Data Science and Trading

The recent proliferation of cryptocurrencies has made young people more interested in informatics, statistics and data mining. The most successful traders tend to be the ones who treat their activity as a science, not a cheap thrill. This is why data scientists are more valuable than ever before when it comes to trading. Experts from a plethora of fields can help fintech companies offer trading services by analyzing data, laying out strategies and implementing innovative techniques.

Firms such as Cane Bay Partners are continuing to build on data science’s capabilities, and help fintech companies grow. As data science is such an expansive field, there are many different trading services that can benefit.

Technical Trading

Graphs, charts and statistical analysis are crucial to technical trading. Signals to buy or sell an asset are easier to find when a data scientist is available to help. Looking for divergence or convergence requires a clear understanding of index or stock graphs, which might be perplexing to new traders. On top of this, a trader must analyze futures contract prices in real-time in order to spot convergence on the delivery date. The end of the delivery is usually when a trader should act fast, so timing is everything. With good analysts on hand, a fintech company can retain more traders by making the process more thorough.

Fundamental Trading

Data science can help traders use a buy-and-hold strategy. An analyst can look at stock splits, acquisitions, earnings reports and other company-specific events. From there, the gathered data can give a trader an idea of how much value a security has. Fundamental analysis goes very deep, as it not only looks at corporate management but the surrounding economic conditions. The resulting insights will enable a trader to know what assets he or she should hold onto. Since prices often take days or weeks to move, traders often keep their assets for a little while.

Scalping

Some traders prefer to make small transactions many times throughout the day. This method of trading is called “scalping”, and it is another technique that data science can help with. To make a profit, a scalper must look at the bid-ask spread, which is the span between the seller’s minimum price and the buyer’s maximum price. This deduction may seem simple, but scalpers must do the math over and over to make gains. Any error or misunderstanding can lead to a missed opportunity. An analysis can not only assess bid offers quickly but make predictions about them preemptively. This can help scalpers accomplish more in a short amount of time.

Momentum Trading

Momentum trading is another technique that seems basic and obvious since most traders will easily notice when a stock is rising quickly. However, riding the momentum for too long can lead to a devastating crash. A data scientist can assess the market and give traders an idea of when they should pull out.

Since trading services are such high commodities now, fintech companies can benefit greatly from experts who know how to examine markets. The more traders get involved in a startup, the more revenue it can make.

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