The study emphasizes the importance of integrating machine learning with other tools for investment managers, pension-plan administrators, financial advisors, and independent analysts to help investors select active mutual funds with positive alpha. It also highlights the significance of fund

RSI, MACD, Stochastic, ROC, CCI, %b - technical indicators come in many shapes and sizes.[1] Their names suggest something very technical at play. Maybe even scientific. Yet, they are a polarizing tool. They generate strong, opposing opinions. Some traders value them with near religious zeal, while

Usually, regime detection is made with an HMM estimation over price returns or price return volatility. However, Chen and Tsang (2021) propose to use the Directional Change indicators as input for a HMM to detect regime shifts. They show that the HMM applied to the Directional Change indicators

This article explains how to build the two Python scripts you need to use premium data to create a custom data bundle using Zipline Reloaded. Step 1: Subscribe to premium data By now you should already have an account with Nasdaq Data Link. If not, head over to https://data.nasdaq.com and set one

The part of the attention of our own research from the last few months was a little skewed on the side of countries’ indices and their corresponding ETFs representing them, and we finally conclude our “trilogy” of investigation on the efficiency of these markets. Firstly, we analyzed

The timing of equity factor premiums has a strong allure for investors because academic research has found that factor premiums are both time-varying and dependent on the economic cycle. For example, Arnav Sheth and Tee Lim, authors of the December 2017 study “Fama-French Factors and Business

One of the hardest parts of trading options is picking the best strike price and expiration date for your strategy. Whether a simple covered call or more complex strangles, the key to success is constructing the position. But backtesting options is tough: There are millions of contracts that trade

Here in Australia, we’re right in the depths of the silly season. We indulge in long lunches, take days off work, and generally let our hair down. In that spirit, I thought I might have some fun punting shitcoins. (Maybe my definition of fun differs from yours, but let’s run with it). For the

Twas the night before Christmas, and all through the house.... OK I can't be bothered. It was quiet, ok? Not a creature was stirring... literally nothing was moving basically. And then a fat guy in a red suit squeezed through the chimney, which is basically breaking and entering, and found a

Wednesday is a Fed Day. Fed Days have historically shown an upside tendency. I have documented this tendency in great detail over the years. A higher close today would not be the most favorable Fed Day setup. A big reason for this is that it would mark a 20-day high close. Fed Day bullishness has

Managed futures / trend following is a valuable strategy to have in a portfolio, but it's also somewhat difficult to hold. The reason is that its positive performance tends to come in bursts, as opposed to steadily over time. This can (and does) lead to frustration as the investment in managed

Small-cap investing is intuitively appealing However, small-caps have underperformed in most markets Screening out low-quality small-caps has not helped significantly INTRODUCTION Investing means parting ways with your money, which is not something we tend to do lightly. The easiest way to get

In this article we will explore simulation of Brownian Motions, one of the most fundamental concepts in derivatives pricing. Brownian Motion is a mathematical model used to simulate the behaviour of asset prices for the purposes of pricing options contracts. A typical means of pricing such options

Here’s a backtest of Gary Antonacci’s DMSR (Dual Momentum Sector Rotation) strategy. The author is best known for his GEM (Global Equity Momentum) strategy, which he popularised in 2014, in his book « Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk »,

The paper, “Adaptive Asset Allocation: A Primer” by Adam Butler, Mike Philbrick, Rodrigo Gordillo, and David Varadi addresses flaws in the traditional application of Modern Portfolio Theory related to Strategic Asset Allocation. It shows that estimating return and (co)variance parameters over

Let’s talk about carry trades. First, what exactly is a carry trade? A carry trade is a trade that pays you to hold it. A position where, if nothing changes except the passing of time, you expect to make money. Let’s go through some examples. FX carry The classic example is the FX carry trade,

Abstract: One of the problems for investment funds is that success contains the seeds of destruction as cash inflows follow outperformance. In his seminal 2005 paper, “Five Myths of Active Portfolio Management,” Jonathan Berk suggested asking, “Who gets money to manage?” He answered that

Long-only trend following is a popular way to protect equity portfolios from huge drawdowns, and for several good reasons: 1) It has the advantage of behaving somewhat like insurance, or put options, in that you’re exposed to much of the upside and not much of the downside. 2) It doesn’t damage

I’ve been trading options contracts for more than 23 years. When I started out, I had to rely on expensive broker data feeds for real-time options data for trading and low-quality free data I scraped from websites for analysis. I spent countless hours reverse engineering the CBOE website for

XGBoost…!!!! Often considered a miraculous tool embraced by machine learning enthusiasts and competition champions, XGBoost was designed to enhance computational speed and optimise machine learning model’s performance. Let's proceed with XGBoost!!! We will cover the following things: Brief

In today’s newsletter, I’m going to show you how to forecast a time series of US unemployment data using decomposition. Time series decomposition is breaking down a single time series into different parts. Each part represents a pattern that you can try to model and predict. The patterns usually

Market efficiency, higher trading costs and higher expense ratios are not the only hurdles to successful active management (market timing and individual security selection). For taxable investors, the burden of higher taxes raises the hurdle.(1) From 2002 until now, S&P Dow Jones Indices has

Is it better to run your quant trading in the cloud or locally? In this article, I outline the pros and cons of each approach and explain why running locally is often better for research while running in the cloud is better for live trading. Don't assume the cloud is better It's common to

I would like to share my research and thoughts about stochastic volatility models and, in particular, about the log-normal stochastic volatility model that I have been developing in a series of papers (see introductory paper with Piotr Karasinski in 2012, the extension to include quadratic drift

Carry on commodity futures contains information on implicit subsidies, such as convenience yields and hedging premia. Its precision as a trading signal improves when incorporating adjustments for inflation, seasonal effects, and volatility. There is strong evidence for the predictive power of

Financial “wisdom” is said to be cyclical rather than cumulative, but that’s unfair. At least in the dominion of portfolio management and design, academics and money managers have made great strides in decoding Mr. Market’s cryptic signals over the past half century. The challenge, having

A common issue encountered in modern statistics involves the inversion of a matrix. For example, when your data is sick with multicollinearity your estimates for the regression coefficient can bounce all over the place. In finance we use the covariance matrix as an input for portfolio construction.

In my last post about the overnight anomaly, I created a trading signal based on the difference between recent overnight returns and recent intraday returns. I calculated the signal for various time frames (ranging from about a week to about a year), and I mentioned that I applied different

Momentum investors utilize different timeframes to identify high momentum equities: past 6, 9, 12 months as an example. Obviously, there is a significant degree of overlap in momentum stocks identified across various past time frames. However, there has been little research focused on understanding

Default plots often include a few or many bars of misleading data where a strategy may have zeros or NAs compared with the benchmark, for example where the strategy uses a moving average lookback period before generating a trade signal. There’s a simple way to start the plot after the strategy is

Many retail investors focus on generating what they consider to be income, leading to the popularity of dividend-focused strategies. To take advantage of this demand, investment firms have marketed covered call strategies that are purported to not only generate income but also reduce volatility.

In finance, the “overnight anomaly” is the name for the unusual phenomenon that overnight stock market returns are much higher than intraday returns. In a 2008 paper, “Return Differences between Trading and Non-trading Hours: Like Night and Day”, the authors break down the U.S. equity

Thanksgiving week has shown some strong seasonal tendencies over the years. I’ve documented this in years past on the blog. From a seasonal standpoint, Wednesday before Thanksgiving is one of the most bullish trading days of the year. The chart below shows performance from Tuesday’s close to

The Equal Risk Contribution (ERC) portfolio seeks to maximally diversify portfolio risk by equalising the risk contribution of each component. The intuition is as follows: Imagine we have a 3-asset portfolio Assets 1 and 2 are perfectly correlated (correlation of 1.0) Asset 3 is uncorrelated with

Imagine you’re picking from 1,000 money managers. If you test just one, there’s a 5% chance you might wrongly think they’re great. But test 10, and your error chance jumps to 40%. To keep your error rate at 5%, you need to control the “family-wise error rate.” One method is to set higher

Commodity futures carry is the annualized return that would arise if all prices remained unchanged. It reflects storage and funding costs, supply and demand imbalances, convenience yield, and hedging pressure. Convenience and hedging can give rise to an implicit subsidy, i.e., a non-standard risk

Causes of Deviations from a Real Earnings Yield Model of the Equity Premium Austin Murphy and Zeina N. Alsalman (Oakland University) October 2023 A market-based forecast of inflation added to equity earnings yields explains much of the variation in stock market returns over multi-year horizons.

“Si vis pacem, para bellum“, is an old Roman proverb translated to English as “If you want peace, prepare for war”, and it is the main idea behind the military policy of a lot of modern national states. In the current globally interconnected world, waging a real “hot war” has very often

Backtesting quant strategies in R requires paying attention to how we lag() our time series. Here be dragons. Lagging a time series relative to another is important in many areas, but we use it a lot in backtesting financial strategies. I’ve struggled with the logic of lag() several times, and

I was doing my usual reading when I came across a sector rotation strategy. I have seen lots of these strategies but this one had a different twist. The strategy was a momentum strategy but instead of buying the top three, it was buying the middle three. The article gave no reason other than it

In this post, I'll discuss in detail an arbitrage trade in SPY options that I'd been running for about a year. (Some of you may have read a short version of this in this twitter post). I'm no longer using it, but it's still a viable strategy to earn some extra money. To be clear,

How long will it take for the current level of inflation to subside? If history is any guide, it could take quite a while. Across 198 policy interest rate hikes of at least 1%, a decrease of 1% in inflation took 2 to 4 years (Havranke and Rusnak, 2013). The authors of this research article conduct

The Wiener-Khinchin theorem provides a clever way of building Gaussian processes for regression. I’ll show you this theorem in action with some Python code and how to use it to model a process. The Wiener-Khinchin theorem states that an autocovariance function of a weakly stationary process is a

Exponential weighting schemes can help navigate the trade-off between responsiveness and stability of the inherently noisy estimates we make from market data. We previously saw examples of calculating the exponentially weighted moving average of a vector, and estimating the correlation between SPY

In recent posts we added nATR as a vol measure, went short instead of flat, and significantly improved quant_rv’s performance over our in-sample test period 2006-2019. Now we look at the more recent record including the Covid Swoon and Inflation Coaster, and the years prior from the Roaring 90s

Attracted by the glamour and potential for lottery-like returns, global private equity (PE) assets under management reached $4.2 trillion in 2022. PE involves pooling capital to invest in private companies by providing venture capital (VC) to startups or by taking over and restructuring mature firms

In today’s newsletter, we’ll explore the SABR stochastic volatility model. It’s a very popular volatility model used by professionals for many types of derivatives. Today, we’ll look at how to calibrate the SABR parameters and use them to fit a volatility smile for equity options. Sound

In a 2011 paper, “To Trade or Not to Trade? Informed Trading with Short-Term Signals for Long-Term Investors,” Roni Israelov discusses how investors could use short-term trading signals that are normally too costly to trade, such as short-term reversal. He describes using the short-term signal

A big part of the job of the indie trader is data analysis. We’re always looking in the past data to validate (or more often, invalidate) a hypothesis about what might predict future returns. And one could argue that recent data is more useful than past data, since it may reflect the current state

Selling protection through credit default swaps is akin to writing put options on sovereign default. Together with tenuous market liquidity, this explains the negative skew and heavy fat tails of generic CDS (short protection or long credit) returns. Since default risk depends critically on