Stress Testing for Your Portfolio

Stress testing is a risk management method to evaluate the impact on portfolio values of potentially negative events. Gloabl Association of Risk Professionals (GARP) recently released a post “COVID-19 Calls for New Risk Measures” highlighted some problems of our traditional risk assessment. The COVID-19 financial turmoil should lead financial professionals to look into their investment portfolios and have a more accurate stress testing since some investment and model portfolios are not prepared to deal with similar risks.

Some known methodologies for stress testing for portfolio management include the use of Value at Risk (VaR) and Extremem Value THeory (EVT). Value at risk focuses on the distribution of risks over the entire distribution curve while the Extreme Value Theory focuses on the shaping the tails. For most stock portfolios, we use VaR because portfolio managers typically are more concern how to flatten the curve rather than hedging certain risks in their investment portfolios.

Stress testings can involve the use of univariate and multivariate stress tests. Univariate test are simple and easy to conduct but its limitations are also apparent because the test might ignore input dependencies and thus leading to collinearity, causing some independent regression coefficients to be wrong, or curve fitting. Multivariate stress tests solve such problems and are recommended for multi-asset portfolios.

Both methods should be used with scenario analysis for more realistic results. Most backtesting tools on the market are based on historical events; but in reality, risk management should be also applied with hypothetical scenarios as well. The financial crisis of 2008 resulted in the lack of understanding of risk dependencies between the risk levels of multiple variables. Another scenario is the use of hybrid scenarios, which use both historical and hypothetical scenarios for  your risk analysis.

We model the distribution of returns with GARCH model combined with VaR for portfolio stress testing. Depending on your portfolio management style and active levels, we might recommend different methods. If you have questions regarding the use of technology and financial model for your portfolios, Contact Us and learn about stress testing for your portfolio. 

Analysis for Portfolio Management

Quantitative Analysis for Portfolio Management provides insight into historic performances of a specific stock. Portfolio managers commonly rely on a public company’s stock price data, dividends, free cash flow, & earnings to value the stock’s intrinsic value for entry and exit purposes. A consistent and well documented use of quantitative methods could greatly improve a portfolio manager’s trading decisions in different market conditions.

Quantifying intrinsic value is a common method for evaluating long-term investment because it provides the insight of the company’s current economic value as a going-concern entity. However, data from financial statements might be skewed by management judgment and manipulation to control stock value. Therefore, it is important to understand both the stock’s fundamentals such as its management team, industry competitiveness, and geographical risks etc.

Fundamental analysis requires market insights and industry knowledge and research analyst should recast and normalize data before performing valuation and analysis. One important is risk premium, which greatly affects the valuation because of the discounting effect. Complete due diligence is required for portfolio managers and analysts to review the data, reasoning, and methodologies used to arrive the cost of capital.

Some portfolio managers include technical analysis as an overlay process to generate market sentiment signals and trading rules for their stock holdings. Portfolio managers use moving average and reversion analysis to generate optimal entry and exit points for a stock.

Although the Mean-Variance Efficiency is frequently challenged (here is a good article from CFA Digest), we like to stress that historical data is use to improve decision making and not as a rule of thumb for complex decision-making process such portfolio management. To help challenge this static thinking, the use of variance minimization, return maximization and Sharpe maximization are also encouraged. You can apply all these regressions without optimization technology. We use multi-level vectorization programming to quickly analyze stock values and trading rules, if you are interested to integrate portfolio management with a quantitative analysis system, learn More about Portfolio Management Solutions

Model portfolios

Model portfolios managed by third party are also known by some RIA in the industry as the separately managed account. Investment advisors use them for accounts with higher AUM (asset under management). There are many benefits for a RIA to use third-party model portfolios. Most prominently, the RIA does not make trade and asset allocation decisions. The RIA is expected to know the product (KYP) but does not necessarily have in-depth knowledge about each security within the model portfolio. The hands-off management allows RIA to focus on client relationships and financial planning and less on trade executions and market research.

There are many factors driving the decision to whether purchase 3rd-party model portfolios or not. Because trades are created for each individual model portfolio, factors such as trading slippage costs, commissions, and spreads should all be considered when making the decision to whether delegate the portfolio management job to third-party provider or not. For many 3rd party model portfolios, the fees are lower than a typical balanced fund but higher than a professionally managed model portfolio built in house. This is especially the case when the model portfolio has a large portion of the asset deployed into low-cost ETF solutions or stocks.

Of course, it might seem economic and good practice to build in-house model portfolios for their clients, most RIAs do not have sufficient research and portfolio management resources to create their model portfolios. The decision to build in-house model portfolios became a lease or purchase business decision.  To manage a good model portfolio, the advisor team should have at least one CFA charterholder in their team. Clearly, if the AUM is large enough, the decision to run in-house model portfolios would be optimal comparing to the high cost of 3rd party model portfolios.

Model portfolio should be one of the top priority for RIA to build in their operating and KYC (know your client) procedure. Because model portfolios must be compliant with the regulatory standards, constantly tracked, and adhered to strict investment mandate and trading policy, clients can have better understanding of potential risks and performances of their portfolio.


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