As far back as 1976, with the publication of Fischer Black’s “Studies of Stock Price Volatility Changes” financial economists have known that volatility and returns are negatively correlated. This relationship results in the tendency to produce negative equity returns in times of high

Serenity's production server is a Linux box sitting next to my desk which runs Ubuntu's microk8s Kubernetes distribution. It runs 24x7 collecting tick data from several cryptocurrency exchanges and once a day uploads the tick data to Azure Blob Storage. This presents a problem: this highly

My last post on Different ranking methods for a monthly S&P500 Stock Rotation Strategy generated lots of emails on other ideas to try. Below are the results of these ideas Base Rules Backtest from 1/1/2007-12/31/2020. Buy It is the last trading day of the month Stock is a member of the

Who has never heard about cryptocurrencies: Bitcoin, Ethereum, Cardano, or even the latest ones, such as Shiba or Safemoon? The investors are rapidly increasing their positions in those assets, although investing in them is usually a pain in the neck. These assets have a high volatility and their

Quant trader Ernie Chan from PredictNow.ai joins us to discuss how to predict the profitability of trades using machine learning, including: Unconditional probability and the problem with win% in backtest reports, Why “conditional probability” is much more useful for a trader and how to apply

This is an independent test of the tactical strategy “All-Weather Quad Momentum” (AWQM) from Todd Tresidder of FinancialMentor.com. Many of our members came to us from Financial Mentor, so it’s fitting that we add a strategy to our platform that demonstrates his approach to asset allocation.

We again present a short article as an insight into the methodology of the Quantpedia Pro report – this time for the Markowitz Portfolio Optimization. As usually, Quantpedia Pro allows the optimization of model portfolios built from the passive market factors (commodities, equities, fixed income,

This study pulls together several threads in the academic literature: (1) the persistence of hedge fund outperformance; (2) the apparent use of time-varying beta exposures by hedge funds, where betas are predicated on conditions such as leverage, carry trade, major events and conditions in the

This post will introduce the first part (of multiple) where we build up a personal finance model to help simulate future time periods based on certain chosen input variables. We will input variables such as our current investable asset base, our annual salary, expected monthly inflows and outflows

Mid-cap stocks are less popular than small or large caps In the US, they only outperformed in one out of 10 decades Globally, they have done better, creating a conundrum for investors INTRODUCTION A few weeks ago, David Stevenson, a well-known journalist and entrepreneur, asked me about my view on

Empirical evidence suggests that investors pay less attention to macroeconomic news when market sentiment is positive. Market responses to economic data surprises have historically been muted in high sentiment periods. Behavioral research supports the idea that investors prefer heuristic

They say that a journey of thousand miles commences with a single step. So, here you are, firm in your own resolutions or hesitating where to go. Graduated from a university or standing and trembling about next move in your life. Fired from one job or looking for another opportunity to seize.

My October 29, 2020, article for Alpha Architect examined the research on the profitability factor. I then reviewed the findings of the June 2020 study “On the Conjoint Nature of Value and Profitability,” which analyzed how combining the profitability factor with the value factor— tilting the

SAVE 200 GBP WITH CODE CM485_QC200. Financial firms must strike the right balance when developing machine learning so that their models are intelligent enough to provide useful information whilst also being simple enough to produce signals that are understood and explainable. Attending this premier

The concept of entropy has many useful applications in finance such as measuring risk, uncertainty, or noise in a signal. In this post we will focus on transfer entropy, a useful tool for causal inference between financial time series. What is entropy? Entropy in general represents the uncertainty,

This is part one of a series of posts about using optimisation to get the best possible portfolio given a relatively small amount of capital. In this short post I present the idea, and discuss some issues that I need to resolve. It's a bit of a stream of conciousness! It's less of a blog

Book to Market (B/M) has been a prominent indicator used to construct "value" tilted portfolios. The love affair with B/M started with Graham and Dodd (1934), but became the gold standard after Fama and French (1992). Historically, B/M was a reasonable ratio to express the value factor and

Liquid alternative mutual funds only captured 10% of the market share from hedge funds The alpha generated since 2013 was essentially zero Long-short equity funds can be replicated simply via market beta + cash INTRODUCTION One of the most perplexing questions in the investment industry is why

This time is different. --John Templeton "This time is different," is a sentiment that leads many investors to stray from using data analysis in their investment decision process and more towards discretionary judgment. The logic as to why data analysis techniques may not apply to

In the business of performance measurement, a recurrent task is the breakdown of a stream of returns into meaningful contributions from different factors, in order to identify the driving financial forces or sources of risk. Eventually, these daily contributions have to be aggregated to explain the

EM equities are highly correlated to US stocks & high yield bonds, limiting diversification benefits They outperform primarily when the USD is depreciating, making it a currency play The largest MSCI EM index members will experience 50% population declines INTRODUCTION Seeing latex slowly

In 2015, 197 nations signed onto the Paris Agreement and committed to limiting global warming to less than 2 degrees C above preindustrial levels. Although the arguments are compelling, the drive to manage carbon risk presents quite a challenge for individual investors and portfolio managers.

Momentum is the tendency for assets that have performed well (poorly) in the recent past to continue to perform well (poorly) in the future, at least for a short period of time. 1 In 1997, Mark Carhart, in his study “On Persistence in Mutual Fund Performance,” was the first to use a momentum

Standard equity factors are autocorrelated. Hence, it is not surprising that factor strategies have also displayed momentum: past returns have historically predicted future returns. Indeed, factor momentum seems to explain all return momentum in individual stocks and across industries. Momentum has

I've long been a critic of the sort of people who think that one should run a different trading system for each instrument that you trade. It is the sort of thing that makes intuitive sense; surely the S&P 500 is a completely different animal to the Corn future? And that's probably

Using Machine Learning and Deep Learning models to solve scientific problems of greater or lesser complexity is a challenge. Referring to neural networks, on the one hand, simple networks with too little capacity will not learn the problem well producing a model that underfits the data. On the other

Since my previous post, on Matrix Profile (MP), I have been doing a lot of online reading about MP and going back to various source papers and code that are available at the UCR Matrix Profile page. I have been doing this because, despite my initial enthusiasm, the R tsmp package didn't turn

When it comes to Value and Momentum investing we often get asked the following set of questions: Should I use value and momentum, in one screen, to form a single portfolio of stocks? ("Blended", "combined", or "integrated") Or should I focus on the value and momentum

Earlier this month, I reviewed a model that estimates a theoretical level for the world’s most-important interest rate: the 10-year Treasury yield. In today’s follow-up, let’s consider a second model for additional context. The goal in this series is to select several models with an eye on

A few winners generate most of the venture capital returns Given this asymmetrical return distribution, portfolios should be constructed equally Missing the winners is simply too risky INTRODUCTION 2020 turned out to be a record year for the venture capital industry, despite the global pandemic.

Applying Machine Learning in Statistical Arbitrage In this series of posts I want to focus on applications of machine learning in stat arb and pairs trading, including genetic algorithms, deep neural networks and reinforcement learning. Pair Selection Let’s begin with the subject of pairs

The online conference for quants and algo-traders. Hear from the best and brightest minds in algo-trading. Join like-minded pros and gain hands-on, actionable information from the best and brightest minds in algo-trading

It’s been over a month since our last post and for that we must apologize. We endeavor to be more prolific, but sometimes work and life get in the way. On the work front, let’s just say we won’t have to spend as much time selling encyclopedias door-to-door, which should free up more time to

Pairs trading is popular due to its simple approach and effectiveness. At the heart of the strategy is how the prices of two assets diverge and converge over time. Pairs trading algorithms profit from betting on the fact that spread deviations return to their mean. One of the more notable hedge

So the crypto markets on May 19th were fun!? If you have been a part of these markets for any time, this volatility is not that surprising. That said it is still pretty amazing that the price can drop 30% in a single day. This is maybe more surprising since it is to the backdrop of an increase in

The value spread is the difference between the value signal in the long versus the short portfolio. This isn’t the first time we have hit on this topic. Wes and I have done several posts on the subject: Timing Value and Momentum with Valuation-Spreads The Returns to Value Strategies When Valuation

I examine the performance records of performance of Ben Graham's well-known disciples: Walter Schloss, Tom Knapp, Warren Buffett, Bill Ruane, Charlie Munger, Rick Guerin, and Stan Perlmeter. The research question I seek to address is the following: Do the academic "value" and

The previous article dealt with John Ehlers’ AM and FM demodulating technology for separating signal and noise in price curves. In the S&C June issue he described a practical example. Applying his FM demodulator makes a strategy noticeably more robust – at least with parameter optimization.

The relationship among ESG ratings from third-party providers has historically produced conflicting results. Differences in sourced information and weighting schemes have produced low correlations between ratings and as a result, have handicapped the efforts to understand the relationship between

The CSI 300 is a capitalization-weighted stock market index that tracks the top 300 stocks listed on the two main stock exchanges in mainland China. In April 2020, South China Morning Post reported that “the 120-day correlation between the CSI 300 Index and the S&P 500 index recently rose to

We track more than 60 Tactical Asset Allocation strategies, which members can combine together into custom portfolios. To make creating those portfolios easier, we provide an optimizer showing the best performing combinations of strategies based on the member’s investment objective, such as

In the 4/12/19 blog I showed a study about US tax day (normally April 15th). The reason tax day may be important is that it is the last day that people can make IRA contributions to count for the previous tax year. This can create a last-minute rush and you will often have an inflow of funds heading

Managed futures strategies aim to exploit short- or long-term trends Short-term trend followers are often seen as offering better stock market crash protection characteristics Our analysis highlights that the differences are marginal INTRODUCTION Aesop’s famous story of the race between the

Long-Horizon Stock Returns Are Positively Skewed Adam Farago and Erik Hjalmarsson (University of Gothenburg) April 28, 2021 At long horizons, multiplicative compounding induces strong-to-extreme positive skewness into stock returns; the magnitude of the effect is primarily determined by

Since the late 1990s, the negative price correlation of equity and high-grade bonds has reduced the volatility of balanced portfolios and boosted Sharpe ratios of leveraged “long-long” equity-bond strategies. However, this correlation is not structurally stable. Over the past 150 years,

In the previous posts I described an Reinforcement Learning approach to “Learning the Exit” part 1, part 2. My initial conclusions there have been: reward smoothing (with the labeler) leads to more robust results than a reward on position exit without smoothing the learning process struggled and

I love programming! There is something really satisfying about solving a complicated problem concisely. That said I see programming languages as a tool to solve a problem rather than purely coding for coding sake. I have used a lot of programming languages over the last 20 years namely Java, R,

In Part 1, we defined fixed income factors. But factors alone will not solve each investor’s problem. Below, we extend the discussion by walking through a case study that shows how an asset allocator might use factors to solve a common problem: how to invest in a low yield environment given the

Getting historical intraday financial data can be a pain, especially for non-US markets. If you have deep pockets you can simply buy the data you need, but for retail investors the cost is prohibitive. If you want historical transaction-level data for the Brazilian stock market, for instance,

This is a snippet from a strategy backtesting system that I am currently building in Mathematica. One of the challenges when building systems in WL is to avoid looping wherever possible. This can usually be accomplished with some thought, and the efficiency gains can be significant. But it can be