With a generating capacity exceeding 11,000 megawatts, PPL Corp. provides electricity to 4 million customers in Pennsylvania and the United Kingdom.

The power company, based in Allentown, Pa., is itself powered partly by investors who purchase its debt in the form of bonds. Like any borrower, it must repay its original loan plus interest.

But PPL can choose the type of interest rate it offers on its bonds. It can issue bonds with a fixed rate of interest or bonds with interest rates that rise and fall with fluctuations in the market. These floating rates, which are often based on the interest rates banks offer each other, are adjusted daily, weekly, monthly, quarterly, or at any other determined interval.

Because of their volatility, bonds with floating interest rates are considered riskier than traditional bonds. They have the potential, however, to yield significantly higher savings.

In September 2007, PPL turned to students in Lehigh’s analytical finance program for help in determining the type and number of bonds it should issue to finance its 10-year debt.

Lehigh’s M.S. in analytical finance draws students from business, mathematics and engineering and trains them to develop and implement solutions to complex, often highly quantitative problems in the finance industry.

The goal for the 14 students in last year’s class was to create a mathematical tool that would adapt to changes in interest rates over time to minimize both risk and total interest paid.

The students began by trying to identify drivers of the LIBOR (London Interbank Offered Rate), a standard often used to set floating interest rates. Theoretically, these drivers could be used to determine future rates.

“We included many different variables, like the slope of the yield curve,” said Drew Garrabrant ’07, ’08G, who holds a B.S. in industrial engineering.

Erdem Aktug, an analytical finance student pursuing a Ph.D. in economics, analyzed the initial results and discovered that the variables the students had included could not predict trends in the LIBOR. Instead of determining future LIBOR trends, said Aktug, these variables were themselves influenced by LIBOR.

In theory, the students realized in retrospect, they should have been able to gather information on current rates, determine the different risks associated with both fixed and floating rates, predict future rates and build models showing the optimal mix of bonds.

In reality, this task proved more difficult than anticipated. This was partially because floating rates have historically been lower than fixed rates, and could not therefore be used to forecast all future scenarios.

Back to square one

“It was interesting to see this contrast between theoretical models and what’s realistic to expect from the data, and then watch the students try to reach a middle ground,” said Aurelie Thiele, the P.C. Rossin Assistant Professor of industrial and systems engineering and the team’s faculty adviser.

“I was very impressed with how ethical the students were.”

The students turned for advice to a Morgan Stanley investment banker, who showed them the methods he had used to create investment portfolios. With a month remaining, the team changed its approach. Instead of trying to predict movements in interest rates, the students compared various ways of determining the optimum mixture of bonds PPL could issue.

On May 12, the team presented its findings to James Abel ’72, ’76 MBA, PPL’s vice president of finance and treasurer, and Russell Clelland ’83 MBA, PPL’s assistant treasurer.

The students were disappointed that they could not predict future interest rates. But they were able to recommend that PPL increase the number of floating bonds it issued.

“Historically, the floating rates offered to PPL were generally lower than the fixed rates,” Aktug said.

The students also advised PPL to set bond rates based on a dynamic model, which would adjust over time, from its current static approach, which does not.

“It’s now up to management to adopt the appropriate strategy,” said Aktug. If PPL adopts a dynamic model, he added, it will have to hire an expert in financial modeling and pay additional research and transaction costs.

“I think this project offered students a taste of what life will be like after graduation,” said Thiele. “In real life, problems are not that well-defined and you don’t necessarily have all the information you need.”

Thiele said the PPL executives were impressed with the students’ work.

“They realized it was a high-quality report. They liked that we gave them the findings and the conclusions. We narrowed their options and saved them time,” she says. “They were very pleased.”