Lucas Downey is the co-founder of MoneyFlows, and an Investopedia Academy instructor. Somer G. Anderson is CPA, doctor of accounting, and an accounting and finance professor who has been working in ...

Over the past couple of years, big data has emerged as an integral constituent in algorithmic trading with regard to how traders perceive markets and make informed decisions. In that regard, a host of ...

With growing client expectations and a constantly developing market landscape, Wesley Bray explores the evolution of algorithmic trading, delving into its use cases, the importance of data and trader ...

The formal entry of XRP algorithmic trading into the US bond and retirement financial system is seen as a significant ...

Algorithmic trading is no longer the exclusive domain of niche quantitative firms—it has become the backbone of modern financial markets. I am already seeing the significant impact AI-driven ...

When first introduced, algorithms were designed primarily for automation to mimic a trader executing orders in pursuit of specific benchmarks. In the second phase, brokers stressed qualitative ...

This is the third in a series of blog posts on MiFID II (Markets in Financial Instruments Directive II). If you missed the earlier posts, seeMiFID II: How Did We Get Here and What Does it ...

While it was once something only Wall Street players could afford, algorithmic trading is now accessible to smaller investors and startups. Algorithmic trading is when you use computer programs to ...

Algorithm trading firms, also known as quantitative trading firms, are financial organizations that use sophisticated algorithms and mathematical models to make investment decisions in financial ...

As hedge funds increasingly turn to machine learning techniques in their trading strategies, regulators and clients are having to come to terms with money being managed by black box algorithms, so who ...