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Natural Resources, a Potential “Natural” Play on Higher Inflation Expectations

Skewered

Have We Seen the Bottom in Japanese Bond Yields?

30 Year old S&P BSE SENSEX conquers the 30,000 mark

The S&P GIVI Japan Posts Impressive Five-Year Live Track Record

Natural Resources, a Potential “Natural” Play on Higher Inflation Expectations

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Tianyin Cheng

Senior Director, Strategy and Volatility Indices

S&P Dow Jones Indices

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As the economy expands and inflation ticks up in the post-election world, fueled by a pledge by President Trump to increase fiscal spending with improvements to America’s crumbling infrastructure, market participants will have to keep in mind the negative effects of increasing prices.  They may want to consider hard-asset-related investments to help maintain the purchasing power of their portfolios.  Stocks of companies in natural resource industries such as industrial materials, agriculture, and energy can potentially help market participants mitigate inflation, as these stocks may directly benefit from increases in the underlying prices.

Over the 14–year period ending Feb. 28, 2017, the S&P Global Natural Resources Index, which is designed to provide market participants with an equity-based approach to natural resource investments through its three commodity-related sectors (agribusiness, energy, and metals & mining), has outperformed the S&P Global BMI by a monthly average of 36 bps in high-inflation months.  The index has underperformed the S&P Global BMI by 29 bps in low-inflation months (see Exhibit 1).

Therefore, for market participants seeking to harness these inflationary trends, carving out a portion of an equity allocation for global natural resource stocks may warrant consideration.

Exhibit 2 illustrates how the characteristics of a conventional 60% equity/40% fixed income portfolio is affected by the addition of the S&P Global Natural Resources Index.  The decline of the S&P Global Natural Resources Index at the start of 2015 did have a negative impact on the portfolio performance, but it has been steadily increasing since January 2016.

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

Skewered

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David Blitzer

Managing Director and Chairman of the Index Committee

S&P Dow Jones Indices

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When an investor buys a stock her largest possible loss is the money invested while the gain is unlimited.  Most investors avoid losing their entire investment, few investors make as much as they hoped. One result of this favorable bias is that the distribution of stock returns is usually skewed to the right. The sketch shows what the distribution would look like.

The skew explains why an equally weighted version of an index often outperforms the cap- or value-weighted version of the same index. It also provides a reason unrelated to fees for active managers’ difficulty in beating their index benchmarks.  If the distribution of prices is skewed to the right with a long right hand tail, the average return across all the stocks will be greater than the median return.  Why? Because a few very high return stocks at the extreme right pull up the average. An investor who owns the stocks in the right hand tail will do much better than either the median or the average. The equal weight S&P 500 returned 12.2% from Election Day to April 26th.  The average return across all the stocks – because of the equal weighting – is close to the 12.2% return. However, in the right hand tail are six stocks that each returned more than 50%.

An active manager would probably hold far fewer than all 500 stocks in the S&P 500.  With each stock he selects for his portfolio there is a 50/50 chance it is below the median and a less than 50/50 chance it is above the average.  There is a much smaller chance he selects a stock in the right hand tail. The active manage must be very skilled, or very lucky, to find those in the tail. But without a few names at the extreme right end of the distribution, it will be difficult to beat the index.  The longer the tail the more important it is to hold those stocks.

A manager who buys all the stocks in the index is assured of owning the right hand tail as well as the worst performing stocks on the left edge — he will be an index manager except for the way the stocks are weighted.

The skew explains one reason why an equal weighted index will typically out performs a cap-weighted index.  In a cap weighted index, the larger the stock the larger its weight in the index and the larger the proportion of money invested in large stocks. In a portfolio tracking the cap-weighted S&P 500, more than half the money is in the 50 largest stocks. If all stocks have an equal chance being among the best performers but half the money is in only 10% of the stocks, a lot of the money is likely to be in the wrong place and miss the best performers. An equal weighted index is different – an equal amount of the funds track each stock so that gives each dollar has an equal chance of being the right place.

Portfolios tracking equal weighted indices also benefit from the small cap effect. Small cap stocks tend to outperform large cap stocks more often than not; and, small caps get more weight in equally weighted than cap-weight portfolios.

 

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

Have We Seen the Bottom in Japanese Bond Yields?

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Michele Leung

Director, Fixed Income Indices

S&P Dow Jones Indices

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While the idea of reflation is picking up steam in global markets, Japan’s core consumer price index rose 0.2% in February 2017, which remained far below the target of 2% set by the Bank of Japan (BoJ). The BoJ kept monetary policy steady in March 2017, continuing the diverging policy paths of central banks.

In fact, despite the rising-rate environment in the U.S., the last BoJ minutes noted that “the monetary policy in Japan should be decided based on Japan’s economic activity and prices.” It also dropped hints by adding, “It will be a considerable amount of time before the Bank will need to change its monetary policy.”  In an attempt to achieve the “price stability target” of 2% at the earliest possible time, the Bank of Japan introduced the quantitative and qualitative monetary easing (QQE) with yield curve control in September 2016.

Japanese sovereign bonds, as tracked by the S&P Japanese Sovereign Bond Index, delivered a total return of -0.01% YTD and -1.79% for the one-year period as of April 26, 2017. Looking at a 10-year period, its yield-to-maturity tightened from 1.14% to 0.05%, after spending 9 months in negative territory last year (see Exhibit 1).  The yield reached its lowest point (-0.25%) on July 8, 2016.

The S&P Japanese Sovereign Bond Index currently tracks 304 bonds with a total market value of 919 trillion yen, which is equivalent to USD 8.4 trillion. As of April 18, 2017, the government debt to GDP of Japan was at 250%, compared with 44% for China and 104% for the U.S.[1]  All eyes will be on the next monetary policy meeting, which is scheduled for April 26 and 27, 2017.

[1]   Source: Trading Economics.  Data as of April 18, 2017.

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

30 Year old S&P BSE SENSEX conquers the 30,000 mark

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Ved Malla

Associate Director, Client Coverage

S&P Dow Jones Indices

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The much awaited 30,000 mark was conquered by the S&P BSE SENSEX on Apr. 26, 2017 where the index level closed at 30,133.35, while the total return index level closed at 42,503.33. It took 557 trading sessions to go from the 29,000 level to cross the 30,000 level.  The S&P BSE SENSEX was launched on Jan. 2, 1986; it is now over 30 years old.  It comprises 30 stocks that represent the broader Indian equity marketplace.  The base year of the S&P BSE SENSEX is 1979, with a base value of 100 index points.

Exhibit 1: Index Returns
Source: S&P Dow Jones Indices LLC.  Data from Jan. 2, 1986, to Apr. 26, 2017.  Chart is provided for illustrative purposes.  Past performance is no guarantee of future results.

Exhibit 1 depicts the price returns of the S&P BSE SENSEX from its launch date.  The total returns version of the index is available from August 1996.

Notable events during the 30-year journey of S&P BSE SENSEX include the following.

  1. S&P BSE SENSEX first passed 1,000 on July 25, 1990.
  2. S&P BSE SENSEX took 1,692 trading days to double the index value on Aug. 21, 1990.
  3. On April 28, 1992, the S&P BSE SENSEX dropped by 12.77%, its worst single day fall.
  4. A major revamp of the S&P BSE SENSEX happened on Aug. 19, 1996, when 15 companies were replaced.
  5. The first ETF linked to the S&P BSE SENSEX was launched on Sept. 1, 2003.
  6. On May 18, 2009, the S&P BSE SENSEX gained 17.3%, the best single day gain.
  7. S&P BSE SENSEX crossed 30,000 during intraday on March 4, 2015; however it closed below the 30,000 level.
  8. S&P BSE SENSEX closed above 30,000 for the first time on Apr. 26, 2017.
Exhibit 2: 1000-Point Level of S&P BSE Sensex
MILESTONE DATE S&P BSE SENSEX INDEX LEVEL NUMBER OF TRADING DAYS SINCE PRIOR MILESTONE
Inception April 3, 1979 124.15
1000 July 25, 1990 1,007.97 2,288
2000 Jan 15, 1992 2,020.18 290
3000 Feb 29, 1992 3,017.68 29
4000 March 30, 1992 4,091.43 15
5000 Oct. 11, 1999 5,031.78 1,732
6000 Jan. 2, 2004 6,026.59 1,060
7000 June 21, 2005 7,076.52 371
8000 Sept. 8, 2005 8,052.56 54
9000 Dec. 9, 2005 9,067.28 63
10000 Feb. 7, 2006 10,082.28 40
11000 March 27, 2006 11,079.02 32
12000 April 20, 2006 12,039.55 15
13000 Oct. 30, 2006 13,024.26 135
14000 Jan. 3, 2007 14,014.92 45
15000 July 9, 2007 15,045.73 126
16000 Sept. 19, 2007 16,322.75 51
17000 Sept. 27, 2007 17,150.56 6
18000 Oct. 9, 2007 18,280.24 7
19000 Oct. 15, 2007 19,058.67 4
20000 Dec. 11, 2007 20,290.89 41
21000 Nov. 5, 2010 21,004.96 715
22000 March 24, 2014 22,055.48 844
23000 May 12, 2014 23,551.00 30
24000 May 16, 2014 24,121.74 4
25000 June 5, 2014 25,019.51 14
26000 July 7, 2014 26,100.08 22
27000 Sept. 2, 2014 27,019.39 38
28000 Nov. 12, 2014 28,008.90 44
29000 Jan. 22, 2015 29,006.02 50
30000 Apr. 26, 2017 30,133.35 557

Source: S&P Dow Jones Indices LLC.  Data from April 3, 1979, to April 26, 2017.  Table is provided for illustrative purposes.  Past performance is no guarantee of future results.

Exhibit 2 shows the details of when the S&P BSE SENSEX crossed various 1,000-point levels.

Over decades, the S&P BSE SENSEX is seen as an indicator of the economic growth of the Indian economy and is tracked to see how the Indian equity markets are performing.  More than 30 years after its launch, the S&P BSE SENSEX closed above the 30,000 level on April 26, 2017.

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

The S&P GIVI Japan Posts Impressive Five-Year Live Track Record

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Tianyin Cheng

Senior Director, Strategy and Volatility Indices

S&P Dow Jones Indices

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The S&P GIVI (Global Intrinsic Value Index) Japan posted an impressive five-year live track record.  It is one of the few multi-factor indices in the market, and it was launched five years ago.  Since its launch in March 2012, the S&P GIVI Japan has outperformed its benchmark, the S&P Japan BMI, by 1.17% per year, with a tracking error of 2.42%.  There has been a larger contribution from the low beta component (0.84%) than from the intrinsic value component (0.39%).  The sequential combination of low beta and intrinsic value appears to have added value.  In terms of risk-adjusted performance, the S&P GIVI Japan had a risk-adjusted return of 0.95, versus 0.82 for its benchmark, due to the reduction in volatility.  The annualized alpha for the S&P GIVI Japan was 1.96%, with a beta of 0.93 against its benchmark.

Having gone through a major sell-off in the last quarter of 2016, Japanese equities, as measured by the S&P Japan BMI, increased 0.47% in the first quarter of 2017.  This was backed by better-than-expected manufacturing and service PMIs; however, a strong Japanese yen remained a major challenge, along with sluggish GDP growth and stagnant inflation.  A combination of ongoing economic improvements and higher expectations for profit growth led to a rebound for cyclically sensitive sectors in Japan, such as energy and materials.

The S&P GIVI Japan underperformed its benchmark index by 20 bps in the third quarter of 2016.[1]  In the first quarter of 2017, the intrinsic value leg and the low beta leg of the S&P GIVI Japan underperformed the benchmark.  The three-year correlation between the excess return of the two legs continued to drop, reaching a low of -0.79.

 

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