Get your Fact(or)s right, how investors can boost alpha in their REITs allocations
Investors in listed real estate can harvest more alpha form their allocations by exposure to factors that drive returns of real estate
As investors weigh their allocations to real estate and the potentially attractive timing to overweight listed real estate compared to private exposures as a result of the disconnect that has emerged between the two they should also weigh the most efficient implementation options to benefit from alpha generation opportunities in listed allocations.
The recent disconnect between listed and private real estate reached historical levels at the end of last year due to rising interest rates and fears of an increased likelihood of a recession. In the US, the listed market represented by the FTSE Nareit All Equity REITs Index fell by -24.9% while the private market based on the NCREIF NFI-ODCE Index returned +7.47%. While listed markets provide daily liquidity and price discovery, private markets on the other hand are ‘priced’ based on valuations which are both slower to adjust to new market conditions and more incremental. Over time and during more normalized market conditions the two tend to converge as both reflect performance of the same underlying asset class. This converging adjustment began at the end of last year with private market valuation component falling by -5.76% for the fourth quarter and listed market rebounding by 10.1% during January of this year. This type of pricing disconnect within the same asset class offers investors opportunities to potentially capitalise on market dislocations to enhance their overall exposures to real estate. This can be achieved not only through traditional active management or purely passive options but also by allocating to specialist systematic or factor-based options that can provide consistent and repeatable alpha capture through exposures to factors that drive real estate returns.
Why real estate factors, the factor disconnect…
Providers of factor-based investments (and indices that are typically replicated) have structured their product offerings mainly around the typical five or so general equity market factors as identified in academic literature and broadly referred to as ‘proven factors’ that originated from the work of Fama and French, so called Fama-French factors. The rapid growth in factor investing has been predominantly based on these backed by clear evidence that these factors can generate positive excess returns over time, in general equity market exposures, ‘in general’ being the operative aspect.
Factors ‘outside’ of the Fama-French framework have until recently been viewed with some scepticism within a ‘reasonable margin’. Typically, reasonable margin or modifications to the ‘proven factors’ have been viewed as acceptable to allow an overlay of proprietary research and definitions in the methodologies of indices and products. While this process at best fine-tunes some aspects of factor construction, it does not alter the core characteristics that are being targeted in any significant way. On the other hand, factors that do not directly aim to replicate the same dynamics have until recently been viewed as something close to ‘data mining’ based on the view that with enough ‘twists and regressions’, those too can ultimately be traced to the ‘proven factors’, at least to a large extent. Therefore, this (general) process has in turn been applied to expand products and to offer the ‘proven factors’ and their variations, at more granular market segments such as for example global regions, single countries and individual sectors, through a cookie-cutter approach.
However, as one migrates from ‘general’ broad equity markets to more specific segments it is obvious that what might hold at an aggregate equity market level does not necessarily translate directly to a more granular level and particularly not at individual sector level. Why? Largely because while regions and countries still offer relatively high level of sector diversification, i.e. potentially capture more of broad equity market dynamics, the same cannot be said for specific sectors, at any level; neither at global, regional nor country level. At individual sector level, any systematic return dynamics are highly dependent on the specific characteristics of that particular sector. Of course, this disconnect in return dynamics applies to various degrees to different economic sectors but it applies to listed real estate in a meaningful and fundamental way (and other listed real assets sectors such as e.g. listed infrastructure, but here we focus on listed real estate only).
Investors know that real estate is a different asset class to general equities, this applies to securitised real estate assets in the form of listed real estate as well. It is different. In our view applying general equity market factors to listed real estate might be inconsistent with the asset class. To get a better understanding of this consider the following points;
Academic research into listed real estate has consistently concluded that real estate securities, over time, correlate more with underlying real estate markets than general equity markets.
General equities can be viewed as predominantly cash flow driven while real estate (and listed real estate) can be viewed as predominantly asset value driven.
Equities typically follow the shorter business cycle (approx. 4-5 years), while listed real estate typically follows the longer real estate cycle (approx. 8-10 years)
Listed real estate accounts for approximately 3% of global equity market capitalisation of developed markets, which could result in any sector specific dynamics not being accounted for at the aggregate broad equity market level.
All these points are academically well documented, consistent through time and highlight clearly the fundamental differences between listed real estate and general equity markets. Importantly, these points also imply that general equity market factors are likely to be sub-optimal for systematic alpha generation in listed real estate securities markets and that investors should consider other more specific approaches. In doing so, it is important to remember is that only because certain economic sectors are fundamentally different from general equity markets dynamics, considering specific return drivers for a specific asset class as factors is not ‘data mining’. It is the exact opposite, it is a prudent and targeted way to apply specific knowledge to a specific allocation. Much in the same way as investors allocate to listed real estate through active managers specialising in the sector, because they have deeper knowledge and understanding of fundamental return drivers within the sector compared to generalists, the same evaluation and selection process should apply to systematic and factor based allocations to the sector.
In order to harvest ongoing alpha from listed real estate allocations, investors might consider gaining targeted exposure to specific factors that drive the returns of real estate and real estate securities, not general equity markets, in combination with actively managed allocations.
About Kania Global Real Estate CAI Index
The Kania Global Real Estate CAI Index, an alternative beta index based on factors relevant to real estate and real estate securities and not general equity market factors, has generated significant and consistent live outperformance to benchmark of approximately +430bps per annum, consistently over 1-, 3- and 5-year periods. This live outperformance profile, magnitude and consistency, highlight the importance of structuring processes and allocations that provide exposure to factors that are fundamentally relevant to real estate and real estate securities markets in a repeatable, consistent way and at the same time eliminating noise and extrapolating anecdotal data and information across diversified portfolios.
For further information about the index and factors, please contact info@kaniaadvisors.com.
About Kania Advisors
Kania Advisors is an independent research and advisory firm focused exclusively on institutional real assets allocations and investment programmes. We provide advice and solutions to improve outcomes in real assets investment programmes. We conduct detailed industry research and custom studies typically focused on quantitative analysis and provide insights which form a critical part of a client's decision process.