In this post, I will describe a measure of the homogeneity of a universe of assets, called the informativeness, introduced by Brockmeier et al.1 in their paper Quantifying the Informativeness of Similarity Measurements. After quickly going through the associated mathematics, I will present two

More specifically, the paper differentiates between: Traditional linear models (ordinary least squares regression and elastic net) and Machine learning methods that allow for non-linearities and interactions (tree-based models such gradient boosted regression trees and random forest and neural

The first lecture from the Experimental Design and Common Pitfalls of Machine Learning in Finance series addresses the four horsemen that present a barrier to adopting the scientific approach to machine learning in finance. The second lecture focuses on a protocol for backtesting and how to avoid

This article will show you how to access the CoinGecko API endpoints in Python to retrieve live cryptocurrency information. You will use the pycoingecko and the Python requests library to fetch data from CoinGecko API. The official CoinGecko API and pycoingecko libraries’ documentations lack

The word spurious refers to “outwardly similar or corresponding to something without having its genuine qualities.” Fake. While the meanings of spurious correlation and spurious regression are common knowledge nowadays, much less is understood about spurious factors. This post draws your

Alternatives with lower correlations to equities & bonds did not lead to greater diversification benefits Correlations often break when markets crash Better metrics are required to measure the diversification potential of alternatives INTRODUCTION Alternative investments accounted for $13

The research summarized here is built upon a documented risk management strategy applied to factor investing (Barroso and Santa-Clara, 2015; Moreira and Muir, 2017). The idea was to overlay a scaled volatility measure designed to change risk exposures and hopefully produce higher Sharpe ratios. That

It goes without saying that 2022 has been a difficult year across markets. Investors have had to contend with an inflationary bear market for which the traditional playbook has proven woefully inadequate. NASDAQ and high yield debt, the darlings of yesteryear, have fallen from grace with few

The size effect was first documented by Rolf Banz in his 1981 paper “The Relationship Between Return and Market Value of Common Stocks,” which was published in the Journal of Financial Economics. After the 1992 publication of Eugene Fama and Kenneth French’s paper “The Cross-Section of

Preference for dividends and stock returns around the world Allaudeen Hameed (National University of Singapore), et al. November 2022 We find strong international evidence favoring dividend payout as a salient stock characteristic affecting expected stock returns. We find that dividend-paying stocks

In the previous article we created a virtual environment and installed QSTrader on all our secondary nodes. We then carried out a test of the sixty forty strategy across all secondary nodes to make sure our installation had been successful. Now that we have successfully paralellised QSTrader we can

Overall, I have had very little success integrating volume into any of my strategies. Either volume would have no predictive value or if it did, using it reduced the number of trades too much to be worthwhile. It has been a long while since I have looked into this and I had some new ideas. The Rules

Probabilistic forecasts are a more comprehensive way to predict future events compared to point forecasts. Probabilistic forecasts involve creating a model that predicts the entire probability distribution for a given future period, providing insight into all likely outcomes. This allows for the

In previous posts, we have seen the basic RL algorithm, Deep Q learning (DQN). We have also seen it applied, using Neural Networks as the Agent, to an investment strategy. We finally even used it for a cryptocurrency investment strategy. This time, we will implement a slightly more advanced

Spikes in inflation and fear of stagflation prompted this study which answers the following question: 1. How do risk premiums and investment strategies behave across inflationary regimes like periods of high inflation, deflation, or stagflation? What are the Academic Insights? By utilizing the

Alternative products with uncorrelated returns do not necessarily provide diversification benefits Out of 10 alternative ETFs, only one product improved the Sharpe ratio of a 60/40 portfolio Correlations should be regarded carefully in fund selection INTRODUCTION Given the demise of the traditional

In quantitative finance, the Volatility of Volatility (also referred to as Vol-of-Vol or VoV) is an important parameter for pricing various derivative products (e.g. Volatility Dispersion Swaps) and its correct estimation is frequently desired. VoV is usually a single number treated an an input

The main theme of these days in the crypto world is unmistakenly clear, it’s the mayhem connected with the collapse of the FTX empire, insolvencies of various lenders, and questions about underlying holdings in GBTC OTC ETF and reserves of exchanges and Tether (or other stablecoins as well). With

Trend following (time series momentum) is one of the most well-documented and well-known factors in investing, demonstrating persistence, pervasiveness, robustness, and implementability (survives transaction costs). Lesser well-known is relative sentiment—an indicator that measures the positions,

Based on previous article Structural Entropy, this article attempts to test the performance of a long short strategy on US sectors using structural entropy. Ideally it should use liquid US sector futures but since data is unavailable (not for free), it uses ETFs as proxy. The assumption in previous

Continuing on trying to fight disinformation about VIX. Everyone knows that VIX index the square root of the expected 30-day variance, and if we drop mathematical precision - 30 day expected volatility of S&P index. Scott Bauer, on CBO's website - "the VIX Index tells us the level of

This tutorial explains how to call Binance API endpoints in Python using the python-binance library and the Python requests function. The Binance API provides extensive documentation on how to call its various endpoints. Furthermore, multiple online blogs explain how to call the Binance API using a

Strategies can be copied by recreating them from scratch or using factor exposures CTAs can be replicated via factor exposure analysis by utilizing only 4 asset classes Not a perfect replication, but surprisingly good given the limited input INTRODUCTION Our two most recent research articles focused

Commodity futures returns are correlated across many different raw materials and products. Research has identified various types of factors behind this commonality: [i] macroeconomic changes, [ii] financial market trends, and [iii] shifts in general uncertainty. A new paper proposes to estimate the

CTAs pursue trends across asset classes, regardless if long or short 2022 is exceptional as CTAs have more short positions than during the GFC No single long bond index position remains, fixed income is one big short INTRODUCTION In our last research article (read Creating a CTA from Scratch – I)

Several studies show momentum works in global equities, corporate bonds, currencies, and commodities. This paper asks the following research question: Does momentum work within option markets? What are the Academic Insights? By focusing on the returns of delta-neutral straddles (from 1996 to 2019)

For every quantity to be estimated (estimand), there’s a plethora of ways to estimate it (estimators). This raises the question of what properties we should be looking for so as to make a sensible choice. Often highlighted as one of such properties is unbiasedness, which we will discuss below with

Academic research on trend-following investing has almost exclusively been focused on testing the profitability of various trading rules. Most of these rules are based on moving averages of past prices. The most popular is the Simple Moving Average (SMA). Less commonly used types of moving averages

The empirical research on the ability of actively managed funds, including such studies as the 2002 paper “Mutual Fund Performance: An Empirical Decomposition into Stock-Picking Talent, Style, Transactions Costs, and Expenses” by Russ Wermers, has found that they do have the ability to identify

The following article is a short distillation of the research paper Leveraging the Technical Competence of a Stock for the Purpose of Trading written by Rishabh Gupta. The author spent a summer internship at Quantpedia, investigating the Patent-to-Market (PTM) ratio developed by Jiaping Qiu, Kevin

Here is the first episode in a new series of podcasts entitled Break into Finance. We will be talking about what it takes to launch your career in finance, what does it mean to become a quant, and where to start. Any questions welcomed!

The Unscented Kalman Filter allows to deal with nonlinear systems in a different way than the Extended Kalman Filter. Find how it works in this post. This is not the first time we talk about the Kalman Filter (and it probably won’t be the last); I recommend you check this and this posts to

There has been a very interesting discussion on twitter, relating to some stuff said by Sam Bankman-Fried (SBF), who at the time of writing has just completely vaporized billions of dollars in record time via the medium of his crypto exchange FTX, and provided a useful example to future school

We have previously mentioned that not all models (such as CAPM) that work well for developed markets (DM, such as the U.S. and Europe) are suited to be applicable in other world parts. The following article is a short analysis that shows that investing in Emerging Markets (EM) has its peculiarities.

CTAs have become popular again given their positive returns in 2022 However, they are typically difficult to grasp given their ever-changing portfolios Building a CTA from scratch is not complicated and reduces the opaqueness INTRODUCTION 2022 has been a long year of disappointments for investors.

This post is the second and final portion of the review on momentum published on Momentum literature. The seminal article on momentum was published by Jegadeesh and Titman in 1993. Although the Jegadeesh article foreshadowed much of the research on cross-sectional and time series momentum at the

In previous articles, we discussed the ideas behind portfolio replication with market factors and presented Quantpedia’s approach to Multi-Factor Regression. Additionally, we examined the methods of market factor data extension used in construction of our historic factor universe we utilize to

“The intelligent investor is a realist who sells to optimists and buys from pessimists.” - Benjamin Graham Sentiment Trading strategies work on market sentiment and the trends around them. The strategies are often determined by the price and value of an asset that may fluctuate. Market

Risk-parity positioning in equity and (fixed income) duration has been a popular and successful investment strategy in past decades. However, part of that success is owed to a supportive macro environment, with accommodative refinancing conditions and slow, disinflationary, or even deflationary

QuantConnect, a quantitative backtesting and trading platform serving mostly retail traders, recently announced a crowdfunding campaign seeking to raise money from its community of users. The company's associated regulatory disclosures (required by the SEC for equity crowdfunding offerings)

At its most basic level, factor-based investing is simply about defining, and then systematically following, a set of rules that produce diversified portfolios. An example of factor-based investing is a value strategy, buying cheap (low valuation) assets and selling expensive (high valuation)

Systematic trading strategies have the unfortunate habit of exhibiting worse performances in real-life than in backtests, partially due to backtest overfitting1. Monitoring their behavior once they are deployed in production is then very important to be able to detect as early as possible any

Many investors are looking for the holy grail of investing. They all want a magic formula that tells them which stocks to buy, and which ones to sell. But experienced investors know that there is no such a thing. I was convinced of it… until I discovered the MOIC formula. MOIC Multiple on Invested

Data is often messy and rarely in perfect shape. This is especially true if the data comes from many different sources and the specifications are loosely defined. If you have access to data that is in great shape, it’s probably because someone else did the dirty work of validating it, cleaning it

In this post we will take a closer look at the expected return that is often stated for investments like stocks and other financial assets, or for certain outcomes in gambling. The point we want to convey is that the expected return is only valid for one period or a single “iteration” (say, one

What are the Research Questions? Several studies reveal variables that predict cross-sectional differences in stock returns but mainly rely on a sample of U.S. stocks, mostly covering the post-1963 period. These studies are often criticized for potential data mining issues since the database never

Algorithmic Trading is seeing a rapid expansion of the application of artificial intelligence (AI) and machine learning (ML). These technological developments have completely transformed Algo trading. Making informed decisions requires carefully analyzing both current and historical market data. In

The S&P 500 increased during two of the three largest wars of the United States Value, size, and momentum factors had positive returns during WW II The top and worst-performing industries during WW II were diverse INTRODUCTION Before 2020, the threat of a global pandemic shutting down the world

There are basically two types of investors, those that are risk averse and, thus, both demand risk premiums for taking risk and diversify their holdings, and those who are risk seekers who have a preference for positively skewed (lottery-like) returns which leads them to speculate and concentrate