Birth of Alpha & K

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Creation of the first French fiduciary & evidence-based financial advisor

Dear readers,

A little personal message today. Just today.

I am very happy to announce the creation of a the first fiduciary financial advisor in France, Alpha & K. We are launching this company today with my partner and friend Philippe Maupas (Twitter account and LinkedIn account). And I just want to present it quickly to you…

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What about your mother ?

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Financial analysis education became too analytical and de-humanized. It needs  to get back to more balanced, human, basics.

3 years ago, as every year for 8 years now, I volunteered as a “mentor” in a student financial analysis contest known as the “CFA Research Challenge”. During the French final, one of the student team was confronted with a very harsh and deep-meaning question about investment, a question they did not expect, a question they should have been taught about.

It was memorable because, while anecdotic at the time, it reached to something bigger, a problem that undermine the way young investment professionals (and some older) relate to their job. A question about the meaning of it.

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Bitcoin, or the inelegance of technology

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Blockchain is a very promising technology. But for now it is young, flawed and still a bit inelegant.

A tech-addict friend of mine recently confessed to me the frustrating pain he felt when he desperately tried, a few weeks ago, to explain the concept of elegance in technology to his smirking colleagues. I padded him he back with compassion, and thought : “OK I will have your back on this. I will write about it”.

Meanwhile I thought about it and realized : “Holly cow ! There is no better example to explain this than to talk about cryptocurrencies !”

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A battle is lost, war is not over

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The asset management lobby just won one more battle in France. The transfer of life insurances between insurers still won’t happen… for now.

You probably missed it completely, but a few days ago a battle of the highest importance for French investors and the French economy took place. It was short, it was brutal.

Indeed, last Thursday, two brave MPs, Amélie de Montchalin and Joël Giraud, proposed, finally, to allow, finally, French life insurance plans to be transferable.

I do know what you think now: “Wwoooo… This post is going to be so boring…

Think again ! On the contrary, it is of upmost importance for French and worldwide investors to read this as a reminder of what is currently at stake and why we fight !

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Global warming. What can we really do about it ?

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Global warming is frightening, and hope is thin to contain it. So maybe we should start not only fighting it, but also preparing for it.

In my last, and more obscure, post about data-mining bias ( that you should of course read, see here ) I illustrated my argument with the example of extreme weather news reports. To sum it up, my point was that while the increasing regularity of extreme heat/frost waves is probably a consequence of global warming, one separate occurrence was absolutely not sufficient to prove anything about it.

In the meantime however, summer passed in the north hemisphere, and it was hot. Damn hot all around. And while still not proving anything “by itself”, it did make me think about global warming. And I am sure you did too.

Global warming is here. No doubt. What was once upon a time a scientific theory became a few decades ago a scientific and political issue. Now it is starting to turn into a scary and material reality for everyone. And it is probably just the beginning.

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Beware of the vicious data-mining bias !

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Scraping large amount of data can lead you to a big mistake. Here is why, and how to avoid it.

In my recent “quiz” about technology, I mentioned that finding usable data buried under mountains of useless one, the activity called “data-mining”, was a perfect application for artificial intelligence and especially neural networks.

But I also mentioned that this activity might also present a huge caveat, a logical bias that we should all be aware of. This bias, very unsurprisingly named “data-mining bias”, is what I want to talk about today.

So let’s talk about this scary “data-mining bias”.

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ESG investing – How to improve it

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This post was originally published on October 11, 2016 on my company website. It is still relevant and interesting for those who have not read it yet. I’m posting it here with some minor updates.

Environmental Social and Governance (ESG) investing is a good concept, and its growth is strong. But are the desired goals achieved?

 

It had been a while since I wanted to look at it more closely. Environmental Social and Governance (ESG) investing has always sparked interest in me, even though it was unfortunately a little bit confidential. I always saw it as a very welcomed way to link investment and finance in a positive way.

This is why I gladly accepted when I was offered to go to the “Responsible Finance Workshops” organized by a French company specialized in this investment field.

Environmental Social and Governance Funds (ESG) choose their investments according to financial criteria and social criteria. For most of them, this is expressed in practice by a refusal to invest in companies that are not respectful of the environment, or have a bad carbon footprint, or are not very respectful of their employees. The variations are numerous, but globally those funds have a discriminating approach of investment: they refuse to buy the lame duck.

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Spring break hot tech quiz

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Summer is coming up. It is about time to check what you really know about the techs that “might” replace you during your vacations.

 

I hear about “technology” all the time. All finance professionals around me seems to be very excited about it, and eager to take full advantage of it, or at the opposite, scared it might eventually make their job irrelevant.

But when I scrape just a little bit under the surface, for both of them, I realize that most of them often don’t really know much about it.

I don’t know much about it either. And this is why I constantly read and watch on various tech subjects in order keep up. This is hard and time consuming but I do think it is unavoidable, and that everyone should do it.

So here is a quick and modest ( I do not pretend to be an expert in those subjects ) little quiz that will check your “basic” knowledge about the 3 main “hot techs” of this spring in service driven industries : crypto & blockchain, artificial intelligence and quantum computers.

It won’t cover much, it won’t give you every information you need. But I do hope you will find it interesting, and that it will help you get interested and further pursue a better understanding of those subjects and the various myths that surround them!

Oh and don’t be scared about the first question ! Every bit of explanation is in the answers…

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How can they possibly still like Trump ?

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Trump’s popularity is still surprisingly high. How can we explain it, and what can it teach us about populism ?

Until very recently I was stunned. I just wasn’t getting it. It was such a huge mystery to me. How, how on earth could a great part of republican Americans still like Trump ? This is how I ended up thinking about it and trying to understand.

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The great ETF dissection of active funds

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Active mutual funds can be mysterious black boxes. Here is a method to sneak a peek inside.

Mutual funds are very opaque structures. There is so much we don’t know about them, so much we are refused to access, even when we invest in them.

It is indeed very hard to access the actual composition of their assets (the individual stocks or bonds they own). This information is barely disclosed by managers for various reasons. They might fear to see their ideas and work “stolen”. They might fear being criticized for every decision they make. They might even fear that everyone realize they charging active fund fee level for passive management (which is called “closet indexing”, and is very bad, look out for it).

The main information they often give us about what we really own, is the “benchmark”. This benchmark is supposed to be a good proxy of the fund asset composition and potential risks. But most of the time the benchmark they choose seems a bit off or even misleading. It is always an index, and is therefore very theoretical, but it is not its biggest flaw.

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