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,

Generating realistic future paths for investment market time series is crucial for risk management, good backtesting1, fully general stress-testing2, and CVaR tail risk optimization, see the Portfolio Construction and Risk Management book3. The recent Time- and State-Dependent Resampling article4

In this episode, seasoned trader Rob Carver shared his nuanced approach to building and managing a diversified futures portfolio—a methodology that appeals to advanced, technical traders, while we also covered off some of the 'basics' of futures trading, such as rolling, back-adjusting,

Welcome to this week's roundup of the latest investing research! Below is a carefully curated selection of highlights from the past week, with each title linking directly to its source for further reading. Thank you for reading and don’t forget to hit the like button! Crypto Token Economics

Credit risk, also known as default risk, is the likelihood of loss when a borrower or counterparty fails to meet its obligations. A lot of research has been conducted on credit risk, and an emerging line of study explores the connection between the equity and credit markets. In this post, we’ll

Can we truly rely on the opening price in OHLC data for backtesting? While the overnight drift effect is well-documented in a lot of asset classes, we investigated its presence in gold using the GLD ETF and then extended our analysis to the GDX – Gold Miners ETF, where we observed an unusually

The interest rate is a key input to pricing various instruments. For example, the price of an option depends on the risk free rate. The return earned holding bonds depends on the bond yield. A good model of interest rates means you can better price these interest rate derived products and have a

Highly illiquid assets trade infrequently making it difficult to know their true market value. To address this issue, funds that invest in illiquid assets create fair valuation estimates at periodic intervals. These valuation estimates determine the share values at which interval and tender offer

The Unintended Consequences of Rebalancing Campbell R. Harvey (Duke University), et al. January 2025 Institutional investors engage in trillions of dollars of regular portfolio rebalancing, often based on calendar schedules or deviations from allocation targets. We document that such rebalancing has

The interactive version of this report can be found here; our previous report on exchange outflows’s predictive power here. With investor sentiment and risk premiums encapsulated in its options data, Bitcoin’s implied volatility is becoming an interesting predictive factor with its dual role as

Tail risk hedging aims to protect portfolios from extreme market downturns by using strategies such as out-of-the-money options or volatility products. While effective in mitigating large losses, the challenge lies in balancing cost and long-term returns. In this post, we’ll discuss tail risk

The Puell Multiple was invented by analyst David Puell, back in March 2019. He developed the metric as a way to quantify miner revenue in relation to historical averages: it compares the daily USD value of Bitcoin mined through block rewards to its 365-day moving average, directly meauring whether

Let’s say you observe some effect in the market and quantify it with simple data analysis. A good question is, “What are the chances I’d see this effect solely due to chance?” And using simple Excel tools, we can answer this question without doing any formal statistics. Before we get into

Dealing with multidimensional data in data visualization is tricky. You have to strike a balance between presenting a lot of useful information, but not cluttering charts too much. There are a lot of flashy and glimmery chart options. Yet it's easy to lose your audience by flooding them with

Commodities Tail Risk Premium in the Crude Oil Market (Li and Li) While the variance risk premium has been widely studied in financial markets, this paper finds that the option-implied tail risk premium is a stronger predictor of crude oil futures returns. Short-term tail risks signal lower returns

Decades of research have uncovered numerous market anomalies, persistent patterns in asset returns that cannot be fully explained by traditional risk-based models. Among the most enduring and well-documented of these is the turn-of-the-month (TOM) effect, characterized by abnormally high stock

"Every great developer you know got there by solving problems they were unqualified to solve until they actually did it." — Patrick McKenzie. Patrick McKenzie is a well-known software developer, entrepreneur, and writer, widely recognized for his work in the software industry,

A bit of a theme in my posts a few years ago was my 'battle' with the 'classic' trend followers, which can perhaps be summarised as: Me: Better Sharpe! Them: Yeah, but Skew!! My final post on the subject (when I realised it as a futile battle, as we were playing on different

Whether we manage our own investment assets or choose to hire others to manage the assets on our behalf we are keen to know how well our […] portfolio of assets is performing1 and the calculation of portfolio return is the first step in [that] performance measurement process1. Now, while the

I recently wrote a post about naive backtesting of investment risk measures1, which is usually performed in the following way: Look at some historical data samples. Optimize portfolios using different risk measures. Crown the investment risk measure with the highest cumulative performance as “the

Thirty years ago, I wrote my dissertation on the low-vol effect, which was really bad timing. This was just after various anomalies highlighted in the 70s and 80s were exposed as the effects of measurement error and selection bias (the low-price effect, the January effect). The small-cap effect was

Fair warning: this article is intended for advanced DIY Tactical Asset Allocation investors, i.e. nerds like us. First, a bit of background knowledge you’ll need to understand this discussion… Background knowledge: What is “timing luck”? Most Tactical Asset Allocation (TAA) strategies trade

I recently tested ChatGPT Pro’s Deep Research functionality (released on Monday, February 3, 2025)—currently priced at $200/month—using the latest o3-mini-high model. My objective? To evaluate how effectively it can assist in developing a US Stock Momentum Trading System for retail traders.

Hello everyone, Over the last few months, we have received numerous messages asking us if we plan to continue with our successful quant research competition in 2025. Last year, we promised our readers that the Quantpedia Awards would be back! And now it’s again time to unveil what we have prepared

The ARFIMA model is well suited for capturing long-range memory in financial time series. However, it’s not always the case the time series exhibits long memory in their autocorrelation. The ARTFIMA model comes to the rescue to capture not only the long memory but also its short one and the

Momentum strategies have long been a cornerstone of investing, relying on the premise that past winners continue to outperform in the near future. This post explores the effectiveness of momentum strategies, analyzing their ability to generate abnormal returns and assessing their viability in

The PDF version of the Portfolio Construction and Risk Management book is now publicly available. You can find links to the book and its accompanying Python code at the bottom of this newsletter. It contains many new perspectives and results that are exclusive to the book, showing you that there are

Dividend yield has long been a cornerstone of equity valuation. In this post, we explore how dividend yield predicts stock returns, its impact on stock volatility, and why it holds unique significance for mature, dividend-paying firms. Relationship Between Implied Volatility and Dividend Yield

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

Every Monday, I get an email from CMC with the new Crypto listings and top trending coins. Here’s the one from this past Monday. I usually give it a quick look and then delete it, but not so long ago, I started wondering: should I give a #@%! about this? It bugged me so I decided to look into it.

We’re back! It’s 2025 and we are planning a cracker of a year! Stay tuned! It was strangely comforting talking to Ernie Chan. Whilst I was completely out of my depth talking about AI and Machine Learning, I came away broadly reinforced in my own belief that great trading still requires a human

The PDF version of the Portfolio Construction and Risk Management book is freely available online at the bottom of this post. The accompanying code to the book is available on GitHub at https://github.com/fortitudo-tech/pcrm-book1. The book has been written through a crowdfunding campaign that you

In the previous post the framework for Generalized Downside Implied Correlations was introduced. You can use this correlation matrix derived from joint risk metrics to replace or augment/blend with traditional correlations for use in analysis or optimization. The challenge is that the resulting

Monte Carlo simulations are widely used in science, engineering, and finance. They are an effective method capable of addressing a wide range of problems. In finance, they are applied to derivative pricing, risk management, and strategy design. In this post, we discuss the use of Monte Carlo

Academics have long been aware of the risks of data mining—torturing the data until it confesses. The concern is that correlation of variables doesn’t imply that the correlation is a result of causation. That is the reason that the prevailing academic standard for researchers is that they should

An Investigation into the Causes of Stock Market Return Deviations from Real Earnings Yields Austin Murphy (Oakland University), et al. December 2024 This research demonstrates that the simple difference between the current earnings yield on the S&P500 and the long-term real TIPS yield has

"If I have seen further, it is by standing on the shoulders of giants.” Sir Isaac Newton. First of all, Happy New Year! When I started Quantitativo a few months ago, I could never expect to gather such an amazing group of like-minded people in such a short time. Your enthusiasm, curiosity,

Factor Investing Origins and Implications The roots of factor investing can be traced to work published in the early 1990s by two academics: Ken French and Eugene Fama. In two of their publications[1], they identified a set of risk factors priced to consistently and robustly provide a return

Can we simplify the complexities of the stock market and distill them into a simple set of quantifiable metrics? A lot of academic papers suggest this, and they offer formulas that should make the life of a stock picker easier. Some of the most compelling methodologies within this realm are the

The general acceptance of cryptocurrencies, especially Bitcoin, was a blessing from Wall Street, which institutionalized them as ETFs for comprehensive access by the general public and institutional investors. There is little to no denying now that this new asset class is becoming more traditional,

Principal Component Analysis (PCA) is a dimensionality reduction technique used to simplify complex datasets. It transforms the original variables into a smaller set of uncorrelated variables called principal components, ranked in order of their contribution to the dataset’s total variance. In

Machine learning models have proven effective in predicting stock returns using lagged stock characteristics, but their success is influenced by a wide range of modeling choices. One critical, yet often overlooked, choice is how stocks are weighted in the objective function during training, with

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

This is a test of two stock market seasonality strategies from Fred Piard’s book Quantitative Investing: Strategies to Exploit Stock Market Anomalies for All Investors. Strategy results from 1970 follow. Results are net of transaction costs – see backtest assumptions. Learn about what we do and

In the previous post I introduced a Drawdown Implied Correlation (DIC) that is a joint time-series measurement which converts maximum drawdowns into a correlation coefficient using a simple formula derived from portfolio math. The DIC had some unique features such as a “point-in-time” reference

Beta is a measure of an asset’s sensitivity to market movements, indicating how much its price is expected to change in relation to the overall market. Beta is often used in CAPM and the calculation of WACC. However, it can also be applied in trading, specifically in arbitrage. In this post,

As most of you know, one of the many projects / things I am involved with is the TTU Systematic Investor podcast series where I'm one of the rotating cast of co-hosts. On a recent episode (at 24:05) we discussed the reasons why 'alt' CTAs tend to do better than traditional CTAs.

By examining data going back to 1792, McQuarrie’s study comes up with a surprising observation : stocks are not as dominant as once thought. The variability of the performance of stocks vs. bonds across various time periods is dramatic. So buckle up, stocks do not invariably outperform bonds.

I tweet a lot (from @saeedamenfx and at BlueSky at @saeedamenfx.bsky.social)! In amongst, the tweets about burgers, I tweet out a quant paper or link every day under the hashtag of #QuantLinkDay, mostly around FX, rates, economics, machine learning etc. Some are directly relevant to what we’re

Investing formulas are simple, easy-to-implement, systematic, stock screeners that provide instructions on how to outperform the total stock market. Marcel Schwartz and Matthias Hanauer, authors of the December 2024 study, “Formula Investing,” evaluated the effectiveness of four such popular