Portfolio Construction

The second part of the Lending Club analysis involves what I already own. My goal for the portfolio is to own a duration laddered portfolio with a geometric weight on grades. That’s a serious mouthful so let me describe each part.

Since I am only investing in 36 month loans, the loans I expect to own have a duration of 36 months to one month. I would prefer to own an equal amount for each month on the duration ladder. That sounds simple enough but these loans pay down principal like any other loan which means it will take exact accounting to validate the purchase.

Weighting based on grades is more complex. The charge off rate increases as the grade gets lower. This is expected and validates the grade. I want to minimize my exposure to loans that will default (be charged off) and that means holding a larger amount in the higher grades. In looking at the 2012 – 2013 loans, the charge off rate versus grade approaches a line. There is an academic realm of consumer behavioral expectations that I would like to explore regarding credit, but this is designed to be about me.

If I were to accept a normal amount of risk, I would weight linearly along the grade scale. However, I am not willing to accept a normal amount of risk due to my age and retirement horizon. Thus, I have decided to use a geometric scale to establish a weighting pattern. The result is a weighting pattern where the highest grade has a target weight 19 times higher than the weight of the lowest grade.

So my routine becomes a simple pattern of downloading the loans for sale, filtering based on my criteria, sorting by the highest discount rate, and determining if the note would fit into my portfolio. Given the bandwidth I have access to, this should take less than five minutes each day.

As an aside, I am a little concerned about the amount of effort I will have to put into this, specifically on the accounting side. Each time a note posts a payment, I’ll need to markdown the principal that is paid. The purpose is to keep the amount available for each duration period accurate. At first I thought there would be only 36 loans — one for each duration period. Then I realized as principal is paid down, I can go into the secondary market and purchase smaller loans to back fill that period. Suddenly, the number of loans I would be owning became a number large and unknowable.

I think I should be able to keep track weekly and it should take less than an hour, but that will depend on whether there is seven loans with payments or seventeen. I really want to only do this weekly. It will match up with the weekly work I perform on the equity side of the portfolio. This will be an interesting experience as I continue learning about peer to peer lending.

Risk Analysis

When I started considering my investment into Lending Club loans, I wanted to choose 36 month loans only. Because these are unsecured personal loans, sixty months seemed to transfer too much risk to me as the lender. That also matches with my personal philosophy to borrow short-term and as cheaply as possible.

I gathered all of the loans from 2012 and 2013, which Lending Club freely makes available, to analyze how 36-month term loans were performing. There are a surprisingly large number still making payments, but it was the Charged Off portion I was most interested in. My goal in this endeavor is to limit my risk, specifically by choosing loans from borrowers least likely to default. For the total pool of loans, 16% were Charged Off.

There are a few data items provided with each loan that give a little bit of information on the purpose of the loan and the background of the borrower. By looking into each item, there might be some useful information to narrow down the list of loans. A data scientist would likely perform a Principal Component Analysis, a look at each independent variable to create a coefficient for a linear equation to determine a predicted value for the dependent variable. Instead, I wanted to do this for a specific subset of variables and I think minimizing risk is a different set of identifiers. We will get into those.

The first variable I wanted to look at was the purpose of the loan. I’ll call this the Category of the loan. There are seven principle categories. In looking at other’s analyses, Credit Card and Debt Consolidation were categories that were possible problems. I also found commentary that people would take personal loans to pay down credit card debt, but would build the card debt back up while paying down the personal loan. As a lender, I have no issue with that. It is a behavior problem that I do not mind as long as they remain current on the loan I own.

In my analysis, four of the categories showed much lower charge off rates. One of those was Credit Card. For these four Categories, the charge off rates were lower for the first six of the seven grades. For the other three categories, the lower charge off rates were only valid for the first three grades.

The result of this took the 16% default rate down to about 14%.

The next variable I looked at was employment length. I don’t really care what the job title is since that can be somewhat misleading. The key to me was an employment length of N/A. This could be because of unemployment, retirement, or privacy wanted by the borrower. In any event, when I looked at charge off rates, the N/A selection was significantly higher than a number in this field. Adding this into the filter brought the charge off rate down to about 13%.

A third variable was Home Ownership. There are five selections here — rent, own, mortgage, none, and N/A. The None and N/A bothered me and the analysis showed these two were clearly different from the other three selections. Including this variable to the filter brought the charge off rate down to 11%.

The final variable I examined was one I created. By taking the annual installment amount and dividing it by the annual salary, I created a payment ratio. I used a simple histogram to show the charge off rate by payment ratio and the was a jump condition if the payment ratio exceeded 7%. Adding this variable to the filter brought the charge off rate down to 9%.

There were a few variables that provided no differentiation — salary and amount borrowed to salary. Both showed some randomness to the output indicating they are likely not a factor towards creating a charge off situation.

Adjusting the charge off rate from 16% to 9% by filtering on a few variables feels like success to me. I had written this analysis up using R and looking at loans for sale on the secondary market. There was quite a bit of manual activity to get through the list. I spent a few minutes converting the program over to accepting a CSV file of the loans for sale and then running the filter. The final step was to sort the loans based on their discount value.

People sell loans for all kinds of reasons but for those who have an urgent need to sell, I am happy to take their loan at a good discount. This is step one. Step two is to look at two characteristics of the loan to see if it fits with my portfolio. That will be the next post.

July 2016 Wrap

After announcing that I had no interest in making purchases on the secondary market, less than one week later, I had made two purchases. Prices on the secondary market are really quite diverse. There are some extraordinarily large premiums associated with some loans and some have very low premiums. I looked at the list of offered securities twice in the month and found none that were offered below par.

While I did purchase two very small loans, each had a premium of less than 2%. While that wasn’t a threshold, I now have an understanding of the secondary market. Purchases settle the next business day, which is as expected. These two fractional loans had a low premium even though the credit rating of the underlying payer had improved. I spent some time trying to figure out prices, but seemingly they were random. Maybe someday I will attempt to sell a loan and see if the system reminds me to update my price. My point being that perhaps these prices were stale.

Of course, people may have placed high prices on their loans just in case someone else was willing to pay it. Like a couple of homes in our neighborhood, it seems the seller is willing to sell but only at a specific price. Zillow calls that the Make Me Move price. I could put an amount on our home, but my wife and I are not at that point. Still, what would be the harm in placing a price that is double the current estimated value?

The new issue that I posted about two weeks ago was funded and issued. That means my portfolio consists of fractional ownership in three loans. My target is to have a portfolio of loans maturing monthly spread across 36 months. By purchasing a new issue plus another on the secondary market with 24 months to maturity, I can reduce the time to create the duration based portfolio from three years to two years. I could reduce it to one year by purchasing loans on the secondary market with one year left to maturity, but the market had extremely small principle amounts for sale. Constructing a list of fractional loans to reach my monthly principle objective seemed too time consuming. For now, I will accept the hole in the duration portfolio. Perhaps looking at the secondary market in August will provide a clue on how to work through the construction of that point in the duration curve.

To close the month, one of the loans purchased on the secondary market had a payment due. It successfully was paid on time. Lending Club takes a fee from the borrower upon loan origination and from the lender at each monthly payment. The loan origination fee seemed high to me and the monthly processing fee seemed low. Of course, the monthly fee happens every month, which is one of the annoying features of our banking system. It was too much for me to hope that Lending Club would be that different.

First Order

The Lending Club account was funded this morning and this afternoon I placed my first order. There is quite a bit of money in the account and I want to create a laddered portfolio. So my first order was just a fraction of the total portfolio.

One alternative I had considered was purchasing on the secondary market. Lending Club allows purchases and sales of individual loans through folioFn. It’s an interesting marketplace where people have placed portions of loans for sale and put their own price on the item. It reminds me of the homes for sale in my neighborhood where some prices are high and some are priced for sale right now. The site shows the Yield to Maturity which helps show where the price is set.

I decided not to follow that idea because the amounts of the loans are set by the original purchase and the remaining value. Given the value I want to have mature each month, it sure would be difficult to figure out what to buy and what priority to put on each. I imagine I could do it, but the amount of time it would take seems daunting.

That makes an interesting point that any purchase I make I should plan to hold on to the loan until maturity. I have structured the portfolio with that in mind. Three years is a long time and plenty to change my mind.

The first order I placed was for a person in Maryland looking to buy a car. I will have a very small portion of the total loan once it is fully funded. Updates to come.

Education Stop and New Frontier

The possibility of pursuing a doctorate came to an end. The educational institution estimated it would take ten to fifteen hours per week to work on the program. I could possibly do ten hours, but there is no way I could do fifteen hours since I already have two jobs. It was a fairly brief discussion with my wife and she agreed that I should not pursue it (something about wanting to see me occasionally). And thus ends the pursuit of another degree.

Recently, I have been looking into making a significant change in my investment portfolio. I have two parts of the portfolio that aren’t really investments, but instead are catastrophic insurance — bitcoin and gold. Neither gain interest and are only truly useful if people lose confidence in legal tender from federal reserve banks. While we have moved well past the financial crisis of 2008, only recently have I actually begun to think the end isn’t near. I think part of this should be credited to Torsten Slok from Deutsche Bank. I have far too many investment emails which portend the end of the world. Torsten has been making the case for over a year that inflation isn’t coming and the economy is stable and growing nicely. It has been interesting to see how my view is changing as I realize I should focus on the current investment landscape rather than worry about an end that is always somewhere out in the foggy future.

So I am going to sell my bitcoin and gold. Also for just about a year, I have been reading about peer to peer lending. Three companies stuck out — Lending Club, Prosper, and Payoff. Lending Club recently had an ethical crisis and has come out of it well positioned and likely sounder institutionally. This fits with the rest of my investment philosophy to buy when others are selling and sell when others are buying. I know that’s easy to say, but it can be easy to structure a buy and sell strategy with technical indicators to follow that mantra without emotion.

Peer to peer lending has been interesting to me for a few years. I have begun to question the banking system which has extraordinary rates for credit cards and equally extraordinary rates for savings accounts. I have mentioned many times in this space the horribleness of the financial repression we have been under for six years now. I have decided it is time to drop the investment direction of another financial collapse and to invest in people.

There is a fair amount of risk in peer to peer lending since a person with a loan can stop payment or default. I can accept that since I am not buying a government bond. The three companies I mentioned have spent some effort to filter out buyers with troubled pasts and have graded accepted requests based on multiple criteria. I suppose this is a simplified version of what banks do when I request a loan for a car or a house. Some of the requests I have seen on Lending Club are exactly for those items.

I will need to spend some time to work through each loan request to see if it matches my own feeling of safety. I have considered writing here about my experience of making a choice, of watching it over time, and seeing it either mature or become an issue. Obviously, the default rate is quite low or this type of financing wouldn’t work. I’ll start dipping my toe in the water next week when the funding of the account begins.

Next Education Opportunity?

I am looking into the possibility of pursuing a doctorate in business administration from City University of Seattle. It is a four year program. Goodness! this is a huge time and money commitment. It will take away all free time and really focus me into a particular line of thinking. I don’t know how I can pursue the degree while handling two jobs. I’m surprised I am even considering this.

Meanwhile, my main job is forcing me to learn SOA (Service Oriented Architecture), RFID data analysis, and blockchain technology. The coalescence of these technologies is leading me to think there is another major internet based revolution in the conduct of business coming very soon (less than five years now).

I have a lot to learn about the degree program. It sure seems like I could pursue the degree while learning these technologies on the job and how they impact business would be part of the dissertation.

I keep telling myself I need to use my blog to consolidate my thoughts. This may become even more necessary as I become busier.

Data Science Software

I have been using the Anaconda release of Python 3.x for a few months. The package updater makes it easy for the maintenance part of my computer. I have been playing around with integrating Python and R and tonight installed the package r-essentials with the command:

conda install -c r r-essentials

Obviously, this post is for myself so I do not forget that command. This should keep me busy for awhile.