Ask any quant why their live strategy underperforms their backtest, and most will eventually mumble something about slippage. But that mumble masks a genuinely thorny problem. Transaction cost modelling is the part of strategy development where wishful thinking goes to die — and on the ASX specifically, the stakes are higher than most traders realise.
The direct answer is brutal and simple: if your backtest assumes mid-price fills, or even best-bid/best-ask fills on every trade, you are almost certainly overstating your strategy's expectancy. On thinly traded ASX small-caps, the effective spread can consume 40–80 basis points per round trip. If your edge is 30 basis points, you never had an edge — the costs ate it before the first trade settled.
Think of it like renovating a house on a budget. You plan meticulously, price the tiles, the paint, the labour. Then the plasterer finds asbestos behind the wall. Transaction costs are the asbestos — invisible in the blueprint, catastrophic when you finally encounter them. The ASX's mixture of liquid large-caps and illiquid micro-caps makes this especially treacherous, because the spread regime changes dramatically across tiers.
A credible cost model for the ASX has at least three layers. First, the quoted spread — the difference between best bid and best offer at the moment your signal fires. Second, market impact — the price movement your own order causes, which scales non-linearly with order size relative to average daily volume. Third, timing cost — the slippage from the moment you decide to trade to the moment your order actually executes. Ignoring any one of these understates your drag meaningfully.
Quantitative researchers approaching this rigorously often use the square-root market impact model, which estimates price impact as proportional to the square root of participation rate. It is not perfect, but it is far more honest than assuming you fill at the touch every time. For deeper reading on microstructure mechanics, the bid-ask spread mechanics explained on Investopedia provide solid grounding, while the academic foundations live in market microstructure theory on Wikipedia. For practitioners building cost models from data, the market impact overview on Investopedia covers the key concepts without the PhD-level notation.
The practical takeaway you can apply today: re-run your best backtest with a flat 30-basis-point round-trip cost applied to every trade, regardless of the stock. If the strategy still shows positive expectancy, you have something worth stress-testing further. If it collapses, the spread just saved you real money.
Transaction costs are not a footnote. They are the exam your strategy either passes or fails before live capital gets involved.
This content is for educational purposes only and does not constitute financial product advice. Past performance is not indicative of future results. Profit Logic Ltd (ACN 688 669 936) accepts no responsibility for errors or omissions in this content or anywhere on this website. Always seek advice from a licensed financial adviser before making investment decisions.