Recently a reader sent me a leveraged ETF strategy that he wanted tested for the blog. Over the last couple of months, I have been noticing renewed interest in leveraged ETF trading. More clients are coming to me to test out leverage trading ideas. I have been testing my own ideas. What I liked

Inflation-themed ETFs have heterogeneous portfolios However, commodities and oil have been better inflation hedges And offer higher diversification benefits INTRODUCTION In November 2021 we analyzed inflation-themed ETFs (read Inflation-Themed ETFs: As Complicated as Inflation) and concluded that

Here’s a thing that I suspect will make money, but that I haven’t yet tested (for reasons that I will explain shortly): Every day, at the start of the trading day, get the SPX straddle price and convert it to an expected SPX price move. Then at the end of the trading day, take the SPX price and

Macroeconomic trends affect stocks differently, depending on their lines of business and their home markets. Hence, point-in-time macro trend indicators can support two types of investment decisions: allocation across sectors within the same country and allocation across countries within the same

The benefits of diversification are well known. In fact, it’s been called the only free lunch in investing. Investors who seek to benefit from diversification of the sources of risk and return of their portfolios must accept that adding unique sources of risk means that their portfolio will

This is a test of the 12-Month High Switch Model, a Tactical Asset Allocation (TAA) strategy from Meb Faber. Meb has done more than anyone to popularize TAA as a trading style, including many of the fundamental concepts used today. This is another of his simple but effective ideas. Backtested

Stocks for a low-growth & high-interest rate environment should have high-quality characteristics However, there are many ways to define quality stocks Historically quality portfolios have not generated excess returns INTRODUCTION Ignoring the past is one of the biggest investing mistakes.

The lifeblood of quant finance is data. The problem is that data is sometimes hard to come by. It may be expensive or just not available. What if we had a way to generate synthetic market data? Artificially recreating a dataset is a complex process. The new data needs to mimic the existing data

Jerry Kaufman, known for his technical indicators bible, presented in TASC 1/24 a trading strategy based on upwards and downwards gaps. For his system, he invented the Gap Momentum Indicator (GAPM). Here I’m publishing the C version of his indicator, and a simple trading system based on it. The

Perhaps the most well-documented and researched asset pricing anomaly is momentum—the tendency of past winner stocks to outperform past loser stocks over the next several months. While average time-series momentum (trend following) returns have been high, strategies employing trend following have

Cryptocurrencies are already one of the major asset classes. They fill the top pages of magazines and are a topic of a day to day conversation. There are a lot of ways to buy them through a lot of different channels. But some of the hardcore HODLers like to keep their coin portfolio safe – they

In the previous post of this series on volatility forecasting, I described the simple and the exponentially weighted moving average volatility forecasting models. In particular, I showed that these two models belong to the generic family of weighted moving average volatility forecasting models1,

Financial modeling has long sought to develop frameworks that accurately capture the complex dynamics of asset prices. Traditional models often focus on either momentum or mean reversion effects, struggling to incorporate both simultaneously. In this blog post, we introduce a two-factor model that

In February 2023, peer Wouter Keller and JW Keuning published a study of an interesting strategy, Dual and Canary Momentum with Rising Yields/Inflation: Hybrid Asset Allocation (HAA), which uses the Treasury Inflation-Protected Securities (TIPS) markets to decide when a strategy should be invested

P/E and ROE factors were highly correlated in recent years However, this is counterintuitive as cheap stocks should not be highly profitable We can explain this perplexity with stocks with negative earnings INTRODUCTION In our recent article “Value vs Quality: More Correlated than Ever?” we

Academic research, including the studies “Do Investors Overpay for Stocks with Lottery-like Payoffs? An Examination of the Returns on OTC Stocks,” “Lottery Preference and Anomalies” and “Do the Rich Gamble in the Stock Market? Low Risk Anomalies and Wealthy Households,” has found that

Market Risk Premium Expectation: Combining Option Theory with Traditional Predictors Hong Liu (Washington University in St. Louis), et al. December 2022 In general, the slackness between the Martin lower bound (solely based on option prices) and the market risk premium depends on economic state

Our article “Log-normal Stochastic Volatility Model with Quadratic Drift” co-authored with Parviz Rakhmonov is published in International Journal of Theoretical and Applied Finance with open access https://www.worldscientific.com/doi/10.1142/S0219024924500031 The log-normality of realised and

Joe Biden will be giving his State of the Union Address tonight, and people are wondering how his talk might impact the market over the next several days. I have looked at performance following State of the Union before and decided to update that research today. The data table below looks back to

Here at Robot Wealth, we trade with Interactive Brokers (IB) primarily because they offer access to global markets at a reasonable price. In recent times, IB has put some time and effort into upping its tech game, including development of an API for interacting with its desktop trading applications.

I've talked at some length before about the question of fitting forecast weights, the weights you use to allocate risk amongst different signals used to trade a particular instrument. Generally I've concluded that there isn't much point wasting time on this, for example consider my

P/E and ROE long-short factors have become highly correlated During certain periods investors favor expensive and unprofitable stocks However, it is difficult explaining the positive correlation outside of bubbles INTRODUCTION The older I get, the less I seem to know for certain about investing. The

This is the final article in our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and effective way

Let me present our recent research paper with Parviz Rakhmonov on the stochastic volatility model for Factor Heath-Jarrow-Morton (HJM) interest rate framework (available on SSRN: Stochastic Volatility for Factor Heath-Jarrow-Morton Framework). Factor Heath-Jarrow-Morton (HJM) model Under the

In a previous article I made a detailed comparison of Mathematica and Python and tried to identify areas where the former excels. Despite the many advantages of the Python technology stack, I was able to pinpoint a few areas in which I think Mathematica holds the upper hand. Whether those are

Multi-timeframe (MTF) analysis lets traders build powerful intraday trading strategies. It does this by analyzing asset prices during different timeframes throughout the trading day. The problem is most people get MTF wrong. It requires a vector-based backtest to speed up the operations making it

“Conventional wisdom” can be defined as ideas that are so accepted that they go unquestioned. Unfortunately, conventional wisdom is often wrong. Two examples are that millions of people once believed the conventional wisdom that the Earth is flat, and millions also believed that the Earth is the

Select portions of quant_rv can be combined to craft a new strategy (qrvx) that provides positive returns, negative correlation to SPY and crisis alpha, making it nice for combining with SPY (like a 60/40 combo) to create strong returns with low drawdowns. In my last “Replacing the 40” post, we

After years of waiting, the recent launch of spot Bitcoin ETFs marked a significant milestone in the cryptocurrency market, making Bitcoin even more accessible for investors. Spot ETFs provide a convenient and regulated way to gain exposure to Bitcoin without the need to hold the digital asset

Tail risk ETFs have achieved similar return profiles despite different portfolios TAIL represents a traditional tail risk strategy, but offers limited diversification benefits BTAL is more diversifying, but not more than CTAs INTRODUCTION Although more than 3000 ETFs are trading on U.S. exchanges,

This article continues our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and effective way to

Portfolio optimization usually requires an estimate of the future returns of the assets in the portfolio. This is hard because we can’t see into the future. Traditional risk parity uses a quadratic optimizer A cutting edge technique called Hierarchical Risk Parity (HRP) uses graph theory and

Regression is one method for combining macro indicators into a single trading signal. Specifically, statistical learning based on regression can optimize model parameters and hyperparameters sequentially and produce signals based on whatever model has predicted returns best up to a point in time.

The academic research, including the 2023 studies “Lottery Preference and Anomalies” and “Do the Rich Gamble in the Stock Market? Low Risk Anomalies and Wealthy Households,” the 2022 study “Lottery Demand and the Asset Growth Anomaly,” and the 2014 study “Do Investors Overpay for

The investment world witnessed a paradigm shift with the introduction of momentum strategies, a concept pioneered by Jagadeesh and Titman in their landmark 1993 study “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency”. Their groundbreaking approach, hinged

As an avid user of both Python and Wolfram Language for technical computing, I’m often asked how they compare. Python’s strengths as an open-source language are clear: Ubiquity – With millions of users, Python has become ubiquitous across fields like data science, ML engineering, web

Absolute and relative momentum can be used as simple asset allocation frameworks Both would have generated a higher return than an equal-weighted portfolio across asset classes However, risk-adjusted returns were lower and drawdowns higher INTRODUCTION Investing is often overwhelming given the

The paper aims to provide insights into the dynamics of benchmark selection, the effectiveness of Relative Performance Evaluation ( RPE ) incentivization, and the broader implications for fund performance and market competition. Self-Declared Benchmarks and Fund Manager Intent: “Cheating” or

Modeling features as expected returns can be a useful way to develop trading strategies, but it requires some care. The main advantage is that it directly aligns with the objective of predicting and capitalising on future returns. This can make optimisation and implementation more intuitive. It also

Investing truly is an intense intellectual undertaking. For a Portfolio Manager (PM) to execute an investment, they must first convince themselves, then others, that the rationale behind the investment is sound. The variables they utilize in developing their rationale are of the upmost importance;

Quants, financial analysis, and traders use fundamental data for investing and trading. These data are derived from quarterly and annual statements that companies file with the U.S. Securities Exchange Commission (SEC). These statements are rich with data that can be used to build predictive factor

Expectations of future earnings growth matter a great deal to valuations because investors, in their collective wisdom, assign higher valuations to companies they expect will grow more quickly in the future (growth stocks). In contrast, firms expected to show slower growth (value stocks) are

Like the Federal Reserve, trend following is often said to have a dual mandate. One mandate is to earn a positive return, and the other is to provide some sort of “crisis alpha”, or an offset to drawdowns in traditional, 60/40 type portfolios. There could be tension between these two goals; for

We track 80+ Tactical Asset Allocation (TAA) strategies, most of which were designed from the perspective of a US investor trading US ETFs. Most European investors can’t access US ETFs, instead trading UCITS funds listed on non-US exchanges, often denominated in currencies other than USD. In this

In this blog, I just toy around with a relatively new framework for querying (large) language models: LMQL, a SQL-like for LLMs. It is a first step toward a novel programming paradigm: Language Model Programming (LMP). These ideas are described in the very interesting paper Prompting Is Programming:

One use of the NLP (natural language processing) features of ChatGPT is to search out patterns in the immense amounts of news, data and other sources of information about specific stocks, and then efficiently convert them into summaries valuable for all types of investors. Can this be accomplished

There are multiple ways to measure interest rate sensitivities “High-duration” stocks like tech and biotech were not more sensitive to rising rates The relationship between interest rates and stocks is weak INTRODUCTION In our first article on the duration of U.S. equities (read Duration of U.S.

Every time we trade, we incur a cost. We pay a commission to the exchange or broker, we cross spreads, and we might even have market impact to contend with. A common issue in quant trading is to find an edge, only to discover that if you executed it naively, you’d get killed with costs. In this

Fund managers report their holdings every month. They don’t want to tell investors that they lost money the latest meme stock. So they will sell the meme stocks and buy higher quality assets, like bonds. We might be able to take advantage of this month-end flow effect by buying bonds toward the

Backtesting of macro trading strategies requires good approximate profit-and-loss data for standard derivatives positions, particularly in equity, foreign exchange, and rates markets. Practical calculation methods of generic proxy returns not only deliver valid strategy targets but are also the