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Carbon Pricing Is Essential for Effective Climate-Related Financial Disclosure

A View of Central Banks in Latin America

60% of Japanese Sovereign Bonds Are Experiencing Negative Yields

Capital Market Performance during Three Years of Narendra Modi Government

The Much-Maligned Market Portfolio

Carbon Pricing Is Essential for Effective Climate-Related Financial Disclosure

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James Richens

Research Editor

Trucost, part of S&P Global

The Financial Stability Board’s Task Force on Climate-related Financial Disclosures published its final report on June 29, 2017, leaving many companies and market participants considering how best to implement its important recommendations.

The recommendations are groundbreaking because they recognize climate change as a systemic risk to the financial stability of the global economy and present actions that all participants in the investment value chain should take—from asset owners to companies—to mitigate the risks and capitalize on the opportunities.

One of its key recommendations is that organizations should consider the scenario analysis of potential business, the strategic and financial implications of climate change and disclose them in their annual financial filings.  Organizations should assess a range of scenarios that cover reasonable future outcomes, favorable and unfavorable, including the transitional risks associated with commitments made by nearly 200 countries under the Paris Agreement to limit the increase in the global average temperature to 2°C.

One of the main transitional risks is increasing carbon regulation through carbon taxes, emissions trading schemes, or fossil fuel taxes.  Carbon prices have already been implemented in 40 countries and 20 cities and regions.  These regulations could drive up the cost of fossil-fuel-based energy and carbon-intensive raw materials, increasing operating costs and reducing profit margins.  Revenue growth may be constrained for companies that sell energy-intensive products when competitors have low-energy alternatives.  Asset owners and banks are exposed to these risks through their investments and loans to companies in carbon-intensive sectors.

However, organizations face uncertainty over the pace at which carbon regulation will be implemented in different regions—particularly those with global operations.  The solution is to conduct scenario analysis using a range of potential carbon prices.  Exhibit 1 illustrates this at a global level, with forecasts from a threefold increase in regulated carbon prices based on full implementation of the existing Paris Agreement commitments (light blue line) to a sevenfold increase, assuming policies needed to achieve the 2°C goal are implemented (navy line).  A range of other possibilities exists between these extremes, as represented by the yellow lines.

Tools exist to help organizations calculate carbon prices, such as Trucost’s Eboard carbon price calculator, which market participants can use to calculate the at-risk revenue of companies in their investment portfolios and create investment strategies to minimize their exposure to that risk.  Trucost also works with companies to calculate internal carbon prices to quantify the financial implications of carbon regulation on cash flow, operating margins, and profits in different regions, highlighting those most at risk.

The Financial Stability Board says that all organizations should strive to conduct scenario analysis that is robust, comparable, consistent, and transparent.  Carbon pricing helps organizations meet these objectives by providing a powerful diagnostic tool to understand climate-related risks and opportunities in financial terms and explain to market participants how they are preparing for business in a low-carbon world.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

A View of Central Banks in Latin America

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Jaime Merino

Former Director, Asset Owners Channel

S&P Dow Jones Indices

On June 22, 2017, Mexico’s Central Bank (Banxico) made another hike in its policy rate, saying that it was consistent with the efficient convergence process of the 3% inflation objective.  For Banxico, this is the fourth adjustment of the year, and the 19th since Banxico started a rising rates cycle in late 2015.  With all the global economic uncertainty, are we seeing the same trends in other countries of the region?  Let’s take a deeper look into what the central banks of Brazil, Chile, Colombia, and Peru have done in the past couple of years and how inflation is one of the main objectives for the changes in policy rates.

First, Exhibit 1 presents the historical policy rates since 2005 of these countries, and Exhibit 2 shows the actual policy rates of the central banks with their target inflations, actual inflations, and adjustments in the policy rates since 2016.  We can see how Peru hasn’t made many adjustments since 2016, with a total of only two in February 2016 and May 2017, leaving the policy rate at 4%—where it was at the beginning of 2016.  Meanwhile, Colombia and Mexico have changed their overnight rates 10 and 9 times, respectively.  Colombia had a cycle of increases in 2016 but decreased rates in 2017, closing May 2017 50 bps above since the start of 2016 (the Central Bank of Colombia has a meeting on June 30, 2017).  On the other hand, Mexico has increased rates by 400 bps after they were steady at 3%, a historical low, for more than 1.5 years.  Also, note that the last adjustment for all central banks has been on the downhill with the exception of Mexico.

One of the key components influencing policy rate decisions is inflation.  For Mexico, it is the main point Banxico has mentioned in their past announcements.  Taking into account market movements and inflation, Exhibits 3 and 4 show the performance and annual returns of the S&P DJI’s inflation-linked bond indices for these countries.

Source: S&P Dow Jones Indices LLC.  Data as of June 23, 2017.  Past performance is no guarantee of future results.  Table is provided for illustrative purposes. For more information, please see: S&P/BM&F Brazil Sovereign Inflation-Linked Series B Bond IndexS&P Chile Sovereign Inflation-Linked Bond IndexS&P Colombia Sovereign Inflation-Linked Bond IndexS&P/BMV Government Inflation-Linked UDIBONOS 1+ Year Bond IndexS&P Peru Sovereign Inflation-Linked Bond Index.

It is interesting how inflation-linked bonds have performed in Peru in 2017, since its inflation is at -0.42% year-over-year as of June 23, 2017.  Also, as discussed in the paper “Liquid by Design-Building Inflation-Linked Bond Indices,” inflation in Brazil has been a concern, leading the inflation-linked bonds to outperform their peers for the past one, three, five, and seven years.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

60% of Japanese Sovereign Bonds Are Experiencing Negative Yields

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Michele Leung

Former Director, Fixed Income Indices

S&P Dow Jones Indices

In our last piece, we discussed the Bank of Japan’s (BoJ) monetary policy and how the yields of Japanese sovereign bonds have responded since 2016. The latest BoJ minutes released on June 26, 2017, reiterated that it “should continue with the current monetary policy,” while it also stated that it is “necessary to reduce the pace of purchases… in order to secure the stability and sustainability of JGB purchases.”[1]

Now that we understanding that the BoJ currently controls the yield curve by keeping the short-term policy rate at -0.1% and targets the long-term rate at around 0.0%, let’s take a closer look at how it has affected sovereign bonds and the yield curve.

As of June 21, 2017, the S&P Japan Sovereign Bond Index tracks 302 bonds with a total market value of JPY 922 trillion, while the S&P Japan Government Bill Index measures the performance of 24 treasury bills with a market value of JPY 83 trillion. Among these bonds, JPY 607 trillion, or 60% of the overall exposure, have yield-to-maturity in the negative territory.  These sovereign bills and bonds have maturities ranging from 2017 to 2025, with one-half maturing in the next three years (see Exhibit 1).

The  yield curve is demonstrated in Exhibit 2. The 10-year period is the breakeven point where yield hovered around 0.06%, in-line with the BoJ’s target.  The 15-year period had active issuances and the yield was about 0.28%, compared with the 20-year period at approximately 0.50%.  The yield curve became flatter toward longer maturities, i.e. the 30- and 40-year period yields, which were around 0.80% and 1.0%, respectively.

Exhibit 1: Total Market Value in Negative Yields Versus Maturity Year

Exhibit 2: Yield-to-Maturity Versus Maturity

[1]   Source: Bank of Japan.  Data as of June 26, 2017.  https://www.boj.or.jp/en/mopo/mpmsche_minu/minu_2016/index.htm/

The posts on this blog are opinions, not advice. Please read our Disclaimers.

Capital Market Performance during Three Years of Narendra Modi Government

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Ved Malla

Associate Director, Client Coverage

S&P Dow Jones Indices

On May 16, 2014, Lok Sabha election results were announced and India gave a clear mandate to Narendra Modi’s Bharatiya Janata Party to form the government.  Narendra Modi was sworn in as the 14th Prime Minister of India on May 26, 2014, and his government recently completed three years of being in power.  In these three years, the government has made several landmark policy decisions, initiatives that have the potential to affect the Indian economy in a big way.  Some of these initiatives are listed below.

  1. GST – The Goods and Services Tax is the biggest tax reform since independence.
  2. Make in India – Aimed at making India a global manufacturing hub.
  3. Demonetization – Aimed at cracking down on black money.
  4. Skill India – Aimed at providing skill development training to youth.
  5. Digital India – Aimed at digitizing India and moving to cashless transactions.
  6. Start-up India – Aimed at promoting entrepreneurship.
  7. Jan-Dhan Yojana – Aimed at bringing banking services to every household in India.

Capital Market Performances Over the Past Three Years

The S&P BSE SENSEX (TR) value moved from 32,735.68 on May 31, 2014, to 43,944.23 on May 31, 2017; that is a three-year absolute return of 34.24%.  The price return version of the S&P BSE SENSEX closed above the 30,000 mark for the first time on April 26, 2017, at 31,145.80.  The S&P BSE AllCap, a broad benchmark index with over 900 constituents, had a three-year absolute return of 49.90%; Exhibit 1 depicts the total returns of the S&P BSE SENSEX and S&P BSE AllCap for the three-year period ending May 31, 2017.

Exhibit 1: Total Returns of the S&P BSE SENSEX and S&P BSE AllCap 

Source: S&P Dow Jones Indices LLC.  Data from May 31, 2014, to May 31, 2017.  Chart is provided for illustrative purposes.  Past performance is no guarantee of future results.

Among the size indices, the three-year absolute return of the S&P BSE MidCap was the highest, at 79.52%, followed by the S&P BSE SmallCap, at 72.11%, while the S&P BSE LargeCap was at 38.56%.  Exhibit 2 depicts the total returns of the S&P BSE LargeCap, S&P BSE MidCap, and S&P BSE SmallCap for the three-year period ending May 31, 2017.

Exhibit 2: Total Returns of the S&P BSE Size Indices

Source: S&P Dow Jones Indices LLC.  Data from May 31, 2014, to May 31, 2017.  Chart is provided for illustrative purposes.  Past performance is no guarantee of future results.

Exhibit 3 below provides the three-year absolute returns of the S&P BSE AllCap series.  We can see that among the sub-sector indices in the S&P BSE AllCap, the S&P BSE Consumer Discretionary Goods and Services and the S&P BSE Finance posted the best three-year absolute returns of 86.99% and 68.45%, respectively, while the S&P BSE Telecom had the worst return of -1.09%.

Exhibit 3: Three-Year Absolute Returns of the S&P BSE AllCap Series
INDEX INDEX VALUE ON MAY 31, 2014 INDEX VALUE ON MAY 31, 2017 3-YEAR ABSOLUTE RETURN
S&P BSE AllCap 2,964.50 4,443.89 49.90%
S&P BSE LargeCap 3,169.73 4,392.10 38.56%
S&P BSE MidCap 9,486.29 17,029.70 79.52%
S&P BSE SmallCap 10,151.26 17,471.09 72.11%
S&P BSE Consumer Discretionary Goods & Services 2,221.81 4,154.63 86.99%
S&P BSE Finance 3,685.57 6,208.31 68.45%
S&P BSE Basic Materials 2,244.72 3,460.52 54.16%
S&P BSE Fast Moving Consumer Goods 8,059.50 12,402.82 53.89%
S&P BSE Healthcare 11,138.54 14,868.22 33.48%
S&P BSE Energy 3,247.41 4,334.31 33.47%
S&P BSE Industrials 2,898.42 3,854.31 32.98%
S&P BSE Information Technology 9,615.65 12,340.20 28.33%
S&P BSE Utilities 1,971.70 2,389.95 21.21%
S&P BSE Telecom 1,364.29 1,349.36 -1.09%

Source: S&P Dow Jones Indices LLC.  Data from May 31, 2014, to May 31, 2017.  Table is provided for illustrative purposes.  Past performance is no guarantee of future results.

The posts on this blog are opinions, not advice. Please read our Disclaimers.

The Much-Maligned Market Portfolio

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Philip Murphy

Former Managing Director, Global Head of Index Governance

S&P Dow Jones Indices

It seems generally acknowledged that no investment strategy should be expected to offer an optimal trade-off between return and risk in all periods.  Yet I often hear criticism of market-cap weighting, presumably because modern portfolio theory (MPT) postulates a hypothetical market portfolio as efficient in the mean-variance sense.  Financial engineers, product developers, and asset managers point to a growing range of alternatively weighted strategies designed to capture various risk premia or market anomalies.  In other words, they seek to harvest greater mean-variance efficiency than cap weighting.  While we all want more return per unit of risk, it is nevertheless worth remembering a few salient characteristics and benefits of cap weighting.

First off, all non-market-cap-weighted strategies aggregate into the market portfolio, which by definition is a cap-weighted portfolio.  Therefore, cap-weighting is the only approach that provides a model of the market.  If one seeks equity returns but has no basis upon which to develop security or factor-level return expectations, buying a model of the market avoids guesswork.

Secondly, market-cap weighting is transactionally efficient and tax efficient, requiring only minimal rebalancing to account for changes in shares outstanding.  I have heard it stated that as companies become larger, there is forced buying of their shares in index funds, but that is not the case.  When a company’s market cap grows, existing shareholders only need to continue holding their shares.  Only net new cash flows into index-based funds (or active funds) produce buying to the extent that asset managers wish to avoid cash drag.  There are also highly liquid exchange-traded derivatives that, in addition to cash market share purchases, offer efficient means of cash equitization.

Lastly, and perhaps related to the forced buying theory above, market-cap weighting is criticized for promoting overvaluation and enabling stock price bubbles.  The premise here seems to be that the largest stocks are the most expensive.  There may be historical examples of such conditions, like the bubble in information technology shares in the late 1990s, but these periods are much more the exception than the rule.  As of mid-June 2017, the largest companies in the S&P 500 (those making up Quintile 1 in Exhibit 1) were no more highly valued relative to past earnings—or expected future earnings—than others.

Factors such as value, momentum, and quality, as well as other alternatively weighted investment approaches, may offer enhanced mean-variance efficiency in particular periods, but it is a Herculean task to identify risk premium leadership period to period and year to year.  Many investors would be better off in the long run choosing a model of the market, trying to save more, and identifying an appropriate level of overall equity exposure that considers their circumstances and risk tolerance.  It’s all about blocking and tackling for a lifetime.

The posts on this blog are opinions, not advice. Please read our Disclaimers.