LMND broke IPO's highest high and will continue to fly!

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LMND the online insurance company with advanced software behind it, went parabolic this week and did a very important step forward - it broke the IPO previous high and all-time high of 95.7.
The stock has broken the first support level towards the end of Oct and has been climbing up in the volume scanners since.

The company has an artificial intelligence-based platform (called 'Maya') that enables the consumer to get a quote on home insurance in less than 3 minutes - tried it myself and it was super quick and simple (this approach is mainly addressing the younger audience).
CEO said in last weeks convention that they intend marketing mainly to people without previous insurance and not existing clients of other insurance companies, as he says it is very difficult to make someone switch insurance provider and the conversion rate will be very low - this is a very different approach than the commonly used marketing approach in the insurance world.
The whole vibe about LMND and the way it conducts itself compared to most insurance companies is fresh!

So let's talk technical:
the stock broke highest high and IPO high and touched 112 - after some correction that can come this week, as it seems at the moment stock will keep rallying, I could be wrong but usually, when a stock has an IPO that shoots up so far and then just gradually falls down a lot, and then it recovers and crosses the IPO highest high it will usually not looks back and we can compare this with a lot of other stocks like Uber, FB, SNOW, and others (see images below).
We expect LMND to give us a pretty big correction first and then rally to 125$ as its next level.

We at FDGT are a strong buy on LMND and whether it will need to correct or stall on its way to its next highest high or not we will wait and keep it in our portfolio cause this company really is stepping up the game in the online insurance world.

UBER Chart - IPO high broken:
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FB Chart :
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SNOW Chart - IPO high broken:
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Trade safe! and happy Xmas
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