Looking back at asset class performance over the course of market history, we notice a hierarchy of excess returns. Small caps generated excess returns over broad equities, which generated excess returns over corporate bonds, which generated excess returns over treasury bonds, which generated excess

Before we dive into this week’s commentary, we want to extend a very heartfelt thank you to everyone who nominated us for ETF.com’s 2016 ETF Strategist of the Year Award. The award ceremony was held on Thursday night and we were fortunate enough not to leave empty handed! We’re incredibly

The study below is one I have shown here on the blog a few times over the years. It examines the bullish inclination the market has had in early April. 2017-04-03 Numbers here appear impressive. Of further note, sixteen of the 1st eighteen years were higher on day 4, but the 2012-2014 instances saw

This is a summary of the recent performance of a number of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies are broadly representative of the

IMHO, there is nothing more exciting these days than researching, analysing, and a good understanding of cryptocurrencies. Powered by blockchain technology, we live in a new world that moves fast forward as we sleep. In my first post devoted to that new class of tradable assets we have learnt how to

Financial research has uncovered many relationships between investment factors and stock returns. For investors, an important question is whether the publication of this research can impact the future size of factor premiums. Asking this question is crucial on two fronts. First, if anomalies are the

As the title suggests, I created a dead simple hedge ratio API called Risk Hedger. Also its free and the Python client is open source. So if you’re in to that kind of thing feel free to read on: What is a Hedge Ratio? Traders and investors buy/sell hedges when they want to reduce the risk of their

Each year I teach my “seminar in investments” course at Drexel, which consists of the Masters in Finance students and a handful of geeky MBA students. The first few weeks of the course involve an introduction to various investment frameworks and how to navigate the source academic literature.

Bubbles for Fama Robin M. Greenwood (Harvard Business School), et al. February 2017 We evaluate Eugene Fama’s claim that stock prices do not exhibit price bubbles. Based on U.S. industry returns 1926–2014 and international sector returns 1985–2014, we present four findings: (1) Fama is correct

Happy Friday. The trader in me could not risk doing Free Friday #13 so I decided to release 2 strategies this week (14 and 14a). The first strategy shorts $GDX, the Gold Miners ETF, and the second strategy goes long $GLD, the Gold ETF. ff14a gdx_ff14 The strategy above is the GDX short strategy. The

We first review empirical evidence that asset prices have had episodes of large fluctuations and been inefficient for at least 200 years. We briefly review recent theoretical results as well as the neurological basis of trend following and finally argue that these asset price properties can be

High-speed trading veteran, Manoj Narang, originally worked on Wall St for the likes of Credit Suisse and Goldman Sachs prior to founding Tradeworx, which became one of the larger trading firms in the U.S. (in terms of volume). He’s since parted ways with Tradeworx to start MANA Partners—an

Gary has over 40 years’ experience as an investment professional focusing on underexploited investment opportunities. Since receiving his MBA degree from the Harvard Business School, Gary has concentrated on researching, developing, and applying innovative investment strategies that have their

Eugene Fama and Kenneth French’s 1992 paper, “The Cross-Section of Expected Stock Returns,” resulted in the development of the Fama–French three-factor model. This model added the size and value factors to the market beta factor. As my co-author, Andrew Berkin, and I demonstrate in “Your

Faced with growing uncertainty in financial markets, investors are worried about the future of their investments. Travelling in time to check the future reality is not yet a possibility. For that reason, we use techniques and create measures to gain confidence in our investments’ future behaviour.

Benchmarks are indispensable for investment analytics. The challenge is picking a relevant one. The stakes are high because the wrong benchmark can be worse than none at all. The good news is that the potential for error can be dramatically reduced by choosing a set of random benchmarks that are

This week's commentary is a long-form presentation all about factor investing and smart beta. We cover four topics. In the first section, we explore the basics of factors: what are they and where do they come from? The second topic explores why implementation details matter and why long-only

The spot VIX index finished last Friday at 11.28, a relatively low number, while the SKEW index was making a new high. The SKEW index is a good proxy for the cost of insurance and right now it appears to be expensive. A high reading of SKEW means investors are buying out of the money puts for

This is the final post. Not the final post of the blog; which may be good news or bad. But the final post in my short series on using the new native python API for interactive brokers. Having got some prices and submitted some orders we want to know whether we made any money or not; and what

In this piece I examine various way in which an investor can think about their active market timing decisions, often labeled with the innocuous term “rebalancing.” Rebalancing a portfolio is the finance version of “eat your vegetables” — the advice is taken as gospel, but very few people

Folks from Quantopian did a new independent analysis of a strategy we have in our database. An article is written by Jeremy Muhia and is focused on Momentum and Reversal Combined with Volatility Effect in Stocks (Strategy #155): https://www.quantopian.com/posts/do-momentum-and-reversals-coexist

This article reviews the backtest results for iron condors (IC) entered at 73 days to expiration (DTE). These tests covered 9 IC variations, with short strike deltas at four locations (8, 12, 16, 20), utilizing 12 exits. In all, there were 432 test runs (9 variations x 4 deltas x 12 exits). Each

Post Outline Part 1 Recap Part 2 Goals Jupyter (IPython) Notebook References part 1 recap In part 1 of this series we got a feel for Markov Models, Hidden Markov Models, and their applications. We went through the process of using a hidden Markov model to solve a toy problem involving a pet dog. We

Welcome to a brand new era of “financial assets” – the crypto-assets. The impossible became possible. Yes, now you can trade cryptocurrencies: money that have been created in a virtual world with a physical impact onto our everyday cash-in-the-bank reality. The grande picture is still

This the fourth in a series of posts on using the native python API for interactive brokers. You should read the first, second, and third, before this one. It is an updated version of this older post, which used a third party API (swigibpy) which wraps around the C++ API. I've changed the code,

The debate rages on over the application of valuation in factor-timing methods. Regardless, diversification remains a prudent recommendation. How to diversify multi-factor portfolios, however, remains up for debate. The ActiveBeta team at Goldman Sachs finds new evidence that composite

There is a lot of information about algorithmic and quantitative trading in the public domain today. The type of person who is attracted to the field naturally wants to synthesize as much of this information as possible when they are starting out. As a result, newcomers can easily be overwhelmed

Machine learning has seen a huge amount of growth over recent years with the increase in available data and processing power. It’s an incredibly powerful toolset for uncovering patterns and relationships in data, however, these tools can be challenging to learn, apply correctly and are also open

I stumbled across a great post on MKTSTK about visualising volatility and correlations of multiple timeseries with streamgraphs, and it got me thinking about where else a streamgraph might be useful to visualise financial data. Rather than looking at an individual assets, I thought it might be

Contrarian Factor Timing is Deceptively Difficult Clifford S. Asness (AQR Capital Management), et al. March 7, 2017 The increasing popularity of factor investing has led to valuation concerns among some contrarian-minded investors, and fears of imminent mean-reversion and underperformance. In this

Many asset management firms are happily enjoying record revenue and profits driven not by inorganic growth or skillful portfolio management but by a seemingly endless increase in US equity prices. These firms are effectively commodity producers entirely dependent on the price of an index over which

Waaaaaay back in the day, I showed how to simulate correlated random walks using copulas…. I was really thinking about the application to pairs trading back then… which was fine, because one of the limitations was that the method could only simulate two random variables at a time. If you wanted

ost market participants are risk adverse and people tend to close their long positions once they perceive a formation of downturn in the market. Large sudden price drops can always be observed near the end of uptrends. On the other hand, people tend to have their own preferences in deciding the

One of the challenges of Mean Reversion trading is deciding when to get into a trade. How far from the mean should we actually wait before we consider getting into a trade? In a trending environment where the dips are shallow, getting in closer to the mean can bring lots of trading opportunities

This is a test of a tactical asset allocation strategy from the excellent paper: The Trend is Our Friend: Risk Parity, Momentum and Trend Following in Global Asset Allocation (1). The strategy combines two important tools: trend-following (to determine what assets to hold) and risk parity (to

A frequently asked question is how I pick which variation from an optimization run to trade. This post will cover a ConnorsRSI strategy on S&P500 stocks. We will use a wide range on the parameters to give us lots choices to be used in the next post. I the next post, I will show how I take the

Since today is Fed day, i thought id take a look at how rate decisions have affected Vix. Vix data starts from early 90’s so we’ll have start from there. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 import quandl import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn

Smart Beta is a label applied broadly to all factor-based investment strategies. In a recent WSJ article on Smart Beta, Yves Choueifaty, the CEO of Tobam, said There's a huge range of possibilities in the smart-beta world, and they can't all be that smart. This paper separates the factor

Gary Antonacci may not be happy to learn that his "Dual Momentum" label has been pirated by a team of academics (Huang, Zhang, and Zhou)(1)(2) in a new paper that explores the combination of price and fundamental momentum stock-picking strategies. The authors also investigate the common

Sector rotation is a popular investment strategy whereby managers actively reallocate capital from one investment sector to another based upon changing market conditions. There are many ways to run sector rotation strategy, including: business cycle indicators, macroeconomic indicators, value-based,

I’ve noted a number of times that Op-ex week in general is pretty bullish. March, April, October, and December it has been especially so. S&P 500 options began trading in mid-1983. The table below is one I have showed in March each of the last several years. It goes back to 1984 and shows

Google “K-means clustering”, and you usually you find ugly explanations and math-heavy sensational formulas*. It is my opinion that you can only understand those explanations if you don’t need them; meaning you are already familiar with the topic. Therefore, this is a more gentle introduction

Nothing quantitative here, just taking a look at how the AAII setiment has been when Spx is making new 21 week rolling highs. The recent AAII setiment has turned siginificantly negative even as Spx is plowing up and wanted to see when has that happened in the past.

This the third in a series of posts on using the native python API for interactive brokers. You should read the first, and the second, before this one. It is an updated version of this older post, which used a third party API (swigibpy) which wraps around the C++ API. I've changed the code, but

In order to present results as realistic as possible in our PAA-paper, we constructed long-term end-of-month data series for popular ETF proxies, like SPY, GLD and TLT (see paper appendix on SSRN). All data series start December 1969. For the pre-inception history, the proxies are derived from

The traditional way to treat the RSI is to treat low RSI levels as good buying opportunities while treating high RSI levels as selling opportunities. However, we seek to gain fresh insight into the nature of RSI, with an eye toward discovering possible momentum return, by exploring the RSI using a

We analyze the worst currency carry loss episodes in recent decades, including causes, attribution by currency, timing, and the duration of carry drawdowns. To explore the determinants of the length of carry losses, a model of carry drawdown duration is estimated. We find evidence that drawdown

Within our unique 2-Day Intensive Workshop in London, UK on Python for Algorithmic and Crypto-Currency Trading we dive into most recent and hot topics in algo-trading. We will cover and analyse a well explored world of classical assets (stocks, FX currencies) extended by trading techniques aimed at

“Prediction is very difficult, especially about the future”. Many of you must have come across this famous quote by Neils Bohr, a Danish physicist. Prediction is the theme of this blog post. In this post, we will cover the popular ARIMA forecasting model to predict returns on a stock and

Two weeks ago, Facebook launched Prophet, an amazing forecasting tool available in Python and R. Here’s a bit of info from the Facebook research website: “Forecasting is a data science task that is central to many activities within an organization. For instance, large organizations like Facebook