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Alternative Thinking

2026 Capital Market Assumptions for Major Asset Classes

We update our estimates of medium-term (5- to 10-year) expected returns for major asset classes. We also include a discussion on currency risk and currency hedging, with particular considerations for U.S. and European investors.


Alternative Thinking

Hold the Dip

We examine the popular “Buy the Dip” strategy and find it consistently underperforms a simple buy-and-hold approach. Our research shows that investors seeking to time markets may find greater success following trends rather than fighting them.


Alternative Thinking

Exploring Capital Efficiency

This paper explores how capital-efficient investments—such as private equity, hedge funds, and portable alpha—can help investors unlock the full benefits of diversification without relying on direct leverage. We show how these approaches can improve portfolio resilience and long-term returns, particularly for leverage-constrained investors.


Alternative Thinking

The Hidden Value of Streaky Returns in Stock Portfolios

Streaky return streams - ones that that can perform well or poorly for extended periods - are challenging for investors to comprehend and stick with. Yet, this very "complexity risk” may be what earns investors an additional risk premium, leading to above average risk-adjusted returns.


Alternative Thinking

2025 Capital Market Assumptions for Major Asset Classes

We update our estimates of medium-term (5- to 10-year) expected returns for major asset classes. We also include a discussion on corporate earnings growth: the market consensus is for more strong growth to come – especially in the U.S. But what is a reasonable medium-term forecast for allocators?


Alternative Thinking

Can Machines Build Better Stock Portfolios?

In the second issue of our 2024 Alternative Thinking series, we showed that machine learning techniques can be used to help improve market timing strategies. In this issue, we extend these concepts to constructing stock selection strategies following a similar framework. Our results indicate more complex models utilizing machine learning techniques yield performance improvements relative to a simple, linear approach in the range of 50-100%, suggesting that machine learning can help to build better stock selection portfolios.


Alternative Thinking

Broad Strategic Asset Allocation

This paper presents one justifiable set of inputs and finds that alternatives earn themselves a sizable strategic allocation. Investors are encouraged to compare these results with their own assumptions, constraints and allocations as they look to build a resilient portfolio for long-term investment success.


White Paper

Portable Alpha: Still A Great Solution For Improving Return Outcomes

In the face of lower-than-average expected returns for equities, some investors may be considering adding active management to their equity allocations. However, the evidence supporting active long-only equities has long been underwhelming. We review an alternative approach – portable alpha.


Alternative Thinking

Can Machines Time Markets? The Virtue of Complexity in Return Prediction

Common wisdom has suggested that small, simple models are best suited for market timing applications, given finance’s “small data” constraint and naturally low predictability. However, we show that complex models better identify true nonlinear relationships and therefore produce better market timing strategy performance. We validate this "virtue of complexity" result in three practical market timing applications.


White Paper

A Fresh Look at Multi-Strategy Alternatives

In this short piece, we review the case for multi-strategy alternatives, explaining why liquid, diversifying alternative strategies may have a decisive role to play in the tougher investment environment ahead.