xaresx 

Hello, how can I contact you?

Be careful when you are going to buy license form unknown websites/people. If you want to use it for proper trading, buy license from authorized sales or on actual website.

TraderGuru 

Be careful when you are going to buy license form unknown websites/people. If you want to use it for proper trading, buy license from authorized sales or on actual website.

thanks for reminding

syswizard 

I am not a big fan of optimization let alone self-adaptive optimization. Reason: curve-fitting.

@syswizard,

Your skepticism is well-placed, and curve-fitting is the right thing to worry about. But I'd push back slightly on lumping all optimization together.

Traditional optimization -- where you run a parameter sweep across the entire dataset and pick the best result -- is curve-fitting by design. You're finding the parameters that happened to work on historical data, with no validation that they generalize.

Walk Forward Optimization is fundamentally different in intent. It segments your data into rolling in-sample/out-of-sample windows and forces the strategy to prove itself on data the optimizer never saw. Robert Pardo's original framework was specifically designed as an anti-curve-fitting test. The Walk Forward Efficiency metric directly measures how well optimized parameters translate to unseen data.

That said, WFO isn't bulletproof. You can still curve-fit the WFO settings themselves -- cherry-picking window sizes, parameter ranges, or fitness functions until you get a passing result. Which is where Matrix Optimization adds value: it tests across a grid of reoptimization periods and out-of-sample percentages simultaneously. If your strategy only passes with one narrow configuration, that's a red flag. If it passes across a wide range -- the "loose pants fit all" principle -- you have stronger evidence of robustness.

On self-adaptive trading specifically, your concern has merit. Automatic re-optimization doesn't solve the fundamental problem if the underlying strategy logic is fragile. The automation just makes curve-fitting happen faster.

The real litmus test: does your strategy work across a range of parameter values, not just one optimal point? If you need heavy optimization to make something profitable, the strategy itself likely needs rethinking -- not better optimization tools.

Have a good weekend!

-- Fi

"The best parameter is the one that still works when the market forgets to cooperate."