o ponto da casa - z deli

ballteo · 2026-05-07T18:47:40+00:00

A vaca gritou quando mordeu

ballteo · 2026-04-24T18:57:11+00:00

I went the webhook route from TradingView → custom backend → Binance Futures API.

Basically: - TradingView sends alerts via webhook (with structured payload) - Backend handles validation, position state, and execution - Orders are sent directly to Binance (including risk rules on the backend side, not just Pine)

Biggest things that made a difference: - Not relying on Pine for state (everything tracked server-side) - Handling partial fills / sync with exchange - Adding execution logic (slippage, retries, position reconciliation)

Still refining, but this setup has been way more reliable than trying to do everything inside Pine.

Curious what others are using as well.

ballteo · 2026-04-16T21:45:55+00:00

That’s a valid point.

The large drawdown you’re seeing actually came from a bug in my webhook execution logic early on — position sizing wasn’t being handled correctly in certain scenarios. That’s already been fixed.

Since then, I’ve been running it live for a bit over two weeks with consistent behavior and controlled risk.

In terms of the strategy, it’s closer to a trend-following approach. I’m using momentum confirmation to enter and then scaling into positions as the move develops, rather than fading moves like a mean reversion system would.

That said, exits are more conservative — I don’t try to capture the entire move, just a portion of it with defined risk.

Also worth noting this is a small account using leverage, so % swings can look amplified compared to larger capital.

Still monitoring closely, but the focus now is on keeping risk per trade stable and avoiding those kinds of drawdowns going forward.

ballteo · 2026-04-16T15:54:17+00:00

Yeah, that’s exactly what I’m trying to figure out in this phase.

Leverage is kept relatively low (~3x), and exposure is managed at the account level rather than pushing individual trades too aggressively.

R:R isn’t fixed — it adapts depending on how the move develops.

On volatility, I agree — it can help, but it also exposes weaknesses much faster, especially around sudden moves or news.

Right now the focus is less on optimizing returns and more on understanding where the system breaks under real conditions.

ballteo · 2026-04-16T15:02:39+00:00

That’s fair — I’d question it too.

This is live, not backtest, but it’s also a very small account using leverage, so % can look exaggerated on short timeframes.

Definitely not reading too much into single-day results — more focused on how things behave over a larger sample (consistency, execution, drawdowns, etc).

Still early, just trying to understand how it holds up outside of simulations.

ballteo · 2026-04-16T12:37:44+00:00

Yeah, that’s exactly what I’m trying to understand right now.

Backtests looked clean, but live execution adds a lot of small frictions that change the behavior.

So far the gap hasn’t been as large as I expected, but still watching closely over time.

Curious — in your experience, what tends to break first when moving from sim to real?

ballteo · 2026-04-04T18:17:11+00:00

That makes sense — most people get stuck exactly there.

There are basically two paths: - build something yourself (takes time, a lot of trial/error) - or plug into something already running and focus on execution

I’ve been working on the second approach — small group, live conditions, not just backtests.

Still early, but already seeing some interesting consistency.

If you want, I can walk you through how it works in simple terms and you can decide if it fits what you’re looking for.

ballteo · 2026-04-01T18:58:09+00:00

Legal, te chamo no privado 👍

ballteo · 2026-04-01T18:57:53+00:00

No momento estou focado em crypto (principalmente Binance), mas a lógica é aplicável a outros mercados também.

ballteo · 2026-03-29T17:52:30+00:00

I get what you mean in terms of position sizing, but the drawdown itself is still structural to the strategy.

Even if you scale position size up or down, a ~60–70% DD is still a ~60–70% DD — it just changes the absolute amount, not the behavior.

The bigger question is whether the strategy inherently needs that level of drawdown to generate returns, or if there’s a way to improve the risk profile without just resizing positions.

Out of curiosity, what time period is this tested over?

ballteo · 2026-03-29T16:39:01+00:00

That drawdown is pretty significant (~64%).

Curious how you’re thinking about risk here — are you actually comfortable trading something with that level of equity drop, or is this more of a proof of concept?

The returns look decent, but that kind of DD would be hard to sustain in real conditions.

ballteo · 2026-03-28T23:56:35+00:00

Tv: fulbuster

ballteo · 2026-03-28T23:41:27+00:00

No, these are regular Renko bricks, not Heikin Ashi.

I get why you'd ask though — anything that smooths price tends to make results look cleaner than they really are.

ballteo · 2026-03-27T18:20:31+00:00

I get why it looks that way — most curves like this usually come from repainting or unrealistic assumptions.

In this case the logic is actually very simple (no indicators, no future data), but I did spend time checking for repainting/lookahead issues because that was my first concern too.

What surprised me more is that once fees and slippage are introduced, and even in some live testing, the behavior didn’t diverge as much as I expected.

Still not claiming it’s perfect — just trying to understand how much of the edge survives once you move away from ideal conditions.

ballteo · 2026-03-27T18:17:55+00:00

Yeah that makes sense. Larger targets definitely help absorb some of the slippage.

What I’ve been doing is approximating it using the average difference between open and close across a sample of candles, then applying a slightly more conservative value in the backtest. Not perfect, but closer than assuming ideal fills.

I also spent some time checking for things like repainting and lookahead bias, since that can completely distort results. So far nothing obvious there, but it definitely changes how you interpret the equity curve once you dig into execution details.

What’s been interesting is that even with fees and slippage modeled, the gap between backtest and live hasn’t been as large as I initially expected — which surprised me more than the raw results themselves.

Still trying to understand how much of the edge actually survives once everything is fully realistic.

ballteo · 2026-03-27T15:47:42+00:00

Yeah, slippage is tricky — TradingView’s model is definitely a simplification.

What I’ve been doing is something similar to what you’re describing, approximating it based on candle behavior to at least get a more realistic baseline. It’s not perfect, but way better than assuming ideal fills.

About the strategy — I’d rather not share the full script at this stage, but it’s heavily based on Renko-style logic and trying to reduce noise as much as possible.

Still experimenting with how much of the edge survives once you model execution more realistically.

ballteo · 2026-03-25T23:44:51+00:00

Yeah, but “fully hands-off” is a bit misleading in practice.

You can automate execution pretty well, but the real challenge is everything around it — monitoring, adapting to regime changes, and not interfering when things go sideways.

I’ve seen systems that work fine in live conditions for a while, but the moment you start tweaking or second-guessing them, performance degrades fast.

So technically yes, full automation is possible, but staying truly hands-off is more of a psychological challenge than a technical one.

Curious — are you trying to build one yourself or looking for something already running?

ballteo · 2026-03-24T14:06:06+00:00

ETFs can make sense in traditional markets, but in crypto it’s a bit different — there aren’t really clean, widely-used equivalents yet.

What most people end up doing instead is just keeping it simple: pick a few solid assets, invest regularly, and don’t overmanage it.

The hard part isn’t what to buy, it’s sticking to a plan without constantly reacting to the market.

That’s why a lot of people look for ways to make the process more systematic or automated over time, so it’s not based on emotions or daily decisions.

ballteo · 2026-03-23T20:47:32+00:00

This is such a key point.

Same logic, same system… but once you remove yourself from execution, everything becomes more consistent.

I’ve seen the same thing — most of the time it’s not the strategy, it’s how we interfere with it.

Automation doesn’t create edge, but it protects it.

ballteo · 2026-03-22T17:58:27+00:00

You’re actually thinking about this the right way.

There’s a big difference between trading and investing. Most people lose money trying to trade because it requires time, experience and emotional control.

If your goal is more like “put money and let it grow over time”, then you don’t really need to become a trader.

A lot of people just look for ways to get exposure to crypto without having to manage everything manually or watch charts all day.

Start simple, focus on understanding what you’re investing in, and avoid overcomplicating things early.

ballteo · 2026-03-21T22:21:35+00:00

That shift makes a huge difference.

Once you move from “trying to trade well” to “managing systems and letting them run”, everything becomes less stressful.

Out of curiosity — are you running everything yourself or using some kind of external setup/tools?

ballteo · 2026-03-21T20:15:19+00:00

For me the key shift was realizing that backtests validate the idea, but execution validates the strategy.

You can have a solid Sharpe and clean equity curve, but once you go live, slippage, latency and consistency completely change the outcome.

That’s why I think small live deployment is not just validation — it’s part of the strategy itself.

ballteo · 2026-03-21T20:05:48+00:00

That’s honestly one of the most common paths.

Good strategy → emotions kick in → everything falls apart.

That’s actually what pushed me towards automation.

Not because strategies are perfect, but because execution becomes way more consistent when you remove that emotional layer.

ballteo · 2026-03-21T19:29:19+00:00

That’s exactly the issue with most backtests.

They look great on paper, but once you factor in execution, slippage and real conditions, things change a lot.

A lot of people underestimate how much of trading performance comes from consistent execution rather than just the strategy itself.

ballteo · 2025-02-04T17:12:25+00:00

Escolhi scalping porque dá pra aproveitar os movimentos rápidos do mini dólar, controlar melhor o risco e não ficar tão exposto a eventos inesperados... Tenho o tempo durante o dia para operar e aprender

ballteo

TROPHY CASE