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Financial Astrology Crypto ML Daily Trend

This daily trend indicator is based on financial astrology cycles detected with advanced machine learning techniques for the crypto-currencies research portfolio: ADA, BAT, BNB, BTC , DASH, EOS , ETC, ETH, LINK, LTC, XLM , XMR, XRP, ZEC and ZRX. The daily price trend is forecasted through this planets cycles (angular aspects, speed, declination), fast ones are based on Moon, Mercury, Venus and Sun and Mid term cycles are based on Mars, Vesta and Ceres . The combination of all this cycles produce a daily price trend prediction that is encoded into a PineScript array using binary format "0 or 1" that represent sell and buy signals respectively. The indicator provides signals since 2021-01-01 to 2022-12-31, the past months signals purpose is to support backtesting of the indicator combined with other technical indicator entries like MAs, RSI or Stochastic . For future predictions besides 2022 a machine learning models re-train phase will be required.

The resolution of this indicator is 1D, you can tune a parameter where you can determine how many future bars of daily trend are plotted and adjust an hours shift to anticipate future signals into current bar in order to produce a leading indicator effect to anticipate the trend changes with some hours of anticipation. Combined with technical analysis indicators this daily trend is very powerful because can help to produce approximately 60% of profitable signals based on the backtesting results. You can look at our open source Github repositories to validate accuracy using the backtesting strategies we have implemented in Jesse Crypto Trading Framework as proof of concept of the predictive potential of this indicator. Alternatively, we have implemented a PineScript strategy that use this indicator, just consider that we are pending to do signals update to the period July 2021 to December 2022: This strategy have accumulated more than 110 likes and many traders have validated the predictive power of Financial Astrology.

DISCLAIMER: This indicator is experimental and don’t provide financial or investment advice, the main purpose is to demonstrate the predictive power of financial astrology. Any allocation of funds following the documented machine learning model prediction is a high-risk endeavour and it’s the users responsibility to practice healthy risk management according to your situation.
リリースノート: A signals prevalence to bullish trend was detected in previous version, there was an issue in the ML signals not performing well to detect the bearish trend days. We have tuned the astrology machine learning ensamble model to balance correctly the bullish/bearish trend detection so in this release we updated the signals arrays. With this new version we expect around 57% to 60% accuracy and 55% prevalence (slightly bias to uptrend).

Additionally a little code refactoring was made to improve the array signals to candles mapping and the future days signal plot was converted into future weeks so is consistent with other financial astrology signals we are creating for other sectors. Now you need to indicate how many weeks of future predictions to plot instead of days, by default it display 2 future weeks.

Finally we did some tweaks to support proper display of the indicator in chart resolutions: 1D, 1H, 2H, 3H and 4H, you can use any of this resolution to view the ML signals predictions. The indicator will not plot future predictions and smooth signal in other resolutions so ensure you use one of the fully supported resolutions.
リリースノート: Support lower than hourly resolutions: 45m, 30m, 15m, 10m and 5m, and symbol charts that are based on USD quote instead of USDT (Tether). On intraday resolutions only project 1 week of future data to prevent that recent price chart display empty astro ML signal. Display a fast and slow moving average of daily trend signal to make simpler to find bull/bear energy turning points.

Join the financial astrology research discussions at Telegram: https://t.me/financial_astrology_stats
Contribute to our statistical analysis and machine learning models at Github: https://github.com/financial-astrology-research
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