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Over the past three decades, a sustained surge in inflation has been absent in developed markets. As a result, investors face the challenge of having limited experience and no recent data to guide the repositioning of their portfolios in the face of heightened inflation risk. In this article, the authors provide some insight by analyzing both passive and active strategies across a variety of asset classes for the United States, the United Kingdom, and Japan over the past 95 years. Unexpected inflation is bad news for traditional assets, such as bonds and equities, with local inflation having the greatest effect. Commodities have positive returns during inflation surges, but there is considerable variation within the commodity complex. Among the active strategies, the authors find that trend-following provides the most reliable protection during important inflation shocks. Active equity factor strategies also provide some degree of hedging ability. The authors also provide an analysis of alternative asset classes such as fine art and discuss the economic rationale for including cryptocurrencies as part of a strategy to protect against inflation. TOPICS:Developed markets, financial crises and financial market history, risk management, portfolio management/multi-asset allocation Key Findings ▪ The authors examine a range of passive and active strategies using a century of data in the United States, the United Kingdom, and Japan and find that passive equity and fixed-income strategies fare poorly during inflation surges. ▪ Commodities provide historical inflation protection, as do collectibles such as wine and fine art. ▪ Active strategies such as trend-following fare well during historical inflation surges, and equity factor strategies such as quality provide some protection.

In the late stages of long bull markets, a popular question arises: What steps can an investor take to mitigate the impact of the inevitable large equity correction? Hedging equity portfolios is notoriously difficult and expensive. In this article, the authors analyze the performance of different tools that investors could deploy. For example, continuously holding short-dated S&P 500 put options is the most reliable defensive method but also the most costly strategy. Holding safe-haven US Treasury bonds produces a positive carry but may be an unreliable crisis-hedge strategy because the post-2000 negative bond–equity correlation is a historical rarity. Long gold and long credit protection portfolios sit between puts and bonds in terms of both cost and reliability. Dynamic strategies that performed well during past drawdowns include futures time-series momentum (which benefits from extended equity sell-offs) and a quality strategy that takes long (short) positions in the highest (lowest) quality company stocks (which benefits from a flight-to-quality effect during crises). The authors examine both large equity drawdowns and recessions. They also provide some out-of-sample evidence of the defensive performance of these strategies relative to an earlier, related article. TOPICS:Equity portfolio management, options, risk management, performance measurement

Over the past three decades, a sustained surge in inflation has been absent in developed markets. As a result, investors face the challenge of having limited experience and no recent data to guide the repositioning of their portfolios in the face of heighted inflation risk. We provide some insight by analyzing both passive and active strategies across a variety of asset classes for the U.S., U.K., and Japan over the past 95 years. Unexpected inflation is bad news for traditional assets, such as bonds and equities, with local inflation having the greatest effect. Commodities have positive returns during inflation surges but there is considerable variation within the commodity complex. Among the dynamic strategies, we find that trend-following provides the most reliable protection during important inflation shocks. Active equity factor strategies also provide some degree of hedging ability. We also provide analysis of alternative asset classes such as fine art and discuss the economic rationale for including cryptocurrencies as part of a strategy to protect against inflation.

Recent studies show that volatility-managed equity portfolios realize higher Sharpe ratios than portfolios with a constant notional exposure. The authors show that this result only holds for risk assets, such as equity and credit, and they link this finding to the so-called leverage effect for those assets. In contrast, for bonds, currencies, and commodities, the impact of volatility targeting on the Sharpe ratio is negligible. However, the impact of volatility targeting goes beyond the Sharpe ratio: It reduces the likelihood of extreme returns across all asset classes. Particularly relevant for investors, left-tail events tend to be less severe because they typically occur at times of elevated volatility, when a target-volatility portfolio has a relatively small notional exposure. We also consider the popular 60–40 equity–bond balanced portfolio and an equity–bond–credit–commodity risk parity portfolio. Volatility scaling at both the asset and portfolio level improves Sharpe ratios and reduces the likelihood of tail events.

In this article, the authors analyze and contrast the performance of discretionary and systematic hedge funds. Systematic funds use rules-based strategies, with little or no daily intervention by humans. In the authors’ experience, some large allocators shy away from systematic hedge funds altogether. One possible explanation is what the psychology literature calls “algorithm aversion.” However, the authors find no empirical basis for such an aversion. For the period 1996–2014, systematic and discretionary manager performance is similar, after adjusting for volatility and factor exposures (that is, in terms of their appraisal ratio). It is sometimes claimed that systematic funds have a greater exposure to well-known risk factors. However, the authors find that for discretionary funds (in aggregate), more of the average return and the volatility of returns can be explained by risk factors.

Over the 2016-2019 period, we released a series of research papers on the topic of “strategic risk management”, or the embedding of risk management into investm

Hedging equity portfolios against the risk of large drawdowns is notoriously difficult and expensive. Holding, and continuously rolling, at-the-money put options on the S&P 500 is a very costly, if reliable, strategy to protect against market sell-offs. Holding ‘safe-haven’ US Treasury bonds, while providing a positive and predictable long-term yield, is generally an unreliable crisis-hedge strategy, since the post-2000 negative bond-equity correlation is a historical rarity. Long gold and long credit protection portfolios appear to sit between puts and bonds in terms of both cost and reliability. In contrast to these passive investments, we investigate two dynamic strategies that appear to have generated positive performance in both the long-run but also particularly during historical crises: futures time-series momentum and quality stock factors. Futures momentum has parallels with long option straddle strategies, allowing it to benefit during extended equity sell-offs. The quality stock strategy takes long positions in highest-quality and short positions in lowest-quality company stocks, benefitting from a ‘flight-to-quality’ effect during crises. These two dynamic strategies historically have uncorrelated return profiles, making them complementary crisis risk hedges. We examine both strategies and discuss how different variations may have performed in crises, as well as normal times, over the years 1985 to 2016.

We study the relative and absolute pricing of CMBX contracts (commercial real estate derivatives) during the recent financial crisis. Using a structural CMBX pricing model, we find little systematic mispricing relative to REIT equity and options. We do find short-term deviations from this relative pricing relationship that are statistically and economically significant. In particular, the CMBX market temporarily overreacts to news announcements. We provide evidence that this temporary mispricing is caused by price pressure due to hedging activities. Finally, an absolute pricing analysis provides no substantial evidence that CMBX contracts traded at fire sale levels during the crisis.

I investigate household interest rate risk management by solving a life-cycle asset allocation model that includes mortgage and bond portfolio choice. I find that most investors prefer an adjustable-rate mortgage and thereby save on the bond risk premium that is contained in fixed-rate mortgage payments. Only older, risk-averse investors hold some fixed-rate mortgage debt. Together with a position in short-term bonds this enables them to hedge against changes in the real interest rate, while the inflation exposure of the debt and bond positions cancel out. Hedging house price changes with bonds only occurs at the end of the life cycle. Early in the life cycle short-sale constraints prevent an effective hedge.

Practical Applications Summary Quantitative investing, which deploys machine learning and other algorithms, now more or less dominates financial markets. In this environment, it9s useful to step back and compare the performance and risk exposures of discretionary and systematic hedge fund managers. Many allocators to hedge funds, large and small alike, avoid allocating to systematic funds, either partially or entirely, believing them to be difficult to understand, to offer less transparency, and to deliver worse performance due to the use of data from the past. These reasons seem to be consistent with “algorithm aversion”—a distrust of systems. In their article Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance, published in the Summer 2017 issue of The Journal of Portfolio Management , Campbell R. Harvey, Sandy Rattray, Andrew Sinclair, and Otto van Hemert compare the past performance of systematic funds with their discretionary counterparts. They show that, after adjusting for volatility and factor exposures, the lack of confidence in systematic funds is not justified.

The fraction of newly-originated mortgages that are of the adjustable-rate (ARM) versus the fixed-rate (FRM) type exhibits a surprising amount of time variation. A simple utility framework of mortgage choice points to the bond risk premium as theoretical determinant: when the bond risk premium is high, FRM payments are high, making ARMs more attractive. We confirm empirically that the bulk of the time variation in household mortgage choice can be explained by time variation in the bond risk premium. This is true regardless of whether bond risk premia are measured using forecasters' data, a VAR term structure model, or a simple rule-of-thumb based on adaptive expectations. This simple rule-of-thumb moves in lock-step with mortgage choice, thereby lending further credibility to a theory of strategic mortgage timing by households.

Using loan-level data, we analyze the quality of subprime mortgage loans by adjusting their performance for differences in borrower characteristics, loan characteristics, and macroeconomic conditions. We find that the quality of loans deteriorated for six consecutive years before the crisis and that securitizers were, to some extent, aware of it. We provide evidence that the rise and fall of the subprime mortgage market follows a classic lending boom-bust scenario, in which unsustainable growth leads to the collapse of the market. Problems could have been detected long before the crisis, but they were masked by high house price appreciation between 2003 and 2005. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org., Oxford University Press.

We study time-series momentum (trend-following) strategies in bonds, commodities, currencies and equity indices between 1960 and 2015. We find that momentum strategies performed consistently both before and after 1985, periods which were marked by strong bear and bull markets in bonds respectively. We document a number of important risk properties. First, that returns are positively skewed, which we argue is intuitive by drawing a parallel between momentum strategies and a long option straddle strategy. Second, performance was particularly strong in the worst equity and bond market environments, giving credence to the claim that trend-following can provide equity and bond crisis alpha. Putting restrictions on the strategy to prevent it being long equities or long bonds has the potential to further enhance the crisis alpha, but reduces the average return. Finally, we examine how performance has varied across momentum strategies based on returns with different lags and applied to different asset classes.

We analyse and contrast the performance of discretionary and systematic hedge funds. Systematic funds use strategies that are rules-based, with little or no daily intervention by humans. In our experience, some large allocators shy away from systematic hedge funds altogether. A possible explanation for this is what the psychology literature calls “algorithm aversion”. We find that, for the period 1996-2014, systematic equity managers underperform their discretionary counterparts in terms of unadjusted (raw) returns, but that after adjusting for exposures to well-known risk factors, the risk-adjusted performance is similar. In the case of macro, systematic funds outperform discretionary funds, both on an unadjusted and risk-adjusted basis. It is sometimes claimed that systematic funds’ returns have a greater exposure to well-known risk factors. We find, however, that for discretionary funds (in the aggregate) more of the average return and the volatility of returns can be explained by risk factors.

Motivated by the explosive growth in CTA assets under management, in combination with the recent poor performance of many managers in this sector, we explore whether the trend-following trading style employed by many CTAs has become crowded. Explicitly, we test for market impact using the following hypothesis: around the turn of the month (TOM), trend-following (MOM) strategies digest sizeable inflows, causing the managers to trade up their existing positions, thereby pushing prices temporarily in their favor. The main empirical test is whether there is an above average return for MOM strategies on TOM days, which we refer to as the MOM-TOM effect. We found a very strong MOM-TOM effect in the Newedge Trend Index returns, with 90% of cumulative returns since 2000 being realized on the three TOM days. In addition, a replicating strategy we designed to closely track the Newedge Trend Index displayed a strong MOM-TOM effect.

I investigate household interest rate risk management by solving a life-cycle asset allocation model that includes mortgage and bond portfolio choice. I find that most investors prefer an adjustable-rate mortgage, and thereby save on the bond risk premium that is contained in fixed-rate mortgage payments. Only older, risk-averse investors hold some fixed-rate mortgage debt. Together with a position in short-term bonds this enables them to hedge against changes in the real interest rate, while the inflation exposure of the debt and bond positions cancel out. Hedging house price changes with bonds only occurs at the end of the life cycle. Early in the life cycle short-sale constraints prevent an effective hedge.

This paper studies optimal intergenerational transfer policy under stochastic labor income and capital returns. It has implications for Social Security, government tax and debt policy, and DB pension funds. A stylized two-period overlapping-generations model is developed where a central planner implements pay-as-you-go transfers. I allow for autocorrelation in the labor income and skewness in the capital return and calibrate the model parameters to US data. I show that state-contingent transfers facilitate intergenerational risk sharing in a way that is similar to portfolio insurance using put options. That is, the working generation provides downside risk insurance to the old on their savings. In addition, when no riskfree asset is available, these transfers improve utility by substituting for this missing asset. I further find that imposing an incentive constraint for the working generation has little impact when transfers also have this substitution role, but it causes the transfer scheme to collapse to the zero-transfer scheme when a risk free asset is available.

We investigate the impact of owner-occupied housing on financial portfolio and mortgage choice under stochastic inflation and real interest rates. To this end we develop a dynamic framework in which investors can invest in stocks and bonds with different maturities. We use a continuous-time model with CRRA preferences and calibrate the model parameters using data on inflation rates and equity, bond, and house prices. For the case of no short-sale constraints, we derive an implicit solution and identify the main channels through which the housing to total wealth ratio and the horizon affect financial portfolio choice. This solution is used to interpret numerical results that we provide when the investor has short-sale constraints. We also use our framework to investigate optimal mortgage size and type. A moderately risk-averse investor prefers an adjustable-rate mortgage (ARM), while a more risk-averse investor prefers a fixedrate mortgage (FRM). A combination of an ARM and an FRM further improves welfare. Choosing a suboptimal mortgage leads to utility losses up to 6%.

We investigate the impact of owner-occupied housing on financial portfolio and mortgage choice under stochastic inflation and real interest rates. To this end we develop a dynamic framework in which investors can invest in stocks and bonds with different maturities. We use a continuous-time model with CRRA preferences and calibrate the model parameters using data on inflation rates and equity, bond, and house prices. For the case of no short-sale constraints, we derive an implicit solution and identify the main channels through which the housing to total wealth ratio and the horizon affect financial portfolio choice. This solution is used to interpret numerical results that we provide when the investor has short-sale constraints. We also use our framework to investigate optimal mortgage size and type. A moderately risk-averse investor prefers an adjustable-rate mortgage (ARM), while a more risk-averse investor prefers a fixedrate mortgage (FRM). A combination of an ARM and an FRM further improves welfare. Choosing a suboptimal mortgage leads to utility losses up to 6%.