The popularity of algo trading software has given rise to severe competition between traders for the ways they use these solutions to accomplish targeted trade. Strategies are conceived, programmed, tested, and implemented on the fly.
Some modeling ideas are standard across the scene and are tweaked slightly according to individual traders’/brokers’ needs only.
Cherry-Picking the Models
Situations are always swerving in different ways during a typical day of trading. It’s doubly turbulent on days when things are not normal. The algo trading software must have standard and other models that can account for such marginal and unprecedented variations and work to give the best possible result in any situation.
The price of securities can vary between stock exchanges at times. The Arbitrage strategy takes advantage of this situation and gives a better-priced trade.
The software will be programmed to identify and grab such an arbitrage while quickly scanning the markets. The speed and accuracy advantage offered by an algo trade makes such trades possible compared to human ones.
The price difference is not necessarily all that great, meaning high-volume stock trades are the norm here to ensure good profits. This strategy comes in hand when making forex trades. The trader gets arbitrage profits once the order is completed.
Mean Reversion Model
It is also known as a reversal or counter-trend strategy. It is based on the premise that the average price of trade remains within a specific price range. Its momentary price fluctuation can be exploited to gain profits when it eventually returns to the expected range.
The software will calculate the average or mean price of a stock based on its history. The moment it detects a deviation in price from the normal, it will initiate a buy or sell action depending on whether the price goes below or above the median.
The drawback of this is when the median catches-up to the price. When that happens, it will significantly influence the profit, or worse, a loss can occur.
Statistical Arbitrage Model
It works best for short-term trades. It exploits errors and inefficiencies in price quotes of securities. This usually happens when the two securities are of similar types.
A trade is initiated by the software when such differences are detected. The software immediately laps up the stock that goes down in price incorrectly. When the price returns to normal upon correction, the stock will be sold for a profit.
Momentum and Trend Based Model
This is the most basic trading model and charts a linear path to trades based on market trends and historical data.
The algorithm follows the overall market trend and that of a particular stock closely. When opportunities arise, it will execute a buy or sell action as the case may be. The programmed strategies will dictate how and when these actions occur.
The algorithms must account for certain assumptions that need to be made to get the trade right. The moving average, price level movements, and other technical indicators are the key factors determining the trade execution.
Weighted Average Price Model
An efficient model, it can be decided on the time-weighted or volume-weighted average price of securities. This objective is to reduce the impact on markets by executing orders near the volume or time-weighted average price.
Large orders are not released at once but are held back and released in small proportions. This release is determined by either the stock’s historical volume profiles or during predetermined slots within a certain period.
The superior accuracy and speed of software will beat humans in making this kind of complex trading possible.
Algo trading software has revolutionized the trading landscape forever, and traders with the best models will gain the upper hand by being in the driver’s seat of these systems.