Financial engineering has been blamed for its role in triggering each and every one of the most notable disasters that have occurred in international financial markets since the Black Monday crash of October 19th 1987. Synthetic portfolio insurance programmes were central in triggering the stock market crash of October 1987. Not to forget the influence of human psychology, hubris and greed in particular, it was the excess and easy availability of leverage combined with supposedly ‘low risk’ arbitrage trading that contributed to the collapse of the Long Term Capital Management hedge fund in the Fall of 1998. Again it was derivatives based innovations which underlay the collapse of Enron in late 2001. More recently, it was the widespread adoption of the Gaussian-Copula ‘magic formula’ in fuelling the massive growth in CDS and CDO markets which led to the dual credit cum liquidity global financial crisis of late 2008-2009. In each of these cases, financial engineers and derivatives traders have been to the forefront of the financial innovations which, for a while at least, brought huge profits to the financial institutions involved, and a supposedly more controlled if not benign risk environment for the clients of those institutions.
You might well ask – given the consequences for the stability of global financial markets, is the ‘computationally scientific’ discipline of Financial Engineering (like it’s not too distant computationally scientific relation Nuclear Engineering) an inherently negative or potentially destructive knowledge domain ? Should the financial innovation genie be firmly put back in its box, to be forgotten about but possibly left to be re-discovered by some unsuspecting future generation ? The answers to each of these questions are firmly in the negative. Lessons have to be, and are being, learned by the incumbent generation. With stricter and hopefully better informed financial regulation coming quickly down the tracks in the form of Dodd-Frank, Basel III, Mifid II (Markets in Financial Instruments Directive) and Emir (European Market Infrastructure Regulation), the brakes may be well and truly applied to the financial engineering arms race that has typified the surge in financial innovation that has occurred in the international financial markets of the last 25 years or so. However, this will not signal the death knell of financial innovation. This author believes that a more controlled and better understood form of financial engineering will continue to thrive. Investors will continue to demand innovative wealth-management products which better balance their tolerance for risk, expectations for return and needs for liquidity. The aviation industry, and in particular the aviation leasing sector, for example represents an end user likely to benefit from this more controlled and better understood form of financial innovation and risk management. This author is actively collaborating with industry partners to bring the ‘best parts’ of financial engineering best-practice to bear in the creation of structured hedges which will significantly mitigate the operating cost uncertainties faced by airlines, and add shareholder value as a result.
Financial engineering will also continue to be taught in leading business schools – but of necessity through a more interactive and experiential delivery mechanism by academics, who themselves must become more industry facing, relevant and connected in their research. Finance students – the financial engineers, traders, risk managers and regulators of tomorrow – are already being taught how to apply financial engineering insights and knowledge, adapting and refining their insights using the feedback signals provided by market simulators, potential future exposure stress-tests, and strategy back-testing using the ever more extensive back-filled financial databases which are now available from suppliers such as Bloomberg. Behavioural Finance theorists will play an increasingly important role in the development, refinement and application of Finance theory. In short, the international financial services industry will continue to demand that Finance graduates combine a quantitatively-founded understanding of market dynamics and financial risk, but will equally expect that these graduates possess the added ability to de-mystify and apply complex financial models with a mix of common sense and keen intuition.