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Machine learning and artificial intelligence is a new technology that has the potential to change the finance and trading industries. It can make the decision-making process faster and more accurate, which can lead to better results for traders and investors.
There is, however, an interesting discussion about why there are no papers about stock prediction with machine learning in leading financial journals on stackexchange
I’m writing my master’s thesis about stock price prediction using machine learning methods. During my literature review, I noticed that a lot of research produced on this topic is of poor quality, published in non-finance related journals or unpublished/peer reviewed alltogether. There is no paper to be found in leading journals like journal of finance or journal of financial economics on the topic.
The poster raised a valid question, but we did not find a good answer. The most popular one is,
Nobody that found a successful technique to generate alpha has published it. I can think of the following causes:
If you’re an academic, why share your brilliant idea?
These techniques require a lot of data and financial data can be expensive, researches that work at firms that have access to this data don’t share their findings with the public.
Academics did find a lot of signals already the old fashioned way.
Despite this, fancy techniques such as AAD and Reinforcement Learning are discussed publicly. These methods don’t generate any alpha however.
In short, the consensus is that machine learning does work in trading, but the results are not available to the public.
The financial markets are extremely complex, and there are a lot of factors that go into price movements, and it’s not always easy to differentiate between a genuine pattern and random noise. We believe that in order to apply machine learning to trading successfully, one should have strong domain knowledge, along with technical skills.
What do you think? Let us know in the comment below.
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