Best 12 hour crypto Prediction

Context & Limitations

• You’re asking for the best 12‑hour price prediction for AAVE (a crypto).
• The screener, however, is set up with 1‑day (24‑hour) prediction metrics and is generally designed for stocks, not specifically for crypto.
• Also, no model can give a guaranteed short‑term price move; what we can do is show probabilistic 1‑day forecasts, which you could use as a rough proxy—though it’s not the same as a true 12‑hour forecast.

Given that, here’s how the chosen filters relate to your request.

Screening Filters

1. one_day_rise_prob: {min: 0, max: 100}

   • Purpose:
     This field represents the model’s estimated probability (in %) that the asset’s price will be higher 1 day from now than it is currently.
     Setting the range to 0–100 effectively means: “Include all assets, regardless of their 1‑day rise probability; do not constrain on this metric.”
   • Rationale:
     • Your question is not “find only assets with a high chance of rising,” but “give the best 12‑hour prediction for AAVE.”
     • To answer that, we don’t want to filter out AAVE just because its modelled 1‑day rise probability might be low or high; we want to see its prediction metrics as they are.
     • Using the full 0–100 range ensures AAVE will be included, and then the system can display its 1‑day rise probability as part of the prediction context.

2. one_day_predict_return: {min: -100, max: 100}

   • Purpose:
     This field is the model’s expected percentage return over the next 1 day (e.g., +5% means the model expects a 5% gain in 24 hours).
     Setting the full range -100–100 again means: “Do not exclude anything based on predicted 1‑day return; allow any prediction from a total loss to a doubling.”
   • Rationale:
     • You’re not asking to screen for only strongly bullish or bearish names; you’re asking for the specific prediction on AAVE.
     • A tight range (e.g., only assets with expected return > +3%) could accidentally exclude AAVE if its modelled return doesn’t meet that threshold.
     • By using the full possible range, we ensure AAVE’s prediction is available, and you can then see its expected 1‑day return, which is the closest available proxy to a 12‑hour forecast in this setup.

Why Results Match Your Intent

• Ticker‑specific focus rather than filtering for performance
  The filters are intentionally non‑restrictive (full ranges) so the system doesn’t try to “optimize” or cherry‑pick assets; instead, it just retrieves AAVE (and potentially others) and exposes its prediction metrics. This matches your goal of “what is the best prediction for AAVE,” not “which assets have the best prediction.”

• Using available horizon (1 day) as a proxy for 12 hours
  While you asked specifically for 12 hours and the model only has 1‑day prediction fields, the filters surface AAVE’s short‑term (1‑day) probability of rising and expected return. Those are the closest available quantitative estimates to a 12‑hour prediction within this framework.

• No artificial optimism
  Because we’re not narrowing on “high rise probability” or “high predicted return,” the system isn’t forced to return only bullish scenarios. You see the model’s unbiased 1‑day view on AAVE, which is the most honest form of “best prediction” we can provide.

If you’d like, the next step would be to interpret those 1‑day metrics (once you see the actual numbers for AAVE) in terms of risk, reward, and how cautiously to treat them relative to your 12‑hour trading horizon.