Top ten crypto by potential ROI

Screening Filters

1. market_cap: {min: 500,000,000}

   • Purpose: Focus on mid‑to‑large cryptocurrencies, excluding very small / illiquid coins.
   • Rationale:
     • The user wants “top ten cryptocurrencies by potential ROI.” In crypto, a high potential ROI is often associated with more speculative, smaller caps, but going too small quickly leads to extreme risk, manipulation, and unreliable data.
     • Setting a minimum market cap of $500M keeps us in a universe where:
       • Price data and forecasts are more reliable.
       • The coin has some established adoption and staying power.
     • This is a compromise between seeking higher upside than mega‑caps while avoiding “lottery ticket” microcaps.

2. turnover_24h: {min: 20,000,000}

   • Purpose: Ensure that only actively traded cryptocurrencies with good liquidity are included.
   • Rationale:
     • High potential ROI is meaningless if you can’t enter or exit positions at a fair price.
     • A minimum 24‑hour trading volume of $20M filters out thinly traded tokens where:
       • Slippage is high.
       • It’s harder to execute meaningful trades without moving the market.
       • Prices may be easier to manipulate.
     • This aligns with the user’s goal by focusing on coins where a high‑ROI thesis is practically tradable.

3. one_month_rise_prob: {min: 50}

   • Purpose: Select cryptocurrencies with at least a 50% model‑estimated probability of rising over the next month.
   • Rationale:
     • “By potential ROI” implies we are ranking by expected or forecasted return, not just size or popularity.
     • A minimum rise probability of 50% ensures we are not including coins where the prediction model believes downside is more likely than upside in the near term.
     • This does not guarantee a gain—it just sets a probabilistic filter favoring assets with a higher modeled chance of positive performance.

4. one_month_predict_return: {min: 0.0000001}

   • Purpose: Require a positive expected one‑month return, even if very small.
   • Rationale:
     • To rank “by potential ROI,” we must first exclude coins where the model expects negative or zero return.
     • Setting the minimum slightly above zero guarantees that every coin passing the filter is modeled to have some positive return potential over the next month.
     • After this filter, we can sort the remaining coins by predicted return to get the “top ten” by estimated ROI.

Why Results Match the Request

• The filters first create a universe of tradeable, established cryptocurrencies (market cap and turnover filters), avoiding illiquid or extremely speculative tokens.
• Within that universe, we focus on coins the model expects to rise, both in terms of probability (one_month_rise_prob ≥ 50) and magnitude (one_month_predict_return > 0).
• From that refined set, the system can then select the top ten by predicted ROI, aligning with the user’s request for “top ten cryptocurrencies by potential ROI,” while using risk‑aware constraints to keep the list realistic and investable.