Small Caps. Big Bags. — The Sprint

You can be right on fewer than one in three trades and still make money.

That sounds counterintuitive, but it is the maths behind the way I’m trying to invest.

Most investors assume you need to be right most of the time. Pick more winners than losers.

Of course, that helps. But it is not the most important bit.

The most important bit is making sure your winners are much bigger than your losers.

Simple. Maths.

I use these numbers to decide how much to put into each trade.

In Part 1 — The Marathon and the Sprint — I covered how I structure my pension and ISA as two separate investment mandates.

The pension is the marathon: a 28-year, low-cost global tracker that gives me a high degree of confidence that, eventually, I should be able to afford the lifestyle I want.

The ISA is the sprint: an actively managed, high-conviction portfolio of UK small-cap investments with the sole intention of getting me ahead by shortcutting the traditional journey to financial independence by 15-20 years.

If you haven’t read Part 1 yet, it’s free and sets up everything that follows.

Part 2 is about the investment philosophy I’m building inside my ISA.

It is not a finished system.

I’m learning as I go, refining the process over time, and trying to build a repeatable way of putting money to work inside the sprint.

Most finance writing, stock ideas, watchlists, model portfolios, clever commentary, and endless opinions are about what might happen next.

This is different.

This is my actual ISA.

Real money. Real position sizes. Real mistakes. Real winners and losers.

I’m not building a fantasy portfolio after the fact. I’m building the process in public as I go.

Worth noting before we begin, this is a high-risk, speculative strategy. When investing in UK small caps on AIM, you should be prepared to lose all your money so no crying in the casino etc. Also, I’m not a financial adviser; these are not typical returns, and this is simply how I think about managing my own money.

Let’s Start With the Numbers

Before getting into the framework, here is my closed-trade history since opening my Stocks and Shares ISA with IG on 13 May 2025.

These are realised trades only — and don’t include my current open positions, which live at smallcapsbigbags.com.

Most brokers let you download your trade history as a CSV or Excel file. Once you have that, an LLM can help work out the basic stats in minutes: win rate, profit factor, average winner, average loser, realised gains, realised losses, realised R:R.

Here are mine.

A few things stand out.

First, I haven’t traded that much in the last year. This is not frantic in-and-out activity. It is a small number of decisions, with position sizing doing a lot of the heavy lifting.

Second, the winners are much larger than the losers. That is the whole point.

7.64x.

For every £1 I’ve lost across all losing trades, the winners have generated £7.64.

So far, the larger wins have done most of the work. That’s what I’m aiming for, but it’s still a small sample.

The 70% win rate is much higher than I need — and I expect it to fall significantly over time.

But as you’ll see shortly, at a target R:R of 1:2 to 1:3, I only need to be right around 25–34% of the time before costs to be profitable. Being right 70% of the time with that R:R compounds the edge significantly.

The average loser of −7.4%? That is discipline. Small losses, cut quickly, then either reassess or redeploy the capital somewhere better.

Cutting losers early is the single biggest upgrade I’ve made to how I invest — more on that later.

The sample size is still small, but it shows the shape I’m trying to build: small losses, controlled downside, and winners that are allowed to become large enough to matter.

Section 1: Risk/reward and win rate

I operate far out on the risk curve. This approach is not for everyone.

I am genuinely prepared to lose 100% of an individual position. If I stay in this part of the market long enough, that will almost certainly happen at some point — not on the whole portfolio, but on individual holdings.

The reason I can say that calmly comes down to one thing: the numbers.

If I’m targeting a 1:3 risk/reward ratio — risking £1 to make £3 — the breakeven win rate is much lower than most people realise.

One important caveat: these are before costs. On AIM, spreads can be wide. Dealing costs, stamp duty where relevant, can move the real-world breakeven higher.

On AIM, 3x and 5x moves are not theoretical. They happen regularly. This is exactly why this market — with all its chaos and illiquidity — is the right place to run this kind of approach.

So I can be wrong on the majority of my positions and still grow the portfolio. That sounds counterintuitive, but it is the whole point of asymmetric investing.

The key is not being right every time. The key is making sure that when I am right, the return is large enough to cover all the losses along the way.

I size and manage trades as if my long-term win rate will settle around 40%, because that feels like a realistic baseline for the type of investing I’m doing. Anything above that is a bonus.

The fundamental analysis doesn’t replace the maths. It just improves the odds.

Section 2: Recovering from a loss

Here’s something most investors rarely sit down and actually calculate.

A −50% loss does not need a +50% gain to recover. It needs +100%.

Lose 75%, and you need +300% just to get back to flat.

A −7% cut, taken cleanly, only needs roughly +7.5% somewhere else to get back to flat.

Plenty of AIM stocks can move that much in a few days.

But wait until you are down −50%, and now you need a double just to get back to where you started.

I used to be terrible at this.

I would watch a position move against me, convince myself the thesis was still intact, and tell myself the market was wrong.

Worse, I would sometimes buy more as it fell to “lower my average”.

That sounds disciplined.

In reality, it often meant adding more capital to a bad trade.

The price kept falling, the loss got bigger, and eventually I would become almost paralysed. Too far down to want to sell, but too uncomfortable to think clearly.

Flybe was probably the clearest example.

I lost something like £4,000 on it in 2023. I thought it was cheap, then it got cheaper, and I treated that as an opportunity rather than a warning. Eventually, the company went into administration and the position was a total wipeout.

That one stayed with me.

It taught me that averaging down is not automatically disciplined or contrarian. Sometimes it is just refusing to admit that something has changed.

That is how a manageable −10% becomes −40%, −50%, or worse.

Every investor does this at some point. Loss aversion is a fundamental cognitive bias in investing. A loss hurts far more than an equivalent gain feels good, so cutting a loser feels like admitting you were wrong.

But the reframe that changed everything for me was this:

“Being wrong is not the problem. Being wrong and staying wrong is.”

Cut quickly, and being wrong costs you relatively little.

Let it run, and being wrong can cost you everything.

You can lose more trades than you win and still compound, but only if the losses stay small enough to survive.

My average losing trade since inception of my ISA is −7.4%.

That number did not happen by accident. It comes from finally learning to cut quickly, move on, and redeploy capital into something with better odds and stronger price action.

It has probably done more for my returns than finding better stocks.

In practice, my rule of thumb is a 15–25% stop on a new position.

AIM stocks are volatile and need room to breathe. Spreads can be wide, too. Cut everything at −5%, and you will get shaken out of good trades constantly.

But if I am down 25% on a new entry, I have to stop and be honest with myself.

Something might be wrong.

Not necessarily the company.

It might be the timing, the price, the liquidity, or simply the fact I forced the trade before the setup was ready.

“You can be right on the company and still buy it at the wrong time”.

There will be times I cut at −15% and the stock bounces straight back within a few weeks.

SysGroup comes to mind.

That is painful. It will happen.

But more often than not, a sharp move against me on a new position is the market telling me to pause, reassess, and ask whether that capital still deserves to be there.

A known, manageable loss is almost always better than sitting there hoping a bad entry fixes itself.

Contrary to the song, the first cut is not the deepest.

In investing, the real damage comes from refusing to cut at all.

This is where philosophy becomes practice: judging conviction, weighing asymmetry, adding when the evidence improves, and cutting before small losses become large ones.

Section 3: Sizing Your Bets — Why Winners Have to Matter

Finding a three-bagger is hard. Finding one and not making enough money from it is a wasted opportunity.

The default investment advice is usually some version of: spread your risk equally. Own 20 stocks. Put 5% in each. Nice and balanced.

It feels sensible. Run the maths and it doesn’t look so great.

You find a three-bagger. Genuinely difficult. You did the research, got in early, and the thesis played out. A three-bagger means the stock is up 200%. But if it was only 5% of your portfolio, that winner contributes just +10% to the overall portfolio.

5% position × 200% gain = +10% portfolio return.

A stock went up threefold. Your portfolio moved ten percent.

Three-baggers are not easy to find. You cannot afford to waste them.

I run a concentrated portfolio of around five stocks. Concentration means the winners actually matter. It also means I can follow the companies properly — five stocks closely is realistic, twenty properly is a fantasy on AIM. There is too much newsflow, too much chart movement, too much company-specific detail.

And your 20th-best idea is not going to have the same conviction as your top five. At that point you’re not diversifying. You’re diworsifying — to borrow Peter Lynch’s phrase.

This is why sizing matters so much. Capital allocation is not a footnote to the strategy. It is the strategy.

“It’s not about being right or wrong. It’s about how much you make when you’re right and how much you lose when you’re wrong.”
— Stanley Druckenmiller

Section 4: The Sizing Matrix

The way I think about sizing comes down to two variables: conviction and asymmetry.

This is not a perfect formula. It is a framework I’ve built to help me think — and stay honest — about risk before I enter a position.

Conviction is how confident I am in the fundamental thesis. It starts with moat — what is genuinely unique about this business that cannot be easily copied or competed away? That could be patents, regulatory approvals, clinical heritage, embedded software, customer switching costs, proprietary data, or specialist know-how. After that: management quality, balance sheet strength, earnings trajectory, insider buying, and whether I’ve properly stress-tested the bear case.

Asymmetry is about the shape of the return profile. How much can I make versus how much can I lose? Price is central to this. A stock at 0.3x sales with a credible recovery has a very different return profile from the same business at 2x sales. Catalysts, cash, strategic investors, and takeover value can all shift the downside calculation.

The line I keep coming back to:

The cheaper something gets without the thesis breaking, the higher the asymmetry — and the more capital it can justify.

The matrix:

The key question before entering any stock is not just “do I like the company?”

It is: if this works, is the position big enough to matter to the overall portfolio?

A good idea sized too small is not a portfolio-changing idea. It is just a nice trade.

Section 5: How I Build a Position

Knowing the target size is only half the job. How I get there matters just as much.

Once the matrix gives me the target allocation, I split it into four equal tranches and build gradually.

I do not go all-in on day one. I want the stock to act well and earn the next tranche.

Before adding, I’m looking for three things to line up:

Price is higher than my last buy — I’m adding into strength, not weakness

Volume is strong — the move is not happening on thin air

Buyers appear to be in control — the trade flow supports the move

That last point is one most retail investors don’t look at. The London Stock Exchange publishes individual trade data with a delay, and you can usually see whether larger trades are being reported closer to the buy or sell side. It’s not perfect and trade classification can be messy — but it’s useful context. If the price is rising, volume is strong, and larger buys are stacking up, that’s a signal worth paying attention to. It suggests the move is being supported by actual demand, not just noise.

Price up. Volume strong. Buyers in control. That is when the next 1/4 goes in.

This is essentially pyramiding — adding as the position moves in your favour, never averaging down blindly because the price is lower. The stock has to prove itself before it gets more capital.

The flip side matters just as much. If the stock drops after the first tranche and hits my 15–20% stop, I’ve only lost 15–20% on the first quarter of the planned position. The damage is contained before it becomes serious. I’m not married to the trade, I haven’t averaged down into weakness, and the capital is free to go somewhere better.

Add to winners. Cut losers. Never the other way around.

Section 6: IHC — The Trade That Brought It All Together

Theory only gets you so far. This is what the framework looked like applied to a real trade.

Inspiration Healthcare Group (LON: IHC) is a UK medical devices company focused on neonatal care. When I first bought in, the market cap was tiny and sentiment was poor.

Exactly the kind of setup this framework is built for.

Running it through the matrix: high conviction in the turnaround thesis, very high asymmetry at the price. Top-right corner. Large position potential — but only if it earned the size.

Phase 1 — Toe in the Water

My first tranche was in May 2025. I bought 9,000 shares at 18p, costing £1,620.

At that point, the thesis was still early. Conviction was building, asymmetry was good, but the position hadn’t earned serious size. So I started small.

In September 2025, I sold the full position at 21p. Small profit, thesis intact — but the stock had started to break down technically. The 10-day and 20-day moving averages had crossed below the 50-day, and the price action was no longer confirming the setup. So I stepped aside and waited.

That patience mattered. A few months later, the stock fell back to 13p.

Same business. Better price. Better asymmetry.

Phase 2 — Re-entry and Conviction Building

In January 2026, I started buying again. The price was lower, the asymmetry was better, and conviction had improved as the new CEO’s progress became clearer. I built the position over six weeks.

Here is how the position was built:

Total invested: £10,500. Average entry: 14.00p. Final position: 75,000 shares.

I was not averaging down into a falling knife. I was adding as the thesis improved and the stock started to behave better. The position earned its size. It was not handed it on day one.

The best trade was not the first buy in May 2025. It was selling, waiting, and re-entering 5p cheaper with a much larger position when the asymmetry improved.

Where It Stood on 7 May 2026

As at 7 May 2026:

75,000 shares. Average entry 14.00p. Current price 30.40p.

The position is worth £22,800. The unrealised gain is £12,300 — +117.1%.

One stock. One thesis. Built patiently in tranches, held through discomfort, sized according to conviction and asymmetry.

At 56.3% of the ISA, the temptation to trim is obvious. I’m not pretending otherwise. But trimming because a position feels large is not the same as trimming because the thesis has changed. The catalyst is still ahead — US FDA approval and a foothold into the US market, if it arrives, would justify the current weight entirely. The thesis is intact. So the position stays.

That is the whole point of having the framework: so decisions are made on facts, not discomfort.

The Philosophy I’m Building

The ISA sprint is not just about finding winners.

It’s about controlling risk, understanding the maths, protecting capital when I’m wrong, and letting the upside take care of itself when I’m right.

IHC is a useful example of that philosophy in practice. It was not a perfect trade, and it proves nothing on its own. But it shows how I want to operate: start small, step aside when the setup weakens, re-enter when the odds improve, let the position earn its size.

The harder balance — the one I’m still getting wrong sometimes — is knowing when a winner deserves to keep running versus when the weight of a single position starts to introduce a different kind of risk than I signed up for. I don’t have a clean answer to that yet.

What I do know is this: cut losers quickly, don’t cut winners too early, and size your best ideas big enough to actually matter.

That is what I’m building inside the ISA sprint. Not a finished system. A real-money process, built in public, around one core idea: protect capital first, then make your best ideas big enough to matter.