Tag Archives: MIT Sloan

What Your Credit-Card Offers Say About You

See the original article on WSJ Experts page>>

credit_card_finances_gettyAs more and more personal data becomes available, businesses are now able to target customers in a personalized and sophisticated way.  On the bright side, that means you can get products and services that are tailored to your needs. As a result, you are much less likely to get catalogs featuring dresses your grandmother might wear. But, according to our research, the downside is that companies can also more effectively target your behavioral weaknesses, self-control issues or lack of attention to the fine print. We find that credit-card companies tend to offer those customers who are least able to manage the complexity of credit-card contracts, the most complex features and hidden charges.

As part of our research at MIT with my colleague Hong Ru, we recently studied over one million credit-card mailing campaigns that were sent to a representative set of U.S. households from March 1999 to February 2011. We devised algorithms to classify the terms of the credit cards and also the advertising material. Studying the wide variety of offers and who received which offer was illuminating. Credit-card terms offered to more financially sophisticated consumers differ significantly from those offered to less sophisticated customers, where educational attainment served as a proxy for sophistication.

The offers differed in both substance and style.  Less-sophisticated borrowers received offers with low teaser rates, more rewards, visual distractions, and fine print at the end of the offer letter. However, these offers also had more back-loaded and hidden fees. For example, after the introductory period, these cards have higher rates, late fees and overlimit fees.

In contrast, cards that are offered to sophisticated customers rely much less on back-loaded fees and instead have higher upfront fees, such as annual fees.  These cards tend to have higher regular annual percentage rates and often carry an annual fee, but they have low late fees and over-the-limit fees and are more likely to carry airline miles as rewards.

Not surprisingly, the worse the credit terms, the more likely they are to appear either in small font or on the last pages of the offer letters.  Similarly, offer letters with back-loaded terms contain more photos and less text, perhaps to distract from the details of the offer—what we refer to as shrouded attributes.

In fact, we found that banks seem to carefully monitor how the use of such shrouded attributes might affect the likelihood that unsophisticated customers will default on their debts. Our study showed that less-educated consumers who have lower default risk are more subject to back-loaded or shrouded fees. We also found that in states where there was an increase in unemployment insurance benefits that help borrowers maintain more stable cash flows in the event of a job loss, banks issued potential borrowers within that state more offers with lower teaser rates but higher late fees and default penalties. Banks also increased the flashiness of the offer letter, with more colors and photos, but moved the information about the back-loaded features to the end of the letter.

Taken together, these results suggest that credit-card companies realize that there is an inherent trade-off in the use of back-loaded features in credit-card offers: They might induce customers to take on more (expensive) credit, but at the same time, they expose the lender to greater risk if those consumers do not anticipate the true cost of credit.

So what’s the upshot of our study? First, you are lucky if you have a good education, since it means that the set of credit cards you get to choose from is already better from the start. But independent of your educational status, consumers should know that they have the power and information to choose well. Each credit-card offer in the U.S. must by law have a text box that contains all the relevant terms of the offer in one place; this is called the Schumer box after Sen. Chuck Schumer of New York.

So the best way to choose a credit card is to literally throw away all the marketing material at the front of the offer and simply focus on the real information in the Schumer box. This is true no matter what your income or education level.

Antoinette Schoar is the Michael Koerner ’49 professor of entrepreneurial finance and chair of the finance department at the MIT Sloan School of Management.

MIT Sloan trek shows MBA students opportunities to work in policy — Valerio Riavez

See the original article on the MIT Sloan Experts Page>>

If you’re interested in policy work at an institution like the World Bank, the Federal Reserve, or the IMF, a PhD is required. At least that’s what MBA students have long thought. However, a recent MIT Sloan career trek to Washington, D.C. revealed that this is no longer the case.

As these institutions don’t typically participate in on-campus recruiting, it can be challenging for business school students to learn about policy jobs. That’s why the MIT Sloan Finance and Policy Club organized a trek for 25 students to Washington, D.C. We wanted to learn more about job options for MBA and Master of Finance (MFin) students, make connections, and get a glimpse of what living in D.C. is like.

We began the trek at the World Bank Group. Most MBAs are familiar with the IFC, which is the private sector development arm of the WB and an active recruiter of business students. However, during this visit we learned that the World Bank Group is also increasingly hiring people without PhDs. The World Bank has an elite program called the Young Professionals Program (YPP) through which it hires and forms the next generation of WB leaders. We were particularly surprised to learn that the majority of YPP hires actually do not have a PhD.

In the afternoon, we headed over to the Federal Reserve where we visited the boardroom and participated in a Q&A session with a senior economist. We sat around the very table where Janet Yellen, Ben Bernanke, and Alan Greenspan made some of the most significant monetary decisions in the history of global economics. For a policy fan, I must admit it was pretty cool.

A takeaway at the Fed was that jobs are mostly reserved for U.S. citizens. Foreign students are generally ruled out unless they are transferred from another central bank through an exchange program. There is a fierce screening process for all jobs at the Fed because it is a central bank and its activities are at the core of national interests.

We also learned how after the financial crisis, the Fed began looking more to private-sector practitioners to work on unconventional monetary policy endeavors to get the economy back on track. When central banks had to design and implement their quantitative easing, they had to rethink how to intervene in financial markets. To do that, they brought in people with experience in the private sector and exposure to financial markets. For students interested in finance at a policy institution, that is an untapped recruiting resource.

In addition to that good news, we saw that this trend seems to extend to other central banks and financial policy institutions, which are increasingly interested in people with business acumen – meaning a PhD is not always required. The governors of central banks still have PhDs, but the world is changing and private sector experience and exposure to financial markets today are crucial for these institutions. As a result, departments involved in quantitative easing are increasingly comprised of MBAs.

We ended our trek with visits to many landmarks in Washington, D.C., including the Library of Congress, the Washington Monument, the Lincoln Memorial, and the Kennedy Center. On our final night, we visited the Saudi ambassador’s home where we enjoyed a traditional Saudi reception and a great discussion about the economy in the Middle East with the ambassador and members of the Washington diplomatic community.

As most of us are still exploring opportunities for after graduation, meeting with MIT alumni in D.C. also helped us have a better grasp of what life is like in the city. After seeing all of the great policy opportunities available to MBA graduates and touring the city, it’s definitely a place to keep on the radar.

Valerio Riavez is a native of Italy and dual degree student at MIT Sloan and the Harvard Kennedy School. He holds a Master’s Degree in economics and previously worked in both the public and private sector in finance. He is co-president of the MIT Sloan Finance and Policy Club.

This is your fund manager’s secret weapon to fight high-frequency traders

See the original post on MarketWatch here>>

Mutual-fund and other asset managers trying to get the best price on a stock purchase or sale face a formidable challenge from fast-moving high-frequency traders — but managers are not defenseless.

To be sure, it’s difficult to execute large trades when HFTs deploy sophisticated pattern-recognition software in search of order-flow information that they can use to their advantage. When an asset manager unintentionally leaves footprints that tip its hand to these HFTs, the price is often impacted to the detriment of the asset manager.

So what can an asset manager do to prevent this from happening? By answering this question, we can help institutional investors improve their execution, reduce transaction costs, and ultimately deliver better investment returns.

In a recent study, my colleague and I looked into this issue. Our goal was to provide a realistic analysis of the strategic interaction between investors trading for fundamental reasons, such as pension funds, mutual funds, and hedge funds, and traders seeking to exploit leaked order-flow information, such as certain types of HFTs.

We find that asset managers have a powerful weapon against HFTs that exploit order flow information: Randomness.

Here is a typical scenario to show how this works: An asset manager legally discovers better information of a stock than the market does and trades to exploit that information. After the order is filled, a “back-runner” legally observes the institution’s filled order. The back-runner could be an HFT that uses sophisticated pattern recognition software to determine the existence of a large investor trying to buy or sell. The back-runner then competes with the institution by using that order-flow information to its advantage.

In this situation, the HFT has no crystal ball; it cannot see an order before it reaches the market. Instead, the HFT is watching the market all the time looking for patterns that indicate the intention of a large investor, as that suggests that a particular stock is over or undervalued. When the HFT sniffs out a large investor, it can become a competitor with its own transactions, driving the stock price up or down.

The best response of institutional investors is to introduce some “noise,” or the appearance of randomness, to cover their tracks. For example, if the real goal is to buy 100,000 shares, then the investor could include some sells in the mix of transactions to essentially play hide-and-seek with the HFT and mask its true intent. It also could change its buying pattern so that the number of shares per trade and the timing of the trades appear random. This use of randomization makes it riskier for the back-running HFT, as it can’t be certain of the institutional investor’s real plans or even its presence.

The takeaway from our research is that asset managers can outfox “back-running” HFTs by making their trades appear random to avoid detection. Although it may seem to be an inefficient way to complete a large trade, randomization will benefit investors in the long run by limiting the back-running behavior that increases investors’ price impacts. Reduced transaction costs not only increase investment returns, but also incentivize asset managers to invest in more fundamental price discovery.

Haoxiang Zhu is an assistant professor of finance at the MIT Sloan School of Management. He is the coauthor of “Back-Running: Seeking and Hiding Fundamental Information in Order Flows,” with Liyan Yang of the University of Toronto.