Special Report
Highlights We update our assumptions for the likely 10-15 year return for a wide range of different asset classes. Our methodology is basically unchanged from our last Return Assumptions report published in 2019, though we have refined our analysis and use of data in some areas. Returns over the next decade will be very low compared to history. We project that a standard global portfolio (50% equities, 30% bonds, and 20% alternatives) will return only 3.0% a year in nominal terms. That compares to a historic return of 6.3%. There are still some assets that will produce better returns, most notably small caps (4.9% a year in the US) and alternatives (6.2% for private equity, for example). But they also carry higher risk. Spreadsheets are available with detailed data. Introduction This is the third edition of our work on return assumptions. Since publishing the previous reports in November 2017 and June 2019, we have had many opportunities to discuss our methodologies with clients and in the Global Asset Allocation course at the BCA Academy. This has allowed us to test and, in many cases, refine our approach. We believe the methodologies we use have stood the test of time. We have always emphasized that this sort of capital markets assumptions (CMA) analysis is an art, not a precise science. We continue to prefer to project returns over a somewhat undefined 10-15 year period, since this allows us to think about the underlying trend of likely returns. Many other CMA papers use five (or even three) year time horizons which, in our view, are problematical since they rely heavily on a forecast of the timing, length, and severity of the next recession. Our approach is based on the concept that the return on the risk-free long-term government bond is the cornerstone to projecting asset returns, and that this return is rather predictable: It is approximately the current yield. Most other asset returns can be built up from that – the return on high-yield bonds, for example, by assuming that their historic spread over government bonds, and default and recovery rates will continue in the future. For equities, we continue to use six different methodologies, which are based on a mixture of valuation and projected earnings growth. This approach – that assumed returns can be built up from a combination of current yield plus forecast future growth in capital values – also works for most alternative asset classes, for example real estate. We have made a few minor changes to our methodology in this edition. We have, for example, made our use of historical data (for spreads, profit margins, growth relative to GDP, etc.) more consistent, using the 20-year average where possible. The biggest change this time is that clients can download here a spreadsheet with all the data in this report in order, for example, to use the data as inputs into their own optimizers. In addition, we have set up our detailed spreadsheet to allow clients to see the underlying inputs, the formulae behind our methodologies, and to input their own assumptions. This will also allow us to update the results of our analysis as often as needed. Please let us know here if you would like more details about this additional service. This Special Report is structured as follows. First, we analyze the overall results: What is the probable return from each asset class over the next 10-15 years, and how do these differ from historical returns. Next, we describe in detail the methodologies we use, for (1) economic growth, (2) fixed-income instruments, (3) equities, and (4) 12 different alternative asset classes. Then, we describe our way of forecasting currency returns, and show the return assumptions in different base currencies. Finally, we update the numbers for volatility and correlations, which many investors need as inputs into optimization programs. The summary of our results is shown in Table 1. The results are all average annual nominal total returns, in local currency terms (except for global indexes, which are in US dollars). The data is updated to end-April 2021 (except for some alternative asset classes where only quarterly data is available). Table 1BCA Assumed Returns Overall Results Returns over the coming decade are likely to be very disappointing compared to history. Our assumptions suggest a typical global portfolio, consisting of 50% large-cap equities, 30% bonds, and 20% alternatives, will produce an annual nominal return of only 3.0%, compared to an average of 6.3% over the past 20 years. A US-only portfolio with a similar composition is likely to produce only a 3.1% return, compared to 7% in history. The reason is simple: Valuations currently are very stretched in almost every asset class. The risk-free rate (the 10-year government bond yield) in the US is 1.6% (compared to a 20-year average of 3.1%). It is negative in the euro area (in nominal terms) and zero in Japan. These rates are the anchor for the returns of all other asset classes, which are theoretically priced off the risk-free rate plus a risk premium. We have long argued that valuations are not a good timing tool for investors. An asset can remain very expensive or very cheap for a considerable period. But all the evidence shows that the valuation at the starting point is a very powerful indicator of long-run returns. The yield on government bonds, for example, has a strong correlation with their 10-year return (Chart 1). In the equity market, the Shiller PE has historically had little correlation with the return over one or two years, but has a 90% correlation with the return over the subsequent 10 years (Chart 2). Chart 1Starting Yield Determines Bond Returns Chart 2Valuation Drive Long-Run Equtiy Returns With valuations in equity markets now expensive relative to history (for example, forward PE for US stocks of 22x compared to a 20-year average of 16x, and 18x in the euro zone compared to 13x), investors should expect that equity market returns will be low relative to history. Our assumptions point to a 2.6% annual return from US stocks, 2.3% from the euro zone, and 1.6% from Japan (compared to 8.5%, 3.9%, and 3.5% over the past 20 years). Our assumptions are significantly lower than when we last published our analysis in 2019; then we projected 5.6% for US stocks, 4.7% for the euro zone, and 6.2% for Japan. The difference is that equity multiples have risen and risk-free rates have fallen significantly since then. So what should investors do? They have only two choices: Lower their return assumptions, or increase their weightings in riskier asset classes. Chart 3Hard To See How US Pension Funds Will Achieve Their Targets The average US public pension fund (Chart 3) still assumes a return of 7% a year, and private pension funds’ assumption is not much lower. And yet corporate pension funds have been pushed by their consultants in recent years to increase their weighting in bonds, to more closely match their liabilities (Chart 4). It is almost mathematically impossible to achieve their targets with that sort of portfolio. In other countries, such as Australia or Canada, pension funds’ return targets are typically inflation or cash plus 3-4 percentage points. But even those targets are challenging. Chart 4...Especially With Over 50% In Bonds There are asset classes which will produce higher returns. For example, we project a return of 4.9% from US small-cap stocks – and 9.7% from UK small caps. US high-yield bonds should produce a return of 3.2% a year (even after defaults) and Emerging Markets local currency sovereign debt 2.7% (in USD terms) – not exactly exciting, but at least a pick-up over other fixed-income securities. The projected returns from illiquid alternative assets continue to look relatively attractive. An equal-weighted portfolio of the 12 alternatives we cover is projected to return 5.7% a year, not much lower than the forecast of 6.1% from our 2019 report (and compared to an average of 7.1% of the past 20 years). There are some alt assets where returns have started to trend down: Private equity, for instance, is projected to return 6.2% a year, compared to 11.1% in history, and hedge funds 4.5%, compared to 5.9%. But the illiquidity premium should not disappear completely, even if the move of alternative investments to become more mainstream has reduced it to a degree. So adding more risky assets to a portfolio is an answer, at least for those investors with a long enough time-horizon that allows them to bear the inevitable big drawdowns that come with having a more volatile portfolio. And, unfortunately, lower returns mean that the incremental return gained for each unit of risk taken has declined compared to the past 10 or 20 years (Chart 5) – the efficient frontier has flattened significantly. Chart 5You Need To Take More Risk To Produce Return How We Came Up With The Assumptions GDP Growth Several of our methodologies use assumptions (for example, in equity methods (2) and (3), based on projections of earnings growth, real-estate capital-value growth, and commodities prices) which require estimates of nominal GDP growth in each country and region. To make these forecasts, we assume that nominal GDP growth can be decomposed into: (1) growth of the working-age population, (2) productivity growth, and (3) inflation. This ignores capital intensity, but it has been relatively stable over history and is difficult to forecast. Table 2 shows the assumptions we use, and our forecasts for real and nominal GDP in each country and region. Table 2Calculations Of Trend GDP Growth For population growth we use the United Nations’ median forecast of annual growth in the population aged 25-54 between 2020 and 2040. This ranges from -1% in Japan to +1% in Emerging Markets – although note that the range of forecast population growth in EM varies widely from 1.2% in India to -1.1% in Korea (and in China, too, is negative at -0.7%). This estimate is reasonably reliable, although it does miss some possible factors, such as changes in the female participation rate, hours worked, and changing openness to immigration. Productivity is much harder to forecast. Over the past 10 to 20 years, productivity growth has trended down in most countries (Charts 6A & B). We take a slightly more optimistic view, assuming that productivity growth over the next 10-15 years will equal the 20-year average. We base this on the belief that part of the decline in productivity since the Global Financial Crisis is due to cyclical reasons which are now dissipating, and also to expectations that new technologies coming through (artificial intelligence, big data, automation, robotics etc) will boost productivity in the coming years. Others take a more pessimistic view. The Congressional Budget Office’s forecast of trend real US GDP growth in 2022-2031 of 1.8%, for example, is lower than our estimate of 2.2% mainly because of its more cautious estimate of productivity growth. Chart 6AProductivity Growth (I) Chart 6BProductivity Growth (II) To derive nominal GDP growth, we assume that inflation over the next 10 years will be on average the same as over the past 20 years, for example 2% in the US, 1.6% in the euro area, 0.1% in Japan, and 3.9% in Emerging Markets (using a weighted average of EM by equity market cap). This estimate, too, has a high degree of uncertainty. One could imagine a scenario whereby inflation picks up significantly over the next decade due to excessively easy monetary policy, overly generous fiscal spending, growth in protectionism, rising labor pressure for wage increases, and the effects of a rising dependency ratio (the ratio of non-working people, especially retirees, to total population).1 But another scenario of continued “secular stagnation” and disinflation, caused by automation-driven job losses and a chronic lack of aggregate demand, is also conceivable. We think our middle-path forecast is the most sensible one to use in projecting likely asset returns, but investors might also want to plan based on these alternative scenarios too. Note that for Emerging Markets, we continue to show two different scenarios, which vary according to different projections of productivity growth. EM productivity growth has been declining steadily since around 2010, and in all major emerging economies, not just China. Our first scenario assumes that this decline ends and that, as in our assumption for developed economies, productivity growth reverts to the 20-year average. The more pessimistic (and, in our view, more likely) scenario assumes that the deterioration in productivity continues and that in 10 years’ time, EM productivity is the same as the average of developed economies. Which scenario will be correct depends on whether emerging economies, not least China, are able to implement structural reforms over the next decade, for example liberalizing the labor market, allowing a greater role for the private sector, improving corporate governance, and institutionalizing more orthodox fiscal and particularly monetary policy. Fixed Income Our anchor for calculating assumed returns is the return on long-term risk-free assets, specifically the 10-year government bond in the strongest countries. It is a reasonable assumption that an investor who buys, for example, a 10-year Treasury bond today and holds it for 10 years will make 1.6% a year in nominal US dollar terms. While this is not perfectly mathematically correct (since it ignores reinvested interest payments, for instance), empirically the return on government bonds has been very closely linked to the yield at the start-point in history (see Chart 1). From this starting-point in each country, we can easily build up the return for other fixed-income assets. These assumptions and the results are shown in Table 3. Table 3Fixed-Income Return Calculations Government bonds in most countries have an average duration of less than 10 years. Over the past five years, in the US it has averaged 6.4 years, and in the euro area 8.0 years. Only in the UK is the average over 10 years: 12.4 years to be precise. To calculate the return from the government bond index for each country we therefore assume that the shape of the yield curve (using the spread between 7-year and 10-year bonds) in future will be the same as the historic 20-year average. Cash. We assume that over the next 10 years the yield on cash will gradually revert to an equilibrium level. We calculate a market-implied real long-term neutral rate from the 10-year historical average of 5-year/5-year OIS implied forwards deflated by the 5-year/5-year implied CPI swap rate. This is a change from the methodology we used in 2019, when we based this off the neutral rate, r*, as calculated by the Holston Laubach-Williams model. But the New York Fed has temporarily stopped updating its calculation of this due to pandemic-induced volatility in the data, and anyway it was not available for every country. We turn the real cash rate into a total nominal return using our assumption for inflation described in detail in the GDP section above, the 20-year historical average of CPI. For inflation-linked securities, such as TIPS, we take the average yield over the past 10 years (a 20-year average was not available in many markets) and add the assumption for inflation described above. Corporate credit. We assume that spreads, and default and recovery rates, while highly volatile over the cycle, remain stable in the long run (Chart 7). We use 20-year averages for these, except that data for investment-grade default rates in Japan, the UK, Canada, and Australia are not available and so we use the average of the US and the euro zone. High-yield default rates are not available for the UK either, and so we do the same. Other bonds. For government-related debt (which is a big part of some bond indexes, 28% in the US for example) we assume that the 20-year historical average of the option-adjusted spread over government bonds will apply in the future too. We use the same methodology for securitized debt (for example, mortgage- and asset-based bonds): The 20-year average spread over the return on government bonds. Emerging Market debt. The assumptions and results for the three categories of EM debt (US dollar sovereign debt, US dollar corporate debt, and local currency sovereign debt) are shown in Table 4. We here assume that the 20-year average historical spread will continue in future. Default and recovery rates are a little harder to calculate, due to a lack of data. For USD sovereign debt (where defaults are rare and so hard to project), we use the rating-based default rate, calculated by Aswath Damodaran of NYU Stern School of Business.2 For USD-denominated EM corporate debt, we use the historical average, calculated by Moody's 2.5%.3 For local-currency debt, we use the same rating-based default rate as for USD sovereign debt. To translate the return into hard currency, we assume that currencies will move in line with the inflation differential between Emerging Markets and the US. For EM inflation we use an average of the IMF’s inflation forecasts for the nine largest emerging markets weighted by their weights in the J.P. Morgan GBI-EM Global Diversified local government bond index, and compare this to our US inflation forecast. This produces an EM inflation forecast of 2.9% a year, compared to 2.2% for the US, thus lowering the USD-based return from local EM debt by 0.7 percentage point. (See a more detailed discussion of forecasting long-term EM currency changes in the Currency section below). Index returns. Table 3 also shows the assumed return for the Bloomberg Barclays bond index for each country and for the global bond index, based on a weighted average of our assumption for each fixed-income asset class and country. Chart 7ACredit Spreads & Default Rates (I) Chart 7BCredit Spreads & Default Rates (II) Table 4Emerging Market Debt Equities The assumptions and detailed results for seven different equity markets are shown in Table 5. We have not made any substantial changes to our methodology for equities. We continue to use the average of six different methods to calculate the probable equity returns over the next 10-15 years. These are: Equity Risk Premium (ERP). The return from equities equals the yield on government bonds (we use 10-year bonds) plus an equity risk premium. For the US, we use an equity risk premium of 3.5%. This is based on work by Dimson, Marsh and Staunton4 showing that this is approximately the average excess return of equities over bonds in developed economies since 1900. We scale the equity risk premium for other countries using their average beta to the US market over the past 10 years. This varies from 0.66 for Japan (giving an ERP of 2.3%) and 1.2 in the euro area (ERP is 4.2%). Growth model. Here we assume that the return from equities equals the current dividend yield plus dividend growth. We need to adjust the dividend yield, however, to take into account that in some countries, particularly the US, it is more tax efficient for companies to do buybacks than to pay out dividends. We do this by adding equity withdrawals to the dividend yield. But this needs to be done on a net basis (taking into account equity issuance). We calculate this using the average annual change in the index divisor over the past 10 years. For the US, this is -0.8%, meaning there are more buybacks than new share issues. But in all other regions, the number is positive, and as high as 5.9% a year for Emerging Markets. This dilution is something that many calculations of assumed equity returns miss. For dividend growth, we assume that the dividend payout ratio remains stable, and that earnings growth is correlated with nominal GDP growth. However, history shows that earnings grow more slowly than GDP (logically so, when you consider that companies usually grow fastest before they list on a stock exchange). So we deduct 1% from nominal GDP growth to derive our earnings growth assumption. Note that for Emerging Markets, we use two different measures of dividend growth, depending on future productivity growth, as detailed above in our explanation of the GDP projections. Growth model (with reversion to mean). To take into account that valuations and profit margins typically revert to mean over the long run, we adjust the standard growth model (No. 2 above) by assuming that the current 12-month forward PE ratio and forward net profit margin for each country gradually revert over the next 10 years to their 20-year average. In the US, for example, that would mean that the current 12-month forward PE of 22.5x falls back to 16.0x, and profit margin of 12.5% falls to 10.7%. In every country and region, the profit margin is currently above the long-run average, and in all except the UK the PE is too. Note that we have changed from using the trailing PE and margin, because to use these now would be misleading given the big pandemic-driven decline in profits in 2020. Earnings yield. An intrinsically intuitive (and empirically demonstrable) way of estimating future returns is to use the earnings yield. This is based on the idea that an investor’s return from owning a stock comes either from the company paying a dividend, or from it investing retained earnings and paying a dividend in future. In the US, for example, a forward PE of 22.5x translates into an earnings yield of 4.4%. Again, here we switched this time to using 12-month forward forecast earnings yield, rather the trailing. Shiller PE. There is a strong correlation between valuation at the starting-point and the subsequent return from equities, at least over the long-run, although not over a period of less than 3-5 years (Chart 2). We regressed the Shiller PE (current price divided by average real earnings over the past 10 years) against the return from equities over the subsequent 10 years for each country and region. Composite valuation metric. The Shiller PE has its detractors. Using a fixed 10-year period does not reflect the different lengths of recessions and bull markets. It may say more about the mean-reverting nature of earnings than about whether the current price level is too high. So we also use the BCA Compositive Valuation Metric, which comprises eight indicators including, besides standard valuation measures such as price/sales and price/book, more esoteric ones such as market cap/GDP and Tobin’s Q. Again, we regress the metric against the subsequent 10-year return. Table 5Equity Return Calculations Alternative Assets Real Estate & REITs. We use the same basic methodology for both: The current yield (cap rate or dividend yield) plus projected capital value appreciation (linked to GDP growth). For US direct real estate, for example, we use the simple average cap rate of the five categories of commercial real estate (CRE), apartments, office, retail, industrial, and hotels in major cities: 6.1%. We also use the simple average of available city and category data for other countries. Cap rates are notoriously hard to estimate precisely; our data include a range of real estate, not just prime locations. We assume that capital values will grow in line with nominal GDP growth (using the same assumptions for this as we used for equities, 4.2%). We then deduct 0.5% for maintenance. This produces an expected return of 9.8% for the US. The only difference for REITs is that we do not deduct maintenance since this should already be reflected in the dividend yield. US REITs have a dividend yield currently of 3.5%, which produces an assumed return of 7.7% (Table 6). One risk with this methodology is that in the post-pandemic world, work and life practices might change. This will hurt office and residential real estate in major cities (which are overrepresented in investible CRE), though smaller cities and rural areas might benefit. As a result, capital values might fall. Table 6Alternatives Return Calculations Farmland & Timberland. Our methodology is similar to that for real estate: Current yield plus projected growth in capital values. For farmland, we use the farmland renter yield, sourced from the US Department of Agriculture. To estimate future land values, we take the gap between land value growth over the past 40 years (3.7%) and nominal growth of world GDP over that time (5.2%), assume that gap will continue and so deduct it from our estimate of global nominal GDP growth going forward (3.6%). This gives a result of 6.5%. For timberland, we assume that annualized returns in the future are the same as over the past 20 years. This produces a return assumption of 5.7%, which is (logically) moderately lower than our assumed return for farmland. Private Equity & Venture Capital. We project the return for private equity (PE) using the 30-year time-weighted average of the three-year rolling annualized return of PE over US large-cap equities, 3.6% (Chart 8). This produces an assumed return of 6.2%. For venture capital (VC), we use the same historical average for VC over PE (0.4%) to arrive at an assumed return of 6.6%. Hedge Funds. We use the 20-year time-weighted return of the Hedge Fund Composite Index over cash, 3.5% (Chart 9). This projects a future annual nominal return of 4.5%. Commodities. We previously used a methodology based on the idea that commodities’ bear markets in history have been rather fairly consistent, lasting on average 17 years, with an average decline of 50%, and that the current bear market began in 2012 (Chart 10). However, there are arguments that a new “commodities super-cycle” may be starting, driven by government infrastructure spending, and investment in alternative energy.5 We are agnostic for now on whether that will be the case, but it makes sense to switch to a neutral methodology, more in line with what we use for other assets classes: The return from commodities relative to GDP over the long run. Specifically, the CRB Raw Industrials Index has risen by an annualized 1.6% since 1951, during which time US nominal GDP growth averaged 6% (Chart 11). We assume that the differential will continue in future (although we calculate growth using global, not US, GDP), giving an annual return from commodities over the next 10-15 years of -0.9%. Gold. We calculate this using a regression of the gold price against nominal GDP growth and the annual change in the real 10-year yield over the past 40 years. For the forward-looking return assumption, we use a forecast of real rates (based on the equilibrium cash rate plus the average historical spread between the 10-year yield and cash) and a forecast of global nominal GDP growth. This produces an assumed return of 3.8%. Structured products. This asset class consists mainly of mortgage-backed and other asset-backed securitized instruments. In the US, these have historically returned 0.6% over US Treasurys. We assume that this premium continues, producing a total future return of 1.1% a year. Chart 8Private Equity Premium Chart 9Hedge Fund Return Over Cash Chart 10Commodity Prices In History Chart 11Commodity Prices Vs. GDP Growth Currencies Chart 12Currencies Tend To Revert To PPP To translate our local currency returns into an investor’s base currency, we need to arrive at some projections for FX movements over the next decade. Fortunately, for developed market currencies at least, it is relatively straightforward to use purchasing power parities (PPP) to do this since, over the long run, all the major currencies have tended to revert to PPP (Chart 12). We assume that in 10 years’ time all currencies will trade at PPP. We use the IMF’s estimate of today’s PPP for each currency to calculate the current under- or over-valuation. We assume that PPP will change in future years according to the relative inflation between each country and the US. The IMF provides five-year inflation forecasts and we assume that inflation will continue at this rate until 2031. For the euro zone, we calculate the PPP of the euro using the GDP-weighted PPPs of the five largest economies. The results (Table 7) suggest that the US dollar is currently overvalued and, given the forecast of higher inflation in the US than elsewhere in the future, will depreciate significantly against all major currencies except the Australian dollar. The USD is projected to depreciate by 1.7% a year against the euro and 1.1% against the yen over the next 10 years. It is likely to appreciate by 1.3% a year against the AUD, however. Table 7Currency Return Calculations Emerging Markets (Table 8) are more complicated. There is no evidence that EM currencies move towards PPP over time. All the major EM currencies are currently very cheap versus PPP (varying from 34% undervalued for the Chinese yuan to 67% for the Indonesian rupiah) but they were 10 years ago, too, and have not significantly moved towards PPP over that time. Table 8EM Currencies To calculate likely EM currency moves against the USD, therefore, we carry out a regression of the nine largest EM currencies against their relative CPI inflation rate to US inflation in history. We assume an intercept of zero. The regression coefficients vary from +0.5 for China to -1.7 for Malaysia. Apart from China, Malaysia, Poland and South Africa, the coefficients were negative, meaning that historically the USD has strengthened against the EM currency at least partly in line with relative inflation. To calculate likely future currency movements, we use the IMF’s five-year inflation forecasts and assume that the same rate of inflation will continue for our whole projection period. This methodology points to moderate annual depreciation of most EM currencies against the USD, varying from 0.8% a year for the Russian ruble to 0.1% for the Indonesia rupiah. The Chinese yuan and Taiwanese dollar are projected to appreciate moderately. We calculate the average EM currency movement using the weights of these nine large economies in the EM J.P. Morgan GBI-EM Global Diversified local-currency sovereign bond index. This produces a small (0.1%) a year appreciation. However, the IMF’s EM inflation forecasts may be too optimistic. It forecasts, for example, that Brazilian inflation will be only 3.3% a year in future, compared to an average of 6.1% over the past 20 years, and Russian inflation 4.0% versus a historical average of 9.3%. This suggests that EM currency performance could be worse than our projections. Table 9 shows the returns for the major asset classes expressed in local currency terms for six base currencies, based on the calculations explained above. Table 9Returns In Different Base Currencies Correlation And Volatility Below, in Table 10, we provide correlations for clients who need these inputs for their optimization calculations. Table 10Long-Run Correlation Matrix Returns can be calculated using the sort of forward-looking methodologies we have described above. For volatility, we think it is reasonable to use historical average data (Table 1, far right column), since volatility does not tend to trend over the long run (Chart 13). But correlation is a different matter. Correlations have varied significantly in history due to structural changes or regime shifts. The correlation of equities to bonds, it is well known, has moved from positive in the 1980s and 1990s, to negative since 2000 – probably because inflation disappeared as a factor moving bond prices (Chart 14). The correlation between equity market has risen as a result of the globalization of investment flows, though note that it fell back in 2010-2019. Chart 13Volatility Is Fairly Stable In The Long Run Chart 14Correlations Are Not Stable So what correlations should investors use in an optimizer? Our recommendation would be to use the longest period of history available. A US investor, for example, might take the average correlation between Treasury bonds and large-cap US equities since 1945, 0.1%. Table 10 shows the correlation since 1973 of all the major asset classes for which data is available. Unfortunately, this misses some important asset classes such as high-yield bonds and Emerging Market equities, whose history does not go back that far. The results are intuitive – and prudent. From these numbers, it would seem sensible to use an assumption of a small positive correlation between US Treasurys and US equities, for example. US investment-grade debt has a correlation of 0.4 against equities. Global equity markets are all fairly highly correlated to each other, ranging mostly from 0.4 to 0.7. The most non-correlated asset class is commodities, especially gold. Garry Evans, Senior Vice President Global Asset Allocation garry@bcaresearch.com Amr Hanafy, Senior Analyst Global Asset Allocation amrh@bcaresearch.com Footnotes 1 These are themes that BCA Research has been writing about for several years. See, for example, please see Global Investment Strategy, "1970s-Style Inflation: Could It Happen Again? (Part 1)," dated August 10, 2018; and " 1970s-Style Inflation: Could It Happen Again? (Part 2)," dated August 24, 2018. 2 Please see http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/ctryprem.html 3 Annual Emerging Markets Default Study: Coronavirus Will Push Up Default Rates https://www.moodys.com/researchdocumentcontentpage.aspx?docid=PBC_1214906 4 Please see, for example, https://www.credit-suisse.com/media/assets/corporate/docs/about-us/research/publications/credit-suisse-global-investment-returns-yearbook-2021-summary-edition.pdf. 5 Please see Commodity & Energy Strategy, "Industrial Commodities Super-Cycle Or Bull Market?", dated March 4, 2021.
