Introducing the first book ever generated by an artificial intelligence on the subject of using machine learning for quantitative trading: “From Data to Trade: A Quantitative Approach to Machine Learning”! This groundbreaking work offers a unique perspective on the use of machine learning in the

As per usual this point in time, I check my blog’s traffic-analytics to see which were the most popular pieces last year. Without further ado.. First: Correlation and Correlation Structure (6) – Distance Correlation (08:33 minutes average time on page) Second: Similarity and Dissimilarity

2022 is the best year for factor investing over the last decade Value generated the best and size the worst return in 2022 Despite the strong returns, investors remain cautious on factor investing INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10

In this article about asset pricing theory, we examine the research on the impact of technological advances that displace human labor in favor of machine capital to asset pricing. Automation and the displacement of labor by capita: Asset pricing theory and empirical evidence Jiˇrí Knesl Journal of

In the last article, we discussed one advantage of probabilistic forecasts over point forecasts - namely, handling time-to-exceedance problems. In this post, we will examine another limitation of point forecasts: Higher order statistical properties. The ideas will be very familiar to those with a

The relprice Index in the Performance Data table shows the price of the stock relative to the S&P 500 index over a specified period. Let’s look at the median relPrice for all stocks that are currently members of the S&P500 index, eliminating any for which the relevant Performance Data is

Generally speaking, one of the major attractions of working in the equities space is that the large number of available securities opens up a much wider range of opportunities for the quantitative researcher than for, say, futures markets. The focus in equities tends to be on portfolio strategies

There are two simple ways to enhance FX carry strategies with economic information. The first increases or reduces the carry signal depending on whether relevant economic indicators reinforce or contradict its direction. The output can be called “modified carry”. It is a gentle adjustment that

The past decade has seen a dramatic growth in sustainable investing—applying environmental, social and governance (ESG) criteria to investment strategies. Investments considered environmentally friendly are often referred to as “green,” while “brown” denotes the opposite. Important

We have already showed How to extend history of any asset, portfolio or strategy to a 100-year long history. We’ve done this by introducing Quantpedia’s Multi-Factor Regression Model, which aims to replicate any portfolio and recreate what its 100-year history would have looked like. The model

We kicked off a new series of go-to solutions for #Cryptocurrencies with #Python. Subscribe to our YouTube channel for regular updates!

Traditional measures of geopolitical risk have been primarily qualitative. In this article, the authors describe and analyze not just new, but novel measures including textual analysis of news and expert reports, novel econometric methods and machine learning applications for measuring geopolitical

The latest inversion of the Treasury yield curve has been a popular topic of conversation among market pundits and participants alike. In this blog, we explain what a curve inversion is, why it is important, and what (if any) bearing it has on bond prices going forward. The 2s10s Yield Curve The

“If we knew what it was we were doing, it would not be called research, would it?” – Albert Einstein December 2022. Reading Time: 10 Minutes. Author: Finominal RESEARCH COMPENDIUM 2022 In 2022, we published more than 50 research articles on a wide range of investing topics including CTA

Multi-factor, long-short portfolios have provided significant portfolio diversification benefits by adding unique sources of risks that have historically produced premiums that meet the criteria Andrew Berkin and I established in our book “Your Complete Guide to Factor-Based Investing”—the

In the previous article I wrote about using VIX / MOVE index ratio as an indicator for SPX returns. Here is the google sheet for your reference and experiments. The ratio itself is very stable - in fact 11 years ago I wrote that VIX = EXP(-1.84+1.06*LN(MOVE)) As you can see the relationship has held

In finance, the performance of an asset is often quantified by alpha (the excess returns above a benchmark return) and beta (the volatility or risk of the asset relative to a benchmark). These metrics are estimated from historical data and are often based on only short track records. Even if a long

What’s the performance of a balanced portfolio during rising rates? How does it behave when inflation is high? What about a combination of these market states? And how do trend-following strategies fare in such an environment? These and even more questions we will attempt to resolve in our

This article explains how to call the Alpha Vantage API to retrieve stock market data in a Python application using the Python alpha_vantage library and the Python requests module. The documentation for the Python alpha_vantage client library is limited. It isn’t easy to understand the mapping

I’ve heard people saying recently that the typical 2nd half of December bullish tendency is unlikely to unfold this year. The theories suggest that the market is often up on the year. And people and institutions flush with profits tend to push it higher as the New Year approaches. There is also

Pastor, Stambaugh, and Taylor (2015) and Zhu (2018) provide significant evidence of decreasing returns to scale (DRS) at both the fund and industry levels. The authors examine the robustness of their inferences after Adams, Hayunga, and Mansi (2021) critique the above two studies. What are the

This is a test of a novel trend-following strategy from the paper Optimal Trend Following Rules in Two-State Regime-Switching Models by Valeriy Zakamulin and Javier Giner. These results aren’t as eye catching as many we track, but the paper contributes some important ideas to the study of tactical

I recently asked on LinkedIn about advice and opinions on infrastructure for collecting, storing, processing, and storing back derived data (features, signals) for some simple mid freq / stat arb trading strategies. I did not expect to receive so much feedback about infrastructure for trading data

MOVE index (Merrill Lynch Option Volatility Estimate) was developed by Merrill Lynch to measure implied volatility of US Treasury markets. ML became a part of Bank of America in 2008, and then indexes were sold to ICE in 2019, so now the index is called "ICE BofAML MOVE Index" The index is

Which assets perform best when rates are rising, and inflation is high? And what happens if rates are still rising but inflation is already falling? And what’s the impact of the business cycle? These are the questions that everyone is currently trying to answer. Today, we will start a longer

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)