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1 " In the Adaptive Markets framework, complexity means we don't have a good narrative for the system. The solution is obvious: we need to get smarter. Complexity can sometimes be reduced by developing a deeper understanding of the underlying structure of the system. For example, now that we understand the potential for liquidity spirals in statarb portfolios, thanks to August 2007, we can better prepare for them.

But the Adaptive Markets framework points to a second problem with complexity, which is the potential divisiveness of special knowledge and the potential for conflict. If the financial system becomes so complex that only a small number of elites truly understand its function and proper maintenance, this knowledge divides the population into those who know and those who don't. Of course, this situation arises with any piece of unique information - I know how to make scallion pancakes in a particular way so they're crispy on the outside but soft and chewy on the inside, and you probably don't. But that piece of knowledge is hardly worth keeping a secret, and the fact that you don't have that knowledge isn't going to get you too upset.

But suppose I know how to cure diabetes and you don't. Or I know how to prevent cancer by avoiding certain common foods and you don't. Or I know how to price mortgage-backed securities and credit default swaps and you don't. In these cases, the knowledge I possess confers a certain power and status to me. Complexity creates the need for better narratives and those who have those narratives will become the high priests of complex systems, the gatekeepers of critical, life-altering knowledge. And the difficulty in joining the priesthood - earning an MD/Ph.D. in molecular biology and having twenty year of work experience at biotech and pharmaceutical companies, in the case of curing diabetes - coupled with the societal values of the special knowledge will determine the divisiveness of this elitism. "

, Adaptive Markets: Financial Evolution at the Speed of Thought

2 " What if we looked at the law as a piece of software, the operating system of the United States of America. After all, laws play the same role as software in providing instructions for a given system - if this, then that, and so on. If a team of software engineers was asked to analyze the entire body of federal law, they would see tens of thousand of pages of poorly documented code, with a multitude of complex, spaghetti-like interdependencies between the individual components. Could the principles of good software design be used to improve the way we write financial regulations?

Li, William, Pablo Azar, David Larochelle, Phil Hill, and Andrew W. Lo. 2015. 'Law Is Code: A Software Engineering Approach to Analyzing the United States Code.' Journal of Business and Technology Law 10: 297.

A useful feature of network graphs if the ability to model contagion. Like an epidemiologist studying the spread of a contagious disease from its point of origin, we should identify the potential linkages through which a financial crisis may travel.

Billio, Monica, Mila Getmansky, Andrew W. Lo, and Loriana Pelizzon, 2012. 'Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors.' Journal of Financial Economics, 104: 535-559.

This approach can also be used to measure the network of banks, insurance companies, and sovereign nations. The idea is to see how macroeconomic problems facing countries might get transmitted to the financial system and vice versa.

Billio, Monica, Mila Getmansky, Dale Gray, Andrew W. Lo, Robert C. Merton, and Loriana Pelizzon. 2016. 'Granger-Causality Networks of Sovereign Risk.' Working Paper, MIT Laboratory for Financial Engineering. "

, Adaptive Markets: Financial Evolution at the Speed of Thought