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Visualizing 90 Years of Stock and Bond Portfolio Performance

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Visualizing 90 Years of Stock and Bond Portfolio Performance

Visualizing 90 Years of Stock and Bond Portfolio Performance

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Last year, stock and bond returns tumbled after the Federal Reserve hiked interest rates at the fastest speed in 40 years. It was the first time in decades that both asset classes posted negative annual investment returns in tandem.

Over four decades, this has happened 2.4% of the time across any 12-month rolling period.

To look at how various stock and bond asset allocations have performed over history—and their broader correlations—the above graphic charts their best, worst, and average returns, using data from Vanguard.

How Has Asset Allocation Impacted Returns?

Based on data between 1926 and 2019, the table below looks at the spectrum of market returns of different asset allocations:

Stock / Bond
Portfolio Allocation
Best Annual ReturnWorst Annual ReturnAverage Annual Return
0% / 100% 32.6%-8.1%5.3%
10% / 90% 31.2%-8.2%6.0%
20% / 80%29.8%-10.1%6.6%
30% / 70%28.4%-14.2%7.2%
40% / 60%27.9%-18.4%7.8%
50% / 50%32.3%-22.5%8.3%
60% / 40%36.7%-26.6%8.8%
70% / 30%41.1%-30.7%9.2%
80% / 20%45.4%-34.9%9.6%
90% / 10%49.8%-39.0%10.0%
100% / 0%54.2%-43.1%10.3%

We can see that a portfolio made entirely of stocks returned 10.3% on average, the highest across all asset allocations. Of course, this came with wider return variance, hitting an annual low of -43% and a high of 54%.

A traditional 60/40 portfolio—which has lost its luster in recent years as low interest rates have led to lower bond returns—saw an average historical return of 8.8%. As interest rates have climbed in recent years, this may widen its appeal once again as bond returns may rise.

Meanwhile, a 100% bond portfolio averaged 5.3% in annual returns over the period. Bonds typically serve as a hedge against portfolio losses thanks to their typically negative historical correlation to stocks.

A Closer Look at Historical Correlations

To understand how 2022 was an outlier in terms of asset correlations we can look at the graphic below:

The last time stocks and bonds moved together in a negative direction was in 1969. At the time, inflation was accelerating and the Fed was hiking interest rates to cool rising costs. In fact, historically, when inflation surges, stocks and bonds have often moved in similar directions.

Underscoring this divergence is real interest rate volatility. When real interest rates are a driving force in the market, as we have seen in the last year, it hurts both stock and bond returns. This is because higher interest rates can reduce the future cash flows of these investments.

Adding another layer is the level of risk appetite among investors. When the economic outlook is uncertain and interest rate volatility is high, investors are more likely to take risk off their portfolios and demand higher returns for taking on higher risk. This can push down equity and bond prices.

On the other hand, if the economic outlook is positive, investors may be willing to take on more risk, in turn potentially boosting equity prices.

Current Investment Returns in Context

Today, financial markets are seeing sharp swings as the ripple effects of higher interest rates are sinking in.

For investors, historical data provides insight on long-term asset allocation trends. Over the last century, cycles of high interest rates have come and gone. Both equity and bond investment returns have been resilient for investors who stay the course.

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Investor Education

How MSCI Builds Thematic Indexes: A Step-by-Step Guide

From developing an index objective to choosing relevant stocks, this graphic breaks down how MSCI builds thematic indexes using examples.

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Title text says “How MSCI builds thematic indexes” and funnel is pictured with the following labels from top to bottom: global parent universe, relevance filter, and false positive control.

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The following content is sponsored by MSCI

How MSCI Builds Thematic Indexes: A Step-by-Step Guide

Have you ever wondered how MSCI builds its thematic indexes?

To capture long-term, structural trends that could drive business performance in the future, the company follows a systematic approach. This graphic from MSCI breaks down each step in the process used to create its thematic indexes.

Step 1: Develop an Index Objective

MSCI first builds a broad statement of what the theme aims to capture based on extensive research and insights from industry experts.

Steps 2 and 3: List Sub-Themes, Generate Keyword List

Together with experts, MSCI creates a list of sub-themes or “seedwords” to identify aligned business activities. 

The team then assembles a collection of suitable documents describing the theme. Natural language processing efficiently analyzes word frequency and relevance to generate a more detailed set of keywords contextually similar to the seedwords.

Step 4: Find Relevant Companies

By analyzing financial reports, MSCI picks companies relevant to the theme using two methods:

  1. Direct approach: Revenue from a company’s business segment is considered 100% relevant if the segment name matches a theme keyword. Standard Industrial Classification (SIC) codes from these directly-matched segments make up the eligible SIC code list used in the indirect approach.
  2. Indirect approach: If a segment name doesn’t match theme keywords, MSCI will:
    • Analyze the density of theme keywords mentioned in the company’s description. A minimum of two unique keywords is required.
    • The keyword density determines a “discount factor” to reflect lower certainty in theme alignment.
    • Revenue from business segments with an eligible SIC code, regardless of how they are named, is scaled down by the discount factor.

The total percentage of revenue applicable to the theme from both approaches determines a company’s relevance score.

Step 5: Select the Stocks

Finally, MSCI narrows down the stocks that will be included:

  • Global parent universe: The ACWI Investable Market Index (IMI) is the starting point for standard thematic indexes.
  • Relevance filter: The universe is filtered for companies with a relevance score of at least 25%.
  • False positive control: Eligible companies that are mapped to un-related GICS sub-industries are removed.

Companies with higher relevance scores and market caps have a higher weighting in the index, with the maximum weighting for any one issuer capped at 5%. The final selected stocks span various sectors. 

MSCI Thematic Indexes: Regularly Updated and Rules-Based

Once an index is built, it is reviewed semi-annually and updated based on:

  • Changes to the parent index
  • Changes at individual companies
  • Theme developments based on expert input

Theme keywords are reviewed yearly in May. Overall, MSCI’s thematic index construction process is objective, scalable, and flexible. The process can be customized based on the theme(s) you want to capture.

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Learn more about MSCI’s thematic indexes.

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