Your Money, Working Smarter

I was a construction manager. Good money, genuinely skilled at the work, but the environment was grinding me down in ways I did not have words for at the time.

So I started learning to code. That led me to RefugeesCode, a not-for-profit that taught coding to newcomers. I ended up becoming its director, which taught me more about building systems from scratch than any other role I had held: how to hold a vision under pressure, how to debug when nothing is working, how to actually finish something. I came out of that phase with a different relationship to complexity. I stopped finding it intimidating and started finding it interesting.

Conventional investing was something I tried alongside all of that. It was a disaster. Not because I lacked information; I had plenty. The problem was that I could not stay calm when things went sideways. My emotions kept overriding my logic. I would read a headline and react. I would see a loss and panic. I would see a gain and get greedy. Classic. Embarrassingly classic.

Then I found Mandelbrot's book, The (Mis)Behaviour of Markets. That was the crack in the door. The idea that markets have a measurable shape, that they follow fractal patterns, that they are not purely random noise and not purely predictable either. I spent years alongside that reading studying the work of Trader Daye and ICT, learning to read market structure at a level most retail traders never reach.

At some point these threads started connecting in my head. What if I could build a system that measured the fractal state of the market and then executed trades based on rules I had written in advance, not feelings I was having in the moment? I started running backtests. The results blew me away. Two months of focused coding later, I had something real.

About a month ago, I stepped back and looked at what I had actually built: five strategies running simultaneously, each one exploiting a different feature of market structure, with combined backtested performance above hedge fund level. I will not pretend that did not feel like a significant turning point.

The problem is not information. Canadians who want to invest are not short of advice. The problem is that most advice assumes you will behave rationally when money is on the line. You will not. Almost nobody does.

Think about two ways to sell food. A shopkeeper makes a judgment call on every transaction: how fresh does this look, is this customer a regular, should I offer a discount today? The shopkeeper has context, intuition, and years of experience, but the shopkeeper also gets tired, distracted, and emotional. A vending machine executes the same logic every time, at any hour, without caring what the market did this morning. It does not panic. It does not second-guess. It does not read the news.

Traditional investors are shopkeepers. They mean well. They research. They have strong opinions. And then a market crash happens, or a media frenzy, or a friend's hot tip, and all that research gets overridden by something older and faster: fear, greed, social pressure.

The system I built is a vending machine. Every decision is encoded in rules written before any trade happens. The software reads the data, checks the rules, and either takes the trade or it does not. No human judgment at the moment of execution. No override for emotion. No "but what if this time is different."

Yes, I know the obvious objection: vending machines are also the things that eat your dollar and keep the chocolate bar. Fair enough. The difference is that this one is monitored around the clock and wrapped in the safety layers I get to in section six. What matters here is the principle, not the hardware: identical logic, every time, with no mood swings.

This is not about being smarter than other traders. It is about removing the single biggest failure mode in retail investing: yourself, in a moment of stress.

Here is the idea that changed everything for me. Markets are not random noise, but they are also not simply predictable. They have a structure, a shape, and that shape is measurable.

The technical term is a fractal. A fractal is a pattern that repeats itself at different scales: zoom in on a coastline and you see the same jagged irregularity you saw from the satellite image. Markets behave similarly. The structure of price movement on a small timeframe echoes the structure on a larger timeframe. Mandelbrot noticed this decades ago. I built tools to measure it.

The key measurement is called the Hurst exponent: a number between 0 and 1 that tells you whether the market is currently trending or bouncing. Plain English: a Hurst reading above 0.5 means the market has momentum, prices are moving in a direction and tend to keep moving that direction. A reading below 0.5 means the market is mean-reverting, prices have swung too far and tend to snap back toward centre. Right at 0.5 means pure randomness, no edge in either direction.

Here is a better way to picture it. Imagine a river and a pendulum.

Sometimes the river flows steadily downstream. If you jump in, you go downstream. That is a trending market: momentum carries you. Sometimes the river is more like a pendulum, swinging side to side around a centre point. Jump in then, and the pull is toward the middle, not one end. That is a mean-reverting market: extremes correct back toward average.

The error most traders make is treating every market like it is always flowing in one direction. Some strategies work in trending conditions. Others work in mean-reverting conditions. Mine measure which state is active right now and trade accordingly.

I run five strategies simultaneously. They are designed to be uncorrelated: each one looks for a different type of market condition, so they do not all win and lose at the same moment. Four of the five are available on eToro. The fifth runs on a different brokerage and is not part of the copy offer.

Each strategy risks exactly 2.5% of your copy allocation per trade. On a $10,000 copy, that is $250 per trade. On a $5,000 copy, that is $125 per trade. The percentage does not change regardless of market conditions or recent performance.

Win rate tells you how often a strategy is right: the share of its trades that ended in profit. It does not tell you how much it makes when it is right versus how little it loses when it is wrong. A strategy can win rarely and still be highly profitable if its wins are large enough, which is exactly what you will see with one of these.

Numbers first, then context. But before either: a quick translation guide, because trading performance gets measured differently from most investments.

A brief word on R multiples

Throughout this document I measure strategy performance in R multiples, where R is one unit of risk. If a trade risks $250 on a $10,000 copy and the trade wins $500, that is +2R. If it loses, it loses exactly $250: that is always -1R. Using R lets me evaluate a strategy's skill independently of capital size; then you multiply by your own per-trade risk to find the dollar outcome that applies to you.

The combined eToro portfolio produced 791R over 6.3 years. At $250 per trade (2.5% of $10,000), that is $197,750 in total profit on top of the original $10,000, for a final account value of approximately $207,750.

Here is what $10,000 grew to over the same six-year window; the Healthy Trader portfolio against simply holding an index or crypto:

In plain terms: the combined portfolio outperformed Ethereum buy-and-hold by more than $33,000, with approximately one-sixth of Ethereum's worst drawdown. Ethereum dropped 79.2% at its worst point in this window. Many people who bought Bitcoin or Ethereum did not actually hold through those drops; the pressure to sell at the bottom was enormous. The portfolio's worst dip was 12%: uncomfortable to watch, but not the kind of number that typically causes people to make panicked decisions.

A quick word on drawdown, since it matters here. A drawdown is the biggest drop from a peak before the value recovers: the worst temporary loss you would have had to sit through on screen. Lower is calmer. Here is the worst peak-to-trough drop each one suffered along the way:

Risk is not managed by hoping; it is enforced mechanically by the software. There are six independent layers, and failure of any one layer does not disable the others.

eToro's CopyTrader is a mechanism for mirroring another trader's positions automatically. When I open a trade, your copy account opens the same trade, scaled to your allocation. When I close it, yours closes too. You do not need to do anything after the initial setup.

Think of it as an autopilot. The rules are set, the system executes, and you can check in whenever you like, but you do not need to be watching. You can pause or stop copying at any time with no penalties from the copying mechanism itself. (eToro may have requirements around managing open positions when you stop; check their current terms.)

Here is what you control:

• The copy amount (only invest what you can genuinely afford to lose)
• When you start copying
• When you stop or pause copying

Here is what you do not control:

• Which instruments are traded (determined by the strategies)
• Entry and exit timing (determined by the algorithm)
• Position sizing (set at 2.5% per trade by the system, scaled to your copy amount)

When the copy offer goes live, here is what signing up looks like. Verify all current eToro Canada terms, fees, and requirements at etoro.com before proceeding; platform details may change.

1. 1

   Create your eToro account

   Visit etoro.com and sign up with an email address and password. The registration itself takes about five minutes.

2. 2

   Verify your identity (required by Canadian law)

   As a regulated Canadian platform, eToro is required under FINTRAC rules (FINTRAC is Canada's federal financial intelligence agency, which oversees identity verification for all licensed investment accounts) to verify your identity before you can deposit or trade. You will typically need to upload a government-issued ID and a proof of address document. The process is completed online and usually takes one to two business days.

3. 3

   Fund your account

   Deposit the amount you want to copy with. Only use money you can genuinely afford to lose. eToro accepts bank transfers, credit cards, and other payment methods; check current minimums and supported methods at etoro.com.

4. 4

   Find The Healthy Trader on eToro

   Use the search bar to find my eToro account. The exact username will be confirmed in the waitlist email when the copy offer goes live.

5. 5

   Click "Copy" and set your amount

   Set your copy amount, review the current open positions and risk settings, and confirm. From that point, your account mirrors my trades automatically.

6. 6

   Set a copy stop-loss limit (optional but recommended)

   eToro lets you set a maximum loss threshold on your copy. If your copy allocation drops by that percentage, eToro automatically stops copying and returns the remaining funds to your account. This is separate from the per-trade stop-losses the system already uses; it is an extra safety net at the copy level. Setting this to a level you are comfortable with, for example 20% to 30% of your copy amount, is a sensible step before the copy goes live.

7. 7

   Check in whenever you like

   You do not need to monitor daily. The system runs continuously, including when you are asleep or away. Log in to see current positions, performance history, and trade details at any time. You can stop copying at any time.

Ten questions I get asked most, answered directly.

Let me be concrete, because "losing periods are possible" is easy to say and hard to feel until you are in one.

The Time-Series Momentum strategy wins 25.5% of its trades. That means roughly three out of every four trades end in a small, controlled loss. The trade risks $250 on a $10,000 copy, and when it loses, the trade closes itself at its pre-set level (the stop-loss described in section six), taking out close to that amount. A typical quiet stretch might look like this across two months: six losing trades, two winning trades. The losers cost around $250 each; the winners bring in $800 or $1,200 each. Net result: roughly flat to slightly negative over two months. Your account might be down $300 to $500.

That does not feel great. I will not pretend it does.

Here is what the system does during that stretch: nothing different. The rules are the rules. It keeps taking signals, keeps applying the same position size, keeps cutting losses at the same level. It does not try to make up the drawdown by sizing up. It does not stop trading because it is in a quiet period. It executes the plan.

And here is what has historically been happening during that same two-month stretch in the other three strategies. The Fractal Hurst strategies, which detect regime, tend to perform whether markets are trending up or down; they just need the market to be doing something definite rather than being formless. The Peters FMH strategy tends to produce some of its best results precisely when markets are uncertain and fragile, which often correlates with periods when momentum strategies are struggling, because fragility and directionless price action tend to occur together.

Across the 6.3-year backtest, there has not been a single six-month window where the combined portfolio was negative. The strategies compensate for each other's quiet periods by design, not by luck. Their uncorrelated nature is a deliberate structural feature, not an accident of the historical data.

The honest version of the risk is not "you might lose everything." It is this: there will be months where your account is flat or slightly down, and if you are watching it daily and comparing it against a market that happened to rally sharply that week, you will feel impatient. That impatience is the psychological challenge. The system handles everything else mechanically.

I want to be useful to you as a decision-maker. That means being direct about what this is, what it is not, and what I do not know yet.