Triple “R” Rated Weighting Models

Last Updated: 2 April 2024

The financial crisis of 2008 and its knock-on effects brought about changes to the way the financial world assesses investments, risks and capital allocation. Investors are arguably focusing more on the risk part of the risk/return trade-off than ever before. And within the indexing and ETF world there’s now a heavy emphasis on replication and rebalancing costs.1

Balancing risk, return and replication costs will determine the future success of exchange-traded funds, especially in fixed income, where most assets are currently invested in funds tracking “plain vanilla”, capitalisation-weighted benchmarks.

In this article, we propose new weighting models which optimise index-related risk, return and replication costs. The underlying index rules are based on comprehensive, coherent and quantitative concepts.


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We present two completely different bond weighting models and a derived third methodology (in three versions), which combines the two pure ones to produce empirical gains in all three dimensions. The country and individual bond weights based on the combined, so-called hybrid form of weighting presented here, and thereby the objective of the passive investment strategy, is to optimise the triangle of risk, return and replication (Figure 1). After all, any active or passive investment manager will seek a rebalancing strategy which minimises transaction costs for the chosen investment strategy.2 For eurozone investment grade government bond selections the empirical tests of the hybrid weighting methodology over a period of 13.5 years from 31/12/1998 to 29/06/2012 show robust comparative results for all the three objective dimensions: risk, return and replication.3

The Universe And Time Series Data Set

We define the eurozone as the universe of eligible countries and this economic region’s investment grade government bonds as the selection dataset. Tradeable quotes from the MTS Cash electronic trading platform are used for the index portfolio components. This means that the level of pricing quality is high, as single bond prices are quoted by a long-term average of 17 market makers. The sources of underlying macro-economic data are EuroStat and the OECD.4

Innovations in Fixed Income Indexing

In this section, we outline two pure weighting schemes for fixed-income index products and compare them to the traditional method of weighting by market capitalisation. A detailed explanation of the market-cap-weighting itself will not be conducted as it has been the subject of many research papers and articles.5 We then introduce the hybrid weighting methodology, comparing it with the previously mentioned pure weighting concepts in an empirical manner.

The weighting methodologies presented in this article refrain from any setting of expectations regarding input or output variables as that would tend towards active management.

Macroeconomic Weighting
Macroeconomic weighting methods in fixed income were developed in response to the perceived disadvantages—such as pricing inefficiency and risk accumulation—of capitalisation weighted indices. Macro-weighting (of government bonds) can also be seen as a fixed income version of the fundamentally weighted indices popular in the equity market.6

The basic idea is that a country’s or region’s economic share within the defined universe, measured by GDP or other macroeconomic figures, determines the country’s or region’s portfolio weight.

Author
  • Luke Handt

    Luke Handt is a seasoned cryptocurrency investor and advisor with over 7 years of experience in the blockchain and digital asset space. His passion for crypto began while studying computer science and economics at Stanford University in the early 2010s.

    Since 2016, Luke has been an active cryptocurrency trader, strategically investing in major coins as well as up-and-coming altcoins. He is knowledgeable about advanced crypto trading strategies, market analysis, and the nuances of blockchain protocols.

    In addition to managing his own crypto portfolio, Luke shares his expertise with others as a crypto writer and analyst for leading finance publications. He enjoys educating retail traders about digital assets and is a sought-after voice at fintech conferences worldwide.

    When he's not glued to price charts or researching promising new projects, Luke enjoys surfing, travel, and fine wine. He currently resides in Newport Beach, California where he continues to follow crypto markets closely and connect with other industry leaders.

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