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Friday, April 27, 2018

Multi-Asset Strategies: The Future of Investment Management


Multi-Asset Strategies: The Future of Investment Management
Larry Cao, CFA et al.
https://www.cfainstitute.org/learning/products/publications/op/Pages/op.v2018.n1.1.aspx


PREFACE
  • The popularity of multi-asset investing arises from investors' demand for investment outcomes rather than relative performance.
  • One reason that multi-asset strategies have not yet been embraced by the entire investment profession is the myth that the asset allocation process and multi-asset strategy products belong solely to the realm of quants. We do not agree.
PART I  NEW FRONTIERS IN ASSET ALLOCATION AND PORTFOLIO CONSTRUCTION

1. ESSENTIALS OF MULTI-ASSET INVESTING
  • In the sections below, I explain (1) the various types of products for multi-asset strategies, (2) the key players in the multi-asset investing process and their respective roles, and (3) key differentiators in managing a multi-asset strategy that sets it apart from an average balanced fund.
1.1. . . TYPES OF MULTI-ASSET STRATEGIES
  • Multi-asset strategy investing in various asset classes typically has an asset allocation program.
  • The four “main” asset classes covered by multi-asset strategies are stocksbondsalternatives, and cash.
  • Stock funds can be managed according to size (large-, mid-, small-, and micro-cap), style (growth and value), sector (consumer, financials, health care, industrials, technology, etc.), and geography (Asia, Europe, Latin America, Japan, BRIC, etc.).
  • Bond funds can be managed according to duration (long, intermediate, and short term), credit (core, government, credit, high yield, etc.), geography (global, United States, emerging markets, etc.), and currency (US dollar, euro, and local currency).
  • Alternatives include various hedge strategies, infrastructure, private equity, and real estate,
  • The fund of hedge funds (FoHF)
  • multi-strategy hedge funds
  • The target-date fund, an asset allocation that varies with the time, or “target date,” of withdrawal. To differentiate, the industry has coined the term target-risk fund to refer to the “old school” fund of funds.
1.2. . . MANAGERS OF AND INVESTORS IN MULTI-ASSET STRATEGIES
  • Multi-asset strategy came into existence for two reasons. First, partly driven by demand for product differentiation, the number of asset classes has exploded over recent decades since the initial proliferation of the product category. Second, tactical asset allocation came into fashion after the global financial crisis, and the name—multi-asset strategy—partly implies (accurately or inaccurately) more flexibility with the asset allocation component of these strategies.
1.3. . . PERFORMANCE EVALUATION IN THE MULTI-ASSET CONTEXT
  • Proper performance measurement, attribution, and appraisal can enhance the probability of success for the entire investment process.benchmark and tracking error can derail an investment process.
  • A particularly tricky point in comparing multi-asset strategies is how to group funds with different allocations to equity. When markets are performing well, the allocation to equity tends to dominate stock selection in terms of impact on total portfolio return.
1.4. . DIFFERENTIATING FACTORS
  • The term factor investing has become rather popular in the industry in recent years. Although it loosely covers the same or similar topics as risk factor allocation, I prefer the latter term because I believe the industry has rightly shifted its focus from the return aspect of risk premiums in the early days to the risk aspect today.
  • Despite the practical challenges, the potential benefits of dynamic asset allocation are substantial. “We have got a model for cross-section diversification. We have to balance that with time-series diversification because, when time diversification fails, cross-section diversification fails too,” said Myron Scholes at an event in Tokyo sponsored by CFA Society Japan. “The greatest reward comes from time diversification,” Scholes observed.
  • Multi-asset investing is a strategy in which practically all types of investment skills can be put to use, be they fundamental or quantitative, stocks or bonds, Asia or the United States. There are no hard and fast rules when it comes to what works in managing multi-asset strategies.
  • Three main aspects can be made active. The first is strategic asset allocation, or a reference portfolio. The second is dynamic asset allocation, or rotation strategies. And last but not least is security selection.
2. RISK FACTOR ALLOCATION

2.1. . . FACTOR VS. ASSET ALLOCATION

2.2. . . ASSET CLASSES VS. FACTOR EXPOSURES
  • the “asset-based” approach is actually an “investment product–based” approach.
  • The factor-based approach is a more modern analytical framework that makes a strong distinction between the investment vehicles themselves and the risk–return exposures that result from owning a particular set of investment vehicles. Under the factor-based approach, rather than assigning weights to assets—which, according to the asset-based approach, indirectly dictates the investor’s factor exposures—the investor consciously allocates weights to the factor exposures as a first step and then chooses a collection of assets that yields the target factor exposures. The investor’s choice of factor exposures will consider how factors interact with one another and the premiums they generate, whereas the choice of a set of assets that achieves the target factor exposures is typically made on the basis of the valuation level of each of the available assets, with the investor using the most “attractively priced” assets to access the desired factor exposures.
  • Researchers generally recognize a few primary sources of economic risk, including shocks to economic growth, shocks to inflation, and shocks to credit availability.
  • adding corporate bonds to a portfolio of high-yield stocks would not necessarily improve the portfolio’s risk exposure diversification, despite the increase in asset class diversification.
  • Because both corporate bonds and high-yield stocks have significant exposures to these three risks in largely the same fashion.
2.3. . . NUTRIENTS ARE TO FOODS AS FACTORS ARE TO ASSETS
  • Think of portfolios as meals, assets as food, and factors as nutrients. People need to consume a mixture of nutrients that varies from one person to another on the basis of individual circumstances. Because nutrients come bundled in various foods (e.g., dairy, grains, meats), people must combine foods to create a meal that supplies them with the desired nutrition. However, it is likely that many different meals would provide comparable nutrition. Thus, personal taste and food prices often dictate the preferred meal.
  • The analogy to food is also helpful for understanding tactical asset allocation (TAA). When food prices change, we may choose to consume the same nutrients at a lower cost by eating a different meal consisting of different ingredients.
  • In the language of factor-based allocation, TAA can be understood as tactically rebalancing toward out-of-favor assets that provide “cheaper” access to a set of underlying economic exposures and away from “expensive” assets offering the same factor exposures.
2.4. . . APPLICATIONS OF THE RISK-BASED FRAMEWORK

APPLICATION 1: RETHINKING “REBALANCING AND THE STRATEGIC PORTFOLIO WEIGHTS”
  • It is dangerous to assume that assets like the S&P 500 or the BarCap Agg have static risk exposures over time.
APPLICATION 2: INTERPRETING HEDGE FUND PERFORMANCE
  • many hedge fund strategies can be mimicked using more liquid and traditional assets, because many hedge funds, despite their exotic holdings and strategies, actually (and probably unintentionally) end up owning fairly commonplace factor exposures. Moreover, for the average fund, there is often little evidence that accessing standard factor exposures through more exotic assets or by using complex trading strategies leads to superior returns.
APPLICATION 3: RISK PARITY
  • the implementation of risk parity often occurs in the asset space. This means there will be parity in the assets’ contribution to overall portfolio volatility but probably no parity in the underlying economic risk exposures.
  • Although the sources of nutrients are diversified, the underlying nutrients are not.
  • a risk parity approach would be more appropriate and consistent with its original intent if applied in the factor domain rather than the asset class domain.
APPLICATION 4: ESG
  • the factor framework suggests that even if an ESG screen changes a portfolio’s country and industry mix, it need not change the portfolio’s factor exposures.
2.5. . CAUTIONARY NOTES
UNDERSTANDING DIFFERENT CATEGORIES OF FACTOR EXPOSURES
  • Three types of factor exposures
1. Those that appear uncorrelated with economic risk exposures yet generate excess returns
(referred to as "behavioral" factors which are not correlated with macroeconomic risk exposures, e.g., global growth, liquidity, inflation, and geopolitical stability)
2. Those that are correlated with macro risks and thus produce excess returns
3. Those that seem to be correlated with sources of risk but do not give rise to excess returns
  • Three types of factor exposures
                     Economic Risk (Corrlation)?
                     Yes  No
Excess  Yes   2.    1.
Return?  No    3.    N/A

THE ROLE OF PRICE IN FACTOR-BASED PORTFOLIO ALLOCATION
  • It is important to remember that investors transact in the asset space and that there are often a dozen different asset mixes that provide exposure to the same factor. The successful investor will buy his factor exposures cheaply.
AVOID GOING TOO FAR WITH THE FACTOR-BASED APPROACH
  • Practically speaking, the lay boards of large pension funds and the patriarchs of family offices are unlikely to be familiar with the factor framework and its nomenclature. Therefore, skilled and effective portfolio allocators must always communicate using the language of the asset-based approach.
2.6. . CONCLUSION
  • When investors analyze choices in the asset-based framework, the large variety of different yet related assets can make the analysis extremely complex; naive investors can often mistake the asset diversity in their portfolios for adequate risk diversification. Further, because the standard view of assets bundles notions of risk and valuation, analysis would be easier if we unpacked the two components, dealing with them in sequence. We have demonstrated that the factor-based approach to asset allocation allows us to separate the two, leading to more intuitive and perhaps more sensible portfolio solutions. Despite the technical jargon and the seemingly abstract framework, the factor-based approach has a great deal to offer investors—particularly in a world where investment options and strategies are becoming exponentially more complex.
3. DYNAMIC ASSET ALLOCATION: GREAT EXPECTATIONS
3.1. . . AN ARRAY OF ASSET ALLOCATION STRATEGIES

  • Equilibrium expected returns are those that provide a real risk-free return and an inflation premium available to all asset classes and risk premiums unique to each asset class. The risk premiums are derived from the nondiversifiable risk embedded in an equilibrium covariance matrix. Thus, the equilibrium covariance matrix serves two purposes: to determine all asset class risk premiums and the risks needed to determine an efficient policy asset allocation.
  • Many asset owners prefer to use strategic asset allocations (SAAs) that are slightly more flexible than their policy allocations. An SAA deviates from the invariant policy allocation for a period of time that is long but not as long as the policy horizon. Occasionally, say, annually or every few years, the asset owner makes a strategic tilt to the policy allocation to capture perceived capital market opportunities.
  • The SAA typically comprises small tilts away from the policy such that the portfolio remains aligned with the specific objectives and constraints that determine the policy mix.
  • Dynamic asset allocation (DAA) and tactical asset allocation (TAA) changes in circumstances. DAA is longer term than TAA in its application.
  • According to Gary Brinson, DAA7 “means deviating temporarily from the normal policy mix. It is based upon judgments that one or more asset classes is in a state of disequilibrium with respect to the investment characteristics that were utilized in forming the policy mix.”
  • DAA is a fundamentally driven, intermediate-term approach that rides the tide of discrepancies between intrinsic values and market prices. Intrinsic values exert a “gravitational” pull on asset and index prices that inexorably drives them toward equilibrium. An index’s price temporarily varies around, but is always drawn toward, its intrinsic value,
  • Brinson distinguishes tactical asset allocation (TAA) by describing market timing as “the alteration of an asset mix motivated by a forecast of future price change.”10 Considering shorter-term horizons, market timing references global tactical asset allocation (GTAA) and its domestic sister, TAA. Price movement forecasts are typically for relatively short horizons and are predicated on the analysis of past prices or underlying macroeconomic and geopolitical developments and such ratios as price to book, and market behavior or mass psychology. Whether one uses a technical analysis of price patterns or price momentum or a top-down fundamental analysis, the objective is to forecast future market price direction and magnitude.
3.2. . . SYSTEMATIC RISK ALLOCATION
  • Asset management has long been characterized as either “traditional” or “alternative.” The exploitation of systematic risks, previously the realm of hedge funds, has spawned part of an entirely new type of asset management vehicle referred to as “liquid alternatives.”
  • investors have realized that many alternative investments are capturing systematic opportunities that can be replicated at much lower cost and with considerably more liquidity.
3.3. . . INVESTMENT TAXONOMY AND LIQUID ALTERNATIVES
  • EXHIBIT 3.2. . . INVESTMENT TAXONOMY AND LIQUID ALTERNATIVES
    • Investment Taxonomy
      • Liquid
        • Traditional
          • Passive
          • Active
        • Alternative
          • Risk Parity
          • Smart Beta
            • Fundamental
            • Factor
            • Low Volatility
            • Equal Weight
            • Other
          • Risk Premia
            • Global Macro
            • Market Neutral
            • Equity Long /Short
            • Event Driven
            • Other
          • Active Currency
      • Illiquid
  • Risk parity portfolios are built on the premise that a portfolio should distribute risk exposures evenly across assets and commodities.
  • In practice, the market portfolio is not the objective of any risk parity portfolio. The more qualitative approach, pioneered by Ray Dalio at Bridgewater, distributes its risks in a manner that balances growth and inflation risks and is designed to perform well in all environments.
  • Risks are derived from historical data, and portfolios are rebalanced regularly.
  • Smart beta portfolios are rules-based strategies that effectively build indexes that are not market-cap weighted. These strategies are all thought to have risk and return characteristics that are superior to those of market-cap-based indexes. Some capture underlying compensated risk factors and others replicate systematic elements of hedge funds. Because systematic exposures can be replicated cheaply, smart beta has disrupted some hedge fund strategies at near-passive fee levels. In addition to being low fee, these strategies are liquid, transparent, and mechanically constructed on the basis of prespecified rule sets. They merely require ongoing rebalancing to maintain compliance with the rule set.
  • Smart beta strategies are rules based and, therefore, passive.
  • Risk premium strategies are total return (not necessarily market neutral) oriented and rely on active long–short investing in liquid securities or instruments. The nature of risk premium strategies effects transparency and relatively low fees.
3.4. . . HIDDEN DIVERSITY IN ACTIVE CURRENCY
  • Active currency, the primary objective of investors in active top-down capabilities is positive real returns without the downside of equities when markets experience a protracted downside.
  • The second valuable feature is diversification. Exchange rates have very low correlations with equities and bonds over time. Theoretically, their correlation is zero, because currencies do not have risk premiums and are not claims on underlying economic wealth generation.
  • Portfolios managed according to the intrinsic value discipline but with requisite shorter-term horizons should be composed of DAA for riding the tides and GTAA for navigating the waves.
3.5. . RISK MANAGEMENT
  • Liquid alternative strategies afford more precise and different risk exposures than previously available. As a result, the primary risk contribution of these strategies is diversification.
  • Downside limitation can come from higher expected returns for a specific risk level, reduced risk, or increased diversification.
  • Lastly, the “Holy Grail” of risk management is creating an anti-fragile portfolio. 
3.6. . CONCLUSION
  • The categories of liquid alternative strategies should continue to increase in number as more exploitable systematic risks are identified and to capture more capital owing to their efficiency and low cost. As this trend continues, the industry will continue to evolve and new taxonomies will emerge.
4. RISK PARITY: SILVER BULLET OR A BRIDGE TOO FAR?

4.1. . INTRODUCTION

  • Risk parity is a class of investment strategies in which capital is allocated across asset classes so that each asset class contributes an equal amount of volatility to the total volatility of the portfolio. Because this approach favors larger allocations to lower-returning asset classes, leverage is used to achieve the desired expected return.
4.2. . . THE RISK PARITY PORTFOLIO AND MODERN PORTFOLIO THEORY
  • The composition of a risk parity portfolio was developed using long-term assumptions for standard deviation and correlation.
  • Unlike mean–variance optimization, there is little consensus among practitioners on the exact methodology for determining the risk parity portfolio. The most simplistic approach ignores correlations between asset classes, arguing that they are unstable and their use leads to increased estimation error. Under that approach, the asset class weights are determined by taking the inverse of their standard deviations and scaling them so that their sum equals 1.
  • A methodology that allows both standard deviation and correlation estimates to determine the marginal contribution of each asset class to overall portfolio risk. This approach allows us to solve for the unique portfolio in which the marginal contributions of each asset class to total portfolio risk are equal.
  • Assumptions for expected return are not required in order to determine the allocation between asset classes. Return expectations are required, however, to determine the appropriate amount of leverage to achieve a given level of expected return.
  • The MPT framework allows us to see that risk parity is an extension of the mean–variance approach with the added degree of freedom created through the explicit use of leverage. This insight leads to two important questions that are critical to evaluating the risk parity value proposition. The first is whether the risk parity portfolio lies on the efficient frontier—that is, does it deliver the maximum expected return on an unlevered basis for its expected level of risk? The second question is whether the capital allocation line is actually linear and sufficiently steep—that is, is the borrowing rate sufficiently low relative to the premium for risky assets to warrant the use of leverage, and is the cost of leverage constant relative to the amount of leverage used?
4.3. . . RISK PARITY AND EFFICIENCY
  • From the standpoint of theory, it would be pure coincidence if the risk parity portfolio and the optimal portfolio were exactly the same. That is because expected return is not used in the derivation of the risk parity portfolio, while it is a critical input in determining portfolios along the efficient frontier. This makes it extremely unlikely that the risk parity portfolio lies on the efficient frontier, let alone on the frontier and at the same spot as the optimal portfolio. Thus, we should accept the fact that in a purely theoretical sense, the levered risk parity portfolio is at best equal to (and probably inferior to) the levered optimal portfolio in terms of efficiency.
  • Although empirical evidence seems to support the persistence of the leverage aversion effect that does not excuse practitioners from attempting to implement truly efficient risk parity portfolios. In practice, this often results in the relaxation of the “parity” constraint for such asset classes as commodities, which have inferior risk-adjusted returns relative to other risky assets (in many cases, they are simply excluded).
  • Some of the other key portfolio construction decisions that must be made in building efficient risk parity portfolios include the following: which asset classes to include; how many asset classes to include; defining the asset classes broadly or narrowly; the time horizon for measuring variance and covariance; how often the portfolio is rebalanced; how such illiquid assets as private equity and real estate should be included, and if they are included, how to measure their variance and covariance; and finally, how much leverage should be applied and how it should be structured.
4.4. . RISK PARITY AND LEVERAGE

4.5. . RISK PARITY PERFORMANCE
  • Practitioners have provided substantial evidence, both through history and across global markets, that the risk parity approach would have historically delivered superior risk-adjusted returns relative to a traditional unlevered mean–variance portfolio.
  • Their conclusions favoring the risk parity approach were robust across the entire set, although the advantage diminished meaningfully as the cost of leverage increased.
  • The performance ranking of the risk parity portfolio would have been quite volatile over the period, bouncing around from the bottom to the top of this broad distribution of diversified multi-asset-class portfolios.
  • Although there has been almost no adoption of the risk parity approach at the policy level among institutional investors, many of them have carved out strategic allocations to the approach as part of their overall asset allocation.
4.6. . . US INSTITUTIONAL HISTORY OF RISK PARITY
  • The importance when selecting a risk parity strategy of having a very clear understanding of how it is constructed, what its targeted risk level is over time, and how it can be expected to perform in a variety of market conditions.
4.7. . CONCLUSION
  • After the global financial crisis, it is not surprising that institutional investors took an acute interest in alternatives to equity-centric strategies. The fact that the previous 15 years had been characterized by two major crises in the global equity markets, a consistently upwardly sloping yield curve, and a general decline in interest rates made risk parity look like a particularly compelling option. Although concerns about peer risk and the use of leverage made adoption at the policy level untenable, many institutions carved out strategic allocations to risk parity in an effort to further diversify their portfolios. Practitioners have responded with a wide variety of products, and assets managed across these strategies have steadily grown. Questions remain about the use of leverage—specifically, levering fixed income—during a period of rising rates or one characterized by a persistently inverted yield curve. Practitioners argue, however, that interest rate risk is but one of many exposures in a well-balanced risk parity portfolio and that the approach will ultimately show its worth over the long run by delivering on its promise of a higher risk-adjusted return.
5. THE MORNINGSTAR STYLE BOX

5.1. . . EQUITY STYLE ANALYSIS: AN OVERVIEW
  • There are two main approaches to style analysis: holdings based and returns based. Holdings-based style tools classify portfolios on the basis of the characteristics of the underlying securities.
  • In contrast, returns-based style analysis compares the portfolio’s total returns (usually three to five years of monthly returns) with the total returns of various style-based indexes (usually 4 to 12 indexes) and makes inferences about style on the basis of how closely the portfolio returns resemble those of different indexes.
  • Because the two approaches are so different, it is important to understand how the models work in order to correctly interpret the results.
5.2. . . HISTORY OF THE MORNINGSTAR STYLE BOX

5.3. . OVERVIEW

5.4. . DRIVING PRINCIPLES
  • EXHIBIT 5.1. . THE MORNINGSTAR STYLE BOX
    • x-axis: Value/Blend/Growth
    • y-axis: Large/Mid/Small
  • Historical measures alone can rarely fully capture a stock’s value/growth orientation. Investors and institutions trade on the basis of historical measures as well as future expectations.
  • The forward-looking measures are primarily based on third-party analysts’ earnings estimates.
5.5. . HOW THE STYLE BOX WORKS
  • In general, a growth-oriented portfolio will hold the stocks of companies that the manager believes will increase such factors as sales and earnings faster than the rest of the market. A value-oriented portfolio contains mostly stocks the manager thinks are currently undervalued in price and will eventually see their worth recognized by the market. A blend portfolio might be a mix of growth stocks and value stocks, or it might contain stocks that exhibit both characteristics.
5.6. . USING THE STYLE BOX
  • APPENDIX A.5. HOLDINGS-BASED VS. RETURNS-BASED ANALYSIS
    • WEIGHING THE TWO APPROACHES
      • Kaplan (2003) demonstrated that the accuracy of returns-based style analysis varies for different styles of portfolios. For example, returns-based style analysis usually results in plot points that are similar to holdings-based plots for large-cap and value-oriented portfolios. However, Kaplan found significant variation between the two methods for small-cap, mid-cap, and growth-oriented funds. Furthermore, he demonstrated that descriptive statistics (such as R2) from the returns-based model can sometimes be misleading, implying more accuracy than is present.
      • Either approach can produce inaccurate results if exposed to certain flaws in the application design or certain limitations in the data. These are practical concerns rather than flaws in the method. Kaplan (2003) argued that most returns-based style applications impose unnecessary constraints that act as fences, keeping the style results within certain boundaries, which makes it difficult to detect more-aggressive positions, such as deep value and micro-cap. Also, the limited availability of data on derivatives often makes holdings-based style analysis less effective for funds with substantial positions in derivatives.
      • Rekenthaler et al. (2004) addressed a different question—namely, the timeliness of the models’ results. Some argue that holdings-based style analysis can be stale, because portfolios are not always available on a monthly basis. Others argue that returns-based style analysis can be stale, because it requires a long string of historical monthly returns. The authors found that a holdings-based style analysis of a year-old portfolio produces better results than a returns-based analysis using “current” data. In other words, a snapshot that is 12 months old is more accurate than a 36-month average. Furthermore, holdings-based analysis is more stable and consistent over time than returns-based analysis and thus provides a better estimate of the portfolio’s future style and risk.
      • Investors should also consider the following characteristics of these models:
        • Because returns-based style analysis requires 20–36 months of performance, this approach cannot be used for portfolios that are brand new or to detect style changes over shorter periods.
        • Returns-based style analysis can be used to validate the completeness and accuracy of reported portfolio holdings. If the returns-based analysis is considerably different from the holdings-based analysis, it may indicate that the portfolio manager is not disclosing all of his or her holdings.
        • Returns-based style analysis is dependent on the choice of benchmark indexes. Holdings-based style analysis is dependent on the choice of style framework.
        • Holdings-based style analysis is transparent. Because stocks and portfolios use the same style framework, portfolio managers can see how each holding contributes to their average portfolio style and can take action if the portfolio’s style is drifting from its target.
        • Returns-based style analysis is most accurate when the correlations between the benchmark indexes are low. If the indexes have performed in a highly correlated fashion, it is harder for the model to detect distinct style patterns in the total returns.
  • APPENDIX C.5. MORNINGSTAR FIXED-INCOME STYLE BOX
    • Fixed-Income Style Box has two key dimensions: interest rate sensitivity (limited, moderate, extensive) and credit quality (high, medium, low).
8. MANAGER INTERVIEW: BEN INKER , CFA

8.3. . . HOW THE GMO TEAM ADDS VALUE
  • The magic of risk parity in recent years has frankly been that stocks and bonds have been negatively correlated. So, the risk parity portfolio has a wonderful advantage in that you have reduced volatility. With a negative correlation, if you run stocks and bonds together at similar volatility levels, the portfolio will have lower volatility overall. That isn’t always the case. If you are running it with leverage and the correlation you are assuming to be negative is positive, that can be very bad for your portfolio.
  • Global macro often means investing on the basis of your ability to predict macroeconomic events. This is a very tricky game. It is not enough to be able to predict macroeconomic events better than the other person (which is hard enough). You also have to be able to predict the market response to those events. The market response to them at some level is more behavioral than rational, because most macroeconomic events don’t change the long-term fair value of assets.
  • Investing is all about risk and return, and the thing I am most appreciative about with regard to factor investing is that it makes you realize risk is not a single number. The important thing from my standpoint about the return side of investing is that you should never separate the question of where do those returns come from what the asset is priced to deliver today. If you can think intelligently about the risks that assets embody and the returns they are priced to deliver, it should work out pretty well in the end.

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