The Forever Stamps Arbitrage

The United States Postal Service wants to increase the price of the first-class stamp from 46 cents to 49 cents early next year. Most of the stamps I own are the so-called “Forever” stamps so the price increase won’t affect me. But I’ve always wondered whether there exists a market to purchase these “Forever” stamps in bulk and re-sell them at a tiny discount (of present first-class stamp price) to consumers. Allison Schrager and Ritchie King explore this potential arbitrage opportunity:

Our plan is to buy 10 million stamps at $0.46 each and sell them at $0.48. The margins, of course, are small. If we buy 10 million stamps, spending $4.6 million, we’ll earn $200,000—a 4.3% profit.

The good news is that you can buy up to 1 million stamps in a single order from the USPS, and pay a mere $1.75 in shipping (shipping is their business, after all).

But $4.6 million (or $4,600,017.50 with shipping) is a lot of money, especially for folks like us (an economist and a journalist) who’ve never raised money before and don’t have many assets. Ideally we’d borrow it all at once, but given our limited financial means, securing a $4.6 million loan would be tough, at least at an interest rate that would still leave room for us to make money.

We’d get better terms on the loan if we had some collateral. But all we can offer is the stamps we plan to buy. So the trick is to get our seed funding by selling equity (we’d like to start with $250,000) and then securing loans for the rest using the stamps as collateral. It may seem a little far-fetched, but it’s not all that different from the kind of leveraged trading that goes on in the financial world.

In the past, our journey would probably end here. There’s no way we could convince our friends and family or millionaires to invest a total of $100,000 in this hare-brained scheme. But thanks to the recent US JOBS Act, we don’t need them. We can crowd-fund all of our equity from the general public on sites such as Crowdfunder. This would be our offer: We’ll split the profits 50/50, with half going to our shareholders and the other half to us.

The Big If: ability to move all those stamps (either independently or via a distributor). I think it’s highly unlikely, and the interest on outlaying loans will exceed the income generated from selling the stamps at a tiny profit. Still, it’s a cool thought experiment!

The Hedge Fund Manager Who Loves Losing Money

“You’ve got to love to lose money, hate to make money.”

That’s a direct quote from Mark Spitznagel, an unusual hedge fund manager who is betting on a huge decline in the markets when the Fed stops its quantitative easing program. Needless to say, investors aren’t exactly lining up to invest with him. The Dealbook blog profiles his fund:

Still, Mr. Spitznagel’s approach is unusual for a money manager. To invest with him, you have to believe in a philosophy that is grounded in the Austrian school of economics (which originated in the late 19th century in Vienna). The Austrian school does not like government to meddle with any part of the economy: when it does, adherents argue, market distortions abound, creating opportunities for investors who can see them.

When those distortions are present, Austrian-school investors will position themselves to wait out any artificial effect on the market, ready to take advantage when prices readjust.

Mr. Spitznagel began his career buying and selling bonds in the trading pit at the Chicago Board of Trade in the 1980s. Everett Klipp, his boss and mentor at the time, encouraged him to take a “one-tick” loss to step out of a trade, rather than risking a 10-tick loss in hopes of a bigger profit.

What Happened in the Markets on September 18, 2013 at 2PM?

This is an intriguing analysis at Nanex of what happened in the financial markets (equities and futures) on September 18, 2013 milliseconds before the FED announcement of “no taper” at precisely 2:00PM.

One of Einstein’s great contributions to mankind was the theory of relativity, which is based on the fact that there is a real limit on the speed of light. Information doesn’t travel instantly, it is limited by the speed of light, which in a perfect setting is 186 miles (300km) per millisecond. This has been proven in countless scientific experiments over nearly a century of time. Light, or anything else, has never been found to go faster than 186 miles per millisecond. It is simply impossible to transmit information faster.

Too bad that the bad guys on Wall Street who pulled off The Great Fed Robbery didn’t pay attention in science class. Because hard evidence, along with the speed of light, proves that someone got the Fed announcement news before everyone else. There is simply no way for Wall Street to squirm its way out of this one.

Before 2pm, the Fed news was given to a group of reporters under embargo – which means in a secured lock-up room. This is done so reporters have time to write their stories and publish when the Fed releases its statement at 2pm. The lock-up room is in Washington DC. Stocks are traded in New York (New Jersey really), and many financial futures are traded in Chicago. The distances between these 3 cities and the speed of light is key to proving the theft of public information (early, tradeable access to Fed news).

We’ve learned that the speed of light (information), takes 1 millisecond to travel 186 miles (300km). Therefore, the amount of time it takes to transmit information between two points is limited by distance and how fast computers can encode and decode the information on both sides.

Our experience analyzing the impact of hundreds of news events at the millisecond level tells us that it takes at least 5 milliseconds for information to travel between Chicago and New York. Even though Chicago is closer to Washington DC than New York, the path between the two cities is not straight or optimized: so it takes information a bit longer, about 7 milliseconds, to travel between Chicago and Washington. It takes little under 2 milliseconds between Washington and New York.

Therefore, when the information was officially released in Washington, New York should see it 2 milliseconds later, and Chicago should see it 7 milliseconds later. Which means we should see a reaction in stocks (which trade in New York) about 5 milliseconds before a reaction in financial futures (which trade in Chicago). And this is in fact what we normally see when news is released from Washington.

However, upon close analysis of millisecond time-stamps of trades in stocks and futures (and options, and futures options, and anything else publicly traded), we find that activity in stocks and futures exploded in the same millisecond. This is a physical impossibility. Also, the reaction was within 1 millisecond, meaning it couldn’t have reached Chicago (or New York): another physical possibility. Then there is the case that the information on the Fed Website was not readily understandable for a machine – less than a thousandth of a second is not enough time for someone to commit well over a billion dollars that effectively bought all stocks, futures and options.

The conclusions the authors draw? The announcement was leaked:

The Fed news was leaked to, or known by, a large Wall Street Firm who made the decision to pre-program their trading machines in both New York and Chicago and wait until precisely 2pm when they would buy everything available. It is somewhat fascinating that they tried to be “honest” by waiting until 2pm, but not a thousandth of a second longer. What makes this a more likely explanation is this: we’ve found that news organizations providing timed release services aren’t so good about synchronizing their master clock – and often release plus or minus 15 milliseconds from actual time. Their news machines in New York and Chicago still release the data at the exact same millisecond, but with the same drift in time as the master clock. That is, we’ll see an immediate market reaction at say, 15 milliseconds before the official scheduled time, but in the same millisecond of time in both New York and Chicago. Historically, these news services have shown a time drift of about 30 milliseconds (+/- 15ms), which places the odds that this event was from a timed news service at about 10%. 

Something does sound fishy based on the charts provided by Nanex. I’ve read some of their analyses before and they have been overwhelmingly convincing. We’ll see how this one unfolds pretty soon, I think.

When Gucci and Louis Vuitton Handbags Serve as Collateral for Loans

Say hello to the handbag-backed loan. A company in Hong Kong, Yes Lady Finance Co., provides loans to customers if they’re able to bring in their beloved handbags as collateral.

Yes Lady provides a loan within half an hour at 80% of the bag’s value—as long as it is from Gucci, Chanel, Hermès or Louis Vuitton. Occasionally, a Prada purse will do the trick. Secondhand classic purses and special-edition handbags often retain much of their retail prices.

A customer gets her bag back by repaying the loan at 4% monthly interest within four months. Yes Lady says almost all its clients quickly pay off their loans and reclaim their bags.

The company recently lent about US$20,600 in exchange for a Hermès Birkin bag, but Yes Lady’s purse-backed loans start at about US$200.

This is bizarre, and one of those “markets in everything” phenomena. The best part? Some people try to get away with bringing in fake luxury handbags. You should read the article on how Yes Lady handles those scenarios…

ZestFinance and the Nuances of Modeling Credit Risk

Pando Daily has a post about Peter Thiel leading a $20 million funding round for a four year old company called ZestFinance. Their goal is to better predict consumer behavior. They model more than 10,000 data points and arrive at more than 70,000 potential signals of consumer behavior. This was the most interesting bit in the article:

Not all signals are obvious, Merrill explains, noting for example that the way a consumer types their name in the credit application – using all lowercase, all uppercase, or correct case – can be a predictor of credit risk. Other seemingly trivial data points include whether an applicant has read a letter on the company’s website and whether the applicant has a pre-paid or post-paid cell phone.

ZestFinance had evolved its business model to that of an underwriting service provider to third-party subprime lenders, “exiting the lending business to avoid the appearance of competition with its new partners.” Will be interesting to see if their methodology gains acceptance in the wider banking sector in the years to come.

Read the entire post here.