Unpredictability and Scenario Simulations in Financial Markets
Yannis Sardis, PhD | 19th June 2023
“The financial markets generally are unpredictable. So that one has to have different scenarios…
The idea that you can actually predict what’s going to happen contradicts my way of looking at the market.“
George Soros, Hungarian-American Hedge Fund Manager and Philanthropist.
The U.S. stock market volatility (as measured by the popular CBOE Volatility Index, VIX) stands at a 3-year low, the U.S. Headline Inflation (as measured by the Consumer Price Index) is at a 2-year low, whilst the S&P500 stock index has reached a 14-month high.
Such elevated stock prices combined with low volatility readings may be deciphered as an indication of market stability that reflects the average investor’s conviction that equities should be overweighed in their asset allocation plan, especially in view of a possible halt of interest rate hikes by the Federal Reserve and even a forward decision to cut interest rates provided that certain economic conditions allow such a policy reversal.
Alternatively viewed however, such low volatility levels paired with a prolonged appreciation of equity valuations, may indicate that investors have become increasingly complacent and pay less frequent attention to their portfolio rebalancing.
Artificial Interventions and Unpredictability
The most recent corporate bailouts (implicit or explicit) employed by the world’s most prominent financial powers may prevent certain businesses from going under (often temporarily), but they also increase the possibility of a system-wide collapse.
Artificially suppressing short-term volatility weakens complex systems, encourages excessive risk-taking and creates a false sense of stability and thus predictability, while in reality it only increases long-term risks at the expense of short-term vulnerable market price growth.
Such ‘volatility-reduction’ policy mechanisms combined with collective behavioural psychology (false stability) and investor inertia (Fear-of-Missing-Out) may also cause volatility to cluster, meaning that large volatility bursts tend to happen more infrequently but at successive over-sized amounts. Empirically, this phenomenon can be thought of as a system’s reaction to defuse and mean-revert an artificially supressed pressure.
So, could we experience a re-emergence of market volatility and an abrupt end to stock index appreciation that may lead to the next financial crisis? Considering that major price reversions in history are often so quick that the less attentive investors had no time to react, can market participants predict an imminent market reckoning and in advance reallocate capital into non-affected assets or cash (notably, the 6-month U.S. Treasury yields a whopping 5.3%), thus preserve their capital through turbulence? The inconvenient answer is no, at least not in a consistent and repetitive manner. The two defining characteristics of future change are the existence of wild fluctuations and the impossibility of predicting it.
In essence, the mission of those involved in the Asset Management business is not to predict the future trajectory of market prices but to manage their positions of high conviction within a disciplined risk-adjusted framework.
Portfolio Scenario Simulations
So, how can investors in practice test their multi-asset-class portfolios’ vulnerability to future violent market fluctuations?
Such a proactive assessment can be done by a Stress Testing analysis which enables one to assess the portfolio’s reaction to adverse market conditions. This can be achieved by either taking into consideration a wide list of major historical events, or by creating tailored custom scenarios which are most suitable to the user’s intuition about the current market environment and the characteristics of one’s investment strategy.
Historical Stress Testing refers to the process of stressing a portfolio under the assumption that a past market crisis would occur again. Its advantages are that it does not require the effort to create a custom scenario, it is a regulatory-approved approach and there is a long list of historical crises to be utilized. A disadvantage, however, is that the selected historical crisis might not entirely adapt to the current investment environment and therefore it may result to skewed estimations.
On the other hand, creating a Custom Scenario, although requires a justification of the reasons behind the implemented changes, it empowers the stress testing assessment by allowing the user to tailor the scenarios to portfolio-specific conditions and ensure the adaptation of one’s investment decisions to the current market environment and driving factors.
Alternatively, one can even use a hybrid model by utilising a predefined Historical Stress Scenario and concurrently amending various factors so that they adapt suitably to current market conditions and risk factor values, as the new inputs in the Stress Testing analysis.
Multi-Factor Stress Testing Methodologies
The aforementioned range of estimation methodologies enables a manager to assess a portfolio’s risk-adjusted performance in extreme market conditions, allowing the development of investment strategies via a diligent stress testing process which may highlight weaknesses or opportunities in hypothetical adverse market movements.
The range of risk factors that one can stress test a portfolio against largely depends on the portfolio structure and composition, and could indicatively include Interest Rates, Interest Rates Term Structure, FX Rates, Index Rates, and Price Time Series.
So, stress-testing methodologies allow us to gauge a portfolio’s risk behaviour (as for instance represented by Value-at-Risk changes at portfolio level, i.e. the maximum potential portfolio loss over a given period, under a confidence level) in different scenarios and view the risk decomposition of a portfolio by asset class, industry sector, currency, credit rating, and geography. This way one can identify and rectify any ‘imbalances’ between portfolio weights and associated risks, and consequently create hedging or defensive rebalancing strategies for a spectrum of shocks.
Stress-testing calculations are not only useful in measuring market related risk. Regulatory stress-testing under various crises scenarios can help determine portfolio risk and consequently create hedging strategies to mitigate potential losses. Retirement and insurance portfolios could also use stress-testing analysis to ensure that unexpected events would not prevent them from maintaining efficient stream of cash flows and pay-out levels for their clients.
Asset managers do not need to predict the financial system’s hidden future vulnerabilities but instead systematically use smart software solutions to dynamically digest the collective information that market volatility provides, in order to make their investment decision-making process more adaptable, disciplined and longer-term successful.
FINVENT Software Solutions is a producer and distributor of financial software applications and custom engineering services for the investment management sector. The firm serves financial institutions in European and African countries, including asset managers, family offices, investment banks, pension funds and hedge funds. Its award-winning KlarityRisk platform specializes in multi-dimensional investment risk analytics, stress-testing simulation scenarios, risk limits management, and fixed income performance attribution reporting.
Nothing contained in the aforementioned article references constitutes an investment solicitation or a recommendation of any type