Humans have been on a quest to know the future for eons.
Can algorithms predict? Yes.
Stocks go up. Stocks go down. And sometimes these moves seem more pronounced than ever. Every time another (big) player’s expectations change, prices do too. That creates a lot of noise, but eventually, markets become a weighing machine.
Like many other areas now, the investment market has changed immensely with the help of technology. There is a new overlord- investment algorithms, which now complete about 90% of all trade in developed countries.
But, what exactly are these so-called “algos”? What can they do?
Why are they super smart?
The Dawn of Algos
Since the financial crisis of 2008, the stock market has changed not just through regulations, new entrants, and shifts of power, but also through the incredible advancement in algorithms.
Algorithms are a set of instructions, which carry out a certain task. The rules are set via a variety of factors: asset type, market, prices, quantity, timing, trends. According to their pre-defined calculation, execution algorithms make decisions and perform trades to maximize profitability. Some algorithms do not execute, they only generate signals, which investors use to manually buy and sell.
Types of Investment Algorithms
When Wall Street firms use algorithms, they are simply encoding a logic into the computer. A trading algorithm can be fundamentally driven–meaning it is based on old-fashioned company metrics–or based on quantitative signals such as a sweep of buying interest known as momentum or technical factors like a particular stock breaking through a 30-day average price. Or, it can be all three.
Algorithms can be complex, taking up thousands of lines, or simple.
Main types of algorithms are mentioned below.
Mean Reversion Algorithms
This mathematical method helps calculate the average price of a stock in a certain time period by past indicators, forecasts, and standard deviation. The average price is an indicator to buy when we the asset is under the mean, or sell when the asset jumps higher than the average value. This analytical technique is very common in the stock market. Algorithms help to automatize the process starting from the analytics to the actual transactions.
Predictive Algorithms
Market timing algorithms aim to predict the performance of an asset through time. They are complex to construct: the development includes 3 different phases, several datasets, and plenty of tests. The aim is to be able to project the changes in the value of an asset through time with complex analytical methods. Knowing the market outcomes opens a possibility to optimized results and very high profits.
Example of an algorithm
This algorithm is based on the concept of “mean reversion,” which is another way of saying that prices over time will return to the average.
It takes a list of stocks and ranks them into companies whose share prices are too high to those that are too low based on a well-used methodology called Bollinger Bands. Then it sells the high ones and buys the low ones. The idea is that over time, the high ones fall and the low ones rise toward the middle.
The next step is sending that list onto an order processing algorithm that goes out and buys or sells the stocks that have been selected.
Benefits of Investment Algorithms
A key factor of investment algorithms is that they completely rule out the human sentiment. No BS with fear, greed, or psychic predictions. Algorithms do what they need to do to achieve the best results.
- Unambiguous decisions: excludes human emotions with a realistic evaluation supported only by data.
- Precise execution: less human-induced errors.
- Resource efficient: needs less manpower than traditional processes.
One of the biggest advantages of algo trading is the ability to remove human emotion from the markets, as trades are constrained within a set of predefined criteria. Why this is an advantage is because humans trading are susceptible to emotions that lead to irrational decisions. The two emotions that lead to poor decisions that algo traders aren’t susceptible to are fear, and greed.
Another advantage to algo trading is the ability to backtest. It can be tough for traders to know what parts of their trading system work and what doesn’t work since they can’t run their system on past data. With algo trading, you can run the algorithms based on past data to see if it would have worked in the past. This ability provides a huge advantage as it lets the user remove any flaws of a trading system before you run it live.
Another advantage of automated trading is the reduced transaction costs. With algo trading, traders don’t have to spend as much time monitoring the markets, as trades can be executed without continuous supervision. The dramatic time reduction for trading lowers transaction costs because of the saved opportunity cost of constantly monitoring the markets.