algorithmic trading

From Losing Manual Trader to Profitable Algo Trader

Libor spent years trading stock index futures manually. He tested his system carefully in Excel, trade by trade, and the results looked excellent. When he started trading it with real money, his $10,000 account initially grew to almost $13,000.

Then everything changed.

By the end of the year, roughly half was gone. Eventually, almost nothing remained of the original $10,000.

But there was a surprising lesson hidden in those losses:

The strategy wasn’t the problem. Libor was.

The rules he had tested weren’t the same rules he actually followed when real money, fear, greed, and stress entered the equation. Losing trades were held too long. Profitable trades were closed too early. After a series of losses, the temptation to increase risk became stronger.

The backtest had tested the strategy. It hadn’t tested the trader.

That realization completely changed the way Libor approached trading.

Instead of searching for another indicator or endlessly rewriting his strategy, he eventually removed himself from execution and moved toward algorithmic trading.

Today, dozens of strategies can operate across thousands of US stocks without Libor sitting in front of six trading windows all day. His live account since December 2023 has more than doubled, reaching approximately +110%, with a maximum drawdown of 19%.

And the transformation wasn’t only about performance.

It changed when trading decisions are made, how closely backtests can correspond to live execution, how quickly ideas can be validated, how strategies can be diversified, and how much time trading requires.

There is also an important reality check: the account has been stagnating this year. Trading systems don’t simply generate a perfectly smooth equity curve forever.

But that’s exactly what makes Libor’s journey worth examining.

In the full video, we break down his journey from manual futures trading and a nearly wiped-out $10,000 account to systematic algorithmic trading — including the five major differences that changed the way he approaches the markets.

If you’ve ever had a strategy that looked great in a backtest but fell apart when you traded it live, this story may change what you look at first.

Watch the full video on YouTube to see Libor’s complete journey and the real results behind it.

 

Tomas Vanek

Tomas Vanek, founder of SimpleDUB.com and QuantMonitor.net, is a visionary in automated trading and AI-powered automation. Driven by a passion for efficiency in finance, data, and scalable technology, he created SimpleDUB as a professional multilingual video translation platform and QuantMonitor.net to deliver robust algorithmic trading solutions. Through QuantMonitor, he simplifies trading strategy development and portfolio management for traders of all levels using advanced templates, intelligent automation, and powerful analytical tools.

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