Sophisticated algorithms are already dominating our everyday life through traffic lights, train schedules, Facebook newsfeed and more.
About 70-80% of overall trading volume is generated through Algorithmic training. In this series, you will find the resources and skills required for Algorithmic trading, the application of AI for trading, and the Future of Algorithmic trading.
Though you probably do not realize it, sophisticated algorithms are already dominating our everyday life, through traffic lights, train schedules, your Facebook newsfeed, and more. An area of algorithmic dominance that often goes unnoticed is in the stock market. These trading algorithms are reshaping the way trading is done on Wall Street. Investors are using algorithms designed for trading to bring greater efficiency to financial markets, and at the same time push us into uncharted financial territory.
Trading is a gruesomely competitive world. And with AI being painted as the new wonder weapon for everything, it’s understandable that there’s a huge amount of interest in discovering how to use AI for trading. AI does play an important role in trading – but maybe not in the way you’d expect. Unfortunately, AI can’t be used to power a superhuman trading machine that steals human traders’ lunches in every market. Then, how AI helps traders make better decisions & improve high-frequency trading?
Algorithmic trading is perceived as a very complex area for beginners. There’s simply way too much to learn as it covers a wide range of disciplines that require a considerable degree of mathematical and statistical maturity. Simply put, if bogged down with the wrong resources initially, it can be very demotivating to understand or learn algorithmic trading.
Introduction Access to and control of data is one of the biggest challenges faced by data analysts and data scientists. Creative, persistent analysts find ways to get access to at least some of this data but doing that efficiently in a way that is also standardized and centralized for everyone on the team is difficult.
Introduction: Prediction is a tricky business. You have to step outside of your comfort zone, your fainted vision of the world and see it thorough across all possible dimensions. In this series, we will discuss the future of “AI”, applications that are yet unexplored.
Introduction: Humans are wired to make tough decisions bringing all the context and principles to bear. Similarly, can devices apply the available information to make the right judgment calls? In this series, we shall discuss some ethical dilemmas faced by emerging technologies.
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