“Without factor models, any kind of reasonable stress-scenario construction is doomed.”
In the following post, Boryana Racheva-Iotova, FinAnalytica co-founder, and now Global Head of Risk at BISAM, discusses the rise of the new "normal" market turbulence, the implications of that new normal on practical risk management, and how institutional asset managers and hedge funds have leveraged the Cognity® market risk platform in response to all of the above.
ESA: Boryana, in your recent video interview with BISAM CEO, William Haney, you talk about turbulence - or spikes in volatility - being the “new normal.” Can you expand upon that, and also outline the pitfalls of having a risk solution that cannot accurately model the related phenomena, g. reliability of risk assessments?
BRI: For many decades, up until the early signs of market tremor in 2007, financial markets were characterized by periods of “normal” behavior, followed by shorter periods exhibiting higher probability of extreme events, i.e. stressed periods. This is no longer the case. “Normal” periods are gone. Stressed or “turbulent” periods are not necessarily the periods with highest volatility. They are the periods when – relative to the local volatility - returns that are both abrupt and large in magnitude can happen with high probability. This is measured by the volatility-of-volatility. As visualized below, based on the Cognity VaR backtesting module: prior to 2007 we clearly had normal and non-normal periods, while the last eight to nine years have been characterized by this new “normal” turbulent regime. The level of turbulence is measured by the difference between fitted Normal tail and a dynamic fat-tailed model tail.
ESA: What caused the normal periods to be extinguished?
BRI: There are both global irreversible factors, and those that are related to the current economic conditions. Starting with the latter: The various stress-points in the global economic and financial markets landscape contribute to the “turbulent” behavior of the markets driven by the behavioral reactions of market participants to news and re-positioning towards anticipated risks (Brexit, China, Oil oversupply associated impacts, etc.). There are simply too many hot-spots burning on the map of the economic and financial risks for the foreseeable future. The irreversible “universe” of factors relates to the natural evolution of the financial system – technology development, evolution of investment strategies, and reach of available products (starting with those available to retail investors and the growing diversity of smart-beta funds, but also increasing complexity of investment strategies across the board, structured products, etc.). Those factors increase the “market speed," crowding, herding and short-term liquidity evaporation – all of which create turbulence and therefore a significant probability for large sudden drops (or spikes/soars) in the markets.
ESA: So how does this relate to practical risk management?
I will mention the top two aspects:
- Historical approaches simply don’t work. It is now more true than ever that we cannot describe the future by what was observed in the past. To put it directly, Historical VaR and related risk measures are simply dangerous for any kind of decision making. What is required are predictive models. Predictive models can only be based on a smart blend of factor modeling and advanced probabilistic and econometric models to project the possible future behavior of the factors. Factor models are essential in our attempts to characterize the economic environment and related behavior of the financial markets. Without factor models, any kind of reasonable stress-scenarios construction (based on both subjective and model-based approaches) is doomed. Risk managers lacking that capability are disarmed and lack the ability to test their portfolios against upcoming (not past) events! The advanced modeling of factors should capture possible regime shifts, volatility clustering and extreme events. Having the factors available, but not being able to model their true behavior properly is equally useless. Even the simplest equity factors, such as leverage, size, etc., behave in a very non-normal way, as demonstrated in the following charts.
Daily Returns via Simulated Brownian Path Leverage (leverage) Returns
Growth (growth) Returns Size (size) Returns
In the Cognity market risk platform, we adopted a unique factor-based-Monte-Carlo simulation approach with “fat-tailed” distributions. We go down to a very granular level of risk drivers and meticulously model all their characteristics in order to generate future scenarios and then re-price and assess the risk of a given investment portfolio (keep reading the BISAM Insights blog for more on this in the future!).
ESA: What should CROs, CIOs, Risk Managers and their peers be asking themselves right now with regard to their current market risk solutions, in terms of the key industry pressures you’ve just described, and the supporting capabilities unique to the Cognity solution?
BRI: Let me approach this question by speaking about two of the core segments which Cognity serves, and what we typically hear from our prospects. The top reasons why the market turns to the Cognity platform, particularly over the last six months, are as follows:
- Institutional Asset Managers are troubled by the quality of their VaR models with exceedances during 2015 far above acceptable levels. In particular, many UCITS funds are now under pressure to reevaluate and improve their VaR methodology. Our methodology has proven itself in producing VaR numbers that pass all the tests under all sort of market conditions.
- Institutional Asset Managers are also looking for flexible approaches to custom stress-test construction. Our universe of stress-tests has increased rapidly. The beauty of the Cognity system is in its capabilities to very granularly describe stress-scenarios and the waterfall of the impacts into different segments of the markets. This unique capability delivers realistic stress-scenarios construction capabilities.
- Further, the ability to roll-up, decompose and evaluate risk based on different views, user-defined grouping and portfolios hierarchies is also a key need for Institutional Asset Managers. They need consistent views of the enterprise roll-up of their risk, and the ability to effectively and quickly do breakdowns by different characteristics, client portfolios, etc. Cognity provides strong capabilities based on its portfolio organization infrastructure, as well as the multi-asset class, multi-liquidity models that we have built. (More to come on this in upcoming blog posts, but please visit bisam.com/risk to request more information in the meantime).
- On the Hedge-Fund side, the top three priorities are precise identification of risk sources, i.e. the ability to spot risk drivers down to a tenor, single equity or vol point. Stress-testing flexibility is a repeating theme, with the need for laser-precision mapping of their risks. Finally, the ability to have Risk on demand (i.e. every five minutes), and related to that, the need for strong API capabilities are becoming crucial.
From a pure modeling perspective, a top priority for our Cognity customers in 2015 was their ability to implement a framework for negative interest rate models. It goes without saying that this affects everyone!
Robust risk analytics are essential for understanding and driving performance of investment portfolios. Cognity®, now a BISAM solution, is a unique , comprehensive, multi-asset class platform for market risk, portfolio construction and investment decision analytics. Visit www.bisam.com/risk to request more information, or send an email to email@example.com.