The fourth and final article in our 'Portfolio Stress Test' series will discuss whether important historical crises can be used by investors to simulate the behavior of their portfolios, should certain factors be stressed to limits that occurred in past periods of extreme economic or market distress.
A portfolio holder continuously faces various risks that could drastically affect the value of the portfolio's holdings. The day-to-day process of evaluating the portfolio’s risk exposure in normal market conditions can be adequately covered by the modern VaR methodologies and their variations, which can even capture the divergence of the returns’ probability distribution from the normality.
However, a robust risk management framework demands the implementation of scenario simulation where the distribution is extremely skewed towards the tails (tail events); a situation that happens in very rare cases. Such shocks could be caused by various macro-economic or idiosyncratic events, which can consequently spread widely to previously thought of as uncorrelated choices of assets (Systematic or else Undiversified risk). Vivid examples of historical crises that resulted to large losses of invested capital within a certain period of time (varying from a few days to a few months) include the Black Monday of 1987, the Gulf War of 1990, the Asian Crisis of 1997, the Russia Devaluation of 1998 and the Financial Crisis of 2008.
Despite the fact that a large portion of such losses were often due to excessive leverage and over-concentration of positions, one wonders if an investor should use such extreme divergences from normality to stress test their seemingly well-diversified multi-asset portfolios.
Admittedly, we should not rely on the assumption that history repeats itself since background conditions and driving factors often differ vastly between distant periods of economic and market activity. However, to assess and verify that adequate capital is preserved in order to cover any unexpected losses, investors could attempt to estimate the impact on the portfolio performance that the re-occurrence of such damaging historical events could have.
In this way, stress testing would give us an idea of how stretched the loss-tolerance levels of a risk management strategy would turn out to be during a crisis of historical precedence.
To conduct such an analysis, one would need to select a historical crisis of relevance (a subjective choice) and apply changes to the risk factors driving the price of various asset classes (e.g. equities, bonds, credit, commodities, foreign exchange) accordingly, in order to assess their impact to the current portfolio if an identical market condition occurs. Such market shocks might be global or local in nature; consequently, geographical disparities in valuation changes would need to be identified and incorporated.
The date ranges one could use for such stress testing, could largely match the length of the referenced historical event, with the return change being the cumulative return over the entire testing period.
This requires the risk management system to give as much flexibility on stress testing modelling as needed since every portfolio or strategy will not be subject to the same risk factors. It should at least contain quantitative information about extreme market movements during historical crises, the application of which, to the current portfolio would have to be straightforward. It would also be advantageous to provide the functionality for a custom stress modelling based on a combination of lessons taken from several past crises such as significant price movements, correlation dislocations etc. The latter, will give the manager the confidence required for estimating the portfolio performance on extreme market conditions with scenarios tailor-made for its unique nature.
Once the adverse scenario simulation has been chosen, regardless of it being based on historical events or custom (hypothetical) market conditions, it can be applied to the current portfolio for a detailed risk evaluation analysis. Methods such as Stressed VaR that is perceived to be common market practice will provide sufficient information, whilst the ability of decomposing the risk exposure into its core sources will provide a more detailed view of the concentration risk the portfolio may face. Moreover, the ability to implement portfolio tail analysis will enhance the manager’s confidence in regards to the capital adequacy to cover significant losses even in the most detrimental conditions.
Our award-winning KlarityRisk platform specializes in market risk analytics and fixed income performance attribution reporting. Finvent is an SS&C Advent distributor since 2001 and its solutions are natively integrated with Advent Geneva, APX, and AXYS.
Guest author, Makis Ioannou, is the CEO of Finvent; the views and opinions expressed in this blog post are those of the author and do not necessarily reflect those of SS&C Advent.
To learn more about the KlarityRisk platform, visit www.finvent.com or discuss it with your SS&C Advent account manager.