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

Few people are brave enough to put their entire net worth into a CTA fund or home grown trend following strategy (my fellow co-host on the TTU podcast, Jerry Parker, being an honorable exception with his 'Trend following plus nothing' portfolio allocation strategy). Most people have

Would you like to see the performance of your portfolio 100 years back in history? Do you want to analyze the risk of your strategy under 100 years of real historical scenarios? All of these, and much more, will be soon (in a few days) available for Quantpedia Pro subscribers. How? We will explain

n this article, the author examines the research published over the last 30 years on momentum and its theoretical credibility. One of the original momentum articles was published by Jegadeesh and Titman in 1993, and is considered the seminal work on the topic. The research review contained in this

Yesterday I found another piece of ignorance on Medium: Stop Watching The VIX, Just Make Your Own tl;dr : Just use ATM straddles. This is of course not correct. As I have written before on this blog that (skipping mathematical rigor) the value of ATM straddle is or about 80% of the expected

The VIX currently trades within its top quartile since 1990 Using volatility to time equity allocations is a widely used strategy However, it is challenging to pursue this over the long-term INTRODUCTION The One Ring from J.R.R. Tolkien’s Lord of the Rings saga is a plain gold ring unless it is

Candlesticks are a common way to represent price and volume of an asset over a period of time. There are various common types of bars such as time, volume, tick bars, hieken-ashi, renko to name a few. There is a lot of information about the implementations of these on the internet so their details

This article discusses the academic research about the Momentum Gap and the role that its predictive potential may have in reducing momentum crashes, hence possibly improving performance. In our book “Your Complete Guide to Factor-Based Investing,” Andrew Berkin and I presented the evidence

A recent paper suggests identifying financial market regimes through the correlations of asset class returns. The basic idea is to calculate correlation matrixes for sliding time windows and then estimate pairwise similarities. This gives a matrix of similarity across time. One can then perform

In this article, the author examines several important questions related to asynchronous trading, or the variation in trading frequency that occurs when trading stocks or other assets. Timo Wiedemann, University of Muenster (Germany) The newest version of the paper can be found here. What are the

A common question I get is whether mean reversion is still working. My response is I am still trading a mean reversion strategy but the edges seem to get smaller. Over the year I have investigated this. I was asked again recently and wanted to investigate again. Here are the results of my 2022

What does live algorithmic trading on the Cloud mean? Rerequisite – Basic Guide What are the pros of deploying your trading strategies to the Cloud? What are the cons of deploying your trading strategies to the Cloud? What is the Cloud Service? What is the Cloud used for? What cloud providers are

In this article we’ll be discussing a fast way of logging in Rust and its application to high frequency trading. The code presented here solves two problems, one is well known, the latter less so. It is a imperative to avoid using IO operations within the strategy thread, but logging operations

“Hedge funds” were pioneered some 70 years ago by Australian financier Alfred Winslow Jones. His idea was to combine a “long” position (i.e., one that profits if the securities go up in price), typically a set of growth stocks, with a “short” position (i.e., one that profits if the

Thematic products underperform the stock market on average The exposure to the momentum factor was low to negative recently Systematic performance chasing beats performance chasing with a narrative INTRODUCTION Space: the final frontier. Where no man has gone before…. Well, wealthy folks can now

The rise of stock indexing has raised concerns that index investing distorts stock prices—indexers are free riders who rely on prices without contributing to price discovery, thus reducing price efficiency. Byung Ahn and Panos Patatoukas, authors of the study “Identifying the Effect of Stock

Announcing that MlFinLab is fully integrated into the powerful backtesting and execution platform of QuantConnect! At the start of 2022, we set out to improve the user experience across all of our products and to improve the accessibility of our libraries. This meant integrations into platforms that

The estimation of empirical correlation matrices in finance is known to be affected by noise, in the form of measurement error, due in part to the short length of the time series of asset returns typically used in their computation1. Worse, large empirical correlation matrices have been shown to be

In this post we look at what major asset classes have proven to be the best defensive choice in months when the market has fallen over the last 50+ years. We’ll look at multiple government and corporate bond assets, diversified commodities, gold and the US dollar. The results? As expected, a mixed

The recent surge in global inflation sent shock waves across financial markets and affected the complicated relationship between stocks and bonds. Today, we would like to present you with a review of two interesting papers, which provide both a deep and easy-to-understand examination of the

The blog has previously addressed interest rates in a post that splits the yield rate curve into three relevant components. This time this post tries to identify the influence of interest rates on fixed income assets by using the Granger causality test. Interest rates obviously have a strong impact

A stock index is just a list of stocks. But an index is a special list because investors use it to make investing decisions. An index is constructed via rules about stocks to include, how much to include, and when to include (or remove it). Finding this data, especially for more obscure indexes, can