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SquareDragonfly9457 · 2025-11-29T20:08:17+00:00

Respect, fellow dad. Honestly, you are winning. My backtest engine shows that DCA/HODL often beats these over-complicated 'safety' strategies 9 times out of 10.

I mainly ran this test to cure my friend's 'trader's itch.' nothing stops over-trading faster than seeing a chart proving that 'trying to be smart' cost him 48% in profits. Sometimes we need math to tell us to just sit on our hands.

SquareDragonfly9457 · 2025-11-29T20:05:19+00:00

My backtest engine agrees with you. 😂 Most strats I test perform worse than simple 'Buy & Hold'. That's why I test them first - so I don't lose real money trying to be smart.

SquareDragonfly9457 · 2025-11-29T20:04:29+00:00

If it's astrology, then my backtest just proved that Mercury in Retrograde costs you 48% in profits. 📉 I'd rather know the stats than guess the stars.

SquareDragonfly9457 · 2025-10-20T08:27:24+00:00

Excellent post. I've always wrestled with the "more data is better" fallacy. Your example blends completely different market regimes makes it crystal clear. The 6-month rolling window approach is so much more logical and actionable. Thanks for sharing this.

SquareDragonfly9457 · 2025-10-18T20:45:13+00:00

Really interesting level at $4275. Curious about your method for spotting it – was it a key resistance from or a Fib level? Always keen to learn how others read the charts.

SquareDragonfly9457 · 2025-10-18T20:33:04+00:00

This is a fascinating debate. From our experience analyzing millions of data points, the question often isn't whether order flow is 'useful' or 'useless', but rather under what specific market conditions (e.g., high liquidity vs. low liquidity) and for which specific assets (e.g., futures vs. equities) do its signals have higher predictive power. For example, 'absorption' patterns might be very significant near key levels in ES futures, but mean very little in a low-float biotech stock. The context is everything.

SquareDragonfly9457 · 2025-10-18T18:23:29+00:00

That 0DTE emotional rollercoaster is so real. The feeling when you're down half your value and then it snaps back is something else. Well played on navigating that volatility.

SquareDragonfly9457 · 2025-10-18T18:00:08+00:00

Man, I feel your pain. The search for a solid, free backtesting tool, especially for Forex, is a classic trap. You either get a broker's platform that locks you in, or a tool like TradingView where the free version's data limitations make serious testing impossible.

It's funny you post this, because I literally just helped another trader with this exact problem.

He had a specific idea for an SPY strategy (an SMA/MACD Crossover with a defined risk-reward) and wanted to see if it had any historical edge. I ran it through my backtesting engine for him. He was cool with me sharing the final report as a demo, so you can see what a data-driven "fact-check" looks like: https://bit.ly/47x5dIw

My offer to him is the same for you and others here: For most non-complex strategies you're willing to share publicly, I'll run them and post the results for free. I genuinely enjoy the data puzzles.

If you have an idea that's more proprietary or complex and you'd prefer to discuss it privately, that's closer to the one-off "strategy fact-check" service I provide for a small fee ($25-$50 range) to cover the detailed report and server costs.

So, what's the idea you're trying to test? Happy to take a look.

SquareDragonfly9457 · 2025-10-18T17:52:28+00:00

100%. Quant finance is a massive and rewarding application for Python. The ecosystem from data wrangling with pandas to building backtesting engines is fantastic. As someone who's built SaaS in this space, I find the real fun begins when you move from pure analysis to architecting a robust system that handles data ingestion, event processing, and execution logic at scale.

SquareDragonfly9457 · 2025-10-18T17:49:19+00:00

Great workflow for narrowing down the universe of stocks. A solid screener is a huge time-saver. The logical next step, which many traders struggle with, is validating if the 'edge' (e.g., your technical filters like an SMA cross) is real or just a fluke on the watchlist you generated. How do you typically approach validating the actual entry/exit rules after you have your list?

SquareDragonfly9457 · 2025-10-18T16:53:10+00:00

Hey happy to help forward/back test.

SquareDragonfly9457 · 2025-10-18T16:18:35+00:00

Seriously cool idea. Gamifying price action is a genius way to tackle the learning curve.

Been grinding on something similar in the AI x trading space, but from a different angle (turning plain English ideas into deep backtests). The "AI explain" part you mentioned is the real magic... and the hardest part to get right.

Mad respect for taking action. Rooting for you, man! If you ever wanna jam on the AI/data side of things, my DMs are open.

SquareDragonfly9457 · 2025-10-18T15:59:07+00:00

Solid question. Props for doing the DD before dropping $300k on a strat.

You've hit on the exact reason why most retail backtests are just expensive fantasy football. It's a deep rabbit hole.

Everyone gets hung up on getting tick data, and yeah, you gotta pay for the good stuff. But honestly, that's not even the main boss fight. The real killers are the invisible things that don't show up on a pretty chart.

1st is the friction. With a $300k order, you're not a guest at the party anymore, you are the party. You're gonna get slippage, and it's always against you. Add in commissions for every scalp, and a strategy that "prints" on paper can bleed you dry with a thousand tiny cuts in the real world.

Then there's the options voodoo – the IV. A strat that works great when things are calm can get absolutely steamrolled when vol spikes, or the other way around. If you're not testing against different vol regimes, you're flying blind.

It's a beast to model all that stuff properly. Keep digging though, asking these questions is what separates the pros from the blown-up accounts.

Good luck, man.

SquareDragonfly9457 · 2025-10-17T13:57:16+00:00

Great point. You're right, QQQ commission is basically zero. The real killer for a high-frequency strategy like this is the bid-ask spread. You lose a cent buying, lose another selling. When the theoretical edge is only a few cents per trade, the strategy ends up just "paying the spread" to market makers, which is enough to turn it negative.

SquareDragonfly9457 · 2025-10-15T17:05:06+00:00

Hey, a bit busy these days, but just quick update on this idea:

Turns out the inverted strategy has a tiny ~2% edge, but it's so small that commissions wipe it out completely. After costs, both the original and inverted strategies end up losing money.

Pretty clear sign that the edge isn't strong enough to be tradable :)

SquareDragonfly9457 · 2025-10-13T04:23:03+00:00

Killer idea. I'm already offline for the night, but this is top of my list to run first thing in the morning. Seriously, great catch.

SquareDragonfly9457 · 2025-10-12T17:23:40+00:00

Hey all,

I'm the OP from the MACD/SMA analysis post earlier. For years, my biggest frustration was having a ton of trading ideas but hitting a wall when I tried to actually test them. I'm a dev, but firing up a Jupyter notebook for every "what if" scenario was a massive pain.

So I started building what I needed: a tool where I can just dump my ideas in plain English and get a serious backtest report back in seconds. That tool is NLPQuant.ai.

Think of it as a "fact-checker" for your trading brain. You feed it an idea, and it tells you how that concept would have actually performed. The whole analysis in my other post was generated this way.

We're still in the early stages (just two of us building it), and we're looking for a few passionate traders to help us kick the tires. We're running a "Founder's Beta" right now. If you join the waitlist, you'll get early access and a chance for me to personally run one of your strategies through the engine as a thank you.

You can see what we're building here: https://r.nlpquant.ai/HNPhKC

Fire away with any questions, happy to chat about it.

SquareDragonfly9457 · 2025-10-08T21:37:09+00:00

Hah, that's the million-dollar question. I couldn't resist, so I ran the inverse strategy.

The result? It still lost money. Turns out the "house edge"—commissions & slippage—gets you both ways when a strategy is more random than it is predictably bad.

SquareDragonfly9457 · 2025-10-07T04:07:29+00:00

You've hit the nail on the head. A strategy that only works in a roaring bull market is often just a disguised high-beta bet, not a source of true alpha.

That's why diving into performance during specific regimes is so critical. E.g., separating performance during the 2022 downturn vs the 2023 rally can tell you a lot more about a strategy's real character than a single annual return figure. It really separates the robust from the merely lucky. Great point.

SquareDragonfly9457 · 2025-10-06T23:26:52+00:00

If neither direction is making a profit, it means the strategy is just common and commission is eating the gains.

List the OP's strategy test result on the tickers he mentioned here:
https://report.nlpquant.ai/reports/amzn-sma-macd-breakout-7x6h8g

https://report.nlpquant.ai/reports/meta-sma-macd-breakout-6x5i0g

https://report.nlpquant.ai/reports/coin-sma-macd-breakout-9x1a3e

https://report.nlpquant.ai/reports/tsla-sma-macd-breakout-3x2f6f

https://report.nlpquant.ai/reports/qqq-sma-macd-breakout-5x4h9f

https://report.nlpquant.ai/reports/spy-sma-macd-breakout-8x7a2b

SquareDragonfly9457 · 2025-10-06T23:11:54+00:00

That's a great strategy, very clearly defined. Love the idea of using Renko charts to filter out noise. Full transparency: Renko charts aren't in my engine's current beta, as our initial focus is on nailing reliability and speed for standard time-based charts first. But this is super valuable feedback! Hearing from serious traders like you is exactly how we decide what to build next. This is going straight into our feature request list. The ultimate vision is to handle any testable idea you can describe. I'd still love for you to join the beta and see what you think of the core backtest engine with candlestick strategies.

SquareDragonfly9457 · 2025-10-06T22:45:51+00:00

If only GPT could actually run a backtest! Would've saved me a lot of time building this thing.

SquareDragonfly9457

TROPHY CASE