Many misconceive high-frequency trading as a highly sophisticated activity reserved exclusively for elite institutions with substantial financial and technological resources. While that might be true for exchange-traded products like stocks and futures, it’s not true for forex and CFDs.
Popular retail forex trading platforms like MetaTrader 4 and cTrader offer powerful API libraries to develop comprehensive trading algorithms that can be executed from modest servers costing as little as $10 per month.
In this guide, we explore various high-frequency trading models, the legality and controversies of HFT and why the forex market is so attractive for HFT strategies.
High-frequency trading (HFT) is a specialised form of algorithmic trading where financial instruments are bought and sold in extremely short timeframes, often in milliseconds or microseconds. HFT strategies aim to capitalise on minuscule price discrepancies and market inefficiencies using high-speed data feeds and ultra-fast order execution.
In the forex market, high-frequency trading systems can thrive thanks to the market’s decentralisation, immense liquidity and 24-hour trading cycle. Forex HFT algorithms are designed to navigate the decentralised nature of currency trading, swiftly reacting to minute shifts in currency pair values across different trading venues and liquidity providers. By leveraging the rapid flow of data and the continuous churn of currency exchange and order book data, these systems seek to extract profit from the most fleeting price differences and short-lived market patterns, all within the blink of an eye.
High-frequency trading encompasses a variety of strategies, many of which are legitimate and provide valuable services to the market, such as enhancing liquidity or helping with price discovery. Here are some common HFT strategies used in the forex market.
Many of the controversial HFT strategies described below are impractical for trading currency pairs and CFDs but are widely used on cryptocurrency exchanges and other exchanges.
Statistical arbitrage, often termed “StatArb,” is a quantitative approach to trading that seeks to exploit relative price inefficiencies between related assets. When applied to currency pair trading, the concept can be used to capitalise on price divergences between correlated currency pairs or even between a currency pair and related financial instruments. Here’s a closer look at statistical arbitrage within the context of currency pair trading:
Statistical arbitrage encompasses other forms of arbitrage, such as triangular arbitrage, index arbitrage and inter-market arbitrage.
High-frequency traders seek order book imbalances, leveraging disparities between buy and sell orders to their advantage. They quickly identify these imbalances through sophisticated algorithms, which often serve as precursors to price changes. An overflow of buy orders, for instance, could indicate a forthcoming price surge, allowing HFTs to buy early and benefit from the uptick.
Additionally, HFTs can step in as liquidity providers in situations marked by imbalance, earning from the bid-ask spread. They also keenly anticipate the impact of large market orders that arise from clear imbalances. Furthermore, when sudden price movements occur due to these imbalances, HFTs might employ reversion strategies, betting on a price return to its average or mean.
Tick data arbitrage is a sophisticated HFT strategy tracking the minute price discrepancies that arise from the granular, tick-by-tick data feed updates in the financial markets. As each “tick” represents a single trade or price update, HFT systems can quickly analyse these micro-movements to identify arbitrage opportunities.
By processing this high-resolution data faster than other market participants, HFTs can execute trades that profit from the briefest price disparities, often existing for mere milliseconds before the market self-corrects.
High-frequency trading has stirred significant debate within the financial industry and has been at the centre of numerous controversies.
Here are some of the main concerns associated with HFT and the reasons why many brokers, particularly market maker brokers, might be wary of high-frequency systematic trading.
Critics argue that HFT can lead to artificial market movements. Rapid buying and selling by HFT can create short-lived, artificial prices that other traders act upon, distorting a financial instrument’s true supply and demand metrics.
The stock market flash crash of May 6, 2010, is often cited in discussions about the dangers of HFT. During this event, the Dow Jones dropped over 1000 points within minutes, only to recover shortly after. HFT was believed to be a primary factor behind this extreme volatility.
There’s a belief that HFT provides an unfair advantage to those with the resources to implement it. Because these firms can execute trades faster than other market participants, they might get preferential prices, leading to a two-tiered market system.
HFT firms can analyse order flows and execute trades milliseconds before larger orders are filled. This practice, known as “front running,” can allow HFT systems to profit from tiny price discrepancies at the expense of traditional traders.
Latency arbitrage is a strategy that exploits small time gaps, known as latency, to disseminate market information between different sources or locations. For instance, if one broker updates its quotes fractionally faster than another, an HFT system can buy the instrument at the older, lower price and then sell at the new, higher price, capturing the difference.
HFT algorithms might initiate a series of orders intended to ignite a rapid price movement, either up or down. Once other traders jump onto this artificial trend, the HFT system can exit, capturing a profit.
Stuffing is a controversial strategy that involves placing and quickly cancelling large numbers of orders to create the illusion of increased market activity, aiming to confuse or slow down other traders or systems.
HFT systems send out small orders, known as pings, to see if any hidden large orders are located at certain price points. Once detected, the system can trade ahead of these large orders.
High-frequency trading is not illegal, and there are many legitimate forms of HFT. However, there are specific strategies or behaviours associated with HFT that regulators, exchanges and brokers in many jurisdictions consider manipulative or abusive and, therefore, illegal or prohibited. Some questionable or illicit practices associated with HFT include quote stuffing, layering, order pinging and momentum ignition.
The capital required for high-frequency trading can vary significantly based on the trading strategy and market conditions. In the context of Forex, where trades are often held for very short durations and brokers offer high leverage, several factors influence the capital requirements, such as leverage, position size and trading frequency.
Leverage: High leverage allows traders to hold large positions with relatively little capital. For example, with 1:200 leverage, a trader can hold a $100,000 position with just $500 of margin. Therefore, a trader can engage in significant trading activity even with a modest account balance.
Frequency of trades: HFT strategies involve executing a large number of trades in a short time. While individual trades might not tie up margin for long, the sheer volume of trades can require a certain capital buffer.
Spread and commission costs: Engaging in a high number of trades means that transaction costs, even if minimal on a per-trade basis, can accumulate. Having adequate capital ensures these costs don’t consume a significant portion of the trading balance.
Risk management: Even with short holding times, there’s always a risk of a trade going against the expected direction. Adequate capital acts as a buffer against unexpected market moves, allowing the trader to weather short-term volatility without facing a margin call.
A robust technological framework is indispensable for retail traders aspiring to dive into high-frequency trading (HFT). That’s why most high-frequency traders use platforms like MT4 or cTrader, which offer algorithmic trading capabilities.
Speed is at the heart of HFT; thus, a high-quality virtual private server (VPS) is essential to ensure minimal latency and uninterrupted trading operations. The VPS should be located close to the broker’s server or, better yet, co-located to reduce execution times further.
Additionally, traders need a reliable, high-speed internet connection to avoid connectivity issues. On the software front, while MT4 and cTrader are equipped with algorithmic trading capabilities, successful HFT may require custom scripts or Expert Advisors (EAs) tailored to the trader’s specific strategy.
Lastly, real-time data feeds and advanced charting tools are critical for accurate strategy back-testing and ongoing analysis. As the HFT environment is highly competitive, continuous investment in technology and tools and consistent updates and optimisations become pivotal for sustained success.