Algorithmic Trading
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Algorithmic Trading is the most important part of financial institutions. In algorithmic trading, there are complex mathematical formulas and lightning speed computations that help the financial companies to devise new trading strategies.
Big Data has had a huge impact on algorithmic trading and data science has become its most important feature.
The data present in the algorithmic trading consists of massive data streams and involves a model that measures and describes the underlying data streams. The aim of the analytical engine is to make predictions for the future market by having a better understanding of the massive datasets.
Benefits for the company
The advantages of algo trading are related to speed, accuracy, and reduced costs. Trading with algorithms has the advantage of scanning and executing on multiple indicators at a speed that no human could do. Since trades can be analyzed and executed faster, more opportunities are available at better prices
Feasability
Medium
Type of expertise/ AI domain
Complex Mathematics/Statistics/ Computing Algorithms
Internal data required
Stock Market Data
External data possible
Market Risk Data/Macroeconomics Data/ Stock Market Data
Machine learning algorithms can simultaneously analyze data from hundreds of sources, identify patterns, and act proactively, holding or buying shares according to forecasts indicating their possible rise or fall.