For investors in equity markets, dividends matter. Take the S&P 500 index of large US companies – dividends have historically represented as much as ⅓ of total returns with the rest coming from capital appreciation. But of course with rewards come risks. And so investors are increasingly hedging against dividend risk with dividend derivatives. It would be useful, then, to better understand this new financial innovation?
Professor Radu Tunaru from the Centre of Quantitative Finance at Kent Business School thinks so. Models of phenomena – whether natural or social – are often a step towards better knowledge but for dividend derivatives we’re not there yet. “It is important to point out,” says Radu, “that currently there is no widely accepted model in the industry to price dividend derivatives. That means there is an opportunity to propose one.”
Radu’s work on dividend derivative models is already gaining attention. A working paper proposing two potential models rose into the top ten of most downloaded papers on SSRN under various themes. Disseminating this research then led to his being invited as a panel speaker to an event organized jointly by the Financial Times Trading Room and the EUREX Exchange in October 2015. The event was attended by almost one hundred participants from the finance industry including investment banks like BNP Paribas, Société Générale, Morgan Stanley and many other hedge funds and investment houses.
“Each model has its own pros and cons but they both preserve the stochastic or unpredictable nature of dividends,” adds Radu. “Moreover, their calibration to real world data is very promising.”
As with many other emerging asset classes, modelling for dividend derivatives has lagged behind their development. But the Centre for Quantitative Finance at Kent Business School is catching up.