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Developing High-Frequency Trading Systems

You're reading from   Developing High-Frequency Trading Systems Learn how to implement high-frequency trading from scratch with C++ or Java basics

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781803242811
Length 320 pages
Edition 1st Edition
Languages
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Authors (3):
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Sebastien Donadio Sebastien Donadio
Author Profile Icon Sebastien Donadio
Sebastien Donadio
Sourav Ghosh Sourav Ghosh
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Sourav Ghosh
Romain Rossier Romain Rossier
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Romain Rossier
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Trading Strategies, Trading Systems, and Exchanges
2. Chapter 1: Fundamentals of a High-Frequency Trading System FREE CHAPTER 3. Chapter 2: The Critical Components of a Trading System 4. Chapter 3: Understanding the Trading Exchange Dynamics 5. Part 2: How to Architect a High-Frequency Trading System
6. Chapter 4: HFT System Foundations – From Hardware to OS 7. Chapter 5: Networking in Motion 8. Chapter 6: HFT Optimization – Architecture and Operating System 9. Chapter 7: HFT Optimization – Logging, Performance, and Networking 10. Part 3: Implementation of a High-Frequency Trading System
11. Chapter 8: C++ – The Quest for Microsecond Latency 12. Chapter 9: Java and JVM for Low-Latency Systems 13. Chapter 10: Python – Interpreted but Open to High Performance 14. Chapter 11: High-Frequency FPGA and Crypto 15. Other Books You May Enjoy

History of HFT

Let's discuss the history of exchanges and financial markets prior to 1930.

When we talk about HFT, it is difficult to give a precise date for when it started. We need to come back to the primitive times when trade arose from human contact. Before the invention of modern-day cash, ancient people relied heavily on trading to trade products and services with one another in a gift economy. Long-distance trade extends back to almost 150,000 years ago, according to Peter Watson. Year after year, with more people, more goods, and more money, trading became one of the major activities of humankind. It is obvious that making money implies more business. One of the parameters was speed. If you make more transactions, you will make more money. Many stories describe the ambition of traders to get technologies such as better transportation to make deals more quickly or to get news more quickly to take advantage of other folks who do not have access to these new technical means.

We did not have to wait for too long before seeing cases of unfair trade involving those who have technical advantages over others. In 1790, a Georgia representative spoke to the US House of Representatives to expose high-speed traders. Indeed, Congress was debating the Secretary of the Treasury Alexander Hamilton's proposal that the US government absorb the previous debts accrued by the states during the Revolution (Funding Act of 1790). Traders who had learned the decision immediately bought or rented rapid boats. Their goal was to front-run messengers and buy the old debts since the passage of the Act would increase the market value. During the twentieth century, the idea of speed trading or HFT appeared.

The post-1930s era

Trading is the exchange of items for other items. It can be financial products, services, cash, digital assets, and more. One of the goals of trading is to make a profit from these transactions. The number of transactions will be correlated with the quantity of money generated by the exchange of assets. When we manage to increase the ratio between the number of transactions and the time, we can increase the profitability over time. Therefore, being capable of increasing the number of transactions is critical. Trading actors understood very quickly that they needed to shorten the trading time and started gathering in some specific places. They used to place their orders in these locations, which we call today the trading exchange (or trading floor). Major events participated in the expansion of fast-speed automated trading:

  • 1969: Instinet was one of the first automated system infrastructures. It speeded up the adhesion of high-speed transactions.
  • 1971: The National Association of Securities Dealers Automated Quotations (NASDAQ) was created in 1971 with electronic transactions.

It was the world's first electronic stock market. Initially, it only used to send quotations.

  • 1996: Island ECN was the pioneering electronic communication network for US equities trading, while Archipelago facilitated electronic trading on the US trading exchange by creating Archipelago Exchange (ArcaEx).
  • 2000s: 10% of transactions are HFT transactions.

The financial sector gathered more and more technologists in the early 2000s. By getting this technological intake, the sector started evolving sharply. Automation, throughput, performance, and latency became words that were well known by trading firms. The HFT transactions reached more than 10% of the market. By 2009, 2% of trading firms accounted for 75% of the equity volume. Nowadays, only a few firms remain in HFT, such as Virtu, Jump, Citadel, IMC, and Tower.

The modern era

The post-1930s era focused on transparency and regulation in the equities markets (and the pit in commodities markets). The modern era gives prominence to electronic trading and improves transparency. In 2000, the US Securities and Exchange Commission (SEC) proposed the Central Limit Order Book (CLOB). The CLOB is a transparent system matching orders between participants. Many more exchanges (such as Island and Arca) came to the trading scene. The number of trading firms, hedge funds, and electronic players kept increasing. They created their own technology stack to trade more quickly and stay competitive. After 10 years, only a few trading firms managed to remain competitive, becoming the 2% of the trading firms accountable for 75% of all equity volume.

The savoir faire for competing in HFT requires heavy investment: money, people, and time. It is a marriage of low-level system expertise and quants, as well as smart money (investors are more and more technology savvy). Engineers capable of creating performant code for designing ultra-low latency systems are very expensive. Only a few engineers had these skills. The performance for such a system required specialized hardware. Routers, servers, and network devices are also expensive. Therefore, the experience and the barrier of entry will prevent a lot of new incomers and will limit the competition. On top of the five firms we talked about previously, there are boutique shops that trade HFT strategies using an edge they found either in the market structure or some technical fact that other firms are not exploiting. The giant HFT firms are the companies responsible for moving most of the equity volume. Nowadays, HFT is estimated to account for at least 50% of the US equity (shares) trading volume. The market share of HFT has declined, as has profitability, since the peak year (2009).

After 2015, the growth of digital currencies cleared the way for new opportunities for high-frequency traders. Today, we can see an extensive growth of HFT strategies working with well-known crypto exchanges such as Coinbase, Binance, and hundreds of other crypto exchanges.

This modern era has anchored technology and automated trading for good. Trading models are data driven and model driven. The market data business definitely became a major part of trading. Exchanges and trading firms started making money by generating or collecting market data, the raw material of any algorithm trader.

You have been reading a chapter from
Developing High-Frequency Trading Systems
Published in: Jun 2022
Publisher: Packt
ISBN-13: 9781803242811
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