The biggest news this week is that Deribit is moving ahead with launching futures on their DVOL Bitcoin volatility index. Like with every new product launch, I am cautiously optimistic, but given that Deribit has ~ 90% market share in cryptocurrency options volume, I think that the product has a

It’s always fun to push the boundaries of technology and see what it can do. The AI chatbots are the hot topic of actual discussion in the quant blogosphere. So we have decided to test OpenAI’s ChatGPT abilities. Will we persuade it to become a data analyst for us? While we may not be there yet,

Simple equity ETFs often have exposures to other asset classes Gold stocks are bond proxies & growth stocks are short commodities Investors may have unintended bets in their portfolios INTRODUCTION ETFs used to be like surgical instruments. StateStreet’s SPY tracks the stocks of the S&P

Towards the end of last year, we ran a couple of free Zoom webinars on: The Basics of Edge Extraction – the “trader smarts” of getting an edge Data Analysis for Traders – an interactive research session. Here are the recordings: Basics of Edge Extraction Data analysis for Traders The colab

From the Volume and Mean Reversion post, a reader sent a suggestion to instead use the ratio of 10 day moving average of the Close times Volume divided by the 63-day moving average of the Close times Volume (CV10/63). I had not tried this before and wanted to see how well it would work. First Steps

US real GDP growth and US stock market returns were positively correlated since 1900 However, the correlation was not consistent and even turned negative The evidence of this relationship from other countries is mixed INTRODUCTION Switch on Bloomberg TV or CNBC at any time of the day, and there is a

How does ChatGPT work? What is behind deep fake images of celebrities? How do we deal with the lack of data in finance? All these issues have in common the same underlying concept; they are based on generative models. Generative models are algorithms that create new instances of data that mimic the

With more than $1.2 trillion under management in the U.S. as of mid-July 20221, investors are more and more using bond ETFs as building blocks in their asset allocation. One issue with such instruments, though, is that their price history dates back to at best 20021, which is problematic in some

In the last third installment, we will finish exploring the world of market timing strategies (see parts 1 & 2). We will focus on yield curve predictors and incorporate all three ideas (price-based, macro-economic, and yield curve predictors) into one final trading strategy that yields an annual

Since the development of the CAPM, academic research has attempted to find models that increase the explanatory power of the cross-section of stock returns. We moved from the single-factor CAPM (market beta) to the three-factor Fama-French model (adding size and value), to the Carhart four-factor

This is an old concept concerning the opening range. The idea is that the opening range often sets the day’s high or low within the first hour of cash equities trading (9:30 am - 10:30 am EST). Recently a trader on [Youtube] made the claim that you can know with 88% probability the high or low of

In this second installment in a series of three articles, we will continue with our goal to construct a market timing strategy that would sidestep the equity market during bear markets. A few days ago, we started with price-based market timing strategies. Today, we will focus on macroeconomic

dplyr 1.1.0 was a significant release that makes several common data operations more syntactically intuitive. The most significant changes relate to joins and grouping/aggregating operations. In this post we’ll look at the changes to joins. First, install and load the latest version of dplyr:

In this series of three articles, our goal is to construct a market timing strategy that would reliably sidestep the equity market during bear markets, thereby reducing market volatility and boosting risk-adjusted returns. We will build trading signals based on price-based indicators, macroeconomic

Are you looking for a way to quickly assess the sentiment of public companies through their tweets without previously training any ML models? The OpenAI API provides powerful, zero-shot classification capabilities so that text data can be classified into multiple categories – regardless of whether

A few select multi-strategy hedge funds generated outsized returns in 2022 However, the average fund lost money The average fund can be simply replicated via the S&P 500 & cash INTRODUCTION Citadel made $16 billion in profits in 2022, Millenium $8.0 billion, and Point 72 $2.4 billion. These

This blog is a follow-up to the series of posts Snorkel Credit Sentiment - Part 1 (May 2019) May the Fourth: VADER for Credit Sentiment? (May 2019) Experimenting with LIME - A tool for model-agnostic explanations of Machine Learning models (May 2019) Using LIME to ‘explain’ Snorkel Labeler

Implementing a successful trading strategy with code can be a challenging task. While some traders prefer to use basic trading rules and indicators, a more advanced approach involving predictive modeling may be necessary. In this tutorial, I will guide you through the process of training and

ETF Dividend Cycles Pekka Honkanen (University of Georgia), et al. February 2023 Exchange-traded funds (ETFs) collect approximately 7% of all U.S. corporate dividends, which they are required to redistribute to investors. How do the funds manage these dividend flows, and does such management have

AlphaVantage were founded in 2017 following the demise of the Yahoo Finance API. They offer OHLC data on 100,000+ securities, ETFs and mutual funds. Along with Forex, Crypto and Fundamental data, all accessible via their REST API. They offer free or premium membership which depend on the number API

We usually compute return attribution to know how much each asset contributes to portfolio return. This calculation is quite easy because return formula is linear and sub-additive. In that context, one can split the whole portfolio return in smaller parts corresponding to each asset. However,

The turbulence index, introduced in the previous blog post, is a measure of statistical unusualness of asset returns popularized by Kritzman and Li1. It provides a way to measure how much the behavior of a group of assets differs from its historical pattern. In this post, based on the paper Optimal

Fifty years ago, Princeton economics professor Burton Malkiel published A Random Walk Down Wall Street. He boldly asserted that a blindfolded chimpanzee throwing darts could pick a stock portfolio that would do as well as one created by many expert practitioners in the field. At the time, Malkiel

Shorting stocks with poor features was unattractive throughout most of the last decade Combining features would not have improved performance It only started working again in 2022 INTRODUCTION Playing the stock market should be easy. When the economy is booming, buy equities. When it’s

This research examines the potential of enhancing a standard momentum strategy using signals derived from Salience Theory (ST). The strategy presented here is to exclude stocks with extreme salience scores and then analyze the risk and return properties of the ST strategy. Salience theory and

We applied Corrective AI (Chan, 2022) to a trading model that takes advantage of the intraday seasonality of forex returns. Breedon and Ranaldo (2012) observed that foreign currencies depreciate vs. the US dollar during their local working hours and appreciate during the local working hours of the

Traditional value strategies use common valuation metrics, such as book-to-market (B/M), price-to-earnings (P/E), price-to-sales (P/S) or price-to-cash flow (P/CF), to establish a ratio between a market value and a fundamental anchor to assess the cheapness of a stock. The largest historical

This is a test of the latest tactical asset allocation strategy from Dr. Wouter Keller and JW Keuning and their paper: Dual and Canary Momentum with Rising Yields/Inflation: Hybrid Asset Allocation (HAA). Backtested results from 1971 follow. Results are net of transaction costs – see backtest

As those of you who follow me on the Elon Musk Daily News App will know, I received physical copies of my new book last week (exciting!). Global supply chains being what they are, you lot will have to wait until April to get your copies. Sorry. Anyway one of the themes I touch on in the book is the

In this article, the authors examine the research on the benefits of international diversification. Some argue that because equity markets generally crash simultaneously, there are no benefits to having equity diversification. The evidence from this paper rejects this hypothesis. Diversification

In this short blog post, we investigate whether a simple systematic market-neutral stat arb crypto book loads on the main components of a statistical risk model. from datetime import timedelta import pandas as pd from tqdm import tqdm import statsmodels.formula.api as smf def

This research note is a guest post from Rodolfo Martell, PhD, Head of Portfolio Strategy, of Pluribus Labs LLC, a San Francisco-based systematic active equity manager that is part of Exos Financial. SUMMARY Religious-themed ETFs have increased their AUM to roughly $1 billion 3 / 4 products

Financial literature has produced a long list of firm characteristics (referred to as factors) that provide information as to future stock returns, with the explanation for the casual relationship between the characteristics and returns being either risk- or behavioral-based. The traditional finance

The problem of missing financial data is widespread yet often overlooked. An interesting insight into the structure of missing financial data provides a novel research paper by authors Bryzgalova et al. (2022). Firstly, examining the dataset of the 45 most popular characteristics in asset pricing,

Unlike other derivatives markets, for commodity futures, there is a direct relation between economic activity and demand for the underlying assets. Data on industrial production and inventory build-ups indicate whether recent past demand for industrial commodities has been excessive or repressed.

Deutsche Bank Currency Volatility Index was developed to provide an implied volatility benchmark for major currency markets. The index is designed to represent investors’ expectation of future volatility, and is calculated as the weighted arithmetic average of the 3-month level of implied

Much like in 2008, managed futures as an investment strategy had an impressive year in 2022. With most traditional asset classes struggling to navigate the inflationary macroeconomic environment, managed futures has been drawing interest as a potential diversifier. Managed futures is a hedge fund

Over the last few years, a number of new market data providers have come online. They tend to have modern websites, broad coverage, and well-documented RESTful APIs. Their services are often priced very competitively – especially for personal use – and usually have generous free tiers. One such

Short-biased hedge funds provided negative S&P 500 beta until 2011 Thereafter returns became less negatively correlated, but worsened The strategy has generated limited diversification benefits for investors INTRODUCTION Running a hedge fund is tough, but some types are tougher to manage than

Bayesian statistics is a powerful field of mathematics that has wide-ranging applications in many fields, including finance, medical research, and information technology. It allows us to combine prior beliefs with evidence to obtain new posterior beliefs, thereby enabling us to make more informed

HAA aims to offer retail investors a tactical asset allocation strategy that is both balanced and aggressive at the same time. HAA’s hybrid approach combines traditional dual momentum with canary momentum which results in robust crash protection with low cash-fractions. HAA effectively selects

Suppose, in a national TV newscast, instead of citing data, analysis and predictions from major government agencies, the weatherperson displayed a chart of recent temperatures, noting “trends,” “waves” and “breakout patterns.” Most of us would not have confidence in such a dubious and

As seen in the table below, the four-year period November 2016-October 2020 could be described as a “dark winter” for value stocks. U.S. value stocks underperformed U.S. growth stocks by 16.81 percentage points per annum (20.35% vs. 3.54%), the largest historical drawdown for value stocks in the

Submergence = Drawdown Plus Recovery Dane Rook (Stanford University), et al. February 2023 Drawdowns and recoveries are often analyzed separately – yet doing so can leave investors with a distorted view of risk. Indeed, this problem is so commonplace that there’s no consistently-used term for

Cryptocurrencies are a high-risk and very speculative asset class that, from being used only by tech geeks worldwide, spread from small retail craziness of early adopters to institutional adoption and mainstream. Some claim it to be a world-changing concept with the utilization of blockchain

The financial industry is constantly searching for models that can help accurately predict the behavior of interest rates. In this article we will explore one of the most widely used models for this purpose, the Nelson-Siegel (NS) model. What is the Nelson-Siegel Model? The NS model is a yield curve

The S&P 500 has meaningful exposure to international markets Measuring geographical exposure can be done top-down or bottom-up However, both approaches have flaws INTRODUCTION Globalization has significantly improved our lives, although some countries like Germany have benefitted more than

Attention all traders! Are you looking for a cutting-edge way to dominate the markets and maximize your profits? Look no further than the power of ChatGPT and TradingView. By combining the advanced AI capabilities of ChatGPT with the unparalleled charting and analysis tools of TradingView, you can

In his TASC February 2023 article, John Ehlers proposed to use the average of open and close, rather than the close price, for technical indicators. The advantage is a certain amount of noise reduction. On intraday bars the open-close average is similar to an SMA(2). It makes the data a bit

The recorded history of modern financial markets and macroeconomic developments is limited. Hence, statistical analysis of macro trading factors often relies on panels, sets of time series across different currency areas. However, country experiences are not independent and subject to common