What are the best practices for backtesting technical trading strategies for cryptocurrencies?

Totally hear where you're coming from. Navigating the backtesting maze can feel like a real head-scratcher, right? So, one golden nugget of advice is to ensure you've got access to high-quality historical data. Without it, you're basically flying blind. And let's not forget about slippage and trading fees - gotta include those in your simulations to get the real picture.

Then there's the pitfall of overfitting your strategy to past data. Easy to do, but it's like preparing for yesterday's weather. Instead, focus on robustness. Can your strategy weather different market conditions without crumbling? Think of it like stress-testing a bridge – you want that thing to stand strong in a storm, not just on a sunny day.

And speaking of testing, stagger your data. Use in-sample data for developing your strategy, but keep a chunk of out-of-sample data untouched for a true litmus test. It's like not eating all your snacks before the movie starts - you'll thank yourself later.

Lastly, keep it simple. Complex models are cool and all, but they can be a nightmare to actually trade with. If you can explain your strategy to a buddy without their eyes glazing over, you're probably on the right track.

Hope this helps put you on a clearer path. Happy to chat more about specifics if you've got questions!

To add to the mix, it's smart to regularly update your strategy as market conditions change; crypto markets are notoriously volatile and what worked last month might not cut it now. Also consider running your strategy across multiple cryptocurrencies to diversify risk and get a better sense of its overall effectiveness. Always be ready to adapt and evolve your approach based on real-world performance.

Alright, jumping in with a bit of skepticism here. While backtesting is definitely a valuable tool, we must be wary of its limitations, particularly in the wild west of crypto markets. The historical data we rely on – how reliable is it really? Given the rapid evolution of the crypto space and the diversity of exchanges, there’s often a lack of standardized, clean data, which could skew your results big time.

Then there’s the issue of market liquidity. Crypto can be super liquid in some instances but turn into a desert in others, which throws a wrench in the works for many a strategy when it's time to execute in the real world. A strategy could show great returns on paper, but when you're trying to execute that same trade in an illiquid market, you might end up moving the price against yourself.

Don't even get me started on black swan events - those random, extreme market conditions that can send a strategy that's been solid for months into a tailspin. You can't always foresee them, and yet, they can make or break your success.

So yeah, while backtesting is part of the homework, it's far from the whole story. It's crucial to proceed with caution, keep expectations realistic, and always have a plan B (and maybe even a plan C) for when things inevitably swing away from the historical norm.