ClementM

You can fully automate investment 'filters' i.e. filter the notes you're willing to invest or not.

I have been doing quantitative data analysis in the investment space for about 10 years.

Happy to hear/talk about methodology if you want to write/talk about it.

I have some details somewhere on my drive. PM me and we can talk

A bit more courtesy would have been welcome. You sound very condescending. And I hope you talk to your clients in a different way!

Let me address your methodology comments nonetheless, which are for the most part unfounded.

* I don't have any finding about annual income. I don't think it is mentionned anywhere in my conclusions.

* "delinquencies and public records has a big impact on returns as newer loans are not aged enough": because I average across vintage, and because I don't average based on volume on the platform, I account for the aging biais.

* "Time is not risk [..] kurtosis etc.": I don't say that time is risk. I suggest the reader to look at the return series through time. Essentially to look at the volatility of the returns ( without pronouncing the word volatility to keep the content accessible to a novice reader). I essentially encourage the reader to visually assess his Sharpe ratio. Which is a good universal risk measure.

* "reconsider average across vintage": averaging across vintage is a first approximation. I acknowledge the fact that a better methodology would be to take a weighted average that matches the amortization profile of a loan.

* I maintain that any statistics you compute in 2006, 2007 or 2008 is less reliable (statistically). Yes it is an important period to have because of the crisis. And this is why I put on the chart. However, you can't compute very reliable returns when you have a dozen of loans to average across.

Anyway, I happy to exchange with you in PM on methodology if you would like to continue the discussion

Hey, i'd love to have a chat. PM me at [email protected] and let's talk

Glad that my findings match yours !

I think it does beat a C.D. from a risk/return perspective. It's probably higher risk than a C.D. but returns largely compensate for it I believe.

To me this is possible because the Lending Club is desintermediating a business that was traditionnally 'high margin'.

There are many pearls to find. It depends on your 'set of preferences'. You want return? you want low-risk ? you care to deploy a lot of money, or not that much?

But I'd say that for starter, anything in the 8%-9% range is a very good deal these days in this environment

Funny you mention ToucanToco. They helped me in debugging the viz.

I did this work for myself at first as I invested some money on the Lending Club.

Plans will depend on feedbacks I receive. If it generates enough interest I will develop the project into something bigger.

Also, it's pretty instructive to look at the Lending Club grading algorithm in details.

They made it public at some point. Now they are a little less transparent about it.

But some details can be found in their SEC prospectus.

I can link that up as well if you guys want.

Look for the Pearl! you can definitely get 8% interest over the long run with a good liquidity on your cash deployed. To me, it's totally worth it for money that you don't need in the really short term

Yes, exactly for all the criteria it is a matter of "the rates compared to marginal increase in risk".

Look at the 'A' grade. They're nice and safe intuitively, but in my opinion they're not a really good investment.

I'll update the post and put a link to a github

The code to process the lending club data is done in python. I got the full history of all payments made on the platform and pre-process it to have something that's light enough to be explored with a good user experience.

For the viz', yes I used DC.js, I can open source the .js if you guys want it.