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This time around we’ll examine 5 extra caseswhere the markets crashed not just under the hasty fingers of nervous traders, but also due to some serious malfunctions in the automated trading software that they used. Before we do that, however, we’ll attempt to address the question that’s probably swirling in your mind as we speak.
Abrupt market crashes, also known as “flash crashes”, are anything but new. And while their effect on the global economies is typically short-lived, there are instances where such downfalls can spark lengthy economic crises, similar to the Black Tuesday—the day that marked the beginning of the Great Depression.
But if history has taught us anything during all these years of trading it’s that sudden market dips are usually a byproduct of either boundless avarice or downright reckless behaviour. In this article, we’ll look into two real-life examples of how greed and carelessness nearly caused the markets to come to a grinding halt.
Incredibly low interest rates over the past decade. Surging debts on a global scale. Escalating trade tensions between leading economic powers. Extreme currency volatility.
These are all troublesome signals that immediately raise red flags in everyone’s minds about an impending financial crisis. And rightfully so since, if history has taught us anything, it’s that the markets go through repeated economic cycles of expansions and contractions.
But while most of us can sense that an economic downturn is probably coming, trying to come up with an accurate market downturn prediction can be a real brain-twister. With that said, what makes a market crash so notoriously difficult to predict in spite of all the “obvious” clues?
For the past decade, we’ve all probably heard the words “blockchain” and “blockchain technology” one time too many, much like a broken jukebox that is hopelessly stuck in an endless loop.
And when the cryptocurrencies drastically declined in price last year, we all thought we saw the end of it. Yet companies like Google and Facebook still seem more than inclined to invest millions into blockchain research.
Why is that? To answer that question, we need to start from the very beginning.