This is the profitable trader story of Michal Zaremba — the first person to go live on AlgoCloud with real money. In this in-depth interview, Michal shares his full trading journey: from losing money on CFDs and futures to building a consistently profitable portfolio using algorithmic stock trading.
Michal’s Real Account Results: A Profitable Trader Story in Numbers
KM: Welcome, Michal! It’s great to have this chance to talk with you. I’m thrilled you’ve chosen to share your full trading journey with us — from the very start to successfully using AlgoCloud. Let’s jump in!
As first let’s check Michal’s real account results:
Real account monthly results
Real money portfolio winrate
In Michal’s portfolio, reversal strategies are a big part now, and a win rate of about 71% aligns with the experiences from backtesting (69%).
Equity chart over 1,500 closed trades on Michal’s real account using AlgoCloud for the first 12 months
There are closed trades only (some open profits too). No dividend part involved.
Example of portfolio results from backtesting
Equity for the above portfolio
Detailed description of the portfolio construction and results: Compounding Titan L Portfolio on AlgoHubb. In real trading, Michal uses a similar portfolio with some exact strategies mentioned above plus new ones he’s been developing.
Before Trading: Michal’s Business Background
KM: What were you doing before you got into trading?
MZ: Buying and selling in a basic form has interested me for as long as I can remember. As a young man in the early 90s in Poland, during the transition from socialism to capitalism, I engaged in various simple business activities.
In the meantime, I finished my economics degree and started working in sales departments, first in the financial industry, and then in 2003, I landed in IT and discovered my second passion — technology. I became responsible for sales at a small company producing mobile systems. We managed to grow the company into a dynamic organization employing over 100 people. I became a shareholder and had the opportunity to work with hundreds of companies including Microsoft, Coca-Cola, Johnson & Johnson, Unilever, Merck, and many others. Today, I have a special sentiment when trading their stocks.
The Profitable Trader’s Journey: From Zero to Automation
KM: When did you become interested in trading?
MZ: In 2017, I realized that I was working hard in business for my money, but I wasn’t doing anything to make the money work for me. That’s when I decided to find ways to effectively grow my money. I analyzed the available options and discovered the stock market and trading. I was completely fascinated by this topic.
KM: How was it in the beginning?
MZ: The beginnings were fascinating but also difficult. The markets are a real labyrinth of opportunities on one side and manipulation and misinformation on the other. I decided not to trust anyone or anything that I hadn’t thoroughly checked myself. That’s why I’ve been using a “lie detector” for years, namely AlgoWizard in SQX.
Whenever I hear or read about a method, I can quickly prototype and verify its usefulness. I often discover that a method praised by someone is at best average and often dooms the user to failure.
The Long Road: From Strategy Generator to Understanding
KM: When did you start using SQX?
MZ: I bought licenses for 2 computers in 2018. Together with my wife Magda, who became my partner in the trading adventure, we used the Builder to search for strategies 24/7 on 2 servers. We generated literally billions of strategies, qualifying about 100 of them for Forex and CFD. However, we had no idea on what principles the strategies operated.
Ask me how many of them I use today? Zero. Because we didn’t understand the strategies, we couldn’t trust them in real trading when drawdown occurred. We then held off on live algorithmic trading — and that was a very good decision.
I decided to start from scratch and learn trading before automating it. In 2020, I focused 100% on trading. I traded for a year in a trading room as a day trader on stocks. I completed an advanced institutional trading course on futures. After hundreds of hours, I realized that although I love trading, I don’t enjoy sitting in front of monitors for hours.
Then I came across educators like Andrea Unger, Kevin Davey, and Ali Casey. I immersed myself in their methods and confirmed that the key to success is “simplicity over complexity.”
Platform Stability Problems Before AlgoCloud
KM: On which platforms did you work on Futures?
MZ: TradeStation with futures and equities accounts, and MT5 + AMP Global for futures. Even with decent strategies and a strong VPS, TradeStation would crash every other day. Problems with losing track of positions occurred so often that unattended work was impossible.
MT5 with AMP worked more stably, but the broker used different time zones in data than CME exchange time. So all candles above 1h had completely different OHLC — making it impossible to compare backtest with real trading.
Then in December 2022, I was invited to beta test AlgoCloud. It was exactly when ChatGPT appeared. But if you ask me what is more powerful for me today, ChatGPT or AlgoCloud — without hesitation, I would choose AlgoCloud.
Why This Profitable Trader Chose Stocks Over Futures and CFDs
MZ: Creating profitable and robust strategies for stocks is much simpler than for futures. The daily interval provides high repeatability. Tests on thousands of instruments provide unmatched robustness. We have 30-40 years of history to backtest. We have extremely low transaction costs. For overnight positions, companies pay dividends.
Additionally, we have almost full position scalability — the key to exponential income growth. And insurance for money up to $500k+ via SIPC.
The main downsides include price gaps, limited diversification during bear markets, margin costs, and the Pattern Day Trader rule for accounts below $25k.
What Makes AlgoCloud Unique for a Profitable Trader
MZ: AlgoCloud and SQX introduced a very easy-to-use Stock Picker mechanism — an advanced technique used by recognized algo traders like Nick Radge, Larry Williams, or Cesar Alvarez. This is completely unattainable on platforms like TradeStation or MultiCharts.
The platform provides full stability and technical predictability. Today, I can go on vacation for weeks and know everything will work flawlessly. The DLOG capabilities were crucial for gaining my confidence — everything is written in plain English and simple math, step by step.
We have everything in one tool: quality data for backtesting, lightning-fast backtest, strategy deployment with a few clicks, broker connection, and TradingView integration.
Results: A Profitable Trader Story After One Year on AlgoCloud
KM: What results have you achieved?
MZ: My strategy portfolio, in backtesting, has generated an average annual return of about 30% over 30 years, with no losing year. My first year of live trading using AlgoCloud brought a return of about 25-30%. I’ve had 11 profitable months and one losing month.
More important than the % return is the relative drawdown compared to the index. Even though I use long-only strategies, during bear markets they also generated about 20% returns annually. The reversal strategies provide predictable returns in various market conditions, and filters automatically adjust exposure in unfavorable environments.
Michal’s AlgoHubb Project
MZ: From the beginning of my trading adventure, I decided that if I managed to find an effective way to trade, I would share the knowledge with others. We decided to build AlgoHubb.com — a place to share strategies, practical knowledge, and tips. In my backlog there are about 100 valuable strategies intended for AlgoCloud, and we are gradually sharing them.