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Pricing Models and Factor-Based Risk Management

Yannis Sardis, 26 November 2021

‘Essentially, all models are wrong (as they are approximations), but some are useful.
George E.P. Box, Prominent British Statistician (1919-2013)

As we have repeatedly emphasized in this series, the evaluation of an investment portfolio’s overall risk exposure to normal, let alone to extreme, market conditions cannot be adequately met by any single risk number or its variations. Instead, one needs to deploy a selection of risk metrics and calculation methodologies, to check that the risk assumed to produce an expected return complies with the prescribed asset allocation policy through time.

The absence of a systematic approach to risk assessment is nowadays amplified by the ever-growing number of diversified investment vehicles, fund types, and illiquid alternatives such as derivatives, private equity, private debt, real estate, and structured products. To utilize the benefits of a multi-faceted portfolio risk analysis, one must be able to ascertain the top risks of a portfolio and their sources, across any instruments held and related factors, whether macro-economic or price induced.

By being able to drill down to the core sources of a portfolio’s risks, a portfolio manager can ensure that the ongoing pursue for out-performance does not unwillingly create uncontrollable long-term risk exposures.

Embedded Valuation Modelling Engines

For a portfolio management system to be able to ensure that a risk assessment takes into consideration all the factors that may drive an investment’s price fluctuations and valuation overall, it is optimal to come with a built-in valuation modelling engine that allows it to extrapolate all those factors that contribute to the risk exposure of the portfolio’s individual holdings. This way, the system can produce an extensive list of sensitivity analysis metrics, as it intrinsically (due to its financial modelling) recognises the key factors that drive the pricing of the underlying instruments.

In addition, such an embedded pricing functionality allows the adequate valuation of complex instruments that need to be accounted for in the risk assessment process, and also provides the means for efficiently calculating the value of illiquid asset pools with no available exchange prices.

The range of risk factors largely depend on the portfolio composition, but could indicatively include Interest Rates (for holdings the valuation of which depends on them, such as Options, Futures, Forwards), Interest Rates Term Structure (if portfolios include Fixed Income holdings, such as Sovereign or Corporate Bonds), Credit Rating Curves (if portfolios include Fixed Income holdings), FX Rates (for holdings denominated in currencies other than the portfolio’s base currency), Index Rates (for holdings linked to an Index, such as Inflation Linked Bonds or Index-Tracking Funds), Price Time Series (for equity-like instruments, such as Stocks and Exchange Traded Funds).

Pricing Liquid Instruments

The range of instruments that a valuation modelling module, that is embedded in a risk management platform, could support depends on the type of the composite portfolio instruments, and could indicatively include Fixed Rate and Floating Rate Bonds, Inflation-Linked Bonds, FX Forwards, Equity Futures and Options, FX Futures and Options, Commodity Futures and Options, Interest Rate Swaps, Futures and Options.

The plethora of instruments that one can use to implement a strategic or a tactical investment view is associated with a large range of pricing methodologies. Depending on the instrument type, one could employ methods of various complexity, indicatively such as the Discounted Cash Flow method, the Black & Scholes Pricing method, or the Cox-Ross-Rubenstein Binomial Tree method.

Pricing Alternative Instruments

To efficiently calculate the value of illiquid assets with no available exchange prices, a valuation modelling module, that is embedded in a risk management system, could utilize a (user-defined) ‘Proxies’ methodology, using a combination of category-factors such as individual securities, benchmark or tailored indices and FX rates.

The system user can then define a number of proxies (factors) within a category and consequently create weighted averages of factors from different categories, the time-series of which will be used for the valuation of that particular holding.

Mainly applicable to Alternative Investments, such multiple time-series combinations can facilitate the estimation of the ‘fair’ value of a wide range of unlisted illiquid instruments, such as Private Equity and Real Estate funds.


Such a multi-factor analysis, within an integrated risk management framework, not only helps one monitor the risk-adjusted performance of a portfolio, but it also allows one to include all cross-correlations between individual portfolios, and thus produce total performance and risk figures for the consolidated firm-wide risk exposure.

All performance and risk metrics can be calculated at the portfolio, portfolio group, or modelled strategy level, and at all levels of granularity such as geography, currency, sector and security level, to provide a detailed view of the portfolio’s sensitivity to all factors and fundamental sources of risk.

FINVENT Software Solutions is a provider of financial software applications and custom software engineering services. The award-winning KlarityRisk platform specializes in investment risk analytics, risk attribution and stress-testing reporting, and it is offered to Private Wealth institutions, Asset Managers, Hedge Fund Managers and Family Offices. Finvent is the sole SS&C Advent distributor globally and its products are integrated with those of SS&C Advent.