Indexology^® Blog

South African equity markets have once again performed poorly, especially in comparison with global equity markets.  One reason for this drab performance was that its GDP contracted 1.2% in the first quarter, although the price of gold—one of the country’s key exports—increased and the South African rand recovered somewhat with respect to other currencies.

Poor economic news, both domestic and international, led to bouts of heightened volatility in the first half of the year, but active equity managers did not seem to be able to take advantage of this.  Across all time horizons studied, both domestic and international active equity funds underperformed their respective benchmarks (see Exhibit 1).

The results regarding fixed income were less clear.  Over the five-year horizon, active managers beat their respective benchmark in the short-term bond category but not in the diversified/aggregate bond category.

To access the full report, please click here.

It’s been a roller coaster week in the aftermath of the startling conclusion to the U.S. Presidential election on November 8, 2016.   As recently as a week before the election, equity markets were quite calm, although volatility levels recognized the possibility of a surprise Trump victory.  When that victory occurred, U.S. futures declined significantly before markets opened on November 9, only to close the day with significant gains.  But the market’s returns were not evenly distributed.  Industries thought to benefit from Trump policies were revalued upward, while those that would have benefited more from a Clinton administration went in the opposite direction.

We can view this adjustment through the lens of equity market dispersion.  S&P 500 dispersion, which measures how individual stock returns deviate from average, peaked this month on November 9 for the S&P 500. It has since leveled off and is currently almost back to its pre-election levels. It has similarly declined in Europe and Asia.  As the Trump administration begins to take shape and we learn more about its priorities and legislative agenda, future surprises are possible, and we’ve learned in the last week how rapidly market conditions can change.  For now, however, narrowing dispersion signals an end to the initial adjustment to a new market consensus.

Buoyed by a good monsoon season, an increased inflow of funds by foreign portfolio investors (FPIs), the passage of a goods and services tax (GST) bill in the upper as well as lower house, and the possibility of an interest rate cut due to low to moderate inflation, the Indian capital market posted its second-best quarterly return of the last eight quarters.  However, industrial production, as measured by the Index of Industrial Production, contracted by 2.4% in July 2016, and India’s GDP growth fell to 7.1% for the quarter ending in June 2016—its lowest level in six quarters.

The S&P BSE AllCap, India’s broad-based benchmark index that covers over 95% of India’s listed market capitalization, had a total return of 6.5% during the quarter that ended Sept. 30, 2016.  During the same time, the S&P BSE SENSEX had a total return of 3.6% (see Appendix for a market heat map and monthly total returns).  With a total return of 12.9%, the S&P BSE MidCap noted best performance among the size indices, and the S&P BSE LargeCap was the worst performer, with a total return of 4.8%.  The S&P BSE SmallCap had a total return of 8.7%. 

On the sector front, metal stocks (part of the basic materials sector) showed a rally, despite subdued demand in the domestic market and continued sluggishness in key export destinations.  Energy shares bucked the trend following a pickup in oil prices in recent months. The basic materials and energy sectors noted the highest total returns, of 14.2% and 15.7%, respectively.

Information technology stocks don’t appear to be out of the woods, as leading companies forecast sluggish growth and possible uncertainty due to the Brexit.  In the case of the telecom sector, despite being one of India’s largest and fastest growing sectors, it noted the worst performance during Q3 2016, due to increased pressure on tariffs after the commercial entry of Reliance Jio.  The information technology and telecom sectors declined by 8.4% and 9.2%, respectively. 

Outlook

A good monsoon should help boost domestic consumption and keep a check on inflation, which may help the Reserve Bank of India further reduce the interest rate.  In addition, factors such as increased inflow of funds from FPIs, the passage of a GST, and the implementation of the Seventh Pay Commission recommendations may help the market.  However, the results of the U.S. Presidential elections, geopolitical concerns, and the possibility of an increase in the interest rate are a few of the key factors to watch out for.

Recently, investment professionals have paid increasing attention to the impact of carbon-intensive businesses on financial returns.  Stricter regulation and increased certainty of higher carbon pricing have made this a mainstream concern.  S&P Global Ratings’ announcement of a green assessment of debt finance in September 2016 is one notable example of this trend.

Water scarcity, as a risk to business, may be less well understood, but it is arguably the nearer-term threat.  With a global population that has risen from 3 billion in 1960 to over 7.3 billion today, demand for fresh water is becoming greater than its practicable supply.  The likely result will be increasing costs.

If water were priced to reflect this scarcity, Trucost’s analysis suggests that company profits would fall by nearly 27%, on average—with certain sectors significantly more exposed (see Exhibit 1).

Some companies already understand the risks and are acting to address them.  The Spanish energy company Iberdrola carefully assesses its own use of water and that of its suppliers.  Iberdrola details all of its supply chain’s water-related risks from a likelihood, financial-impact, and geographic-location perspective.  Unfortunately, most companies do not pursue this level of risk management, so market participants may need to take the initiative to make sure they are not “hung out to dry,” so to speak.  That may mean encouraging the companies they invest in to measure and disclose relevant water risks.

A number of larger and more sophisticated market participants are already doing this.  A typical approach is to focus on certain sectors, identify material issues, and analyze company reporting on these risks, along with mitigation strategies.  Trucost recently completed such an exercise for 120 global utility companies.  The study found that the majority (approximately 55%) were not addressing water-related risks in a meaningful way.  Only 5% of the companies provided robust reporting on how water risks are managed within their operations and along their supply chain.  About 20% of the companies did have targets to reduce water consumption and usage intensity or increase water recycling.  However, many of the targets did not specify a base year or even  a target year.

For those market participants not yet looking at water risk, how should they begin to consider it alongside other risk management considerations?

The first step could be to create a water footprint of equity holdings to identify water-intensive companies, based on either  direct use or supply chains.  The second step would be to encourage these companies to report adequately on their water dependency and ability to manage associated risks.  Ceres, a U.S.-based coalition of market participants, has produced “Aqua Gauge,” which is a framework for assessing corporate management of water risk.

There is significant legislation already, such as the EU Water Directive, and much more is on the way that seeks to bring about adequate water pricing as an incentive for the sustainable use of water resources.  Market participants that consider water risk may encourage better company performance, better financial returns, and a better environment in which to enjoy them.

Capital market benchmarks are, of course, widely used yardsticks of investment performance. For the production of the S&P STRIDE Index, in addition to providing performance data we also calculate hypothetical retirement income for vintages of the index that are at, or past, their target date. Hypothetical retirement income is expressed in index points, and can be used as a yardstick for systematic withdrawal strategies – expanding the role of S&P STRIDE from wealth accumulation benchmark to decumulation benchmark.

Each January we determine the level of hypothetical retirement income for the upcoming year in every STRIDE Index whose target date is current or past. For example, in January 2015 we began calculating hypothetical retirement income for the S&P STRIDE 2015 Indices, and we continued updating it for the S&P STRIDE 2005 and 2010 Indices. Hypothetical retirement income is derived from the proportion of index value in the TIPS-LDI allocation for each target date by dividing that figure by then-current cost of income.

Below are 2015 values of hypothetical retirement income, called “Decumulation Points”, for the S&P STRIDE 2005, 2010, and 2015 Indices. These values are available on S&P STRIDE Index websites in the “Additional Info” menu. The file is called S&P STRIDE Metrics. The January 2015 Decumulation Rate is equal to [January Decumulation Points / January STRIDE Index Level].

Source: S&P Dow Jones Indices, LLC

As explained in Waring and Siegel (2015), it is imperative to take the cost of income into account in development of systematic withdrawal policies. Doing so scales withdrawals for changes to income cost in addition to account value. However we could still be left with a lot of volatility in the periodic withdrawal a portfolio can support. To mitigate that volatility, a portfolio can be managed to offset changes in income cost with changes in account value (and vice versa) – exactly what S&P STRIDE does. For portfolio allocations pursuing strategies similar to STRIDE, our calculation of hypothetical retirement income therefore provides a sound basis for estimating how much can be withdrawn from that portfolio in a conservative, sustainable way.

The data in the above table can provide a useful comparison between one’s personal withdrawal strategy and the benchmark. For example, suppose I had $500,000 invested in TIPS at the end of January 2015. I’m pursuing an LDI strategy similar to S&P STRIDE, I retired in 2010, and I seek for my TIPS withdrawal strategy to last 25 years from retirement until 2035. In January 2015 I observe that the benchmark calculated a sustainable 2015 withdrawal rate of 4.3%. I can apply that percentage to my $500,000 TIPS-LDI portfolio to determine that the benchmark decumulation, when applied to my account, would be $21,500 for the year. Amounts greater than that may imperil the length of time my withdrawal strategy can last, and amounts less than that would potentially lengthen the time it can last. So S&P STRIDE can be used as a way to gauge sustainable withdrawals just as readily as it can be used to compare month-to-month investment performance.