Clustering algorithms are one of the main techniques in the field of unsupervised learning. In the machine learning context, we understand by unsupervised learning the process of analyzing and identifying patterns in unlabeled datasets. Unsupervised learning algorithms observe similarities and

Value strategies attempting at determining a fair value of an asset are one of the first-ever employed strategies in the markets. We all know about Benjamin Graham and Warren Buffet that are one of the best known examples of Value pioneers. Since then, however, Value strategies have evolved

Risk parity strategies have become available via mutual funds and ETFs, but portfolio construction varies Rising interest rates are seen as a threat and recent performance was disappointing However, rising correlations between stocks and bonds would be more concerning INTRODUCTION Risk parity has

n my past life as a rower, I spent a lot of time figuring out which way the wind was blowing: Would it be a headwind and slow things down? Or would it be a tailwind and shorten the race? But a tailwind that went against the current could cause choppy water…which would slow things back down.

Momentum, the tendency of past winner stocks to outperform past loser stocks over the next several months, is one of the most well-documented and well-researched asset pricing anomalies. In our book “Your Complete Guide to Factor-Based Investing,” Andrew Berkin and I presented the evidence of a

When dealing with factors information is important to go to the detail and get insight about how the factor is built. Ratios combination improves robustness. When we read papers or studies about the Factor Premium of different factors we almost always come across with the problem of how to define

The Nobel price laureate physicist Niels Bohr once said, “Prediction is very difficult, especially if it’s about the future.” This quote captures the reality in the markets rather accurately. Is Bitcoin breaking through the 50k mark this year? Or even the 100k mark? Will Ethereum outperform

Finding a good data source with quality data and long history is one of the greatest challenges in quantitative trading. There definitely are some data sources with very long histories. However, they tend to be on the more expensive side. On the other hand, cheap or free data usually lacks quality

Given the current rise in inflation, there has been a lot more interest in assets that do well during these times. Gold is one asset that is frequently brought up as an inflation hedge. I have also seen more lately about combining these two into a portfolio. Testing Notes The test range is from 1970

Academic research suggests that high and rising consumer price inflation puts upward pressure on real discount rates and is a headwind for equity market performance. A fresh analysis of 17 international markets since 2000 confirms an ongoing pervasive negative relation between published CPI dynamics

This blog is a follow-up on a first naive modelling of Matalan notes using Bayesian nets. Bayesian nets are a good tool to quantify qualitative knowledge, as explained here. The work presented in this blog post was mostly realized by Zhiyuan Shen in the context of his financial mathematics master of

Plenty of research ( most recently, Cziraki et al. 2021) shows that insider buys contain value-relevant information while insider sales include little to no information. But what about the action of “not trading”? The authors of this study ask the following: Are the trades of portfolio insiders

This is a follow up to our previous post. Same subject, additional data. Both stocks and government bond funds have suffered major losses this year. Stocks and gov bonds form the core of most portfolios. Gov bonds tend to counterbalance risk assets, helping to smooth returns during periods of market

Short answer up front–very little.(1) This was a simple question posed to me by one of our blog readers–what impact does excluding stocks trading at 10x P/S have on a Momentum portfolio? A good question–especially for those who are “value” investors that are interested in momentum. For

Outperforming the market, before expenses, is a zero-sum game—if one group of active investors outperforms, another group of active investors must underperform. Is there a group of sophisticated investors who persistently exploit more naïve investors? The body of research has found that before

I am sometimes asked if I recommend any stock market data (web) API for a personal use, especially because I mention Alpha Vantage in a couple of previous posts1. I will describe in this post part of the thought process and of the due diligence which led me to select this financial market data

Another brief post this month; the deadline for the first draft of my latest book is only a couple of months away and I haven't got much free time! But I was asked an excellent question on twitter recently, which was how the various types of trading rule have contributed to my p&l this

The Internet is full of articles covering all kinds of aspects related to finance. Stocks, crypto, indexes have always been a hot topic and many are seeking new ideas in these areas. It is true that in a vast amount of the content one may get lost. There are tons of blogs with irrelevant, outdated,

Value and momentum are two of the most powerful explanatory factors in finance. Research on both has been published for over 30 years(1). However, it was not until recently that the two had been studied in combination and across markets. Bijon Pani and Frank Fabozzi contribute to the literature with

Graph Theory is widely used in almost every area of interest for visualization or analysis purposes but, for some reason, it is not usually applied in finance. Why not trying to take advantage of its potential in portfolio management? Introduction Current uncertainty is causing very pronounced

In this article, the authors expound on the importance of the factor “revolution” in finance. Factor investing has moved from a bedrock position to a future of innovation and disruption. With respect to factors the authors discuss where we have been and what can we look forward to. What are the

Economic growth differentials are plausible predictors of foreign exchange return trends because they are related to differences in monetary policy and return on investment. Suitable metrics for testing growth differentials as trading signals must replicate historic information states. Two types of

In this video kaggle grandmaster Rob Mulla takes you through an economic data analysis project with python pandas. We walk through the process of pulling down the data for different economic indicators, cleaning and joining the data. Using the Fred api you can pull up to date data and compare,

In the previous post, I reviewed the turbulence index, an indicator of financial market stress periods based on the Mahalanobis distance, introduced by Chow and al.1 and Kritzman and Li2. In this post, I will review the absorption ratio, a measure of financial market fragility based on principal

How often do you think about the weights of the assets in your portfolio? Do you weigh your assets equally, or do you prefer value-weighting? The researchers behind a recent research paper analyzed various weighting schemes and examined their effect on factor strategy return. They studied five

The 2014 study by Andrea Frazzini and Lasse Pedersen, “Betting Against Beta,” established strong support for low-beta (as well as low-volatility) strategies. The authors found that for U.S. stocks, the betting against beta (BAB) factor (a portfolio that holds low-beta assets leveraged to a beta

Random Forests are widely used Machine Learning algorithms. In finance, certain financial ratios are used to try and predict whether or not a company will outperform the market. Can we use the random forest on financial ratios to articulate an investment strategy which outperforms a buy and hold

Investors assume that token prices increase with product utilization in the token ecosystem However, the correlation between the token prices and token volumes has been zero Likely explained by token prices substantially being driven by speculation INTRODUCTION Much of the crypto world is, by

Inflation is perhaps the least well understood phenomenon in economics. Once said to be exclusively a monetary phenomenon, our current predicament is significantly more complicated and there is little consensus as to the root cause. Until recently the concern was that inflation would run permanently

A clear and informative time-series visualisation is often a challenge. Especially this is true when it comes to candlestick charts in Python. Searching the Web for a perfect solution may bring you to the Plotly package which stores in its arsenal the corresponding function allowing for easy

Capturing the systematic premia is the main aim of many quantitative traders. However, investors tend to overlook an important factor when backtesting. Trading costs are an essential part of every trade, and yet even when we consider them, we often only use an approximation. The recent article from

In financial time series it is very common to make predictions of single points such as expected future prices or returns. But is there any other way of adding more information in our forecasts? In today’s post we will be making probabilistic forecasts for time series data using recurrent neural

A common mistake made by many passive investors is that they view all index funds in the same asset class as “commodities(1)”, often considering only the expense ratio when making their investment choices. However, not all index funds are alike, and not all passively managed funds (what I refer

In this research, the authors explore the role of financial intermediaries in contagion or comovements in pricing efficiency. Specifically, lead market makers (LMMs) like Goldman Sachs, Cantor Fitzgerald, RBC Capital Markets, and others, have funding constraints that may influence their ability to

Thematic indices from MSCI have outperformed their benchmark since 2018 However, they have a rather unattractive factor mix Going against decades of research is not a sound investment strategy INTRODUCTION Although much of the future is uncertain, some technological innovations are rather certain.

Most government bond funds have suffered major losses this year. What is worse is that those major losses have come when they’re needed most, when stocks and other risk assets are also falling. During times of market stress, gov bonds tend to act as a counterbalance to risk assets, but so far this

One of the challenges in portfolio management is the timely detection of financial market stress periods, typically characterized by an increase in volatility and a breakdown in asset correlations1. Chow and al.2 propose to detect such periods through the usage of the caste distance, a measure

FX forward-implied carry is a valid basis for trading strategies because it is related to divergences in monetary and financial conditions. However, nominal carry is a cheap and rough indicator: related PnLs are highly seasonal, sensitive to global equity markets, and prone to large drawdowns.

A Look Under the Hood of Momentum Funds Ayelen Banegas and Carlo Rosa (Federal Reserve) February 2022 Momentum investing has surged over the past few years, with assets growing at three times the rate of conventional funds. Using a comprehensive dataset of US equity funds, this paper examines the

Eight years! Wow. In late 2013 I walked out of an office for the last time where I had been working for AHL, a large systematic futures trading fund. A few months later, in April 2014, I had my own very small systematic futures trading account, and I started doing these performance reviews. And this

As the chief research officer of Buckingham Strategic Partners, the issue I am being asked to address most often is about fixed income strategies when yields are at historically low levels and inflation risk is heightened due to the unprecedented increase in money creation (through quantitative

“Sell in May and go away” is an old stock trader’s wisdom. But in his TASC May 2022 article, Markos Katsanos examined that rule in detail and found that it should rather be “Sell in August and buy back in October”. Can trading be really this easy? Let’s have a look at the simple seasonal

This second article offers a different look at high inflation periods, which we already analyzed in What’s the Best Factor for High Inflation Periods? – Part I. In this second part, we look at factor performance during 10-year periods of high inflation. High Inflation Periods As we already

In the previous article we learnt how to setup a prototyping environment for algorithmic trading using Jupyter Notebooks. We used Yahoo data with Pandas DataReader. In this article we will be looking at another free market data provider Stooq. If you would like to follow along with the tutorial and

In the past couple of weeks, we have done a few event studies, analyzing events that in one way or another resemble what is happening in the world today. At the beginning of March, we examined Factor Performance in Cold War Crises, and at the end of March, we brought you an article analyzing Nuclear

Trend following and beta-neutral factor investing are considered diversifying strategies However, since 2009 their correlations to stocks moved in tandem Both strategies had related performance drivers and risk exposures INTRODUCTION Asset classes seem easy to distinguish at first. For example,

After five consecutive years of drought, Northern Californians welcomed the heavy rainfall in the winter of 2016-2017. By February, however, the rain had led many to worry about the integrity of the Lake Oroville Dam. Officials evacuated over 200,000 residents who lived downstream of the dam along

The growth of ETFs has been explosive (and we aren’t helping the matter via ETF Architect which facilitates low-cost high quality ETF white label services). At the end of 2020, there was roughly $5.4 trillion invested in ETFs in the United States, representing more than 25% of US market trading by

Datasets from real-world scenarios are important for building and testing machine learning models. You may just want to have some data to experiment with an algorithm. You may also want to evaluate your model by setting up a benchmark or determining its weaknesses using different sets of data.

Firm characteristics such as size, book-to-market ratio, profitability, and momentum have been found to be correlated with expected returns. The predictive power of these characteristics may stem from their industry component, their firm-specific component, or both. For example, while the study