In this exclusive interview, veteran trader Christos reveals his trading strategy secrets — the systems, tools, and thinking that have kept him profitable since 1987. Christos shares his full approach to building and running live algorithmic strategies on Alpaca using StrategyQuantX and AlgoCloud.
He talks openly about:
- The 7 strategies he runs live (and why they’re long-only)
- How market regimes determine when his systems trade
- His method for robustness testing and avoiding overfitting
- Why strategy simplicity often outperforms complexity
- The tools and resources that shaped his success
Christos doesn’t just talk theory — he shares real setups, performance insights, and decision-making processes from decades of experience. Whether you’re developing your first strategy or managing a portfolio, this interview offers serious, practical value.
Watch: Trading Strategy Secrets from a 30+ Year Veteran
Watch the full conversation now on YouTube and learn from someone who’s built profitable systems that last.
Full Interview Transcript: Trading Strategy Secrets
Christos’s Trading Journey Since 1987
Cornel: Hello, everyone. In our podcast about algo trading, which is part of the current StockLab course, it’s my pleasure to introduce today Christos, who is a professional trader for many years, has a very interesting path of a trader and he’s a successful trader. So there will be a lot of insights. For example, right now, as we are recording the interview, there is high volatility in the market due to the situation in the United States. And Mr. Trump’s steps — and Christos will touch on how he’s dealing with it and basically how he’s successfully dealing. So again, hello, everyone. Christos, thank you for joining us today. And please tell us something about you.
Christos: You’re very welcome, Cornel. It’s a pleasure of mine to meet you online and discuss some of the approaches and successes I had with AlgoCloud. I’ve been a trader since 1987. I started my trading journey just doing simple stock trades back then. And then I transitioned to full-time trading in 2000. In 2000, I started exploring some automation for executing trades. But I concentrated mostly on index products, such as the S&P 500 via the SPY ETF. And later, I transitioned to the ES futures. But I was always interested in doing stock trading automatically. But I never seemed to find the proper tools, the proper software tools to, first of all, do the data exploration, the data mining. And then to transition whatever strategies I was coming up with onto a specific platform. About 14 months ago, I came across SQX and AlgoCloud. And I immediately realized this is a very powerful tool.
The 7 Live Trading Strategy Secrets Christos Runs on Alpaca
Christos: Today, I have a total of seven strategies running on Alpaca Live. I will go now into details of what I have running to give a sense of the blend, of the combination of the strategies that I have, which incidentally have low correlation among each other — less than 0.4 correlation with each other.
I will start with the first strategy that has helped me in this high volatility environment. It’s a gap strategy based on the Russell 3000. Basically, it looks for volatile conditions in the market and specifically when the market opens with a specific gap. And then from that, it has a special ranking function, which determines which of the universe of the 3000 stocks in the Russell 3000 are the most promising to enter a long position. Incidentally, all my strategies are long only strategies.
In addition, I have a seasonal strategy operating on the S&P 500. I like to point out a very valuable feature of AlgoCloud and SQX — the fact that you can create your own stock group. So what I have done is I’ve looked for strong seasonal patterns at specific dates. And then you can apply a mean reversion or a trend following or breakout strategy on this refined universe of stocks.
I have another approach which is a combination of momentum and seasonal on the S&P 500. This particular strategy also takes advantage of the fact that in AlgoCloud, you can define secondary time series. So when you’re doing stock picking, you can define SPY as your second time series. And if the SPY itself behaves in a particular way, then it allows the strategy to enter different positions.
Why Market Regime Is the Most Important Trading Strategy Secret
Christos: I think the most valuable thing for traders to pay attention to is the market regime — whether we’re in a trending up market, trending down market, low volatility or high volatility environment. In fact, quite a few of my strategies shut down in a high volatility environment.
How do I measure volatility? Alpaca doesn’t give me the option of accessing the VIX. So what I’ve done is I use the variance function within AlgoCloud. I compare the variance historically — how it’s behaving presently versus the past. And if certain conditions are met, some of the strategies completely shut down.
Another strategy I have looks at the breakout universe in the Russell 3000. This one is strictly a breakout strategy that attempts to reduce the drawdown. Another is a mean reversion that operates on Nasdaq 100 — I noticed the Nasdaq 100 stocks tend to be strongly mean reverting. I also have a continuation strategy in the Russell 3000 — a very short-term oriented strategy. And finally, a classic mean reversion on the S&P 500.
In addition to these seven live strategies, I have 59 strategies running on Alpaca Paper going through an evaluation phase.
Sources of Inspiration for Trading Strategy Secrets
Christos: I got a lot of inspiration from Malik Keis’ YouTube channel. But in addition, I have an extensive book library. These books were published a long time ago and a lot of the strategies are effectively out of sample right now — it’s very instructive to see how they perform using a tool such as SQX.
I recommend: Trade Like a Hedge Fund by James Altucher, In the Trading Cockpit by Gil Morales, and the all-time classic Long-Term Secrets into Short-Term Trading by Larry Williams.
What I like is that within SQX and AlgoCloud you can very quickly prototype a strategy. My Gap Russell 3000 strategy has just three lines of code. People don’t realize how useful the ranking function is.
Robustness Testing: A Critical Trading Strategy Secret
Cornel: May I ask you, Christos — you mentioned robustness testing. Can you tell how you look at a strategy? What’s a sign of robustness?
Christos: Basically, I do the Monte Carlo simulations. Before I even enter the Monte Carlo simulations, I actually manually vary the parameters to get an initial feel. Because a strategy that does not work actually collapses with a small perturbation of the input values.
I look for return to drawdown, profit factor, profitability — how vulnerable they are to parameter perturbation. I find particularly useful the 3D mapping to give you a very quick look at how stable your parameters are. Now most of my strategies — 95% of them — are very simple strategies. Therefore, I don’t have a multi-parameter state space, which helps avoid overfitting.
I also test single asset strategies — if the assets are mildly correlated, they should show the same behavior. For example, if you have a strategy that shows profitability on Exxon Mobil but not on another petroleum company, then there’s obviously something wrong.
When to Turn Off a Strategy
Christos: I first test all strategies with a 25-year horizon. I want to see how well they perform throughout different market regimes. If I see a strategy giving me two consecutive months of losses in backtesting but four months of losses under live conditions, then obviously something is happening. But I’m very reluctant to turn off a strategy just because it’s showing a couple months of losses.
I rely mostly on having a secondary time series based on SPY or QQQ and determining from there what kind of market regime we’re in.
Portfolio Construction and Risk Management
Christos: How you combine all these strategies into a portfolio — that’s the real challenge. One question is: do you include strategies that make money when the market goes down? The answer is yes. Markets have a long-term upward bias, but it’s worth considering strategies that also make money in a downturn.
A third way is to trade assets that are not highly correlated — gold, oil, silver and other ETFs. I’m exploring now having a portfolio of just ETFs that includes both long-only and short-only ETFs blended together. It’s all within the Alpaca platform — just a matter of what assets you choose.
The Psychological Aspect of Developing Trading Strategies
Christos: It’s easy to get discouraged in the beginning. Because of my electrical engineering background, one of the most valuable metrics is called signal-to-noise ratio. Markets are incredibly noisy, incredibly chaotic. So it’s easy for someone starting to develop algorithms to get discouraged.
But if you come up with simple ideas, model them with SQX and AlgoCloud, you can definitely come up with successful strategies. The challenge with long-only strategies is taking care of the times when the market takes a deep dive. Either you put switches in your strategy that completely shut off, or you include some reverse ETF like SQQQ as part of your portfolio.
Cornel: Thank you, Christos. It was a great interview — a whole package which a trader needs to start and can get a lot of inspiration from it.
Christos: Always a pleasure. Thank you.