Own-research

This research examines the critical quantitative investment problem of systematic tactical allocation to international equity mandates—specifically Emerging Markets (EM) and Europe, Australasia, and the Far East (EAFE)—amidst conjectured macroeconomic regime transitions. The investigation is precipitated by observable deteriorations in USD hegemony, elevated geopolitical risk premiums, and protracted macroeconomic uncertainty. These factors collectively challenge the post-Global Financial Crisis paradigm of consistent US equity outperformance, suggesting a potential inflection point in relative returns and currency-adjusted Sharpe ratios.

The central research question is whether a statistically robust, signals-based framework can be engineered to systematically time exposure to EAFE equities, thereby capitalizing on these postulated regime shifts. We move beyond traditional, static mean-variance optimization by developing a dynamic model that integrates momentum variables to generate actionable, out-of-sample allocation signals.

Alternative ETFs sit at an unusual intersection of public-market accessibility and hedge-fund-style investment techniques. They package managed futures, merger arbitrage, and option-based income strategies into exchange-traded products, yet they remain thinly traded and relatively niche compared to mainstream equity or bond ETFs. This combination makes them intriguing: they offer exposure to alternative risk premia, and their limited liquidity raises possibilities to build short-term reversal strategies. 

Calendar strategies are often viewed as weak when assessed individually. Their annualized returns tend to be low, market exposure is limited, and trading activity is sparse. Compared to trend following or swing strategies, which can remain invested for extended periods, calendar strategies may appear inefficient at first glance. This impression, however, largely stems from evaluating these strategies outside of their intended context. Calendar strategies are not designed to operate as standalone trading systems. Their primary role is within a portfolio, where their structural properties become relevant rather than their individual performance metrics.

Pragmatic Asset Allocation is a systematic, multi-asset investment strategy designed to adapt dynamically to evolving market conditions. Rather than maintaining a static equity exposure, the model actively allocates capital across a diversified set of asset classes—including equities, bonds, commodities, gold, and cash-like instruments—using momentum-based signals and disciplined periodic rebalancing. The strategy’s primary objective is to deliver attractive long-term returns while materially reducing drawdowns during adverse market environments.

It has now been two highly volatile years since we first published our paper on PAA, making this an opportune moment to review the strategy’s performance over the past year.

This article develops a price-based macro–financial model of gold that formally links its medium-horizon return dynamics to cross-asset risk-premium configurations. Although gold has traditionally been conceptualized as a non-yielding inflation hedge or safe-haven asset, contemporary empirical evidence reveals a substantially more intricate structure: gold’s forward returns are systematically conditioned by the joint momentum of (i) gold itself and (ii) long-duration U.S. Treasury total-return indices. The alignment of these two signals appears to encode macroeconomic information—specifically the direction of real interest rates, the stance and expected trajectory of Federal Reserve policy, and the prevailing global risk-appetite regime.

One year is again behind us (in this case, it was 2025), and we are all a little older (and hopefully richer and/or wiser). Turn-of-the-year period is usually an excellent time for a short recap. Over the past 12 months, we have kept our pace and published nearly 70 short analyses of academic papers and our own research articles. So let’s summarize 10 of them, which were the most popular (based on the Google Analytics ranking). The top 10 is diverse, as usual; once again, we hope that you may find something you have not read yet …