There are a number of different types of forex execution algorithms. Some of these include Quantitative front-running, Liquidity-seeking, Arbitrage, and Spreading large orders. In this article, we look at the various types of forex algorithms and what they are used for. This article also provides some information about some of the strategies used by forex trading algorithms.
Quantitative front-running
A recent example of quantitative front-running in forex execution algorithms is the case of a former trader for HSBC. This trader, who was the bank’s global head of foreign exchange cash trading, was convicted by a federal jury for illegal front-running. In front-running, the trader places orders for his or her own account ahead of the client’s.
This method of arbitrage trading involves using software that can read the current price of multiple assets at the same time. This method allows traders to take advantage of market inefficiencies in the short-term and long term. In order to do so, a computer program must have the capacity to read price feeds from both AEX and LSE, and it must have back-testing and order-placing capabilities.
Liquidity-seeking
Liquidity-seeking forex execution algorithm aims to match order flows from different venues proportionally to limit the footprint of a transaction. The algorithm learns from market moves and adjusts its fill probability model in real-time. This strategy is ideal for clients who want to minimize the market impact of a transaction.
Liquidity-seeking forex execution algorithm uses a complex execution strategy to locate the most advantageous price in a volatile and fragmented market. It can look for liquidity in multiple markets, venues, or an internal pool. Its performance depends on 150+ parameters that can be controlled by the trader. The algorithm is designed to collect data on market liquidity, historical performance, volatility, hit ratio, and preference, among other criteria.
Another type of liquidity-seeking forex execution algorithm is TWAP. Its objective is to trade at a consistent pace over a specified time frame. In addition, it adapts to changing market conditions and chooses the most advantageous venue for execution. Recently, HSBC has released a third-generation version of its TWAP solution. Unlike the first generation, the third generation algorithm uses probabilistic assessment of market activity in real-time. The algorithm uses the bank’s in-depth market expertise.
Arbitrage
Arbitrage is a method of trading in foreign exchange that exploits differences in price between currency pairs. The decentralized nature of the Forex market creates price discrepancies that can be exploited by arbitrageurs. They can buy a currency pair below its current price, sell it for a higher price, and lock in a profit on this divergence.
To take advantage of this strategy, you must have a large initial investment. For example, if you made a $50 profit on your arbitrage trade, you would have made $25,000 in profit. However, this method is not perfect. If the price difference between two currencies is too small, an algorithm may fail to execute the order.
Spreading out large orders
When setting up your forex execution algorithm, it is important to consider how you are going to spread out large orders. You can use a strategy called time-weighted average price, or VWAP, to spread out large orders by placing smaller ones as the price moves. This is a popular choice for funds that need to buy a large amount of currency. It works by breaking large orders into smaller ones and executing them based on historic volume data. The goal is to fill large orders at prices that are near the average volume of the past few days.
Notional execution cost
The rise in use of execution algorithms has led to a reduction in the notional execution cost of forex trading. These algorithms are designed to optimize price movements by identifying and executing orders that will yield the lowest cost. The cost is based on a benchmark, such as a time-weighted average price, and is a measure of the price impact of buying or selling an asset. The goal of an algorithm is to minimize this impact while maintaining the most accurate price estimate possible.
Traders are increasingly demanding better execution. While most best-execution conversations revolve around hitting the highest bid, a growing number of traders will demand that their capital is used efficiently. Capital optimization has been a focus for banks and hedge funds for some time but has just recently gained momentum among asset managers. This year, most asset managers will prioritize capital optimization as a priority. They will also adjust their UMR thresholds to include the use of capital.
