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I've always felt that blind DCA leaves money on the table, so I built a backtesting tool to see how much optimizing DCA (using sentiment) actually improves returns.

For example, in the screenshot, a combined strategy outperformed a normal DCA by over 100% in a 1-year backtest.

I'd love to hear what the community thinks about the retail Google trends metric or if there are any other open-source APIs I should be pulling from.

Hace mucho trabajo en el DCA, el mejor rendimiento a medida que pasa el tiempo es el diario (después el semana, bi-semanal y/o mensual) son similares

Para que tomes en cuenta sumar el diario

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Hace mucho trabajo en el DCA, el mejor rendimiento a medida que pasa el tiempo es el diario (después el semana, bi-semanal y/o mensual) son similares

Para que tomes en cuenta sumar el diario

Thank you. This is great feedback!

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1 sat \ 0 replies \ @balthazar 23 Mar -50 sats

On the data sources question specifically:

Google Trends caveat: It's a lagging indicator — people search after seeing the price move, not before. Still useful as a retail temperature gauge, but don't expect it to front-run price.

Free/open-source APIs worth looking at:

  • https://alternative.me/crypto/fear-and-greed-index/ — free REST API, updated daily, composite of volatility, momentum, social volume, dominance, and trends
  • mempool.space API — for on-chain fee pressure as a proxy for demand
  • Blockchain.com stats API — free historical data for active addresses, transaction volume

On-chain metrics that tend to lead sentiment:

  • MVRV ratio (market value vs. realized value) — spikes above ~3.5 have historically aligned with tops; free data from LookIntoBitcoin
  • Funding rates on perpetual futures — available from most exchanges' public APIs; extreme positive funding often precedes corrections

One thing I'd watch for in backtests: sentiment-weighted DCA can underperform in prolonged bear markets because sentiment stays low for extended periods, causing you to over-invest into a continuing decline. Worth stress-testing against 2018 and 2022 specifically.