The purpose of the Foreign Exchange (Forex), the richest market in liquidities, is to trade currency. Each day of trading, fortunes are made, lost or incrementally increased or decreased, depending on the boldness of the trader and the favors of the gods of the market.
However, modern technology has quickly seeped into the financial industry, this time under two shapes. The first one consists of the methods and practices of predictive analytics.
Predictive analytics use already known data to formulate a model that can be used to predict values for different or new data. As such, the end-result is a probability of the target variable based on the input variables. Specifically, trading becomes a business of algorithms, custom indicators, market moods, integrated beliefs and more.
The second shape is that of Big Data. These are collections of data sets that may be analyzed computationally to reveal patterns. When the trading markets moved to electronic platforms in the 1990s, they were one of the first big data generators of human behavior.
Buying and selling were no longer a force of nature, an “invisible hand” subjected to its own unknowable whims, but something that could be studied, understood and most of all, predicted.
Together, predictive analytics and Big Data potentiate one another and give traders, forex brokers and researchers ways in which to understand the market better.
Brokers on the foreign exchange market, and through them the financial institutions, are not investors. Their purpose is to assist international trade by providing currency conversions. However, these numerous conversions can also turn a sizable profit. A broker can obtain and hold a position for a very brief time before closing it for a small profit. This is called scalping trading.
To do so, real-time valuable information and forecasts are essential. While a thorough study of patterns and trends can offer an overview of a larger period, predictive analytics also works to provide quick answers to brokers and financial institutions regarding possible short-term trends.
Aside from registering a financial event, like the buying of a company by another or the bankruptcy of a private retirement fund, Big Data also records everything that goes on in the market before, during and after that moment. This serves as a powerful database that can be studied, analyzed and integrated into future expected patterns of behavior in the exchange market.
As a result, trading using the predicted outcomes provided by analyzing datasets has become somewhat of a norm for Forex brokers.
