SUPERALGOS GOVERNANCE
Data Mining Team Proof of Value, August 2022
We’re super busy, but we never forget you, dear SA friends !
Summer has not seen regular report from the Data Mining team, but the whole team has worked on several projects in preparation for future announcements. But let’s get back to the August Proof of Value of the team !
This time, the whole team has been involved in subkects that only the Data Miners could have studied so brilliantly. From indicators building to preparing the signal broadcasting system, at different levels, everyone contributed !
Indicators
Quantum8 : our dear friend has granted us with a new data mine plus 2 new indicators at the Quantum data mine and Pivots.
In Undulated data mine, he actually built 4 indicators :
- The DIDI indicator consists of three moving averages. The differences between these moving averages are then calculated to produce the long and short indicator values shown on the chart.
- The Percentage Price Oscillator (PPO) is a technical momentum indicator that shows the relationship between two moving averages in percentage terms. The moving averages are a 26-period and 12-period exponential moving average (EMA) (source : Investopedia)
- The Gopalakrishnan Range Index (GAPO) is inntended to measure volatility in a stock or commodity.
- The Qstick indicator is a technical analysis indicator developed by Tushar Chande to numerically identify trends on a price chart.
Pivot data mine :
- The Murrey Math Lines indicator attempts to find the horizontal support and resistance levels of the price action. It works in a similar fashion to Fibonacci retracements and pivot point indicators.
Quantum data mine :
- The HARSI-BB indicator uses the RSI as it’s basis to show strength in a price trend. It then calculates the standard deviation to create a Bollinger Band style plot around the RSI values.
Thomas : I have concentrated my efforts essentially on building original indicators with a reccurent theme : probabilities. My goal was actually to provide SA users with breaking edge tools to avoid mild reactivity of mainly used indicators.
- The Periodic Return Bands intend to provide a stastical estimation of the expected return around a candle by casting the moving average Periodic return with its standard deviation on a long period moving average. It helps to build grid trading strategies as to decipher and/or confirm the trend too.
- The probability adjusted moving average, along with probability optimized trend tracker and enhanced probability optimized trend tracker are a set of indicators based on probability filters to help finding trends and entry points. The trand trackers come also with a rolling analysis of the price extremum to identify turning points. They can be accessed independently or as a whole in different product definition.
- The Density of Frequency adjusted EMA uses the same concept as the probability filters but this time with the frequency distribution.
- The Super Ratio is a totally novel approch of harmonic analysis of the rolling extremum of the price to totally detrend the market and identify with very high success the mean reversion opportunities
- The super divergence indicator, alongside with the enhanced super divergence, use a divergence calculation between high probability filtered and low probability filtered price to point at local trend reversals. The enhanced version uses a very high speed and accurate low pass filter.
- The Harmonic deep divergence indicator analyse local trend reversals deduced from the position of the price, a moving average and volatility bands to give information on the strength of the reversal
Trading Signals and P2P Signal Broadcast System
This month is the milestone where things got real for the trading signals broadcasting system. BlaaSwe and 9808us have started to test the system and are actually exchanging signals literally at 2 locations continent wide distant !
README
After many hours of testing, watching development footage from Luis Fernando Molina and writing a comprehensive README was put together that explains
- How to send signals
- How to receive signals
Please check it out:
https://github.com/9808us/SA-P2P-README/blob/main/README.md
BUGS
The following bugs were found and later corrected :
- If you joined a broadcasted signals when the a buy has already occurred (and waiting to sell), you can’t process the signals. It was believed that you were out of sync and you needed to join when the trading session is holding quoted asset to be able to process everything correctly.
- Error 404 occurred randomly when listening to signals, which stopped the signals from being processed.
- Unknown bug that stopped the sending of signals
- Running different network services on the same network (for instance Testnet) caused errors for Machine Learning Project.
LIVE
Both @9808us and @BlaaSwe have confirmed that the Trading signals work during backtesting but also Live trading.
What’s even better is that it works for both open peer-to-peer networks (for instance Testnet) as well as permissioned peer-to-peer networks.
Conclusion
This month, mainly original or very well polished indicators provided by the Data Mining team with some of the indicators created from days of reasearch and intelligence on tons of market data !
With their collective efforts, BlaaSwe and 9808us have brilliantly demonstrated how the signal broadcast works, debbugged a few issues and wrote the Readme at the GitHub repository.
Keep an eye on the DM team activities on the upcoming months… some mind blowing stuffs are still under engineering process but will soon come to the Superalgos community for an awesome ride !
If you find this work interesting and useful for the project, feel free to put voting power on the Data Mining Team Proof of Work and on the claims of the actors of the project in the Governance system.
Want to join the team and put some claims in the Governance project to earn some SA Tokens?
Come and visit us in our regular channels!
- Superalgos project: https://superalgos.org
- Superalgos Community : https://t.me/superalgoscommunity
- Superalgos Support Group : https://t.me/superalgossupport
- Superalgos Develop Group: https://t.me/superalgosdevelop
- Superalgos Data Mining : https://t.me/superalgosdatamining
- Superalgos Machine Learning Group: https://t.me/superalgosmachinelearning
- On Discord Server: https://discord.gg/CGeKC6WQQb
- Superalgos en Français : https://t.me/superalgos_fr
