markets to instantaneously respond in a negative fashion.

Machine learning and social theory: Collective machine behaviour in algorithmic trading

2021 ◽  
pp. 136843102110560
Author(s):  
Christian Borch
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Financial Markets ◽  
Social Theory ◽  
Collective Behaviour ◽  
Algorithmic Trading ◽  
Human Decision ◽  
Securities Trading

This article examines what the rise in machine learning (ML) systems might mean for social theory. Focusing on financial markets, in which algorithmic securities trading founded on ML-based decision-making is gaining traction, I discuss the extent to which established sociological notions remain relevant or demand a reconsideration when applied to an ML context. I argue that ML systems have some capacity for agency and for engaging in forms of collective machine behaviour, in which ML systems interact with other machines. However, ML-based collective machine behaviour is irreducible to human decision-making and thereby challenges established sociological notions of financial markets (including that of embeddedness). I argue that such behaviour can nonetheless be analysed through an adaptation of sociological theories of interaction and collective behaviour.

The profitability of algorithmic trading systems based on football sentiment

2020 ◽  
Vol 42 (1) ◽  
pp. 33-46
Author(s):  
Raúl Gómez-Martínez ◽  
Camila Marqués-Bogliani ◽  
Jessica Paule-Vianez
Keyword(s):  
Financial Markets ◽  
Investment Decisions ◽  
Futures Market ◽  
Algorithmic Trading ◽  
Investment Strategies ◽  
Measurable Effect ◽  
Behavioural Finance ◽  
Trading Systems ◽  
European Football

Behavioural finance has shown that investment decisions are the result of not just rational but also emotional brain processes. On the assumption that emotions affect financial markets, it would seem likely that football results might have a measurable effect on financial markets. To test this, this study describes three algorithmic trading systems based exclusively on the results of three top European football teams (Juventus, Bayern München and Paris St Germain) opening long or short positions in the next market season of the futures market of the index of each country (MIB (Milano Italia Borsa), DAX (Deutscher Aktien Index) and CAC (Cotation Assistée en Continu). Depending on the outcome of the last game played a long position was taken after a victory and a short position after a draw or defeat. The results showed that the algorithmic systems were profitable in the case of Juventus and Bayern whereas in the case of PSG, the system was profitable, but in an inverse way. This study shows that investment strategies that take account of sports sentiment could have a profitable outcome.

scholarly journals Can Economic Factors Improve Momentum Trading Strategies? The Case of Managed Futures during the COVID-19 Pandemic

Economies ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 86
Author(s):  
Renata Guobužaitė ◽  
Deimantė Teresienė
Keyword(s):  
Financial Markets ◽  
Risk Premium ◽  
Trading Strategies ◽  
Economic Factors ◽  
Momentum Strategies ◽  
New Approach ◽  
Managed Futures ◽  
Asset Classes ◽  
Momentum Trading ◽  
Insight Into

Systematic momentum trading is a prevalent risk premium strategy in different portfolios. This paper focuses on the performance of the managed futures strategy based on the momentum signal across different economic regimes, focusing on the COVID-19 pandemic period. COVID-19 had a solid but short-lived impact on financial markets, and therefore gives a unique insight into momentum strategies’ performance during such critical moments of market stress. We offer a new approach to implementing momentum strategies by adding macroeconomic variables to the model. We test a managed futures strategy’s performance with a well-diversified futures portfolio across different asset classes. The research concludes that constructing a portfolio based on academically/economically sound momentum signals with its allocation timing based on broader economic factors significantly improves managed futures strategies and adds significant diversification benefits to the investors’ portfolios.

Financial Markets and Exchanges Law

2021 ◽  
Keyword(s):  
Financial Markets ◽  
New Technology ◽  
Payment Systems ◽  
Regulation Of Financial Markets ◽  
Market Location ◽  
Clearing And Settlement ◽  
The Uk ◽  
Securities Trading ◽  
Market Infrastructure ◽  
Financial Technology

The book provides a comprehensive and authoritative analysis on the regulation of financial markets and market infrastructure. It focuses on stock markets and exchanges, associated trading, clearing, and settlement, and on payment systems, set in their historical and current contexts. This new edition addresses a number of major developments that have impacted the UK, wider European and international financial markets, such as within the UK, the PRA, the FCA and the Bank of England have become established financial regulators, each with its distinguishing responsibilities; MiFID has been substantially revised and strengthened through new directly applicable EU regulation; MiFID 2 also addresses the challenges posed by the use of fast-technology such as high frequency and algorithmic trading; and new technology is beginning to make an impact on the infrastructure of financial markets. This new edition includes updated content on the growing importance of financial technology with two new chapters on the emerging impact of financial technology on markets and on the regulation of markets. There is also a new chapter on MiFID 2 and MiFIR – the new securities trading architecture that will see the introduction of a new trading venue as well as significant changes to and the pre- and post-trade transparency and reporting regime. The introduction of mandatory trading of derivatives on trading venues is addressed together with the related post-EMIR regime for the mandatory clearing of certain classes of derivatives. Chapters on the role of the European Commission and ESMA have been updated, and consideration is given to the possible implications of Brexit for market location and access

Uncharted waters: Investors get access to foreign exchange-traded funds

2021 ◽  
pp. 54-70
Author(s):  
S. R. Moiseev
Keyword(s):  
Financial Markets ◽  
Foreign Exchange ◽  
Driving Forces ◽  
Market Competition ◽  
Secondary Market ◽  
Portfolio Diversification ◽  
Exchange Traded Funds ◽  
Investment Funds ◽  
Retail Investors ◽  
Securities Trading

In 2022, Russian investors will get access to the wide possibilities of the global financial market. The Bank of Russia opens the market for foreign exchange-traded funds (ETFs) — one of the main savings instruments for households. The economy of ETFs differs from other investment funds, whose shares do not have secondary market. The opening of the ETFs market is intended to solve a number of issues for retail investors: moving away from the preference to individual foreign shares towards portfolio diversification, cost reduction, ensuring sustainable profitability, abandoning the aggressive securities trading, and supporting market competition. Soon, ETFs will be one of the driving forces in financial markets. However, their rapid growth is fraught with little-studied effects.

scholarly journals The Spatial Dimension Of Take-Offs And Sustainability: The Case Of East Asian Countries

2016 ◽  
Vol 32 (2) ◽  
pp. 719
Author(s):  
Paul Moon Sub Choi ◽  
Jinhwan Oh ◽  
Changsu Ko
Keyword(s):  
Financial Markets ◽  
East Asian ◽  
Spatial Dimension ◽  
Asian Countries ◽  
Economic Openness ◽  
Human Capital Development ◽  
The Past ◽  
Capital Development ◽  
The Relationship ◽  
The U.S

This study examines the relationship between the size of a country and its “take-off” for economic development. We find that most countries which experienced economic upheavals in the past decades are relatively small in terms of area. Specifically, take-offs appear to be quicker for smaller landmasses with larger potential workforce and higher population density, controlled for financial markets maturity, corporate governance, economic openness, and human capital development. We also find that take-offs are not sustainable by nature as most countries in East Asia that which experience take-offs are currently facing slow-downs of their economies. Through this finding, we predict that China may experience a slow-down at around 36% and may reach to the 50-60% of income level of the U.S.  

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