What is Machine Learning?
Written by BAM.money
Nowadays, we hear a lot of talk about Machine Learning. But, what is Machine Learning? In simple words, Machine learning (ML) is a way to train a computer system to identify trends using a given data set and autonomously learn from it. The system learns by analyzing large data samples and identifying common relationships and patterns. This is highly useful in the realm of finance, since the machine can determine trends and decide if they should buy, sell, or hold assets.
In order to maximize the risk-adjusted return on any investment, you need to be able to accurately “predict” entry and exit. The return associated with this residual but fundamental component is often called alpha. Alpha is the uncorrelated risk by what’s left after beta times market return is discounted.
The general belief that prices convey everything about an asset is incorrect. In fact, most of the time, prices offer high level context, so one can’t treat them as investment signals. Instead, asset values are dictated by factors like an investor’s opinion. But, are humans the only ones capable of analyzing and predicting an investor’s opinion?
Today’s machine learning algorithms have become so refined that they often don’t need so-called “intuition” to gauge “opinion.” In some cases, one might even say that they’re objectively better at examining emotions, because of their pattern recognition ability.
Although most traders rely on their expertise, experience and intuition to generate alpha, they could incorporate Machine Learning in their decision-making processes. The key benefits of machine learning1 are:
· Identifying signals and shifting indicators
· Using Alternative Data insights
· Maximizing Gains by Managing Risks.
Through signals, sentiment analysis and alternative data insights, ML helps traders recognize alpha, and gives them a competitive market advantage.
The efficiency of ML brings up the question, if traders should be threatened of being replaced by machines? The answer is “NO.”
First, machines are unable to define their own tasks. Machines still need people to give them a designated purpose, at least for the foreseeable future. As the owner and operator, you still hold the keys. This means that as evolved as some systems are, machine learning is still susceptible to certain problems. It can still suffer from inaccuracies, discriminatory outcomes, and even embedded biases from the data set that you provide them.
Second, machines have no feelings. Machines don’t have feelings or concepts of ethics or morality. These traits, while exclusive to humans, indicate that people will have to regulate machines. Machines, unlike traders, don’t get emotional or distressed. Traders are still responsible for the sustainable and ethical use of the machines.
Third, machines cannot predict the future. Although supervised learning relies on historical data and assumes that what has happened in the past is representative of what will happen in the future, this is faulty logic in times of political regime shifts, public relations scandals, natural disasters, and even worldwide pandemics. Inevitably, there will be things that algorithms can never predict. It’s important to note though that nobody can accurately predict these kinds of things. These flaws are shared by almost any other investment tool and technique. Your human insight and analysis into the situation will be needed.
No one can deny that using machine learning to generate alpha has its merits. While it has its problems, so do other investing tools. But the field is still growing, and it’s growing fast. The benefits of machine learning could very well double or even triple in a few years’ time.
Right now, we have millions and millions of data points that we can use to analyze people’s behavior, and this number will only keep growing. At the moment, banks and institutions, such as fintech startups, are 10 to 100 times better at predicting consumer behavior and creditor behavior, among others, than every theory that ever has been devised by financial professors.
Start incorporating machine learning in your investment strategy and start generating higher alpha today. Artificial intelligence can boost your analytical and decision-making abilities by providing the right information at the right time. Machine learning will only make the process of gathering information so much easier, and will give you the tools you need to make better investment decisions.
If you’d like to gain more information about Machine Learning, and what are some of its benefits, see our article “Key Benefits of Machine Learning”.
