Fairtree Wild Fig Multi Strategy Hedge Fund Q3 Investor Update
Introduction
The broad-based market decline linked to “Trump 2.0” and his US trade and tariff policies has, at least for now, been largely shrugged off, as most asset classes continued to grind higher during the quarter. Global equities extended the strong momentum seen in Q2, driven by ongoing AI enthusiasm, resilient economic growth, and supportive US monetary policy. In US dollar terms, major indices delivered robust gains: S&P 500 (+8.0%), Nasdaq 100 (+11.4%), MSCI ACWI (+7.6%), Hang Seng (+11.8%), and Euro Stoxx 50 (+8.4%).
Buoyed on by strong earnings, particularly in artificial intelligence (AI) and technology stocks, the US stock market continued its strong rally, achieving 23 new all-time highs during the quarter, marking the most record-setting days in a single quarter since 1998. The Fed cut rates twice during the quarter – 25bps on each occasion. The Fed’s median projections indicate that the federal funds rate is expected to fall to a range of 3.50%–3.75% by the end of 2025, suggesting the possibility of additional rate cuts in the coming months.
China’s economy remains resilient, recording year-on-year GDP growth of 4.6%, broadly in line with the government’s target of around 5%. However, headwinds from the ongoing trade tensions and subdued inflation continue to weigh on the economy, particularly in the manufacturing sector. The U.S.-China trade dispute remains unresolved, with a temporary tariff truce set to expire in November 2025. If no new agreement is reached by that deadline, tariffs could revert to previously higher levels, potentially escalating trade tensions and creating uncertainty for exporters and global supply chains.
Domestically, the JSE All Share (ALSI) Index rose 12.9% in ZAR during the quarter, breaking through the psychological 100,000-point mark for the first time. The year-to-date return of 31.7%, while certainly welcome for local investors, conceals the narrow and highly concentrated nature of the rally. Much of the index’s gains were driven by a handful of large-cap mining stocks, particularly in the precious metals sector, where soaring gold and platinum prices delivered outsized returns. In contrast, performance across the broader market was more uneven, with sectors such as general retailers, financials, and consumer-facing stocks posting muted gains, underscoring the lack of breadth behind the index’s rally. The Rand appreciated marginally (c.1%) during the quarter against the dollar.
In summary, the Fairtree Wild Fig Multi Strategy FR QIHF, “Wild Fig”, our flagship multi-strategy balanced hedge fund delivered a positive return for the quarter (+1.4%) on the back of positive returns in Q2 which have helped offset the drawdown in Q1. The fund is marginally positive year to date. The fund remains true to its investment objective of compounding clients’ capital over the long term. We thank you for entrusting us as stewards of your capital.
Wild Fig Multi Strategy
Portfolio Management Team
Quarterly Performance: Wild Fig FR Multi Strategy QIHF
Source: Bloomberg
On an asset class level, the marginal positive performance during the third quarter – was attributable to positioning in Fixed Income (more specifically our SA Fundamental strategy). Commodities detracted from performance whilst Equities was flat.
Source: Bloomberg
Equity strategies were broadly flat for the quarter. Losses from the South African and global market neutral strategies offset gains from the local directional equity strategy. Positive contributions came from exposures to the materials, consumer staples, and consumer services sectors, while positions in consumer discretionary, real estate, and healthcare detracted.
The Fixed Income Fundamental strategy delivered a strong quarter, supported by the South African Reserve Bank’s rate cut in July and expectations of further easing. The strategy remains positioned for additional rate cuts and continued improvement in the country’s fiscal outlook. South African government bond yields (both nominal and real) remain elevated relative to emerging-market peers. Much of the performance came from positions on the mid- and long-end of the yield curve. The Fixed Income Quantitative strategy was marginally negative for the quarter.
Within the Commodities strategy, some pairs have moved into multi-decade extreme levels of dislocation. Despite a negative return for the quarter, the team has conviction that their positioning will play out positively over time. One of the overarching themes that negatively affected the commodity strategy performance this quarter was the sharp rise in U.S. cattle prices. The increase was driven by import tariffs on Brazilian beef and delays in reopening the Mexican border following disease concerns, which limited feeder cattle supply. While some relief came from heavier slaughter weights and continued imports, overall supply remained tight, supporting higher prices and weighing on our positioning. As a reminder, the agricultural and soft commodity market neutral strategy remains one of the lowest heartbeat strategies (from a volatility standpoint) within the Wild Fig construct.
Source Bloomberg
Quarterly Insights: The Rebalancing Premium
Executive Summary
Portfolio rebalancing is often seen primarily as a risk-management exercise – a way to ensure that asset allocations remain aligned with strategic targets and based on an investor’s predetermined risk tolerances. However, beyond maintaining discipline during market turbulence, systematic rebalancing can also serve as a source of incremental returns.
By enforcing discipline, moderating risk, and harvesting market volatility, rebalancing has the potential to generate a rebalancing premium – an incremental return advantage that compounds over time, as part of a diversified portfolio. Under the right conditions, this disciplined reallocation can enhance long-term geometric returns and improve portfolio efficiency, making rebalancing a critical consideration for both multi-asset investors, and multi-strategy fund managers.
Rebalancing 101
Rebalancing is the process of realigning a portfolio to its intended asset allocation after market movements have caused asset weights to drift. For instance, in a 60/40 equity-bond portfolio, a strong rally in equities may increase the equity share to 70 percent, leaving the investor more exposed to equity risk than intended.
Figure 1: Asset Allocation of Drifting vs Annually Rebalanced 60/40 portfolio
Note: The 60% equity/40% bond portfolio return data are from December 31, 1989, through December 31, 2021. U.S. bonds are represented by the Bloomberg U.S. Aggregate Bond Index, non-U.S. bonds by the Bloomberg Global Aggregate ex-U.S. Index, U.S. equities by the Dow Jones Wilshire 5000 Index.
Source: Vanguard Research, Rational Rebalancing 2022, DataStream
In this scenario, rebalancing involves trimming equities back to 60% once predefined criteria are met, for example, at periodic intervals (such as monthly) or when asset weights breach specified thresholds. The proceeds are then reallocated to bonds, restoring the portfolio’s risk profile to its original design. Because investors’ portfolios should remain aligned with their objectives and risk preferences, rebalancing plays a vital role in maintaining an appropriate asset allocation over time.
Figure 2: Asset Allocation and Risk of Return Dispersion
Note: Return data are from January 1, 1926, through December 31, 2021, rebalanced monthly. U.S. bonds are represented by the Standard & Poor’s High Grade Corporate Index from 1926 to 1968; the Citigroup High Grade Index from 1969 to 1972; the Lehman Brothers U.S. Long Credit AA Index from 1973 to 1975; Barclays U.S. Aggregate Bond Index thereafter. U.S. equities are represented by the Standard & Poor’s 90 from 1926 to 1957; the Standard & Poor’s 500 Index from 1957 to 1974; the Wilshire 5000 Index from 1975 to 2005; the MSCI US Broad Market Index through 2013, and the CRSP US Total Market Index thereafter.
Source: Vanguard Research, Rational Rebalancing 2022, DataStream
While this adjustment is often, and rightly so, justified as a way of keeping risk in check, it also has an important and widely unappreciated return dimension. By selling portions of assets that have appreciated and buying those that have declined, rebalancing creates a mechanical process of buying low and selling high. Over time, this discipline can generate a return premium above the simple weighted average of the portfolio’s components. The premium does not emerge in all circumstances, as it depends on sufficient volatility, diversification, and relatively low costs of execution. However, when those conditions are met, rebalancing can transform from a risk-control measure into a source of added return. In general, multi-strategy funds, and especially multi-strategy hedge funds, create a favourable backdrop for rebalancing premium harvesting, due to the uncorrelated and diversified nature of the underlying building blocks and the wider toolset available to the hedge fund manager versus a traditional long-only fund.
What is the Rebalancing Premium?
The rebalancing premium, often referred to as the “rebalancing bonus” or “volatility harvesting”, refers to the incremental geometric return captured when a portfolio is regularly returned to fixed weights. By selling portions of assets that have appreciated and buying those that have declined, the portfolio mechanically implements the timeless rule of buy low, sell high.
The premium arises because:
- Volatility of long-term expected returns creates oscillations between asset prices, generating trading opportunities in-between long-term return expectations,
- Low or moderate correlation ensures asset prices move somewhat independently, enhancing diversification,
- Geometric compounding ensures that harvesting volatility through disciplined trading can add to long-term return relative to a buy-and-hold drifted allocation.
The result is a steady source of return if costs are contained and implementation is disciplined, without relying on discretionary trade timing, which has historically added little value.
The Origins of the Rebalancing Premium
The rebalancing premium arises because of the difference between arithmetic and geometric compounding. Individual assets compound at their own rates, but when combined in a diversified portfolio, the interplay of volatility and correlation can create additional opportunities.
If assets are volatile and not perfectly correlated (ρ>1), their weights will diverge as prices move. Returning the portfolio to target weights crystallises gains from the outperforming asset and redeploys them into the underperformer, setting up the potential to benefit from future mean reversion or continued uncorrelated diversification.
Academics have formalised this effect by showing that portfolio returns can be decomposed into two components: the weighted average return of the assets and an additional diversification premium that arises from rebalancing. The magnitude of this premium depends on the volatility of the underlying assets and the degree to which their movements are independent of each other.
In a 2010 research paper, Vanguard found that annual or hybrid rebalancing policies often deliver most of the benefits while limiting unnecessary turnover. Gains typically amount to a few tenths of a percent per annum in balanced stock-bond portfolios. William Bernstein, cited in his works titled “The Rebalancing Bonus”, found that 50/50 stock-bond allocations rebalanced regularly outperform their buy-and-hold equivalents by 0.3%–0.8% p.a. over long horizons. And INSEAD/SSRN academic papers examined a formal decomposition of returns to demonstrate that a portfolio’s performance can be expressed as the weighted average of component returns plus a diversification (rebalancing) premium, explicitly quantifying conditions under which it exists, including accounting for trading costs, and rebalancing methods.
The Rebalancing Bonus in Practise
Let’s assume an investor (Investor A) has a desired portfolio asset class composition of 50/50 S&P500 Index (Equity) and US Treasury Bonds (Bonds). Traditional finance, as pioneered by Markowitz in his work on portfolio selection, would argue that the portfolio return is equal to the weighted sums of the individual component returns, or:
In a simple framework, the portfolio’s return can be expressed as the weighted sum of individual asset returns, where wᵢ represents the weight of asset i and Rᵢ its return. However, this relationship applies only to individual portfolio components over a single period, without accounting for the effects of cumulative rebalancing over time.
Perold and Sharpe, in their seminal work Dynamic Strategies for Asset Allocation, describe rebalancing as a concave strategy, in contrast to convex strategies such as portfolio insurance, with buy-and-hold representing a “flat” approach. They note that convex strategies and buy-and-hold tend to outperform in markets with prolonged directional trends, whereas concave rebalancing strategies perform better in range-bound or mean-reverting environments.
However, this dynamic shifts meaningfully when applied to highly diversified, uncorrelated, and unconstrained strategies such as the Wild Fig Multi-Strategy Hedge Fund, where the breadth of return sources and the non-directional nature of exposures create a structurally favourable environment for harvesting the rebalancing premium.
Rebalancing on a Portfolio Level
Let us assume a hypothetical portfolio, composed of equal parts of two assets: Asset A and Asset B. Further assume that each has a return of either +30% or -10%, with equal probability, and that the portfolio is rebalanced to 50/50 at the end of each year. The expected annual return (E(r)) of each asset is 10%, and the long-term return of each asset is 8.1665% when annually compounded, with a standard deviation (𝜎) of 20%.
If the annual returns are perfectly correlated (i.e., ρ =1) then the equal mixture of A and B will have the same risk and return as each individual asset, and no gain in risk or return is obtained by diversification, or rebalancing.
Now assume that there is a zero correlation (ρ = 0) between the returns of A and B. This can be illustratively represented by hypothetical random returns for four periods:
In this example, the portfolio yields an annualized return of 9.0794%, and a standard deviation of 14.142%. The standard deviation of the portfolio has been reduced by a factor of the square root of 2 (and the variance halved) as predicted by Markowitz. However, the return is 0.9129% higher than the Markowitz return. Further, this excess return would not have been realized without rebalancing. This portfolio thus has a rebalancing bonus of 0.9129%.
When running the same principle return analysis on a multi-strategy hedge fund and again using hypothetical assumptions per sub-strategy (that are coincidentally not too dissimilar to Wild Fig’s underlying building blocks), we can test the same assumption and prevalence of a potential return premium inherent to the portfolio composition.
Let us assume the underlying sub-strategy allocations and return assumptions, then the following graph is a hypothetical illustration of potential returns over a 5-year period, rebalanced annually:
When running a Monte Carlo simulation of a 1000 potential outcomes of the same underlying assumptions, even under realistic, modest correlations (0.1 – 0.4) and monthly rebalancing, the simulated portfolio exhibits an average rebalancing premium of roughly 0.3% p.a. This mirrors the initial findings and hypothesis – that volatility plus imperfect correlation creates a small but persistent geometric compounding edge when weights are reset regularly.
The dispersion is tight: in only ~5 % of cases is the premium negative, while most scenarios cluster between 0% and 0.5% p.a. Over a multi-year horizon, that edge can accumulate into a 1 – 2% total performance uplift while stabilizing risk.
Strategic Significance for Investors
The practical significance of the rebalancing premium extends well beyond its academic implementation, however. At a practical level, rebalancing acts as a governance tool, ensuring portfolios adhere to their intended risk budgets rather than drifting with market trends. It reduces the likelihood that a prolonged equity rally, for instance, leaves an investor unintentionally concentrated in riskier assets. It also introduces an element of discipline, automating the contrarian behaviour of trimming exuberant winners and reinforcing lagging positions, a pattern that many investors struggle to maintain in the absence of formal rules.
Moreover, the premium compounds quietly in the background, adding incremental return while smoothing volatility. For institutions with long-dated liabilities, such as pension funds or endowments, this translates into improved portfolio efficiency and reduced sequence-of-returns risk. While rarely dramatic in any single period, the compounding effect across decades is economically meaningful.
Balancing rebalancing
Rebalancing is ideally suited for investments that dance to different beats, but which are likely to end up in similar long-term positions, or stated otherwise, that have high expected returns but are uncorrelated in the path to generate these.
Conclusion
Rebalancing should not be viewed solely as a defensive measure to control drift. Under the right conditions, it provides a return premium that, though modest in size, compounds meaningfully over long horizons and improves risk-adjusted performance. For a multi-strategy hedge fund, the challenge is not whether to rebalance, but how: choosing the right rules, executing intelligently, and rigorously measuring outcomes.
Disciplined rebalancing is therefore not just maintenance, it is an alpha-adjacent process that, when thoughtfully designed, becomes an enduring contributor to long-term portfolio efficiency.
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