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By Thomas Sweeney, Valuations Associate, Cirium Ascend Consultancy

In the current supply constrained environment, the majority of aircraft values are on an upward trajectory. All of our existing market analysis indicates that this constrained supply will continue for several years yet and potentially for the majority of this decade. Demand is projected to resume its growth trend, although there is some risk in this assumption. Having just experienced the extreme downturn of the pandemic we are well placed to assess the risk that each asset presents based both analysis of historical data and understanding of the market dynamics of that type.

To illustrate how various assets have performed, we plot the graphical distribution of Market-to-Base Value ratio around a balanced market, which is represented by a MV/BV ratio of one. Below are examples of these graphs for three different aircraft types on a 10-year horizon which demonstrate the full range from stable to highly volatile.

The Airbus A350-900 is an asset which has proved very popular with operators and investors. An efficient new generation aircraft, it is an optimal size for many operators’ long-haul networks and production has been more stable than for its competitor, the Boeing 787. This has resulted in relatively stable values for the type:

It is unsurprising that Market Values for the type have mostly been below Base, given that a large proportion of its in-production life has been taken up with the pandemic.

It is more noteworthy that Market Values have barely gone below 90% of Base.

It demonstrates the relatively low volatility of this type. Demand for this aircraft is high with a diverse operator base and it has had time to prove its performance. It is the largest in-production type at present, as the 777X continues to struggle in certification. This is driving the view that demand, and hence values, are unlikely to fall significantly in the near and medium-term.  

The newest Boeing 737-700s (2012-2018) have a less stable profile, with Market Values showing significant time spent between 75% and 90% of Base:

The Boeing 737NG family has been a very successful programme and demand for this key narrowbody type can only fall so far. However, this variant of the family is one of the more volatile types. The smallest variant in a family is generally less popular as a consequence of its relatively poorer seat mile economics. The -700 is highly concentrated with Southwest Airlines, which has 380 aircraft, comprising over half of its in-service commercial fleet. These younger aircraft are both a smaller portion of the fleet and face faster depreciation and higher volatility as they are late in the production cycle, already being taken over by newer technology. Despite these aspects, the type retains the same engines as other more popular variants of the 737NG family and as such, is prevented from the extreme volatility that can be seen on other types.

The Airbus A380 is an example of a type that has shown very high volatility as scepticism over its economic viability became increasingly widespread over the past decade:

By now, the Airbus A380’s weaknesses are well known – such a large aircraft requires a high load factor to remain profitable and selling enough seats to maintain this load factor is challenging on all but the densest routes.

Its very high concentration in Emirates’ fleet, with which the type is almost synonymous, and very small operator base renders it difficult to trade on the open market.

The pandemic showed that the A380 was amongst the earliest aircraft types to be stored or retired and this is reflected in the third chart, where the Market Values fall below even 50% of Base.

In conclusion, understanding the value trends and market dynamics for different aircraft types is essential in the current supply-constrained environment. These types show that there isn’t one key factor in volatility. Both elements of the physical value of the asset, such as position in production cycle and technical capability, and economic value, such as an optimised size for high load factors and yields, play a part in volatility. A statistically rich historical dataset and understanding of the market position of each asset allows us to both quantify downside value risk and predict future volatility.