Introduction
Lending Club is a peer-to-peer lending website. It receives and screens loan applications from borrowers, places them into grades (low-interest, low-risk to high-interest, high-risk), and posts these loans online along with information on the borrower. Investors deposit money, then buy shares in $25 increments in the loans. The borrowers make monthly payments for 3 or 5 year terms. For the borrowers, it is a place to get better rates than elsewhere. For investors, it is a place to get higher returns than in the stock or bond market.
Data on past loans is made available on the website, which opens up the possibility of various types of statistical analysis. I became interested in doing some analysis about a year ago and have worked on the project over the course of around 6 months.
Evaluation
What made the project attractive to me? The website advertises fairly good results of average investors. In other words, just buying loans at random has a decent average rate of return, given diversification. So a statistical edge only improves on this rate of return.
Actually, to be more precise, we need to consider the concept of uninformed and informed investors. In the stock market, the average person is an uninformed investor. They don't know anything special about any stock price, so the best they can do is invest in index funds. That is, they invest in a pool of many stocks to avoid the risks associated with individual stocks ("diversification"), with the assumption that the stock market as a whole tends to go up. Therefore, stock indices are often used as a sort of benchmark for the performance of other investments.
Informed investors/traders know something about stock prices due to expertise or research. They aim to get returns exceeding the benchmark. They don't tend to diversify as much, because they are confident they can pick winners and losers. Moreover, they usually only have an edge on a small set of securities. For example, stock analysts tend to focus on a single stock, and would only trade on that one stock.
Uninformed or informed, an important fact of investing or trading is to not compete against somebody better informed. As the poker saying goes, "If after X minutes at the table you don't know who the sucker is, it's you". In order for an trader to get above-average returns, somebody else must get below-average returns. In the context of Lending Club, how this would happen is that well-informed investors will snatch up good loans quickly, leaving bad loans for others.
Though I can't say for sure, it seems that Lending Club investors tend to be uninformed. Most bloggers and forumites seem to advocate intuitive criteria for investing. Some stats bloggers have done good work on various aspects of Prosper (another P2P lending site) and Lending Club data, but I have yet to come across any mention of a full investment model. There are some institutional investors, and undoubtedly there are some quiet investors with good picking strategies, but heuristically it seems unlikely that investing on Lending Club is currently competitive. There's not really that much room for profit for big players; the total amount of outstanding loans these days is less than $10 million. There's no way to borrow on margin and leverage (i.e. I would like to invest in $500 in loans with $100 in my account, but I can't, whereas I could on the stock market). Therefore, I doubt that any group of investors is systematically snatching up all of the good loans.
Risks
What risks are present, and can they be avoided or mitigated?
1. Individual risk: Any given borrower can default (fail to repay the loan) or repay the loan early (reducing the interest return). This is actually a non-issue since it is what is considered by the model.
2. Financial risk: Some macroeconomic effect could cause interest rates to go up or a large amount of borrowers to default all at once. This can be mitigated by some sort of hedge on the stock/bond market.
3. Model risk: I screw up my model and it gives me bad results, perhaps because of overfitting. I can eliminate this by backtesting.
4. Institutional risk: Lending Club goes bankrupt and all outstanding loans are left hanging. I believe this is no longer an issue because Lending Club has an agreement with another company that will service the loans if this happens.
5. Institutional risk (again): Lending Club suddenly lets the quality of its loans drop. I don't think this is likely since they have been careful to reject most loans, even during a time of rapid expansion.
Sounds promising. More later.
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