Helping Blind Navigation In Broken Markets: The Cockpit Of Complexity-Based Systemic Risk Alerts

How do you handle portfolio management in fake markets, where monetary jiujitsu is relentlessly utilised to cook the books and rig price discovery?

A range of new-generation tools based on Complexity theory to assist in tackling an unconventional and unsustainable market environment.

In days gone by, we predicated that the next crisis will show how badly we need new tools to understand market risk and the systemic implications of monetary policy overdose. In a recent piece, we summarized the state-of-the-art of Fasanara Complexity-Based Systemic Risk Alerts.

These indicators are strictly non-volatility based. Volatility is a bad predictor of impending chaos (if anything, it is a necessary condition to systemic cliffs) and has stopped long ago being an effective measurement of risk: yet, all market participants use it as the sole compass to portfolio management, when it comes to determine levels of leverage, position sizing, risk exposure, expected shortfall, etc. In perfect vox clamantis in deserto style, we continue our search for better tools, on our elected path of non-conventional truth-seeking market discovery.

We previously discussed:

• A Tool For Visualising Tensions In The Market Structure, Over Time
• A Tool For Monitoring/Quantifying The Variant Impact Of A Market Epidemic
• A Tool To Estimate The Proximity To A Long-Term Large-Scale Systemic Risk Event
• A Tool To Capture Short-Term Small-Scale Market Events

Now it is time to add a new utensil to the toolkit: the 5-days ETAS indicator. Author of the working paper and the math behind is Carlos Saenz de Pipaon, a valuable recent addition to the Fasanara Analytics team.

This indicator will help spot small-scale market drops. The genius idea behind is that any major market crash will begin as a small market drop. Every crash will go through the check-point of a failed Buy-The-Dip, inevitably. We therefore need to be equipped with both long-term large-scale fragility detectors and short-term small-scale warning signals. The combination of the two will assist in blind navigation of broken markets, at a time when they station at the edge of chaos and are subject to far-from-equilibrium dynamics.

Again, the indicator is complexity based, not volatility driven. It means that it is derived by some selection of the general properties of systems in transition, according to complexity science, using the analytical tools available to non-linear socio-ecological systems. Chaos theory and Catastrophe Theory can help shed light on the current set-up in markets, after years of monumental Quantitative Easing / Negative Interest Rates monetary policy affected the behavioural patterns of investors and changed the structure itself of the market, in what accounts as self-amplifying positive feedbacks. The conceptual framework is to look at financial markets as complex dynamic systems, similar to other natural ecosystem like lakes, forests, the human brain. Predicting a market event is then similar to predicting the extinction of fisheries in a lake, epileptic seizures hitting the brain, snowflakes accreting to form avalanches, desertification rapidly over-setting a green valley, a volcano breaking into eruption, a forest burning itself out, a pandemic breaking loose.

Systems theory is a superior tool vis-à-vis conventional market analysis at a time when systemic implications are forgotten by most policymakers, and the system takes a life of its own. It is a great complement to both Efficient Market Hypothesis market theory and Behavioural Finance. It allows for better insights, more information value, and breaks the smoking mirrors projected by the artificial, fake markets we live within.

An example of a tool that has been previously discussed in Fasanara’s ‘’Thematic Research | Measuring Systemic Risks’’ is the Market Structure System Resilience Indicator (SRI). This tool allows to quantitatively asses the fragility of the market based on its network structure. Additionally, one can plot the network for visual analysis (and some pleasant eye-candy). Below there is an example of this tool in action. In particular, the GIF shows the week-by-week dynamics of the network structure of stocks in the S&P500 since January 2018.

The modelling framework of this new study is based on the Epidemic-Type Aftershock Sequence model (ETAS) developed by Ogata in 1988, which has been widely studied by geophysicists over the years. It models the occurrence rate of earthquakes (seismic activity above a given threshold) as a Hawkes process. The methodology presented is a novel approach to market crash warning systems that proves to be effective and provides advantages over the VIX and other GARCH-based indicators. When used in conjunction with the existing Ricci Curvature-based indicators in Fasanara's toolkit it provides a powerful tool to alert of forthcoming turbulent markets.

Happy reading!