This is the sixth (!) post in a (loosely defined) series about finding the best way to trade futures with a relatively small account size. This first (old) post, which wasn't conciously part of a series, uses an 'ugly hack': a non linear rescaling of forecasts such that we only take

Recent research, including the 2020 studies “Explaining the Recent Failure of Value Investing” and “Intangible Capital and the Value Factor: Has Your Value Definition Just Expired?,” have investigated the impact on U.S. value strategies of the increase in the relative importance of

A reader recently suggested leaving the limit orders for a mean reversion trade on for a couple of days. Typically, these orders are good only for one day unless the stock sets up again. I did not think that this would help but as I always tell my consulting clients when they ask me if an idea will

This is the third and final article from the clustering series. If you’ve missed the previous parts, here you can find the first and second parts of the series. This section examines trading strategies based on previously introduced clustering methods. The complete Portfolio Clustering report will

The shape of the US Treasury curve over the past five decades has provided investors with the opportunity to create more efficient long duration exposure than simply buying long-dated Treasuries. In this article we will show how the most efficient long duration exposure is often generated by

The CAPM model was a breakthrough for asset pricing, but the times where the market factor was most widely used are long gone. Nowadays, if we exaggerate a bit, we have as many factors as we want. Therefore, it might not be straightforward which factor model should be used. Hanauer et al. (2021)

The authors of this paper identify aggregate supply and aggregate demand shocks for the US economy utilizing macroeconomic data on inflation, real GDP growth, core inflation, and the unemployment gap. They then go on to extract how these shocks to supply and demand impact the term structure of

Options trading has increased to record highs Some data points indicate changes in the market structure However, these changes are likely temporary rather than structural INTRODUCTION During the 1954 recession in the U.S., Sir John Templeton wrote to his clients that “this time it’s different”

A mainstay of academic research into the market is the Random Walk Hypothesis (RWH). This is the idea that market moves are random and follow a normal distribution that can be easily described using a concept borrowed from physics called Brownian Motion. This makes the market mathematics manageable,

Today’s guest is Grzegorz Link, who professionally works as a quant for an investment fund. Grzegorz is a physicist by education, which may surprise some. However, the thing is that in building market models, skills such as programming and mathematics are the primary tools, which is the same for

My March 23, 2021, article for Alpha Architect addressed the issue that in recent years the field of empirical finance has faced challenges from papers arguing that there is a replication crisis because the majority of studies cannot be replicated and/or their findings are the result of multiple

Abstract: I examine trailing stops in real markets and various autocorrelation and volatility regimes using synthetic data. Exits are notoriously under-studied and may be a source of edge. I examine three key hypotheses using my take on Tom Basso’s random entry method to remove entry from the

Imagine you’re a relatively small, independent trader trying to turn trading from a hobby into a serious business. If that’s you, then there are a few concepts that will help you pick the right trades to get after. This is important because picking the right trades is most of the game. First,

Kris Longmore from RobotWealth joins us to discuss 4 key areas part-time traders need to take seriously to be successful, including: Why it’s important to understanding market participants and why they’re trading, 3 common things traders do that almost guarantee they will blow up, Setting

In this post we are going to examine two alternative methods of calculating the factor contribution to the performance of an equity portfolio. To evaluate the performance of an equity portfolio regarding the exposure to risk factors, it is common to calculate the contribution of each factor to the

The Korean drama ‘Sisyphus’ is a story about a couple of heroes who struggle against a villain from the future. Villains need deep pockets to pull off large schemes, and in Sisyphus’ case, the villain amasses his wealth by using his knowledge of the future to make money on the stock market. In

Many studies identified by the Quantifnder Monday afternoon showed the strong selling and closing lows to be potentially bullish. And Turnaround Tuesday is typically the best day for a bounce to begin. The study below considered the long-term uptrend, intermediate-term low, and strong selling on

ESG products have been flooding the market and it is difficult for investors to assess the ground truth. To make matters worse, with limited sample size periods and datasets, trying to determine “evidence-based” ESG insights, is challenging. Nonetheless, we’ve been covering the academic

Do motives of financial market researchers justify strong skepticism of their findings? In his brief August 2021 paper entitled “Be Skeptical of Asset Management Research”, Campbell Harvey argues that economic incentives undermine belief in findings of both academic and practitioner financial

The correlation of stock markets has stopped increasing since the GFC The Value and Momentum factors are trading at peak correlations Correlations can change dramatically when using different data sources INTRODUCTION Globalization is less of a smooth ride on a river barge and more akin to river

We present a new database of banking-crisis interventions since the 13th century. The database includes 1886 interventions in 20 categories across 138 countries, covering interventions during all of the crises identified in the main banking-crisis chronologies, while also cataloguing a large number

At the beginning of October, we plan to introduce for our Quantpedia Pro clients a new Quantpedia Pro report dedicated to clustering methods in portfolio management. The theory behind this report is more extensive; therefore, we have decided to split the introduction into our methodology into three

A large body of evidence, including the studies “Is There Momentum in Factor Premia? Evidence from International Equity Markets,” Factor Momentum Everywhere (Summary)” and “Factor Momentum and the Momentum Factor,” has demonstrated that momentum exists across financial markets (stocks,

For fundamental equity investors, the financial statement is the launchpad for the search for value. True, quants use financial statements too. But they spend less time on what the numbers mean, than on what they are. To produce a financial statement that adequately captures the economic (not GAAP

This text is a primer on how to develop a high-frequency-trading system/simulation lab, with focus on the Nasdaq exchange and the ITCH protocol. The code is entirely written in C and follows the data-oriented-design methodology. The reason for picking C instead of C++, when the latter is the

As the name suggests, long short equity strategy is one where we take both long and short positions in different equities. This strategy is normally used by hedge funds to generate greater risk adjusted returns due to its inherently low risk characteristics. In this article, you will learn about how

There is no consensus whether an equal or market cap-weighted allocation model for stocks is superior Both generated similar drawdowns during stock market crashes on average Theoretically, equal-weight is superior, but practically cap-weighted INTRODUCTION “Diversify, reduce fees, avoid active

Moving average indicators are commonly used to give traders a general idea about the direction of the trend by smoothing the price series. One of the big drawbacks to most common moving averages is the lag with which they operate. A strong trend up or down may take a long time to get confirmation

The application of alternative data is currently a strong trend in the investment industry. We, too, analyzed few datasets in the past, be it ESG data, sentiment, or company fillings. This article continues the exploration of the alt-data space. This time, we use the research paper by Joenväärä

Sometimes it is too costly, even impossible, to explicitly optimize an equation. Today we will see how to optimize implicitly using genetic algorithms. Sometimes, in finance as well as in other aspects of life, a problem presents itself in the most clear of terms: an explicit equation which we must

From 2017 through March 2020, the relative performance of value stocks in the U.S. was so poor, experiencing its largest drawdown in history, that many investors jumped to the conclusion that the value premium was dead. It is certainly possible that what economists call a “regime change” could

As mentioned several times, Quantpedia is a big fan of transferring ideas from one asset class to another. This article is another example; we use an idea originally tested on Chinese stocks and apply it to the commodity futures investment universe. The resultant return new asymmetry investment

One of the more difficult challenges for modeling is deciding how (or if) to deal with extreme data points. It’s a common problem in economic and financial numbers. Fat tailed distributions are standard fare in stock market returns, for example. Meanwhile, the dramatic collapse in the economy

Portfolio diversification benefits are often driven by correlation coefficients, but this analysis can get complicated, fast. Over time academics and practitioners have realized that it is not enough to simply calculate a correlation using short return intervals (daily?, monthly?) over a sample

The hedge ratio estimation problem is one of the most important issues for portfolio managers. The key concept of the hedging problem can be posed as the following equation: S_{t}=P_{1, t}+\sum_{n=2}^{N} \omega_{n} P_{n, t} where P_1 represents the market value at observation t of a portfolio we

In this short post, I will introduce the Hierarchical Risk Parity portfolio optimization algorithm, initially described by Marcos Lopez de Prado1, and recently implemented in Portfolio Optimizer. I will not go into the details of this algorithm, though, but simply describe some of its general ideas

How many years does it take before you can be confident in a trading strategy? Does one great year mean you have a tremendous strategy? Does one bad year mean you should pack it up and try something else? How soon can you tell that a system is flawed and needs changing? These aren’t easy

This will be a bit different from my normal posts. It's basically some personal reflections on the LIBOR fixing scandal, prompted by having just read this book written by Stelios Contogoulas: This post isn't really a book review, although I will say that the book is definitely worth

The Moving Average Convergence-Divergence (MACD) is a popular and versatile indicator that appears in a number of trading systems. In it’s most basic form, we have the difference between two exponential moving averages (EMA), one fast and the other slow. The MACD is the difference between these

Nowcasting in financial markets is mainly about forecasting forthcoming data reports, particularly GDP releases. However, nowcasting models are more versatile and can be used for a range of market-relevant information, including inflation, sentiment, weather, and harvest conditions. Nowcasting is

Back in May of this year I posted about how I had intended to use Matrix Profile (MP) to somehow cluster the "initial balance" of Market Profile charts with a view to getting a heads up on immediately following price action. Since then, my thinking has evolved due to my learning about the

One of the major challenges that users face when trying to do data science is how to handle big data. Leaving aside the important topic of database connectivity/functionality and the handling of data too large to fit in memory, my concern here is with the issue of how to handle large data files,

The Alpaca brokerage service is very useful for algorithmic traders that comes with an API to retrieve data and execute trades in a paper or live environment. While you can also check the status and returns of your positions through the API, Alpaca has spent some time creating a frontend where users

Academic research has found that factor premiums are both time-varying and dependent on the economic cycle. For example, Arnav Sheth, and Tee Lim, authors of the December 2017 study “Fama-French Factors and Business Cycles,” examined the behavior of six Fama-French factors—market beta (MKT),

This post is something that I've banged on about in many presentations at several conferences* (most complete slides are here), and in various interviews, but never actually formally described in a blog post. In fact this post has existed in draft form since 2015 (!). * you know, when you leave

Purchasing Power Parity (PPP) is a well-known measure used to compare the currencies of different countries in terms of price levels. So, in this post, we are going to explain PPP and study, through an example, its relation with the currency pairs. PPP is based on the law of one price (LOOP). For

Is the ratio of implied volatility of implied volatility (CBOE VVIX Index), interpretable as a measure of changes in investor fear level, to CBOE VIX Index itself a useful indicator of future stock market returns? To investigate, we relate monthly VVIX/VIX and monthly change in VVIX/VIX to monthly

Elton, Gruber, and Busse (2004) as well as Hortacsu and Syverson (2004) suggest that mutual fund markets are not perfectly competitive and that fees do matter to investors. In contrast, the neoclassical view of mutual funds (see for example Berk and Green, 2004; Pastor, Stambaugh and Taylor, 2019

This is a series where we aim to cover in detail various aspects of the classic Ornstein-Uhlenbeck (OU) model and the Ornstein-Uhlenbeck Jump (OUJ) model, with applications focusing on mean-reverting spread modeling under the context of pairs trading or statistical arbitrage. Given the universality