Algorithms To Make Money And Save Money Whats The Difference?
Investopedia defines algorithmic trading as “A trading system that utilizes very advanced mathematical models for making transaction decisions in the financial markets.” Some of these decisions are intended to make money and others serve to save.
Let’s examine money making algorithms. Algorithms of this type are commonly the domain of hedge funds and market makers seeking to take advantage of pricing inefficiencies with the goal of making money. These algorithms more often than not are derived from buy side proprietary financial models and tend to be high frequency in nature. Fast computers that are optimally connected to both price and execution venues exact trades in the millisecond to microsecond time frame. The algorithms themselves are generally the creation of the trader focused on the inefficiencies she is trying to exploit. Algorithms can be statistical in nature seeking out aberrations in volatility (beta) or patterns in pricing. They can also be event or news driven acting ahead of others whose trading systems may not be as reactive as their own. The number of these types of algorithms are as many and as varied as there are quant shops on the street.
On the flip side are algorithms whose goals are to save money. That is to say they are intended to seek best execution and not adversely impact the market. Typical examples of this are VWAP and Implementation Shortfall (their are others but are branded differently by each broker). The intent here is to have your bids filled when you buy or offers lifted when you sell. Crossing the spread or lifting the offer when you buy or hitting the bid when you sell, while inevitable, is the worst case scenario for these types of algorithms. Mid point executions offered by some brokers as a money saving feature are intended to let buyers (sellers) pay (forgo) only half the cost of crossing the spreads (hence mid point). I know that ITG tracks historical spreads for stocks and when the market is showing a tighter spread than it has been historically it will lift (or hit) the others side. (Anyone else know who is doing this?).
From the market impact side which is more the focus of the IS order the goal here is to get you order done as quickly as possible without moving the market too much. “Clever” algos will monitor the depth of the bids and the offers to decide if it makes sense to cross the spread or wait to get filled. If you are a buyer of 100,000 shares and wish to complete your order in 5 minutes where the bid side shows a market of 1,000,000 shares and the offered side shows 200,000 shares it’s likely that the price is going to move up so your algo should cross the spread before someone else does. Granted their are several other factors at play such as volatility, average daily volume and time of day but this simple example was meant to be illustrative. Typical long only or low frequency traders have decided what to buy primarily from a fundamental standpoint and are seeking to maximize their fill price (and alpha) by saving on transaction costs.
The minds behind the money making algorithms also want to to get the most out of a trade and would be happy if they didn’t cross the spread but the reality is they don’t want to hold the trade for any length of time. They are in and out of a trade as long as they make money. As such it’s very likely these money making algorithms are the ones feeding the money saving ones.