If inflation is a primary concern, an investor may be tempted to assemble a stack that attempts to match inflation one-for-one: positive performance in inflationary periods and negative performance in deflationary periods.

An approach like this, however, may miss the overall purpose of inflation protection: immunizing a portfolio from undesirable price instability.

To design a portfolio more oriented towards the types of inflation that an investor may be concerned with, the portfolios we construct will be designed to match the payoff profile of either a call option or long straddle struck at the expected rate of inflation[^footnote: For inflation expectations, we utilize the Survey of Professional Forecasters, provided by the Philadelphia Fed.

One limitation of an optimization of this type is that we are limited by the history available. Over the time period used, inflation volatility around expectations has been fairly muted, aside from brief bouts of inflation (2021-2022) and short periods of deflation (2008 and 2020). In order to emphasize the positive and negative inflation readings that an investor likely cares about, we also incorporate a weighting function to the optimization whereby large deviations from inflation expectations receive a greater weight than periods when inflation is close to expectations.

This final step ensures that the optimization process doesn’t simply default to asset classes or strategies that provided consistent positive returns, and focuses on additions to the portfolio that may perform well in periods of larger price instability.

In most cases, investors typically care about either high levels of inflation, or deflationary periods. To construct a portfolio for these concerns, the Inflation Convexity Stack attempts to match the payoff profile of an inflation call option, while the Price Convexity Stack seeks to match the payoff profile of an inflation straddle, both struck at the expected level of inflation.

The directional approach typically offers stronger upside capture when inflation surges, whereas the convex design sacrifices some peak hedge strength for broader regime resilience.

Return stacking provides a modern, research‑driven framework for strengthening traditional portfolios through intentional overlays. This post examined the Inflation‑Hedging stack, analyzing designs to provide positive returns during inflationary periods or positive returns in periods of overall price instability to show how a modest layer can help preserve purchasing power without disturbing a familiar 60 / 40 core.

Because the overlay remains deliberately modest, it keeps portfolios straightforward and links construction choices directly to client concerns about unexpected price shocks.

Our earlier posts explored Anti‑Beta and Absolute Return sleeves; together with inflation hedging they form a cohesive toolkit for addressing drawdown sensitivity, the need for consistent returns, and the threat of inflation. Advisors can combine these stacks or deploy them selectively to align portfolio design with client objectives in a changing market landscape.

Global Equities: MSCI ACWI Net Return Index USD. The MSCI ACWI Index captures large and mid-cap representation across 23 Developed Markets (DM) and 24 Emerging Markets (EM) countries*. With 2,884 constituents, the index covers approximately 85% of the global investable equity opportunity set.

U.S. Core Fixed Income: Bloomberg US Agg Total Return Value Unhedged USD. The Bloomberg US Agg Index is a broad-based flagship benchmark that measures the investment grade, US dollar-denominated, fixed-rate taxable bond market. The index includes Treasuries, government-related and corporate securities, MBS (agency fixed-rate pass-throughs), ABS and CMBS (agency and non-agency).

TIPS: Bloomberg US Treasury Inflation Notes TR Index Value Unhedged USD. The Bloomberg US Treasury Inflation-Linked Bond Index (Series-L) measures the performance of the US Treasury Inflation Protected Securities (TIPS) market. Federal Reserve holdings of US TIPS are not index eligible and are excluded from the face amount outstanding of each bond in the index.

High Yield Fixed Income: Bloomberg US Corporate High Yield Total Return Index Value Unhedged USD. The Bloomberg US Corporate High Yield Bond Index measures the USD-denominated, high yield, fixed-rate corporate bond market. Securities are classified as high yield if the middle rating of Moody’s, Fitch and S&P is Ba1/BB+/BB+ or below. Bonds from issuers with an emerging markets country of risk, based on Bloomberg EM country definition, are excluded.

Commodities: S&P GSCI Index Spot Index. The S&P GSCI® is widely recognized as a leading measure of general price movements and inflation in the world economy. It provides investors with a reliable and publicly available benchmark for investment performance in the commodity markets.

Gold: XAU Currency. Gold spot price quoted in USD per ounce.

Real Estate: Dow Jones U.S. Select REIT Total Return Index. The Dow Jones U.S. Select REIT Index tracks the performance of publicly traded REITs and REIT-like securities and is designed to serve as a proxy for direct real estate investment, in part by excluding companies whose performance may be driven by factors other than the value of real estate. The index is a subset of the Dow Jones U.S. Select Real Estate Securities Index (RESI), which represents equity real estate investment trusts (REITs), and real estate operating companies (REOCs) traded in the U.S.

Merger Arbitrage: PivotalPath Event Driven : Merger Arbitrage Index. The PivotalPath Event Driven: Merger Arbitrage Hedge Fund Index is an equal weighted index which comprises funds that typically purchase shares in one company and short sell the assets in another. The strategy is generally used in the expectation of a pending announcement of a company takeover, where the fund will take a long position in the target firm and a short position in the acquiring firm. The Index tracks the monthly performance, net of fees in USD, of its constituents with a minimum fund track record of 18 months and a minimum fund AUM of $50mm. The constituents are fixed at the end each calendar year for the following calendar year.

Managed Futures: PivotalPath Managed Futures Index. The PivotalPath Managed Futures Hedge Fund Index is an equal weighted index of funds that typically forecast market trends and determine whether to invest long or short in futures contracts across metals, grains, equity indices and soft commodities, as well as foreign currency and U.S. government bond futures. The Index tracks the monthly performance, net of fees in USD, of its constituents and is representative of funds with a minimum fund track record of 18 months and a minimum fund AUM of $50mm. The constituents are fixed at the end each calendar year for the following calendar year.

Systematic Global Macro: PivotalPath Global Macro: Quantitative Index. The PivotalPath Global Macro: Quantitative Hedge Fund Index is an equal weighted index which comprises funds that typically use a quantitative approach to systematically invest across multiple geographies and asset classes. The Index tracks the monthly performance, net of fees in USD, of its constituents with a minimum fund track record of 18 months and a minimum fund AUM of $50mm. The constituents are fixed at the end each calendar year for the following calendar year.

CPI: Consumer Price Index for All Urban Consumers: All Items in U.S. City Averages (CPIAUCSL). The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a price index of a basket of goods and services paid by urban consumers. It can also represent the buying habits of urban consumers. This particular index includes roughly 88 percent of the total population, accounting for wage earners, clerical workers, technical workers, self-employed, short-term workers, unemployed, retirees, and those not in the labor force.

One-Year Ahead CPI Inflation Forecast (INFCPI1YR): This series reflects the median forecast for average Consumer Price Index (CPI) inflation over the four quarters following the survey quarter. It is derived from the Survey of Professional Forecasters and is calculated using the geometric average of quarter-over-quarter median CPI inflation forecasts.

The PivotalPath index/indices used in this information is/are produced by the hedge fund research and investment consultancy firm, PivotalPath Inc. The information is representative of the overall composition of the hedge fund universe, as well as specific sub-strategies, including but not limited to the PivotalPath Hedge Fund Composite Index; the PivotalPath Credit Index (and associated sub-indices); the PivotalPath Equity Diversified Index (and associated subindices); the PivotalPath Equity Sector Index (and associated sub-indices); the PivotalPath Event Driven Index (and associated sub-indices); the PivotalPath Global Macro Index (and associated sub-indices); the PivotalPath Managed Futures Index; the PivotalPath Multi-Strategy Index; PivotalPath Equity Quant Index; and the PivotalPath Volatility Index.

PivotalPath Indices are the proprietary product of PivotalPath Inc. They represent Hedge Fund Indices based on collected data from individual hedge funds and while PivotalPath considers the sources of such information and data to be reliable, such information and data has been verified but has not been audited by PivotalPath. No representation is made as to, and no responsibility or liability is accepted for, the accuracy or completeness of such information and data. PivotalPath Index constituents may be removed at any time and any PivotalPath index may be restated, adjusted, or corrected at any time without notice.

PivotalPath data is being used under license from PivotalPath, Inc, which does not approve of or endorse any of the products or the contents discussed in these materials.

The portfolio optimizations presented throughout this paper are based on a simulation-driven framework designed to reflect realistic market behavior. Specifically, we employ a block-bootstrap methodology that aims to preserve key time-series and cross-sectional dynamics observed in asset class returns.

For each simulation, return series are aligned by calendar month. To generate a 10-year simulation period, we randomly select 20 non-overlapping 6-month return blocks. The initial block is chosen at random, while subsequent blocks are selected using a normally distributed jump process. Each new block start date is determined by adding a normally distributed random variable (centered at zero with a standard deviation of 36 months) to the prior block’s start date. This approach allows for more realistic regime persistence and transition dynamics than uniform bootstrapping.

An optimal stack is then computed for each simulated path, allowing up to a 20% total stack allocation. Final allocations are determined by averaging the portfolio weights across all simulations. Approximately 300 simulations are generated, with the resulting portfolio being the average of the optimized results across simulations.

This methodology helps preserve empirically observed characteristics such as autocorrelation, autoregressive and heteroskedastic volatility patterns, and time-varying cross-asset correlations, key features that are often lost in naïve or overly simplified simulation approaches.