Derivatives and structured products’ complexity, current practices, industry habits and, regulatory attempts.

Rene Hess and Meriem Kanzari

What makes a structured product complex? There is no standard definition of perceived or real complexity in the financial derivatives industry.

Some products may be labeled “complex” or “exotic” based on subjective criteria such as their lack of popularity. Inversely, one may oversee the complexity of frequently traded products simply because market participants got used to trading them: the force of habit. The gap between financial complexity and investor sophistication makes it essential to define product complexity.

1. Motivation to define complexity

The marketing of complex products gives retail investors access to asset classes, market segments, and investment strategies that were previously only available to professional clients. To make informed decisions, investors should understand the risks, costs, and expected returns of some complex products and/or the drivers of risk and return.

While the vast majority of structured products are considered by ESMA and other regulators as complex, measuring this complexity is key to determine if clients have sufficient financial knowledge and experience to understand the key features, benefits, and risks involved in a given investment.

"It is surprisingly hard to find a practical definition of complexity."

Despite its importance, it is surprisingly hard to find a practical definition of complexity. It is even harder to establish a rigorous one. This is in fact posing a challenge for financial regulators. The latest regulatory alternatives mostly seem to focus on providing investors with more information about the products. However, increasing product information does not solve the problem as it may lead to information overload.

2. Regulators’ attempts to define and regulate complexity

There have been some attempts to define derivatives and structured products’ complexity in Europe through the International Organisation of Securities Commissions (Iosco) and a couple of national regulators, notably the French and Belgian Financial regulators. Iosco’s approach is based on the extent to which the product is understandable by retail investors; whether its valuation requires technical skills, and whether it has limited or no secondary market.

Let us take a look at two European regulators' methodologies. The Financial Services and Markets Authority (FSMA) has elaborated a framework based on four criteria:

  1. Underlying value transparency

  2. Strategy’s complexity: calculation formulas complexity and transparency regarding costs

  3. Credit risk

  4. Market value

On the other hand, the Autorité des Marchés Financiers (AMF) suggested three different criteria:

  1. Count of the features in the payoff formula

  2. Number of nodes in the decision tree (the decision tree describes the payoff distribution, depending on whether events provided in the formula occur or not)

  3. The number of scenarios affecting the product’s performance

"The FSMA and AMF criteria to define complexity do not have much in common."

Comparing the FSMA and AMF methodologies, we first observe the difference in the number of criteria. We also notice that the FSMA considers values such as the Underlying and Market values as opposed to the AMF. Suggested criteria range from observed variables to risk metrics such as the “Credit risk” in the FSMA criteria. But can we mix up risk and complexity?

"Observing how the US democratization principles get tricky when it comes to retail investors, while Russia divides qualified and non-qualified investors."

In the US, the Securities and Exchange Commission (SEC), does not wish to intervene in proscribing a given structured product based on the belief that investors should make up their own minds if they have access to “full and accurate disclosure to make their investment decision.” see this article for more details. This market democratization principle gets tricky when it comes to retail investors. Structured products sold in the retail market face enforcement actions by the SEC and the Financial Industry Regulatory Authority (FINRA). The Complex Financial Instruments Unit is an example of a “police” workforce protecting retail investors.

Meanwhile, Russia’s innovative approach has caused much debate. It involves dividing “qualified investors” and non-qualified investors, where non-qualified investors will have to go through a testing procedure to gain access to financial instruments and transactions. The testing phase is supposed to start in October 2021, let’s see how this goes. Find out more on this page.

3. Non-regulatory attempts to define complexity

While there are ways to express risk in both absolute and relative terms, this is more difficult when measuring complexity. There is no standard measure to express complexity as an absolute. Therefore, a meaningful rating for complexity needs to be calibrated against reputed and widely accepted as simpler or more complex products.

3.1 The checklist-based approach

Using a checklist to determine the complexity of a product is one of the most popular approaches. Different characteristics of the products are evaluated and allocated a score. The overall score will then determine the complexity of the product.

"The checklist approach is popular thanks to its simplicity."

Common characteristics include:

  • Transparency of the underlying value, i.e. accessibility to market prices
  • Existence of conditional features (i.e. capital protection, coupon)
  • Asymmetry of the payoff
  • Number of components (e.g. underlyings)
  • Number of conditions to determine payoffs

    This approach looks at enumerating product characteristics and determines their complexity from that angle.

    3.2 An approach based on product behavior given market evolution

    The prior method determines the perceived complexity of a product by looking at the description. The following approach intends to determine the complexity by analyzing the predictability of the outcome based on investors’ market views.

    The outcome of a product can be linked to various conditions:

  • No Condition: a fixed amount is paid over the life of a product (e.g. Fixed Rate Deposit)
  • Linear Function: payoff has a constant correlation to an underlying value
  • Piecewise linear function: payoff can be determined by knowing the value at a given point in time, i.e. European Options
  • Path dependent product: payoff cannot be determined by knowing the underlying value at a single point in time, i.e. European KO Options

    One way to measure this dependency is to analyze the correlation between underlying assets' evolution and the lifetime payoff of a product.

    The less certain the outcome of a product -by having a clear view of the relevant underlying prices at maturity- the more complex it is. We illustrate this claim through the example below.

    Let us assume Alphabet Shares are at USD 1’500 today and that they will be at 1’400 in 1 years, one could do the following investments:

    Investment Outcome (if price is indeed at USD 1’400 at expiry)
    Reverse Convertible 8% - Strike 1’300 Initial Investment + 8% Coupon
    Reverse Convertible 8% with Quarterly Autocall Initial Investment and either 1, 2, 3 or 4 Coupon Payments at 2%
    Put Option Strike 1’500, with a American Knock Out at 1’600 Either 0 or USD 100 / per option, subject to the knock-out
    Cash Settlement Accumulator, Knock Out at 1’575 and Strike at 1‘350 No meaningful prediction possible due to the very high number of potential permutations

    The charts below show the distribution of the potential outcome at maturity (y) and the price of Alphabet at maturity (x).

    alt text Chart 1: Reverse Convertible potential outcome at maturity (y-axis) and the price of Alphabet at maturity (x-axis).

    alt text Chart 2: Barrier Reverse Convertible potential outcome at maturity (y-axis) and the price of Alphabet at maturity (x-axis).

    alt text Chart 3: Accumulator potential outcome at maturity (y-axis) and the price of Alphabet at maturity (x-axis).

    This approach requires a more sophisticated simulation method making it tedious to implement.

    4. Conclusion

    Defining an approach for complexity depends on multiple factors: objectives, context, target use, audience sophistication, technical capabilities, and regulatory requirements. Market participants seem to tend towards a mixed approach.

    The checklist-based approach seems to be a good start to give a hint about product-level complexity.

    One thing is sure to us: one should not mix up complexity and risk.


    1. MiFID practices for firms selling complex products, ESMA, 2014
    2. The Complexity of Structured Products Marketed in France: What Impact Has The AMF’s Action Had? AMF, 2020
    3. The Structured Products Law Review: USA by Christopher S. Schell, Yan Zhang and Derek Walters Davis Polk & Wardwell LLP, 2020
    4. State Duma approves draft law in second reading on selling financial instruments and protecting non-qualified investors, Bank of Russia, 2021


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