This post is inspired by Leo Breiman’s opinion piece “No Bayesians in foxholes”. The saying “there are no atheists in foxholes” refers to the fact that if you are in the foxhole (being bombarded..), you pray! Leo’s paraphrase indicates that when complex, real problems are present, there

SPX managed to make an intraday high for the 5th day in a row on Friday. An interesting study from the Quantifinder looked at the possible impact of 5 higher highs occurring. The studies examined the impact of the position of the market when the 5 higher highs occurred. I broke it down again over

A new proxy formula for equity market-to-book ratios suggests that (the logarithm of) such a ratio is equal to the discounted expected value of (i) differences between return on equity and market returns and (ii) the net value added from share issuance or repurchases. A firm with a higher

This is part two in a series of posts about using optimisation to get the best possible portfolio given a relatively small amount of capital. Part one is here (where I discussed the idea). You should read that now, if you haven't already done so. In this post I show you and explain the code and

Equity Tail Risk in the Treasury Bond Market Mirco Rubin (EDHEC) and Dario Ruzzi (Bank of Italy) December 23, 2020 This paper quantifies the effects of equity tail risk on the US government bond market. We estimate equity tail risk as the option-implied stock market volatility that stems from large

Pairs selection is the first crucial step to building a pairs trading strategy. And it is no surprise, to perform it correctly, one must diligently examine, compare and contrast numerous test results, graphs and characteristics. For example, cointegration analysis alone can be performed in one of

Recently I ran across an interesting paper published by National Bureau of Economic Research entitled “Return Based Measue of Firm Quality”. I happen to have a suitable data and thought why not reproduce it on data from polish stock exchange in the free time. It turned out not so bad and thanks

In the previous blogs, we examined supervised learning algorithms like linear regression in detail. In this blog, we look at what unsupervised learning is and how it differs from supervised learning. Then, we move on to discuss some use cases of unsupervised learning in investment and trading. We

Last year when bitcoin had its fourth drawdown of 80% in the past ten years, I thought It might be a good time to reenter that market. Having traded digital assets in 2017, I was familiar with the reasons for owning bitcoin. I won’t reiterate them here. You can find information on bitcoin,

The J.P. Morgan Efficiente 5 Index is a tactical asset allocation strategy designed by J.P. Morgan based on a broad universe of 13 ETFs. This post will illustrate how to replicate this strategy with Google Sheets. Notes: A fully functional spreadsheet corresponding to this post is available here.

Cryptocurrencies are a hot topic in the investing world, but is it possible to create an investment methodology combining modern Reinforcement Learning with classical indicators? Along this blog we have covered topics such as how to automate cryptocurrencies investment or whether reinforcement

The concept of pairs trading is pretty straightforward. As described in [Gatev et al. (2006)], we first find two stocks that have moved together historically and then monitor the spread between these stocks. If the prices of the two stocks diverge, we short the winner and go long on the loser,

As the following table demonstrates, since its inception in the 1970s, the private equity industry has grown significantly. According to Preqin data, there are now more than 18,000 private equity funds, with assets under management exceeding $4 trillion. Source: NACUBO endowment studies, FY

While portfolio optimization is well known in the Equity space, in the Fixed Income industry, the subject is less discussed although it has very specific needs and it can be more complex compared to its Equity counterparts. One key difference between the two of them is the trading lot size. In

Catastrophe bonds offered exceptionally high risk-adjusted returns since 2005 These were uncorrelated to equities, making cat bonds attractive for diversification However, cat bonds might have underpriced risk historically, raising concerns going forward INTRODUCTION The global pandemic continues to

Last week Tommi looked into whether hedge funds could time factors. The conclusion? Probably. This week we're going to see if Mutual Fund managers have any skill at cracking the factor timing code. The conclusion? They aren't great factor timers! The authors of the paper study a large

There’s no doubt that buying and holding index ETFs is a long-term profitable strategy. But it has two problems. It does not reinvest profits, so the capital grows only linearly, not exponentially. And it exposes the capital to the full rollercoaster market risk. A sure way to go out of the market

Asset-pricing research consistently produces many different explanations for the same empirical facts. As a rule of thumb, you should expect asset-pricing researchers to wildly overachieve. Behavioral researchers can typically point to several psychological biases which might explain the same

In a previous MathInvestor article, we mentioned how absurd it would be if someone offered predictions of stock or bond prices or cryptocurrency rates based on astrological signs. Consider for a moment that financial market prices are based on a confluence of many thousands of factors worldwide,

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