BLOG — Aug 25, 2021
SEC 18F-4 - What it is and what fund managers need to consider
by Luke Armstrong
SEC 18F-4 - What is it?
The Securities and Exchange Commission on October 28, 2020 announced an enhanced regulatory framework for derivatives use by registered investment companies, including mutual funds (other than money market funds), exchange-traded funds (ETFs) and closed-end funds, as well as business development companies where derivatives exposure is greater than 10% of net assets.
The proposed rule and rule changes will establish a modernised, comprehensive approach to regulating these funds' derivatives use that meets investor protection concerns and considers decades of developments.
Derivatives in this context means any swap, futures/forward contracts, or options particularly where the transaction may require a potential future payment or delivery. Excluded are instruments where there are no future obligations such as purchased options or structured notes.
A fund that uses the rule must generally adhere to a value-at-risk, or "VaR," based outer limit on fund leverage risk. This upper limit is determined by comparing the fund's VaR to the VaR of a "selected reference portfolio" for that fund. In general, a fund can utilise either an index that fits specified criteria or its own securities excluding any derivative positions.
The rule will mandate that a VaR model consider and incorporate certain market risk characteristics related to a fund's investments, as well as disclose parameters for the VaR calculation's confidence level, time horizon, and historical market data.
The rule does not require a fund to use the same VaR model to calculate the VaR of its portfolio and the VaR of its designated reference portfolio. Any VaR model a fund uses for the relative or absolute VaR test must analyse and incorporate all important, identifiable market risk variables associated with the fund's investments, according to the rule.
A non-exhaustive list of common market risk characteristics that a fund must account for in its VaR model, if appropriate, is included in the rule. These market risk factors are: equity price risk, interest rate risk, credit spread risk, foreign currency risk and commodity price risk; including options and positions with embedded optionality; and the sensitivity of the market value of the fund's investments to changes in volatility.
Historical simulation, Monte Carlo simulation, and parametric models are the three most common modelling methods for VaR models. Each technique has advantages and disadvantages that may make one method more or less appropriate based on a fund's strategy, investments, and other considerations. Some VaR techniques may fail to account for all of the material risks associated with specific investments, as well as all of the material risks associated with the nonlinear price characteristics of some derivatives.
The final regulation is designed to allow each fund to employ a VaR model that is appropriate for the fund's investments by identifying some parameters but without dictating specific VaR models. The guideline stipulates that a fund's VaR model must use a 99 percent confidence level and a 20-day trading horizon. To establish an outer limit for a fund's leverage risk, the final rule will generally require a fund engaging in derivatives transactions to comply with a relative VaR test. However, the fund could instead comply with an absolute VaR test if the fund's derivatives risk manager reasonably determines that a designated reference portfolio would not provide an appropriate reference portfolio for purposes of the relative VaR test.
When?
Funds will need to comply by August 19, 2022
What can you do?
The initiative will establish a uniform risk management framework for funds while also allowing each fund to adjust its risk management to its own risks through principles-based tailoring. Risk guidelines including internal reporting and escalation, and programme review, must all be included in the programme. The rule requires the calculation of VaR, VaR backtesting and stress testing.
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