Even the largest, most regulated crypto exchanges with billions in trading volume have fallen to hackers. What the history of exchange hacks really teaches us is simple: security isn’t about paperwork — it’s about infrastructure. Anonymous, privacy-first platforms like EXMON that avoid storing personal data often turn out to be far more resilient in the real world.
New traders often feel overwhelmed by market chaos—candles jumping around, indicators contradicting each other, and news creating panic. Many trade impulsively, relying on gut feelings or random signals, which often leads to blowing up their account.
In a world where your every move is tracked, where your data is bought and sold like a cheap commodity, and where “compliance” is just another word for submission, we stand for something different.
In this article, we’ll break down lesser-known but highly effective crowd signals that can help you time your trades, avoid common traps, and capitalize on the herd’s emotional swings.
Algorithmic trading is no longer exclusive to hedge funds and institutional players. Thanks to Python and open-source libraries, anyone can develop their own trading strategies, automate processes, and even create profitable systems. In this article, we’ll cover how to write trading algorithms, what tools to use, and how to test your strategies before deploying them live.
This article will break down how to efficiently use bots to trade on multiple crypto exchanges at the same time, covering specific tools, frameworks, and real-world applications you can implement immediately.