Over the past 60 years, a rich history of quantitative research has emerged aimed at the investing community. None has had as much influence as the concept of portfolio optimisation.

According to research, portfolios do better when optimised for low risk and high returns. This has prompted the growth of passive index funds, because the idiosyncratic risks of individual stocks aren’t compensated enough, limiting the alpha that stock pickers can generate.

More recently, the idea of smart beta has become fashionable. If you divide the universe of stocks by factors such as size, momentum or value and optimise your exposure, you can outperform the index and demonstrate this using a backtest. Analytics provided by MSCI Barra or Bloomberg make this as easy as pushing a button. Today, hundreds of billions of investment dollars are being allocated to smart beta products.

In reality, the theory behind this fashion is shakier than many investors realise. When applied naively to input data, optimisation models can lead to extreme or unstable trading strategies.