Rotational system

The goal of our article is to examine the long-term relationship between small value and large growth stocks using more than 100 years of data and test whether the spread between small value and large growth portfolios shows trends that could help investors switch between the two styles. Using the Fama and French 2×3 and 5×5 size and book-to-market portfolios, we construct the small value minus large growth (SV–LG) spread and apply simple trend-following signals based on moving averages and momentum with horizons ranging from 3 to 12 months. Our results show that trend-following strategies are able to capture part of the value outperformance on the long side. Timing periods when growth stocks dominate is much more difficult.

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.

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.

Investors are increasingly exploring alternative indicators to gain an edge in financial markets. Traditional signals, such as earnings reports or macroeconomic data, often come with delays or may already be priced in. As a result, unconventional metrics have attracted attention. In this article, we examine the Producer Price Index (PPI) for the Corrugated and Solid Fiber Box Manufacturing industry, including corrugated boxes and pallets. Our motivation is to evaluate this index’s effectiveness as a predictive signal for the S&P 500 ETF, sector-specific ETFs, and individual stocks such as Amazon (AMZN), one of the largest consumers of materials tracked by this index. We present several investment strategies that incorporate this indicator and assess whether it can enhance risk-adjusted returns.

The U.S. equity market has periodically been dominated by a few technology-driven stocks, most recently the so-called “Magnificent Seven.” Historically, similar dominance occurred during the Nifty Fifty era in the 1960s–1970s and the dot-com boom in the 1990s. These periods of concentrated leadership often led to temporary outperformance, but systematically capturing such gains has proven challenging. Our study investigates the potential to exploit technology sector dominance using momentum-based strategies across Fama–French 12 industry portfolios, analyzing whether long-only, long-short, and rolling-basis approaches can generate persistent alpha, and assessing the limitations of simple timing methods.

Understanding seasonality in financial markets requires recognizing how predictable return patterns can be influenced by investor behavior. One underexplored aspect of this is the impact of front-running—where traders anticipate seasonal trends and act early, shifting returns forward in time. We have already explored seasonality front-running in commodities, stock sectors, and crisis hedge portfolios. Our new research examines whether this phenomenon extends to country ETFs, an asset class where seasonality has been less studied. By applying a front-running strategy to a dataset of country ETFs, we identify opportunities to capitalize on seasonal effects before they fully materialize. Our findings indicate that pre-seasonality drift is strongest in commodities but remains present in country ETFs, offering a potential edge in portfolio construction. Ultimately, our study highlights how front-running seasonality can enhance ETF investing, providing an additional layer of market timing beyond traditional trend-following approaches.