In global financial markets, any approach that brings high potential profits is of significant consideration. It includes the most modern technologies that may give investors a strong edge.
Satellite Images
Imagine you know exactly how the Russia-Ukraine war is unfolding in real time. You stay up-to-date on all Russian tankers and the current state of Ukrainian wheat production. With this information, how possible is it to make big profits with low risks? Does this sound like fraud to ordinary investors?
There are many satellite image providers in the market such as RS Metrics, Descartes Labs, Orbital Insight, and Planet. This proves to create a huge competitive advantage for clients of these companies during global and macro events. Having this information just one second before the news announcement can potentially bring large profits.
In practical applications, automobile counting is the most basic approach used to assess the potential of retailers. Other approaches include counting solar panels, timber inventories at sawmills, and counting metal mining vehicles worldwide.
Although promising, it’s currently not feasible in Vietnam because the market size is very small. Satellite imagery is unlikely to add much value. Besides, Vietnamese investors cannot, due to laws, invest in foreign markets where this approach can be of good use.
Sentiment Analysis
At 1:07 pm on Tuesday, April 23, 2013, the Associated Press Twitter feed stated Barack Obama had been injured in an explosion at the White House. The stock market fell 0.9% immediately in just a few seconds. After confirming the tweet is fake, the market has fully recovered. It’s still a vivid example, however, of how sentiment strategy works in real trading.
In principle, a sentiment strategy is an approach that uses words from global news, such as social accounts of supposed credible sources. They are to capture the latest news or the crowd mentality on a topic. From the data, the algorithm automatically opens the corresponding trading positions. Investors interested in this approach may consider Sentifi solutions.
At the time of publishing, there’s no evidence that sentiment-driven algorithmic trading has a competitive advantage in Vietnam. Still, this approach is a compelling and intriguing idea to follow.
Machine Learning and Artificial Intelligence
This approach is probably the most well-known for its applicability in various fields. However, in the financial sector, not many machine learning or artificial intelligence algorithms are known to be sustainably profitable. It is due to the random nature of the financial sector, which can be very different from other scientific and rule-based domains. In random datasets, many models that perform well with the past data will not guarantee future performance. This fact can make the trading performance of machine learning and artificial intelligence models ineffective. However, in the future, artificial intelligence will still dominate the trend in financial market research as we collect more and more data.