Indexology^® Blog

November 9, 2016, was the day when the world witnessed two big unexpected events—one was Mr. Donald Trump winning the U.S. presidential election, and the second was the Indian Prime Minister Mr. Narendra Modi announcing that 500 and 1,000 rupee notes would no longer be considered legal tenders.  Both of these events were expected to affect India in a big way.

On November 8, 2016, Mr. Narendra Modi came on national television and announced that at the stroke of midnight, 500 and 1,000 rupee notes would no longer be legal tenders.  These notes constituted 86% of the total currency in circulation.  This announcement was by far the boldest economic decision taken in recent years.  The rationale for this unexpected decision was to remove counterfeit currency notes from the system, end the parallel black market economy, and digitize the Indian economy.

The old notes were proposed to be replaced with new 500 and 2,000 rupee notes.  The deadline to deposit or change old notes was December 30, 2016 (50 days after the announcement).  There were restrictions imposed on withdrawal, as it would take some time to release the new currency notes into the system.  Millions of people rushed to banks and ATMs to deposit old notes and collect new ones, which were unfortunately in shortage.  The unregulated cash economy had suddenly come to a standstill.

Demonetization was the topic of discussion across the length and breadth of India.  While many supported this bold move, there were others who criticized it.  Many people felt that it was a landmark decision that would have enormous benefits in the long run, while some argued that it was a decision that only caused inconvenience to the people, especially the poor.

We will analyze the effect of demonetization on the four leading S&P BSE Indices, the S&P BSE SENSEX, S&P BSE LargeCap, S&P BSE MidCap, and S&P BSE SmallCap.

Source: S&P Dow Jones Indices LLC.  Data from November 8, 2016 to March 14, 2017.  Table is provided for illustrative purposes.  Past performance is no guarantee of future results.

In Exhibit 1, we can see that all four indices have given a positive return.  The returns of the S&P BSE SENSEX and S&P BSE LargeCap were higher than those of the S&P BSE MidCap and S&P BSE SmallCap post demonetization.

Exhibit 2: Index Total Returns

Source: S&P Dow Jones Indices LLC.  Data from November 8, 2016 to March 14, 2017.  Chart is provided for illustrative purposes.  Past performance is no guarantee of future results.

From Exhibit 2, we can see that after the demonetization announcement, all four indices fell for about two weeks due to uncertainty in the economy.  This was followed by a stable period of two weeks, during which markets even recovered.  Nearing the cut-off date for depositing old notes (December 30, 2016), the markets again fell as there was uncertainty about the future due to the shortage of new currency in circulation.  The S&P BSE MidCap and S&P BSE SmallCap fell more compared with the S&P BSE SENSEX and S&P BSE LargeCap, as the demonetization had a greater effect on smaller companies. Since January 1, 2017, the markets have been bullish and have continued the upward trend.

Considering the upward movement in all four indices post demonetization, as well as the recent state election results (especially that of Uttar Pradesh, where the Narendra Modi Government obtained majority), we can conclude that the demonetization decision has been backed by most people and it has generally had a positive impact on capital markets in India.

Chinese authorities will allow market participants to buy onshore bonds through transactions carried out in Hong Kong, which will further broaden foreign access to China’s onshore bond market. While no additional details have been provided, a “bond connect” scheme that provides cross-border cash bond trading is anticipated by market participants.

Despite currency volatilities, China bonds offer better yields and diversification benefits. However, foreign investors are concerned with the potential credit risk.  Besides the non-parallel rating systems between local and the international standards, the implicit government guarantees prevented bond defaults, which had made it difficult to analyze the true underlying credit risk.

However, following the first bond default in 2014, the number of bond defaults has been accelerating, including those of state-owned enterprises. According to WIND data, over 60 bonds defaulted in 2016, with the affected sectors including land development, mining, steel-iron, and oil & gas.  The biggest default in 2016 was from China City Construction, a Chinese construction and development firm, with a collective defaulted amount of CNY 8.55 billion.  In the first two months of 2017, bond defaults amounted to CNY 4.1 billion from Dongbei Special Steel, Dalian Machine Tool, and Inner Mongolia Berun.

From 2014 to February 2017, China recorded a total of CNY 58 billion of bond defaults, which is equivalent to 0.11% of the current overall market value, as tracked by the S&P China Bond Index. The top two industries that had the highest default amounts were mining/diversified and landing development/real estate, reflecting the sharp slowdown in Chinese manufacturing and construction.

The defaults are perceived to be healthy for the long-term development of China’s onshore bond market. In the search for higher-quality corporate bonds, we adopted a two-tier screening approach in our index design and launched the S&P China High Quality Corporate Bond 3-7 Year Index. As per the index methodology, issuers must first be investment-grade rated by at least one of the international rating agencies, and then securities must be rated ‘AAA’ by at least one of the local Chinese rating agencies.

Exhibit 1: China Corporate Bond Defaults by Company Industry (Total Par Amount)

This morning’s Wall Street Journal reported, rather breathlessly, that “U.S. bond yields are topping a key measure of the dividends that large U.S. companies pay—a shift that has broad implications for investors….”  The headline was triggered by the observation that the 2.50% “yield on the 10-year U.S. Treasury note…exceeded the 1.91% dividend yield on the S&P 500.”

Does this fact have important implications? On the contrary, we’d argue that this isn’t news, and that it tells us nothing about the market’s future direction.  For historical context consider the chart below:

In September 1958, the yield on the 10-year Treasury note rose above that of the S&P 500, a condition which continued unabated for the next 50 years.  Stock yields rose above bond yields briefly at the end of 2008, but have remained below bond rates for most of the time since then.  In other words, for the vast majority of recent history, the yield on bonds has exceeded the yield on stocks.

Does the current upward move in interest rates pose “a threat” to the stock market, as the Journal suggests?  The historical evidence here is ambiguous; since 1991, the average return for the S&P 500 has been higher in months when interest rates rose than in months when rates fell.  There is clearly no concrete relationship between the direction of rates and the direction of the stock market, as the chart below makes clear:

It’s certainly possible that increased competition from higher bond rates will cause weakness in the equity market.  It’s equally possible that the economic strength which is producing higher bond yields will also sustain earnings and stock prices.  In either event, the news that bonds yield more than stocks hardly qualifies as news at all.

One of the objectives of low volatility strategies is to provide higher risk-adjusted returns than their respective benchmarks over the long run, primarily by reducing drawdowns during market downturns.  In the U.S. market, both the S&P 500^® Low Volatility Index and the S&P 500 Minimum Volatility Index have shown outperformance over the S&P 500, not just on a risk-adjusted basis, but also in absolute terms (see Exhibit 4 of Inside Low Volatility Indices).  To understand how the volatility strategies performed in the most significant down markets, we look at the three largest drawdowns of the S&P 500 since 1990:

In all three drawdown periods, the low-risk strategies outperformed the benchmark.  In the financial crisis (2007-2009), the S&P 500 Low Volatility Index outperformed the S&P 500 by over 15% and the S&P 500 Minimum Volatility Index outperformed by more than 6%.  The return differential during the tech bust (2000-2002) was more extreme, with the minimum volatility outperforming by 30% and the low volatility index outperforming by 50%.  During the Russian currency crisis (1998), the S&P 500 dropped 19% in under two months, and the low-risk strategies were again able to limit losses.

Did the low-risk indices outperform during the market downturns for the same reasons, or did the methodology differences (as outlined in a previous post) lead to different sources of excess return?  A common approach to analyzing this is to run a sector-based performance attribution, which breaks down the total excess return of a portfolio versus a benchmark between an allocation effect and a selection (+ interaction) effect.  The allocation effect will show the effect of over- or underweighting a sector relative to a benchmark, while the selection effect will show the effect of over- or underweighting individual securities within a sector relative to the benchmark.  The sector-based attribution results for the low-risk strategies during each of the three largest drawdowns of the S&P 500 are shown in the following exhibits, with the sector that had the highest total effect highlighted for each index.

During the largest drawdown, the financials sector was the largest contributor to excess return for both volatility strategies, with a total effect of 3.91% in the S&P 500 Minimum Volatility Index and 7.04% in the S&P 500 Low Volatility Index.  While both outperformed, the allocation and selection effect figures show contrasting reasons for the outperformance.  In the minimum volatility index, the allocation effect for financials was negative (-1.50%), as the financials sector in the S&P 500 underperformed, and the minimum volatility index had an average sector weight higher than the benchmark.  However, it was successful in selecting or weighting securities within the sector (selection effect of 5.41).  In the low volatility index, the financials sector’s weight was significantly reduced during the period, with an average weight of 9.23% lower than the S&P 500.  The underweight led to an allocation effect of 4.86%, while the selection effect contributed 2.17%.

The second-largest drawdown (tech bust) highlights the methodological differences for sector diversification.  Both low volatility strategies allocated away from information technology, but the minimum volatility index sector constraints (±5% relative to the benchmark at rebalancing), whereas the low volatility index can move completely out of a sector.  This occurred for the information technology sector in the low volatility index, which lead to a total effect of 18.39%.

What is evident in examining the drawdown periods is that the majority of outperformance can come from different effects for the two low-risk indices.  The selection + interaction effects drove most of the outperformance for the minimum volatility index, while the allocation effect drove the majority of the outperformance for the low volatility index.

Our related research paper, Inside Low Volatility Indices, expands on the comparison between the two low-risk strategies.

March 22, 2017, is World Water Day, the U.N.’s annual bid to raise awareness about the water crisis.  Climate change, pollution, and overconsumption are making fresh water an increasingly scarce resource.  Worldwide, 663 million people currently have no access to clean water.  By 2030, it is predicted that there will be a 40% shortfall in water supplies.[1]

Good quality water is essential to the production of nearly everything, from the food we eat to the clothes we wear.  Trucost research found that in 2016, listed companies reported exposure to water risks totaling almost USD 126 billion, due to higher operating costs associated with declining water quality and water supply disruption.  However, when taking into account the thousands of listed companies that do not disclose on water dependency, the risk could be up to USD 439 billion.

The main problem is the lack of an appropriate market price for water—one that reflects its full economic, social, and environmental value.  In most regions, there is little correlation between the price paid for water and its availability or quality.  In many places, water is cheapest where it is most scarce.  Weak regulation means water basins can be polluted by effluent discharges.

As good quality water gets scarcer, companies become increasingly exposed to water-related risks.  Market participants are also exposed to these risks through equity holdings, corporate loans, and project finance in water-intensive sectors.

Analysis by Trucost shows that if the full costs of water scarcity and pollution had to be absorbed by companies as a result of reduced water allocations, higher conditioning costs, or tougher effluent discharge requirements, average profits could fall by 18% in the chemical sector, 44% in the utilities sectors, and a massive 116% in the food and beverage sector (see Exhibit 1).

To understand and manage these risks, companies need better data on where water risks are in their global operations.  Analytical tools, such as Aqueduct by the World Resources Institute,[2] provide a way to screen locations where water is scarce.

Ecolab’s Water Risk Monetizer[3]—powered by Trucost and Microsoft—extends the insights from the Aqueduct tool and puts a monetary value on water risks, including scarcity and quality, so that they can be factored alongside operational costs and revenue forecasts.  The Water Risk Monetizer also allows users to calculate asset-level avoided risk and return on investment of water improvement projects, illustrating how businesses should prioritize investments, engage with other water users, and monitor local water conditions.

Market participants can manage risk by encouraging better corporate disclosure of water-related financial risks.  This was recognized in draft recommendations published by the Financial Stability Board’s Task Force on Climate-related Disclosures[4] in December 2016, which said that all organizations, from companies to financial institutions, should disclose information on their governance, strategy, risk management, metrics, and targets for managing climate risks, including water scarcity.  Enhanced disclosure on water will accelerate mainstream green finance as more relevant information reaches the market.

The first step is for companies and market participants to understand the water risk exposure of operations, suppliers, assets, and investments so they can build resilience against increasing water scarcity and pollution impacts, identify opportunities from water stewardship solutions, and engage with stakeholders to drive change through the market.

[1]   http://unesdoc.unesco.org/images/0023/002318/231823E.pdf

[2]   http://www.wri.org/our-work/project/aqueduct

[3]   http://waterriskmonetizer.com/

[4]   https://www.fsb-tcfd.org/publications/recommendations-report/