Subjective thinking is one of the biggest threats in the investment world, which is why alongside the technological development we saw a dramatic surge in the use of algorithms to make investing decisions. As a result, robo investing and the usage of mathematical models seem to be the future, considering that artificial intelligence and machine learning are able to generate further improvements.
Whether we like it or not, the interference of emotions in our decision-making process is perhaps one of the most important factors dampening our results. Emotional trading is knee-jerk and clouds rational thinking and by putting algorithms taking care of the process, any type of investment strategy can be applied automatically.
From a psychological point of view, we humans are very bad investors mainly because of a particular characteristic of our brain called the negativity bias. Inside our brain, we’ll find twice as much neural links for negative events as compared to neural links for positive events or tasks. Staying disciplined and working against our biology is a difficult challenge even for the most skillful investors, which is why some people had taken the path of algorithmic decision-making.
Types of investment algorithms
Index Fund Rebalancing algorithms are used to rebalance the underlying assets of a fund after a predefined period of time. Investment funds have a fixed strategy in terms of spreading capital among different asset classes (Example: 60% bonds and 40% stocks) and as the time goes by and valuations change, adjustments to the portfolio need to be made.
Mean reversion investment algorithms are using methods to calculate the average price of a particular instrument based on past indicators, forecasts, standard deviation, and other metrics. Market timing algorithms, on the other hand, are used to predict the performance of an asset through time with complex analytical methods.
The last type of popular investment algorithms are the ones using arbitrage. What they basically do is to take advantage of small price discrepancies in different markets.
Reduction of costs and speed increase
Another important advantage of using algorithms for investing is the limiting or reduction of transaction costs, allowing investors to retain more of the profits. Also, if a regular person can initiate a transaction per second, the most advanced algorithms that currently exist can do tens of thousands in a single second.
Some drawbacks still require monitoring
Although algorithms have already proven to be way more efficient than humans in making objective investment decisions and despite their ability to factor in a larger amount of data, they should not be seen as perfect investing tools. With so many variables that could impact the price of assets, it is almost impossible at the time being to build software able to incorporate everything. That is why even investing algorithms must be monitored and tailored to work in specific markets or environments.
The bottom line is that investors should treat algorithms as complementary tools that simplify their work and not as some sort of Holy Grail that can anticipate everything at any time.