Three lines of code implementing Argos machine learning to quickly interpret industry news

Author: Zero, Date: 2020-04-23 18:51:02
Tags: StudyMyLanguage

The Argos

https://www.quantinfo.com/Argus/

Blowing the skin

Argus ργος, the one-hundred-eyed giant of Greek mythology The system is an online project of the inventor, after five years of research and development, the whole network monitors the price fluctuations and information related to futures, stocks, options, commodities and foreign exchange. It's been trained hundreds of millions of times using the latest in AI neural networks. It is possible to predict stock listings, predict financial asset price movements, predict S&P 500 index volatility, optimize portfolios, predict price movements based on news headlines.

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Landing

While bullshit is fine, the embarrassing fact is that it's better than this AI-powered Argos, which predicts upselling and downselling. Some people are crazy, and I'm afraid of others, because it predicts the public's mood, their desire to make money, and vice versa.

The strategy

With strong syntax support from the inventor platform, the enhanced version of My language was selected for the most intuitive display effect, the data source returns a decimal from 0 to 1 to describe the probability of a chicken, the user needs to access data from other varieties, the policy code can be modified by changing the variety name in the URL.

Effects

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Finally

If you want to define your own third-party data source, refer to the APIhttps://www.fmz.com/api#exchange.getdataThis is just a demonstration of how to call a third-party data source for backtesting verification, please do not use the real disk!!!


(*backtest
start: 2019-10-01 00:00:00
end: 2020-04-21 23:59:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Bitfinex","currency":"BTC_USD"}]
*)

预测值:DATA('https://www.quantinfo.com/API/Argus/history?symbol=比特币');
预测值>HV(预测值, 5)&&预测值>0.6,SPK;
预测值<LV(预测值, 10)&&预测值<0.4,BPK;

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