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Data Science in the trading industry - THREAD
Financial trading is a precise job that can’t afford many mistakes before falling apart. That’s why people are starting to implement data and artificial intelligence to help out. #DataScience #BigData (1/14)
Financial trading is a precise job that can’t afford many mistakes before falling apart. That’s why people are starting to implement data and artificial intelligence to help out. #DataScience #BigData (1/14)
That way, everything can be done faster and more accurate. Here are just a few examples of how data science is making massive changes in the financial trading industry. The prediction that something’s going to rise or fall can lead to safe, smart decision making in the future.
1. BIG DATA ANALYTICS
Data about financial trading doesn’t just cover prices and fluctuations. It also tries to understand why costs fluctuate the way they do. Rates are often a reflection of supply and demand. Social and political trends can also affect sales.
Data about financial trading doesn’t just cover prices and fluctuations. It also tries to understand why costs fluctuate the way they do. Rates are often a reflection of supply and demand. Social and political trends can also affect sales.
However, the reasons behind the supply and demand could be assessed and possibly fixed. This data collection process paves the way for creating predictive models. Data can start observing trends while machine learning spots early patterns humans could easily miss.
2. STOCK EVALUATION
The software can observe patterns, trends and likely outcomes in regards to money. The AI can make these assumptions thanks to the correlations across underlying stocks and how previous patterns work with current trends.
The software can observe patterns, trends and likely outcomes in regards to money. The AI can make these assumptions thanks to the correlations across underlying stocks and how previous patterns work with current trends.
AI’s impact on the stock market doesn’t stop with predicting where stocks will go, though. Data can tell you a reasonable trading price, no matter if you’re buying or selling. Using this information, you’re likely to take fewer risks and get higher returns.
3. REAL-TIME INFORMATION
Financial trading has always been extremely fast-paced, especially when discussing the stock market. Now, you can get information back instantly, too. Real-time data can grant you better, faster decision making.
Financial trading has always been extremely fast-paced, especially when discussing the stock market. Now, you can get information back instantly, too. Real-time data can grant you better, faster decision making.
4. MACHINE LEARNING
The first thing to understand is that the technology isn’t artificial intelligence, but rather a subset. ML is the part the recognizes patterns and comes up with predictions based on amassed data. We’ve already made leaps with machine learning.
The first thing to understand is that the technology isn’t artificial intelligence, but rather a subset. ML is the part the recognizes patterns and comes up with predictions based on amassed data. We’ve already made leaps with machine learning.
The reality, however, is that we’re still on the cusp of this technology’s full potential. Big companies are just now jumping on the AI train.
JPMorgan implemented its first robot to complete trades across its global equities algorithms business. https://channels.theinnovationenterprise.com/articles/how-financial-markets-are-adapting-to-big-data
JPMorgan implemented its first robot to complete trades across its global equities algorithms business. https://channels.theinnovationenterprise.com/articles/how-financial-markets-are-adapting-to-big-data
5. COMPANIES STARTING WITH AI
A lot of companies work with AI to make the best financial trading decisions possible. Some of them continue to experiment with new ideas, pioneering steps the rest of the world is slowly starting to take.
A lot of companies work with AI to make the best financial trading decisions possible. Some of them continue to experiment with new ideas, pioneering steps the rest of the world is slowly starting to take.
Greenkey Technologies, based out of Chicago, has started using speech recognition and language processing with the interest of saving as much time on the trading floor as possible.
Auquan hosts a data science platform that allows anyone to showcase their algos and get ideas flowing.
AITrading, uses AI to increase profit from trades and maximize opportunities. Needless to say, there is a lot of ML already happening in trading.
AITrading, uses AI to increase profit from trades and maximize opportunities. Needless to say, there is a lot of ML already happening in trading.
6. FINANCIAL TRADING OF THE FUTURE
As we learn more about AI and ML, we become more efficient in the work we’ve always done. Financial trading has been around a long time and isn’t going anywhere anytime soon.
As we learn more about AI and ML, we become more efficient in the work we’ve always done. Financial trading has been around a long time and isn’t going anywhere anytime soon.
If you want to remain sustainable, optimizing the process is the only leap forward that’s possible to make. When it comes to this much money in the trade sector, you can’t afford to make mistakes or find problems at the last minute.
