Quote from: Text on October 18, 2024, 07:39:35 AM

I think combining a mix of trend-following indicators with momentum-based ones can help balance signals, especially across different timeframes. For instance, Bitcoin often responds well to long-term EMAs, while some altcoins might benefit more from oscillators on shorter timeframes. However, I've noticed that different coins react differently to these indicators.

Combining indicators can indeed be tricky. Many traders find success using a blend of MAs, RSI, and MACD for different coins. Each coin has its own quirks, so you might need to fine-tune per asset. Consider backtesting with historical data to find the best combinations.

I’ve tested around 30 different indicators and calibrated them for various timeframes and the lifespan of each instrument. The results were mixed: some coins always showed sideways movement, while others, like STRK, predicted a +20% gain just before a pump. In fact, when 90% of the coins indicate a long, a long actually happens.

However, the issue is that the AI struggles to accurately pinpoint the start of local corrections. It feels like something is missing...

Quote from: Synchronice on October 18, 2024, 02:16:45 PM

Quote from: lets.trade on October 16, 2024, 01:40:22 AM

The AI already uses basic indicators, but I want to figure out how to combine them. Or maybe use all of them at once, it's still unclear.

I'm open to a public test and am trying to launch a beta version, but I don't have enough resources yet.

Thanks for the idea about open-source trading bots, I hadn’t thought of that before.

What does AI mean in this case? I'm afraid it's a buzzword to gain attention.
Is your AI forecaster really an intelligence? Can it check Elon Musk's twitter, read his posts, analyze them (if he posts about Doge going to the moon) and make a prediction? I want to know what's AI in your software, is it capable to think on its own?
I think that you should train your AI to check different indicators, make a prediction on each coin with each indicator and then it will collect the data about which indicator works best for which coin. If that's truly an AI, then it should be able to achieve that level itself.

It's indeed AI, if we can even say that ML equals AI.

The logic of your AI is correct, but that's not how it works. A simple language model can't function the way you describe; everything needs to be built modularly.
First, you need to calibrate the pattern recognition in regular price fluctuations. Sentiment and news analysis is the second module, but that requires more power, like Amazon or Google Colab.

There are also modules 3 and 4, but that's another story.

Quote from: DenBlad on October 18, 2024, 07:05:35 AM

Quote from: lets.trade on October 16, 2024, 01:40:22 AM

The AI already uses basic indicators, but I want to figure out how to combine them. Or maybe use all of them at once, it's still unclear.

I'm open to a public test and am trying to launch a beta version, but I don't have enough resources yet.

Thanks for the idea about open-source trading bots, I hadn’t thought of that before.

what resources do you need?

I need a PC (2x4090, 128GB RAM) that can process the maximum dataset in under one minute. Right now, it takes about an hour.
The AI is already operational, but it's currently working with a dataset that has limited price history detail.

Here's the link: https://t.me/ai_lets_trade_1h

Every hour, it gathers new market data, trains on it, and sends a report to the channel. However, the report is incomplete—it only includes the minimum and maximum forecasted prices.
In reality, the forecast represents a continuous stream of prices. The module that will display this is still under development, as is an additional AI that will analyze the forecasts generated by this AI. Grin

If you have any suggestions or feedback, please feel free to provide them. I am always open to constructive input.