asset class picking - QuantPedia

Fear, Not Risk, Explains Asset Pricing

April 17, 2025

With financial markets increasingly whipsawed by geopolitical tensions and unpredictable policy shifts from the Trump administration—investors are once again questioning how to understand risk, fear, and the true drivers of returns. A recent and compelling paper dives into this debate with a provocative thesis: in “Fear, Not Risk, Explains Asset Pricing,” authors Rob Arnott and Edward McQuarrie argue that traditional models built on quantifiable risk have failed to explain real-world returns, and that fear—messy, emotional, and deeply human—is the missing piece.

Navigating Market Turmoil with Quantpedia Tools: A Rational Guide for Portfolio Management

April 7, 2025

The recent imposition of sweeping global tariffs by President Donald Trump has triggered a sharp and sudden selloff across global equity markets. In times like these, it’s natural for panic to set in. However, as quantitative investors, our strength lies in data-driven decision-making, risk management, and maintaining discipline when others lose theirs.

Rather than reacting emotionally, the prudent course of action is to reassess the robustness of our portfolios. Are we diversified across uncorrelated strategies? Do we have components in place that act as hedges during market crises? Fortunately, the tools provided by Quantpedia can help investors, traders, and portfolio managers identify, test, and deploy crisis-resilient strategies in a structured and evidence-based manner.

Can Margin Debt Help Predict SPY’s Growth & Bear Markets?

March 5, 2025

Navigating the financial markets requires a keen understanding of risk sentiment, and one often-overlooked dataset that provides valuable insights is FINRA’s margin debt statistics. Reported monthly, these figures track the total debit balances in customers’ securities margin accounts—a key proxy for speculative activity in the market. Since margin accounts are heavily used for leveraged trades, shifts in margin debt levels can signal changes in overall risk appetite. Our research explores how this dataset can be leveraged as a market timing tool for US stock indexes, enhancing traditional trend-following strategies that rely solely on price action. Given the current uncertainty surrounding Trump’s presidency, margin debt data could serve as a warning system, helping investors distinguish between market corrections and deeper bear markets.

Using Inflation Data for Systematic Gold and Treasury Investment Strategies

February 21, 2025

Inflation significantly impacts the prices of gold and treasury bonds through various mechanisms. Gold is often viewed as a hedge against inflation, while treasury bonds exhibit a more complex relationship influenced by interest rates and investor behavior. This relationship between inflation, gold, and treasuries is well understood, but the real question is whether we can systematically capitalize on it. In this article, we explore how inflation data can be used to build trading strategies—and as our findings suggest, the answer is a definite yes.

Seasonality Patterns in the Crisis Hedge Portfolios

January 30, 2025

Building upon the established research on market seasonality and the potential for front-running to boost associated profits, this article investigates the application of seasonal strategies within the context of crisis hedge portfolios. Unlike traditional asset allocation strategies that may falter during market stress, crisis hedge portfolios are designed to provide downside protection. We examine whether incorporating seasonal timing into these portfolios can enhance their performance and return-to-risk ratios, potentially offering superior risk-adjusted returns compared to static or non-seasonal approaches.

Refining ETF Asset Momentum Strategy

January 10, 2025

Today’s research introduces a refined ETF asset momentum strategy by combining a correlation filter with selective shorting. While traditional long-short momentum strategies usually yield suboptimal results, the long leg proves effective on its own, and the correlation filter demonstrates significant value for improving the timing and performance of the short leg. We propose a final strategy of going long on 4 top-performing ETFs while selectively shorting 1 ETF with a 30% weight. Our findings demonstrate that this combined long-short selective hedge strategy significantly outperforms standalone momentum strategies and the benchmark, delivering superior risk-adjusted returns and effective hedging during unfavorable market conditions.

Trader’s Guide to Front-Running Commodity Seasonality

December 5, 2024

Seasonality is a well-known phenomenon in the commodity markets, with certain sectors exhibiting predictable patterns of performance during specific times of the year. These patterns often attract investors who aim to capitalize on anticipated price movements, creating a self-reinforcing cycle. But what if you could stay one step ahead of the crowd? By front-running these seasonal trends—buying sectors with expected positive performance (or shorting those with negative seasonality) before their favorable months begin—you can potentially gain a significant edge over traditional seasonality-based strategies. In this blog post, we explore how to construct and backtest a systematic strategy using commodity sector ETFs to exploit this seasonal front-running effect.

Pre-Holiday Effect in Commodities

October 14, 2024

Our research will explore the intriguing phenomenon of the Pre-Holiday effect in commodities, particularly crude oil and gasoline. Historical data reveals a short-term price drift prior to major U.S. holidays, suggesting a trend in these markets. We hypothesize that this anomaly may be driven by increased demand for oil and its derivatives, such as gasoline, as people prepare for travel, often by car, during the holiday season. This seasonal behavior offers unique opportunities for market participants.

Payout-Adjusted CAPE

August 19, 2024

Professor Robert Shiller’s CAPE (cyclically adjusted price-to-earnings) ratio is well-known among the investment community. His methodology for assessing a valuation of the U.S. equity market is undoubtedly the most cited and discussed. Therefore, it’s not surprising that there exists quite a lot of papers that try to refine and expand the CAPE’s methodology. One such last attempt is the work of James White and Victor Haghani, whose research paper revolves around the use of a modified version of the Cyclically-Adjusted Price Earnings (CAPE) ratio, termed P-CAPE. Their methodology aims to improve the estimation of long-term expected real returns of the stock market by incorporating the dividend payout ratio into the traditional CAPE metric.