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Considerations when Adding Equity Volatility Instruments to Your Portfolio
By Paul McLornan | February 18, 2021

Markets across the world were rocked last year by the COVID-19 pandemic. Between February and March of 2020 tumbling equity markets combined with high correlations hit issuers of structured equity products especially hard. 

In particular, a number of European “Blue Chips” announced freezes or cuts to their dividend payouts as regulators pressured their respective banking sectors into holding additional capital buffers to protect against anticipated losses in the wider economy. These unanticipated actions caused turmoil in particular to the autocall market. The issuers of these autocallables faced substantial directional exposure as they all struggled to re-hedge exposure which predominantly faced the same way. This manifested itself in wider bid-offer spreads with a resulting hit to their P&Ls.

Despite the first order impact of the pandemic and the second order impacts, driven by re-hedging activity in the autocall market, investors still “starved” of yield continue to seek opportunities to capitalize on higher levels of volatility. Their reasons vary but are concentrated on speculating on future realized volatility, trading the spread between realized and implied volatility and/or hedging their existing volatility exposures. We’ve seen a great deal of activity with customers seeking to value and risk manage variance and volatility swaps of various flavors amongst other structured equity offerings that help investors to realize similar goals.

The dynamics of these products against the backdrop of an increasingly uncertain macroeconomic environment calls for tools which are flexible enough to capture and risk manage these products accordingly. I’ve highlighted a few considerations when thinking about adding products like these to your portfolio.

Structuring Flexibility

It is crucial to be able to capture the variations seen in the market. Further it should be possible to modify or add to the existing products with minimal investment.

Dealing with exotic, or even semi-exotic, products necessitates flexibility in relation to how the products are described and captured. Looking at the variance swap market, conditional and corridor variance swaps borrow features from the broader structured product market. These features provide enhanced flexibility to investors and permit targeting of specific goals and market conditions. This flexibility comes at the price of additional complexity in the products.

Looking at the wider equity structured products market we can think about many other features such as barriers (European, American and window-style), caps, floors, early redemption features, conditional and accumulating coupons. Each of these features have an impact upon the valuation and subsequently the risk profile of the products which embed them.


Having flexibility in the choice of modelling, calibration sets and market data is crucial in a fast paced trading environment. 

On the market data side, being able to apply your own axe or assumptions to the market data is crucial in understanding the dynamics of the portfolio and how it may react to changes. In volatile markets the volatility smile can be very steep, exposing noisy data and arbitrage concerns. Being able to flexibly accommodate different volatility parameterisations, such as SVI/SSVI/SABR, along with different modelling techniques gives users a choice in how they understand their model risk and how the risk evolves over time under different regimes.

Risk Management

As well as computing the standard “Greeks” the tool also needs to be flexible in how scenarios can be defined. 

The sensitivities for equity products are wide and dynamic. Any solution needs to be able to quickly and accurately produce valuations and risk sensitivities. Managing a book of such products generally requires macro-hedges. Product specific hedges are typically less useful as the costs of hedging the risk factors individually is prohibitively expensive.

As well as the standard first and second order “Greeks,”it becomes necessary to build and look at different scenarios to find the “sharper” edges of the book. As well as cross-risks this typically involves understanding how risk factors, for example movements of volatility, impacts the entire book - often with different weighting assumptions across different tenors and strikes of the volatility surface.

On the other hand structurers and distributors of these products tend to appreciate a more product-centric approach whereby outputs can be tailored for their intended audiences. This can take the form of simple what-ifs, such as solving for option strikes or barrier levels that provide customers a particular view on the market through to more complex and dedicated product-specific outputs. Typical examples of this include understanding the time spent in/out of a corridor, in a Variance Swap, or quantifying probabilities of a autocall product knocking-out.

Ease of Use

Managing a book of exotic and semi-exotic equity products is a complex task. The solution needs to be easy to use without sacrificing capability.

Given the complex numerical tasks involved with pricing and risk managing a derivatives book, it is widely accepted that the best performance can be achieved by the underlying libraries utilizing C/C++. With that said, adding features to C/C++ can be a costly exercise, requiring a particular blend of software, quantitative and financial domain expertise.

To improve ease of use and “time to market” the solution should expose an interface in a higher level language. We love Python because it is often familiar to both finance professionals and software engineers. This combination permits a best of both worlds approach where the highly optimized analytics, written in C/C++, may be driven by an interface in the higher level language. Code written in such a higher level language tends to be a lot closer to English, so business users can get their hands dirty directly by writing code or if they prefer to involve IT resources - the business analysis becomes much smoother as both parties are talking in a language that is closer to the domain.

Learn More

For additional discussion on this topic, check out our related blog, Managing Volatility Risk During the COVID-19 Crisis. This post touches on a couple ways to manage the volatility swings we’ve been seeing in the past months. 

For more information, be sure to register for our upcoming Workshop on Managing Equity Volatility on Tuesday, February 16. 


About the author
Paul McLornan
Paul McLornan
Head of Pre-Sales | FINCAD

Paul McLornan joined FINCAD in 2019 and is Head of Global Pre-Sales and leads all of their pre-sales activities. Prior to FINCAD, Paul worked with other financial software vendors in various quantitative and developer roles. His previous titles include XVA Developer, Business Solutions Consultant and Market Risk Analyst.