Financial Complexity & Nonlinear Dynamics

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Very exciting! Published now our eBook "Financial Complexity & Nonlinear Dynamics" a collaboration between Complexity Labs & Fasanara Capital. Much thanks to Joss Colchester the co-author on this one. Download available here.

Complexity Labs is a platform for researching and designing complex systems, an authority in the fascinating field of Complexity Science. Its vast database is available online.

This book presents a high-level overview to the application of complexity theory to finance, first presenting the more theoretical side to complexity finance before going on to illustrate more practical examples of nonlinear dynamical modeling applied to capital markets.

In a recent interview George Soros captured much of the predicament that finance as a science finds itself in today when he said “The efficient markets hypothesis has failed and it is recognized that it has failed and therefore economist need to find a new understanding of financial markets…. this is what science is, it is a trial and error. Unfortunately, we don’t have a properly developed alternative and that is what we are looking for.” He goes on to say that the approach to finance that we developed under the efficient markets paradigm is not applicable to the real world and that he, in fact, made his money betting against the efficient markets hypothesis.

Since the financial crisis, much of economic and financial theory has been called into question. We are increasingly recognizing the limitations of the many kinds of financial models that are dependent upon assumptions of linearity and equilibrium; that agents are rational and independent and that the future will resemble the past. We come to increasingly recognize that linear development is but one kind of change, nonlinearity is another and of equal importance, if we are to build a more comprehensive understanding of financial systems. When systems involve synergies and feedback then they become nonlinear. You can get cascading effects that take the system out of equilibrium and into phase transitions and that these periods of what seems to be chaos, in fact, have their own kind of dynamics. By understanding the science of nonlinear dynamics we stand a much better chance of seeing and dealing with these periods of exponential and fundamental transformation.

This is indeed an exciting time for economics and finance as after almost two centuries of studying equilibrium solutions economists are beginning to study the emergence of non-equilibria and the general evolution of patterns in the economy. That is, we are starting to study the economy out of equilibrium and increasingly doing this through a computer-based algorithmic approach. This new complexity approach is certainly a paradigm shift, one of its creators W. Brian Arthur describes the essence of this change in perception when he notes “really it is a shift from looking at the world in reductionist terms, from the top down and imagine everything holding everything else in equilibrium where not much is changing at all, to looking at the world as alive everything is affecting everything.”

A key tool in this new approach is agent-based modeling (ABM) that gives us an inherently dynamic vision of markets, as patterns are continually being created and recreated through endless computations across complex networks of interaction; just as we see in the real world. When seen in this way financial markets show themselves not as mechanical, deterministic systems always moving towards stability and equilibrium but instead more like an ecosystem continuously evolving and creating new structures and patterns.

‘Complexity Markets’ Became Fragile, Inherently Unstable And Currently Sit ‘On The Edge Of Chaos’

Financial markets are best analyzed as Complex Adaptive Systems, borrowing from the inter-disciplinary studies offered to us by Complexity Science, where the Positive Feedback Loops between extraordinary monetary policymaking and a growingly passive investment community undermined System Resilience and brought to the brink of Critical Transformation

Abstract: FINANCIAL MARKETS AND COMPLEXITY THEORY

This note posits that Systemic Risk in financial markets is better analyzed through the prism of Complexity Science, using the analytical tools available to non-linear socio-ecological systems, where a shift in positive loops comes in anticipation of a dramatic transformation. Chaos theory and Catastrophe Theory can then help shed light on the current set-up in markets. Years of monumental Quantitative Easing / Negative Interest Rates monetary policy affected the behavioral patterns of investors and changed the structure itself of the market, in what accounts as self-amplifying positive feedbacks. The structure of the market moved into a low-diversity trap, where concentration risks of various nature intersect and compound: approx. 90% of daily equity flows in the US is today passive or quasi-passive, approx. 90% of investment strategies is doing the same thing in being either trend-linked or volatility-linked, a massive concentration in managers sees the first 3 asset managers globally controlling a mind-blowing USD 15 trillions (at more than 20 times the entire market cap of several G20 countries), approx. 80% of index performance in 2018 is due to 3 stocks only, a handful of tech stocks – so-called ‘market darlings’ - are disseminated across the vast majority of passive and active investment instruments. The morphing structure of the market, under the unequivocal push of QE/ZIRP new-age ideologism, is the driver of a simultaneous overvaluation for Bonds and Equities (Twin Bubbles) which has no match in modern financial history, so measured against most valuation metrics ever deemed reputable; a condition which further compounds potential systemic damages. The market has lost its key function of price-discovery, its ability to learn and evolve, its inherent buffers and redundancy mechanisms: in a word, the market lost its ‘resilience’. It is, therefore, prone to the dynamics of criticality, as described by Complexity Science in copious details. This is the under-explored, unintended consequence of extreme experimental monetary policymaking. A far-from-equilibrium status for markets is reached, a so-called unstable equilibrium, where System Resilience weakens and Market Fragility approaches Critical Tipping Points. A small disturbance is then able to provoke a large adjustment, pushing into another basin of attraction altogether, where a whole new equilibrium is found. In market parlance, more prosaically, a market crash is incubating - and has been so for a while. While it is impossible to determine the precise threshold for such critical transitioning within a stochastic world, it is very possible to say that we are already in such phase transition zone, where markets got inherently fragile, poised at criticality for small disturbances, and where it is increasingly probable to see severe regime shifts. Fragile markets now sit on the edge of chaos. This is the magic zone, theorized by complexity scientists, where rare events become typical.