4 factors to measure the performance of a trading system:

1 - Accuracy
There is no such thing as 90% Accuracy without compromising on other factors (like profit factor, etc)

Fact - A good trading system will have only 35-60% accuracy without compromising other factors.

(1/n)

2 - Profit Factor (PF)

It is similar to risk-reward. It is derived using the below formula:

Profit Factor = Total Profit by winning trades / Total loss by losing trades

Fact - A trading system above 1.2 PF is good if it scores well with other factors.

(2/n)
3 - Maximum Drawdown

The maximum drawdown also plays a vital role psychologically while picking a trading system.

Fact - Maximum Drawdown in any trading system should not exceed 20%. I suggest picking only the techniques which have less than 10% maximum drawdown.

(3/n)
4 - Maximum Consecutive Losers

We all feel bad even if we lose only Rs.1,000 in a trade. Because it is not only about the money, it is emotionally difficult to accept the failure.

Fact - A good trading system will have less than 15 consecutive losing trades.

(4/n)
TRADE LIKE CRAZY

10 Profitable Intraday Trading Systems, which are backtested against 10-years of Banknifty Historical Data!

(n/n)
https://t.co/BuUie17Ish

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Recently, the @CNIL issued a decision regarding the GDPR compliance of an unknown French adtech company named "Vectaury". It may seem like small fry, but the decision has potential wide-ranging impacts for Google, the IAB framework, and today's adtech. It's thread time! 👇

It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details):
https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha

I've read it so you needn't!

Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.

The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.

Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.