Covered call strategies aim to offer index-like returns with lower volatility and higher yields They have underperformed their benchmarks significantly over longer periods They are tools for market timing, but that is difficult to execute successfully INTRODUCTION JP Morgan has been a late-comer to

In time-series analysis we often examine signals for specific volatility patterns. The simplest one is a periodic or quasi-periodic modulation. In finance these modulations are of paramount importance allowing for signal decomposition, separating short-term variations from long-term trends.

Value as an investment strategy has long been popular in both academia and among practitioners and is supported by valuation theory, which provides a framework for identifying the drivers of expected returns: the prices investors pay and the expected future cash flows investors will receive.

In the research report Random rotations and multivariate normal simulation1, Robert Wedderburn introduced an algorithm to simulate i.i.d. samples from a multivariate normal (Gaussian) distribution when the desired sample mean vector and sample covariance matrix are known in advance2. Wedderburn

For v1.2.0 we take a step back from 1.1.0 to meet some of the new goal requirements right off the bat, and to play explore. In particular, we remove the code to test QQQ (or other ETFs) and related vars. Next we change code to make it easy to explore parameters (like the volatility threshold) to see

So we need some starter code, and some goals for where we’re going. The starter code comes from a blog post by Learning Machines back in April 2023. He’s got some great stuff on his blog (we’ll use some of his ideas here), so take a good look through his Quantitative Finance category, at

The Forex Market is the global marketplace where currencies are bought and sold. It is the largest and most liquid financial market in the world, with trillions of dollars traded daily. A currency pair is an asset composed of two currencies traded on the financial market. Its price represents the

This blog post serves as a summary and exploration of ~100 papers, providing insights into the key trends presented at ICML 2023. The papers can be categorized into several sub-fields, including Graph Neural Networks and Transformers, Large Language Models, Optimal Transport, Time Series Analysis,

All popular factors generated negative excess returns in 1H 2023 Small caps performed best, low-risk stocks worst Somewhat surprisingly, long-short multi-factor products produced positive returns INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10

Executing a live trading strategy can be a daunting task. From analyzing market data and identifying trading signals to deploying and monitoring trades in real-time, the process requires precision, speed, and accuracy. Fortunately, advancements in technology have paved the way for innovative

Effect J. González 28/06/2023 No Comments In a previous post we saw how avoiding being in the market during Earnings publications could be a zero-sum game in the long run. In this post our purpose is to study if it is possible to take advantage of the effect in the stock prices based on the

Since the discovery of the size, value, and momentum effects in the 1980s and 1990s, a plethora of other factors have been identified in the asset pricing literature, which led John Cochrane to coin the phrase “zoo of factors.” It has raised questions and led to research into how many factors

How does a company's profitability affect its stock returns? In this post, I use Alphalens, a Python library for analyzing alpha factors, to investigate the relationship between operating margin, a profitability ratio, and future returns. This is the second post in the fundamental factors

In the previous article we wrote a Python function which utilised the Polygon API to extract a month of minutely data for both a major (EURUSD) and exotic (MZXZAR) FX pair. We plotted the returns series and looked at some of the issues that can occur when working with this type of data. This article

Developments in the use of Large Language Models (LLM) have successfully demonstrated a set of applications across a number of “domains”, most of which deal with a very wide range of topics. While the experimentation has elicited lively participation from the public, the applications have been

The rapid evolution of language models has the potential to revolutionise financial analysis GPT outperformed when analyzing earnings calls, followed by Word2Vec and BERT However, overall models should be selected carefully as each has its pros and cons ABSTRACT This paper aims to evaluate the

In the previous article of the main series, we looked at robustly tracking our trading inventory and built an Inventory component for our Quant Infrastructure. In this article, we look at tracking and managing orders and build an OrderExecutor for this purpose. Orders require a different approach

Abstract: The “Intangible Value Factor” (IHML) can play an additive role in factor portfolios alongside the established market, size, value, quality, and momentum factors. This Six-Factor Model avoids the problematic “anti-innovation” bias of traditional factor portfolios and can be easily

The Realized Information Ratio and the Cross-Section of Expected Stock Returns Mehran Azimi (University of Massachusetts Boston) January 2023 This study investigates the predictability of asset returns with the information ratio and its specific variant, the Sharpe ratio. We find that the realized

The article aims to explore the possibility that changes in fundamentals play a role in the attenuation of stock market anomalies, offering an alternative explanation to the prevailing arbitrage-based explanation. Can the changes in fundamentals explain the attenuation of anomalies? Choi, Lewis and

So, thanks to my former boss, and head of direct indexing at BNY Mellon, Vijay Vaidyanathan, and his Coursera course, along with the usual assistance from chatGPT (I officially see it as a pseudo programming language), I have some more software for the Python community now released to my github. As

In crypto market, stablecoins are meant to maintain their constant value with respect to the underlying currency. At least in theory. The problem begins with an idea of stablecoin’s value to be stable or being stabilised over time. Different backup mechanisms are at work. For example, Tether

There is a huge number of ways how one can transform financial times-series in order to discover new information about changing price dynamics. We talk here about certain transformation that takes price time-series (or return-series) and transforms it into a new domain. Every solid textbook on

In Return StackingTM: Strategies for Overcoming a Low Return Environment, we advocated for the addition of managed futures to traditionally allocated portfolios. We argued that managed futures’ low empirical correlation to both equities and bonds and its historically positive average returns makes

There are several significant, well-documented benefits of index funds. In addition to outperforming a large majority of actively managed funds, they tend to have low fees, low turnover (resulting in low trading costs and high tax efficiency), broad diversification, high liquidity, and near-zero

Local-currency import growth is a widely underestimated and important indicator of trends in fixed-income markets. Its predictive power reflects its alignment with economic trends that matter for monetary policy: domestic demand, inflation, and effective currency dynamics. Empirical evidence

Preferred income funds offer exceptionally high yields However, the higher the yield, the lower the total return The diversification benefits of these funds were limited INTRODUCTION Although the job of a stock analyst is not easy, fixed-income analysts have it arguably harder. Sure, there might be

Many factor investors are familiar with “small-cap value investing,” which is a reasonable allocation for long-term investors who can tolerate a lot of volatility. Why are there so many small-cap value investors? Small-cap value investors have been told that the value premium is higher, on

When researching fundamental factors, analyzing alpha shouldn't be your first step. You can save time and spot issues early by starting with a basic exploration of your factor's distribution and statistical properties, a process known as exploratory data analysis (EDA). This post looks at

In my post Linking Impact in Divergence Attribution I explained the need to use linking algorithms in order to aggregate single-period returns. I ended my exposition by setting out the formula for adjusted returns using Andrew Frongello’s algorithms (arguably the ones with best qualities in the

As a portfolio manager, of a mutual or dedicated fund, you have to regularly report the performance of your fund on a specific time frame (monthly, quarterly, yearly, etc.). One of the common tools is the performance attribution analysis, which is a framework that allows to isolate the effect

Momentum strategies have been popular since the original Jagadeesh and Titman article was published in 1993. Variations on the strategies have employed calculating momentum on an individual and industry basis. For instance, in a 1999 study, Moskowitz and Grinblatt produced a positive and significant

This week is options expiration week. And we have known for a long time that opex is often a bullish week for the market. Interestingly, that seasonal tendency has not seemed to hold true since the COVID crash in 2020. Below is a look at performance of all opex weeks since 1984. Opex week

Ideally diversifying funds are uncorrelated and generate positive returns However, identifying such funds is more challenging than expected Creating a diversified portfolio requires thoughtful fund and asset class selection INTRODUCTION In our last research note (read Diversification versus

In this article we examine the research about how artificial intelligence influences stock returns by analyzing a measurement of firm-level AI exposures called Alness. AI Narrative and Stock Mispricing Arka Bandyopadhyay, Dat Mai, Kuntara Pukthuanthong SSRN, Working Paper A recent version of the

In his original 1991 article Investing in the 1990s1, John Bogle described a simple model to help investors setting reasonable expectations for long-term U.S. government bond returns. This model relies on what Bogle describes as the single most important factor in forecasting future total returns

While reading the January 2023 issue of Technical Analysis of Stocks & Commodities, I came across an article about Efficiency Ratio (ER) by Perry Kaufman. In the article, he discusses using ER to decide when to trade mean reversion strategy vs a trend following one. My curiosity on this was

Yet another experiment with ChatGPT-4: Active reading a semi-technical book. Chapter 1 Can a Combination of Treasuries and Equities Replace Credit in a Portfolio? What is the size of the corporate bond market? As of my knowledge cutoff in September 2021, I don’t have the most recent data on the

Financial markets are looking at a growing and broadening range of correlated time series for the operation of trading strategies. This increases the importance of latent factor models, i.e., methods that condense high-dimensional datasets into a low-dimensional group of factors that retain most of

Hedging and diversifying strategies have different objectives Downside betas can be used to differentiate these Alternative strategies have overtaken bonds as the most diversifying strategies INTRODUCTION In investing, some terms are used interchangeably, despite these having quite different

Science has been in a “replication crisis” for more than a decade. Researchers have discovered, over and over, that lots of findings in fields like psychology, sociology, medicine, and economics don’t hold up when other researchers try to replicate them. There are many interesting questions of

Negative exclusionary screening refers to an investment strategy in which socially controversial firms in particular sectors are excluded from the portfolio. The Global Sustainable Investment Review reports that, in 2020, more than $15 trillion (43% of total sustainable investments) were invested

Readers have asked for our take on “the single greatest predictor of future stock market returns”, aka the Aggregate Investor Allocation to Equities. This indicator was first shared by Philosophical Economics back in 2013, and recently resurrected by Portfolio Optimizer (two excellent sites you

Neither equity generalists nor sector specialists have generated alpha on average There is no consistency in alpha generation by either type of fund manager The most consistent alpha generators produced no alpha out-of-sample INTRODUCTION When I joined Citigroup as an analyst in their mergers &

Skewness is one of the less-known but practical measures from statistics that can be used in trading. It is defined as a measure of the asymmetry of the probability distribution of a random variable around its mean. Financial mathematics and most quantitative models assume some kind of symmetric

Another experiment with ChatGPT-4: Active reading a semi-technical book. This book by Michael Isichenko is probably the best I have read so far in this field. Let’s dive into it! You can (and should) buy this book. Chapter 1 Market Data Gautier’s Prompt: The author mentions in his book that

The past decade has witnessed a dramatic increase in spending on intangibles (not just research and development and advertising expenditures, but also expenses related to human capital) relative to tangible capital expenditures on plants and equipment. Given the change, it is not surprising that

We recently hosted our 6th Annual Democratize Quant Conference (sign up here for updates). This post is a recap of what we learned at the conference and some resources we can make available to the public. The agenda for the 2023 conference is outlined below: Date Time Topic Presenter Notes 5/18

Rotational trading is a strategy used by investors that involves purchasing top-performing assets and simultaneously selling the underperforming ones in their portfolio. It’s a great way to periodically manage a portfolio by holding winners and selling losers. Backtesting a rotational trading

This paper helps investors better understand drawdowns and recoveries, in terms of empirical facts, practical implications, and strategies for handling them. It shows the importance of the “interplay” between drawdowns and recoveries (which the authors call “submergence”), which should not