Illiquidity discounts: DLOM and the key to locked assets
Illiquidity discounts: DLOM and the key to locked assets
Illiquidity might seem like a simple concept, but it can complicate selling assets quickly, or may require a significant discount. Businesses and individuals who ignore the risks of their illiquid assets run the chance of costly mistakes. Overlooking it or using a simplistic approach can result in heavy losses. This is particularly true for Locked Assets like IPO Shares, Restricted Stock, Letter Stock or Share Buyback Agreements, which can't be traded publicly for a set period for contractual or regulatory reasons.
For example, Letter Stock issued under SEC Rule 144 can't be sold for at least six months to one year after acquisition – a critical consideration for both national and foreign firms seeking to participate in private placements in American capital markets.
Similarly, Restricted Stock - often used as employee compensation - becomes transferable once certain conditions are met, like continued employment or achieving financial targets. Naively, these have been valued as options with a strike price of zero, which then mimic the shares themselves, which entirely neglects the core impact of the ‘vesting’ restriction.
These securities face a challenge – how do you quantify the impact of the time away from the market? You will need to determine a discount for the asset compared to its unrestricted counterpart, due to its inability to trade publicly during the restriction period. This discount can compensate for potential losses during the restriction, whether the assets drop in value or miss out on price increases. This is known as the Discount for Lack of Marketability (DLOM), and it is crucial for valuing restricted securities fairly.
Illiquidity discounts – what is DLOM in valuations?
Estimating the DLOM involves intuitive elements. The discount should increase with the restriction period length, because each day adds downside risk. But should the increasing discount be proportional? Is one day in a year's time as impactful as today? Would you bet on it?
Factors affecting the DLOM
Different types of assets might be affected differently by time off the market. A volatile asset is more likely to drift from its current price, incurring a greater discount, because any gains can't be realised before the restriction ends.
These considerations don't have a universal solution. You will need to understand specific frameworks and use them effectively, while dealing with imperfect information and changing requirements.
Consider a restricted and unrestricted stock of the same firm, trading at £100 at the start of a one-year restriction. The stock might move in various ways:
- If the price steadily declines, the unrestricted holder can sell before the year ends, limiting losses. The restricted holder must wait, potentially selling at a lower price.
- If the price rises then falls, the unrestricted holder can capitalise on gains. The restricted holder must accept the price at the restriction's end.
Only if the price rises continuously is the restricted holder not disadvantaged. The DLOM quantifies this disparity.
Unlocking illiquidity
Once we identify key elements, we can assess how they interact to quantify the DLOM's impact on the restricted holder. To guard against downside risk, the holder might buy a European Put option with a strike equal to the asset's current price and maturity matching the restriction's end. This offsets any adverse effects, as price drops are compensated by the Put option's value.
If you hedge the effects of illiquidity, the hedge's cost then equals the asset's liquidity value. The value of the illiquidity discount matches the cost of the Put option.
Frameworks agree on this but differ on what 'adverse effects' include. If the asset's value rises then falls to its original price, is avoiding strict losses enough? Or should the DLOM account for lost upside?
Illiquidity discount models
There are several methods to incorporate adverse effects, from using the expected maximum to preferring an average.
Chaffee model
Chaffee captures the adverse effects from price drops below the current price, quantified by a European Put Option price, and uses the Black-Scholes formula with assumptions like log-normal returns and constant volatility.
Longstaff model
The Longstaff model argues that Chaffee neglects potential gains during the restriction, suggesting a Lookback Put Option with a strike at the stock's maximum price, using a closed-form solution based on expected maximum price.
Finnerty and Ghaidarov models
The Finnerty model and Ghaidarov model agree on incorporating lost potential but find capitalising on the maximum unrealistic. They suggest using an Average Strike Put Option, with a closed-form approximation.
Each of these approaches offers different nuances for calculating the DLOM and defining 'adverse effects'. They agree the DLOM represents adverse effects from restricted marketability.
Do you deal with illiquidity? How can we help?
Businesses need a scientific approach to illiquidity and a comprehensive understanding of frameworks to avoid potential pitfalls. Ignoring the risks of your illiquidity can be costly if your approach is too simplistic.
Our Quantitative Solutions team has deep expertise and advance analytics in pricing and risk management for financial instruments, tackling complex challenges in quantitative finance. We use our experience gained from leading banks and consultancies to support you with illiquidity and DLOM related nuances in valuation and can bring a practical approach to break down these instruments and frameworks in simple terms.
To learn more, get in touch with the team today.