The Key Impacts of Big Data Analysis on Financial Trading
While there are numerous trends that define the modern technology market, big data is arguably the single most influential. This is certainly borne out by the statistics, with the big data analytics market set to achieve a cumulative value of $103 billion by the year 2023.
Not only this, but at present there are also an estimated 2.5 quintillion bytes of data created every single day, with such data sets used for a wide range of applications from business intelligence to financial trading.
The latter application is particularly interesting, particularly given the role of big data in influencing forex and stock market trading. We’ll appraise this in the post below, while asking whether this influence has been largely positive.
What is Big Data?
In simple terms, big data is a relatively new and advanced field that explores ways to analyse and systematically extract information from incredibly large and complex datasets.
Such datasets are typically too vast to be processed by traditional software applications, and in this respect, big data has created new opportunities for businesses to effectively target consumer demographics.
Interestingly, big data also has the potential to process fundamentally disorganised datasets, such as those found on social media. This is a huge boon for businesses and investors, especially those that want to uncover influential but otherwise hidden trends.
When it comes to existing financial models and analysis, it’s fair to surmise that these rely heavily on the volume and accuracy of data collated. So, the more data that is produced, the more accurate the models become, enabling everyone from finance offices to investors to make more informed (and ultimately profitable) decisions.
Make no mistake; we’re definitely seeing big data analytics used to create more predictive models in the financial realm, which can accurately estimate specific rates of return and outcomes on investments.
Big Data, Machine Learning and AI – The Impact on Financial Trading
Big data has also collided with artificial intelligence (AI) and machine learning, creating increasingly powerful tools for investors to utilize.
Machine learning essentially enables computers and software to learn from historical trends and past mistakes, before making informed decisions based on brand new information as it’s received.
This is the very embodiment of AI and when combined with incredibly high and organised swathes of data analysis, is capable of underpinning an optimal investment strategy that can ultimately eliminate human error, emotion and bias.
As a result, the combination of big data and machine learning has already begun to revolutionise forex trading in particular, while improving the efficacy of algorithmic and high-frequency trading throughout the marketplace.
Some may argue against these types of trading due to their ability to create a more volatile market, but the introduction of big data could at least lead to more informed trades and superior decision making.
Is This Creating a Gap Between Big Institutions and Smaller Traders?
Interestingly, the emergence of online trading platforms and tools such as the MT4 has historically empowered part-time investors and levelled the playing field between them and institutional investors.
However, the advent of big data and AI is arguably changing the landscape once again, widening the gap between these entities and affording a clear competitive edge to institutional investors that can harness advanced big data tools.
Of course, this may not always be the case, simply because such technology will become increasingly commonplace and affordable as it develops over time.
In the meantime, there’s no doubt that big data is already a seminal technology in the world of financial and forex trading, particularly when you consider its relationship with AI and machine learning.