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

I achieved my life’s biggest accomplishment in 2004, when I defeated dozens of other contestants to clinch the Canadian Settlers of Catan championship. “Settlers”, as it’s called by its enthusiasts, is a strategy board game where players collect resources, build settlements, trade with and

Finally, what are the five top-performing quantitative trading strategies in 2021? In part 1 of our article, we analyzed tendencies and trends among the Top 10 quantitative strategies of 2021. Thanks to Quantpedia Pro’s screener, we published several interesting insights about them. In part 2 of

We recently explored using stocks to create an inflation-proxy portfolio that resulted in a collection of stocks with strong sector and factor biases. Specifically, the portfolio exhibited overweights in energy and financial stocks, perhaps as expected, as well as a long position in the value and

Start learning all about the Dijkstra algorithm for finding the shortest path. We briefly review the Kruskal algorithm, Prim algorithm, Johnson algorithm and Bellman algorithm as well. We'll cover: What is the Dijkstra algorithm? How does the Dijkstra algorithm work? Pseudo code of Dijkstra

This is a test of a tactical strategy based on contrarian timing of the business cycle, increasing risk during periods of stress and decreasing risk during periods of calm. The strategy adds trend-following to this countercyclical approach to manage short-term market shocks. Backtested results from

Since the development of the capital asset pricing model (CAPM) about 50 years ago, academic researchers have documented hundreds of “anomalies” that generate significant positive alpha. There are now so many that economist John Cochrane, in his 2011 presidential address to the American Finance

As we have mentioned several times, the best course of action for a quant analyst who wants to develop a new trading strategy is to understand a well-known investment anomaly/factor fundamentally and then improve it. Quantpedia is a big fan of transferring ideas derived from academic research from

Determining the strength of a trend can provide a valuable edge to your trading strategy and help you determine when to go long and let it ride, or not. This is what the Trend Intensity Indicator (TII) was designed to do. This indicator is as simple to interpret as more familiar values like the RSI.

This is the second installment of my series on regression analysis used in finance. In the first installment, we touched upon the most important technique in financial econometrics: regression analysis, specifically linear regression and two of its most popular flavours: univariate linear

For the mean reversion strategies that I have created in the past and are trading now, they typically enter at the next day’s open or wait for a further pullback intraday before entering. My current mean reversion strategy, which enters on a limit down, was doing great until a few months ago when

Remember HML? It was the original formulation for estimating the “value” premium published by Fama & French in 1992. In that seminal article, FF argued based on the results they obtained, that the risk of owning equity is multidimensional. One of those dimensions of risk they used was

Financial research has consistently shown that correlations between assets tend to increase during crises and tend to decrease during recoveries1. The recent COVID-19 market crash was no exception, as illustrated on Alvarez Quant Trading blog post Correlations go to One for both the individual

The year 2021 has been an incredible year for passive equity investors so far. However, in the first part of our article, we talked about quantitative strategies which achieved even better results in 2021 than passive US equity investors. Indeed, there do exist such strategies, at least definitely

Long volatility strategies can be built without using options Securities can be selected on different risk metrics like the VIX or high yield spread Although portfolios differ, the strategies exhibited similar trends INTRODUCTION We started our exploration of long volatility strategies by analyzing

Unlike market price trends, macroeconomic trends are hard to track in real-time. Conventional econometric models are immutable and not backtestable for algorithmic trading. That is because they are built with hindsight and do not aim to replicate perceived economic trends of the past (even if their