This post will be a modified backtest of the Adaptive Asset Allocation backtest from AllocateSmartly, using the Hierarchical Risk Parity algorithm from last post, because Adam Butler was eager to see my results. On a whole, as Adam Butler had told me he had seen, HRP does not generate outperformance

How much higher can smart beta adoption climb? Now in its fourth year, FTSE Russell’s latest annual survey of global institutional asset owners indicates that smart beta adoption is at an all time high and that investors continue to find new applications for its use. The survey, Smart beta: 2017

Motivated by behavioral theories, we test whether recent past performance of the momentum strategy (Past Momentum Performance--PMP) negatively predicts the performance of stale momentum portfolios. Following periods of top-quintile PMP, momentum portfolios exhibit strong reversals 2-5 years after

While seeing some “sell in may” headlines a while ago, thought i’d pull up the monthly mean returns for spx and vix. I wanted to see them on an even keel, so that each month starts at 0%, to better gauge their monthly behaviour 1 2 3 4 5 6 7 8 9 import pandas as pd import numpy as np import

Quick note... for those not already listening, my buddy Patrick O’Shaughnessy has one of the (if not the) best investing podcasts out there with his podcast Invest Like the Best. Each week he sits down with some of the best capital allocators, investment thinkers, etc... in the world and really

One of the great debates in finance is whether the source of the value premium is risk-based or a behavioral anomaly. In our book, “Your Complete Guide to Factor-Based Investing,” my co-author Andrew Berkin and I present the evidence showing that there are good arguments on both sides. Thus,

Imagine you’re a financial economist who thinks that some risk factor,{\color{white}i}f_t, explains the cross-section of expected returns. And, you decide to test your hunch. First, you regress the realized returns of N different assets on{\color{white}i}f_t to estimate each asset’s exposure to

The investment industry has investors convinced that the only path to better performance is through stock selection. As a result, most investors approach the challenges of portfolio construction exactly backward and miss out on the most important opportunities to produce differentiated performance.

are to Editor’s Note: The Academic Research Insight will be a weekly short-form research summary on research that is directly related to investing. Elisabetta Basilico (a PhD and a CFA!) will be driving the effort, which will supplement our long-form summaries, in-house research, and general

Algorithmic trading has seen great traction in recent years and the numbers of students, engineering graduates, and finance professionals looking to explore this lucrative domain has been growing exponentially with each passing year. Are you among the ones looking to learn quant skills and also make

This post will be about replicating the Marcos Lopez de Prado algorithm from his paper building diversified portfolios that outperform out of sample. This algorithm is one that attempts to make a tradeoff between the classic mean-variance optimization algorithm that takes into account a covariance

Momentum-based sector rotation is a popular investment strategy. Recent academic studies have shown that alternative implementations of standard momentum – including risk-adjusted momentum, residual momentum, and “frog-in-the-pan” momentum – can significantly improve the risk-adjusted and

his is the second in a new advanced series of posts written by Imanol Pérez, a PhD researcher in Mathematics at Oxford University, and a new expert guest contributor to QuantStart. In this post Imanol continues the theoretical discussion of Rough Paths and Signatures and begins applying them within

The recent decision by Yahoo to screw with their API for financial data (and in the process disabling all packages/functions in various programing languages obtaining EOD (end-of-day) data, at least temporarily) shows us two important things: Nothing is free and reliable forever It’s a good idea

This is Part 1 of a new series I'm doing in semi real-time to build a functional options data dashboard using Python. There are many underlying motivations to attempt this, and several challenges to implementing a tool like this from scratch. Where to get the data? Is it affordable? Easily

Recently, Yahoo Finance – a popular source of free end-of-day price data – made some changes to their server which wreaked a little havoc on anyone relying on it for their algos or simulations. Specifically, Yahoo Finance switched from HTTP to HTTPS and changed the data download URLs. No doubt

On 18 May 2017 the ichart data api of yahoo finance went down, without any notice. And it does not seem like it is coming back. This has left many (including me) with broken code and without a descent free end-of-day data source. Something needs to be done. Now. Apparently Yahoo! does not want us to

We introduce a new approach to algorithmic investment management that yields profitable automated trading strategies. This trading model design is the result of a path of investigation that was chosen nearly three decades ago. Back then, a paradigm change was proposed for the way time is defined in

Just a quick post in the light of a very recent event. Users of financial functions of R, MatLab, Python, or Zorro got a bad surprise in the last days. Many scripts and programs based on historical price data suddenly don’t work anymore. And our favorite free historical price data provider, Yahoo,

This post will be about creating constant expiry (E.G. a rolling 30-day contract) using VIX settlement data from the CBOE and the spot VIX calculation (from Yahoo finance, or wherever else). Although these may be able to be traded under certain circumstances, this is not always the case (where the

Why do CEOs decide to pay dividends? That is an interesting question, and one that academics have been researching for years. Miller and Modigiliani in 1961 show that if one assumes perfect and efficient capital markets, and investors should have no preference as to whether or not a firm pays

This is the second in a series of posts written by Frank Smietana, an expert guest contributor to QuantStart. In this detailed post Frank takes a look at the different ways in which an algorithmic trading business can be established—and why you might want to consider it. - Mike. Setting up an

We suspect you’re skeptical, and that’s a good thing. In fact, the more skeptical you are, the more you need to download our full 26-page paper “Tactical Alpha: A Quantitative Case for Active Asset Allocation.” In it, we discuss research from such luminaries as Brinson, Ibboston and Kaplan,

"Today the VIX traded below 10 briefly intraday. A pretty rare occurrence. Since 1993, there have been only 18 days where it traded below 10 intraday and only 9 days where it closed below 10." (source: some random dude on my linkedin feed) ... indeed 18 observations is a long.... long...

A lot of people look at this bull market, valuations, and think somehow that value has forsaken us. And that the much discussed CAPE ratio doesn’t work. They look at the CAPE ratio, at a current value of about 30 in the US, and think somehow that markets rising along with multiples expanding

This review is a book review of Gary Antonacci’s Dual Momentum Investing book. The TL;DR: 4.5 out of 5 stars. So, I honestly have very little criticism of the book beyond the fact that the book sort of insinuates as though equity momentum is the be-all-end-all of investing, which is why I deduct a

Bitcoin, Ethereum and some other cryptocurrencies seem to be in the spotlight again due to their most recent acceleration. C_y2pGfXoAApvdI Source: CEOTechnician Ethereum is up multiples since January. I thought we could take a look at importing Etherum price data in R and then seeing if we can draw

In this case study, we explore building a simple, low cost, systematic municipal bond portfolio. The portfolio is built using the low volatility, momentum, value, and carry factors across a set of six municipal bond sectors. It favors sectors with lower volatility, better recent performance, cheaper

To date QuantStart has generally written on topics that are applicable to the beginner or intermediate quant practitioner. However we have recently begun to receive requests from academics and advanced practitioners asking for more content on research-level topics. This is the first in a new series

The Oracle of Omaha just commented on the Chinese stock market in this year’s Berkshire’s annual meeting: …Markets have a casino characteristic that has a lot of appeal to people, particularly when they see people getting rich around them. And those who haven’t been through cycles before are

Thus far in the series we've explored the idea of using Gaussian mixture models (GMM) to predict outlier returns. Specifically, we were measuring two things: The accuracy of the strategy implementation in predicting return distributions. The return pattern after an outlier event. During the

Are portfolio managers skilled in stock-picking? It is a popular subject for academic research and majority of papers show that active funds underperform their respective benchmarks. But... It doesn't mean professionals do not know how to pick stocks. It can simply mean that a lot of managers

There are a number of recent studies that propose a more rigorous criteria for evaluating the practical significance of factors published in academic research journals. First, Harvey, Liu, and Zhu (2015) argue that a t-stat of 3 should be replacing the old 2 as a rule for statistical significance.

Here it goes, finally a strategy backtest (sort of) on this blog (what an intro). In their 1973 paper “Risk, Return and Equilibrium: Empirical Tests”, Fama and MacBeth introduce a method for estimating betas and risk premia for any risk factors that determine asset prices. Under the assumption

Shrinkage in statistics has increased in popularity over the decades. Now statistical shrinkage is commonplace, explicitly or implicitly. But when is it that we need to make use of shrinkage? At least partly it depends on signal-to-noise ratio. Introduction The term shrinkage, I think, is the most

The role of luck in (algorithmic) trading is ever present. Trading is undoubtedly a field that experiences vast amounts of randomness compared to mathematical proofs or chess, for example. That being said, a smart trader must be conscious of the possibility of outcomes and not just a single outcome.

This is a test of the Tactical Permanent Portfolio from the brains at GestaltU and ReSolve Asset Management. The strategy adds a number of dynamic features to a classic buy & hold strategy to better manage volatility and losses. Results from 1970, net of transaction costs, follow. Read more

Well, Its here, spot Vix close below 10. From what i read from the web, people are piling into short vol strategies on an escalating scale. I suspect unwinding of that trade will be rather brutal. I wish good luck to every short vol trader out there and dont forget to wear a helmet 🙂 1 2 3 4 5 6 7

Over the last several months I have shared the results from an extensive set of backtests of SPX iron condors (IC). In all, I backtested 600,912 individual SPX IC trades entered at varying days to expiration (DTE) between January 2007 and September 2016. The prior articles can be found at the links

Market expectations are a key input in the portfolio construction process. These expectations can be either qualitative or quantitative. How to form expectations for more complex strategies (e.g. managed futures, covered calls, and alternatives) is often less straightforward than forming

In today’s algorithmic trading having a trading edge is one of the most critical elements. It’s plain simple. If you don’t have an edge, don’t trade! Hence, as a quant, one is always on a look out for good trading ideas. One of the good resources for trading strategies that have been gaining

Financial research has uncovered many relationships between investment factors and security returns. Given that popularity is a curse in investing, the growing popularity of factor investing has led to worries that factors have become overvalued, posing risks to investors in these strategies. For

As the old joke says, “math is what mathematicians do.” Somehow this simple tautology is lost in the dishonest world of finance Quantitative investing: A crisis waiting to happen In a recent WSJ article, Jason Zweig brilliantly summarizes the unbearable hype and hubris exhibited by some

Does the conventional wisdom to “Sell in May” (and “Buy in November”, hence also the term “Halloween Effect”) work over the long run, perhaps due to biological/psychological effects of seasons (Seasonal Affective Disorder)? To check, we turn to the long run dataset of Robert Shiller.

Credit Spreads, Daily Business Cycle, and Corporate Bond Returns Predictability Alexey Ivashchenko (University of Lausanne) May 4, 2017 The part of credit spread that is not explained by corporate credit risk forecasts future economic activity. I show that the link with aggregate business risk and

April 2017 Trend Following: DOWN -1.35% / YTD: -11.65% April was another down month for the Wisdom State of Trend Following, with the index already in double-digit territory, on the negative side, for the year. Below is the full State of Trend Following report as of last month. Performance is

I have been troubled by the following paradox in the past few years. If a stock's log returns (i.e. change in log price per unit time) follow a Gaussian distribution, and if its net returns (i.e. percent change in price per unit time) have mean m and standard distribution s, then many finance

Over the past few years, we’ve been asked questions related to the relationship between stock prices and interest rates. Forms of the question typically look like the following: If interest rates rise, what happens to stock prices? What is the relationship between stocks prices and bond yields?

The S&P 500 index (SPX) is an American market index based on the stocks of 500 large companies. It’s one of the world’s most important market indexes and, therefore, predicting its movements is the goal of many finance analysts. In previous posts we have reproduced the SPX through clustering

In Simple ConnorsRSI Strategy on S&P500 Stocks I showed a ConnorsRSI strategy on S&P500 stocks. In ConnorsRSI Strategy: Optimization Selection, I narrowed down the optimization to three potential variations that one could consider trading. This post will explore Sensitivity Analysis (also