Compared with machine learning or signal processing algorithms of conventional trading strategies, High Frequency Trading systems can be surprisingly simple. They need not attempt to predict future prices. They know the future prices already. Or rather, they know the prices that lie in the future

In the previous post I revealed a web scraping trick that allows us to defeat AJAX/JavaScript based web pages and extract the tables we need. We also covered how to use that trick to scrape a large volume of options prices quickly and asynchronously using the combination of aiohttp and asyncio. The

As my co-author Andrew Berkin, the director of research for Bridgeway Capital Management, and I explain in our new book, “Your Complete Guide to Factor-Based Investing,” there is considerable evidence of cross-sectional return predictability. Citing more than 100 academic papers, we present the

Traditional portfolio management focuses explicitly on the trade-off between risk and return. Anecdotally, investors often care more about the growth of their wealth. Due to compounding effects, wealth is a convex function of realized returns. Within, we explore geometric mean maximization, an

LASSO stands for Least Absolute Shrinkage and Selection Operator. It was first introduced 21 years ago by Robert Tibshirani (Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B). In 2004 the four statistical masters: Efron, Hastie, Johnstone and

June 2017 Trend Following: DOWN -3.44% / YTD: -16.88% The whole first half of 2017 was negative, with the June result following the same trend. The YTD figure is now well in the red and it would take a good reversal of that equity curve to erase the losses through the second half of the year. Below

This the third in my Hedge Fund Hacks series in which I dig just below the surface of some of the common hedge fund performance statistics. In the previous post I highlighted some of the ways in which Compound Annual Growth Rate can be distorted by chance. In this post I provide a simple hack to

While I am a believer of APT more than of CAPM, I will share some of my findings on CAPM. CAPM has many flaws: there are capital taxes, high transaction cost on illiquid securities with few floating shares, licensed leveraged funds do influence prices with outsized positions, different analyst has a

This is a summary of the recent performance of a wide range 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

In the previous installment, we discussed the use of a popular asset allocation/market timing rule (10M SMA rule hereafter) to size a short option position. The strategy did not work well as it was the case in traditional asset allocation. We thought that the poor performance was due to the fact

Real estate investment trusts (REITs) are often considered to be a distinct asset class. But, do REITs deserve this designation? While exact definitions for asset class may vary, a number of statistical methods can provide strong evidence either for or against the suitability of the designation. The

Be sure to check out our guest post over at research supersite Alpha Architect: Tactical Asset Allocation: Does the Day of the Month Matter? Backtests of long-term strategies like tactical asset allocation are usually shown trading at the end of the month, both because it makes the analysis simpler

This Free Friday, Free Friday #19, is a user submission! It is a long/short strategy for $IWM - the Russell 2000 ETF. Both the long and the short strategy only have two rules each and only hold for 1 day. Below I’ve posted the long strategy on the left and the short strategy on the right. Short

US Sector Rotation with Five-Factor Fama-French Alphas G. Sarwar (University of Greenwich), et al. June 16, 2017 In this paper we investigate the risk-adjusted performance of US sector portfolios and sector rotation strategy using the alphas from the Fama-French five factor model. We find that

Most long-term approaches to investing, like tactical asset allocation or factor investing, are designed to trade infrequently, generally once a month or once a quarter. This is a feature, not a limitation. Trading infrequently forces a strategy to ignore day-to-day noise and focus on long-term

So far, we’ve discussed the importance of investment universe selection and price momentum in designing a robust asset allocation methodology. If you haven’t read those articles, we would strongly encourage you to do so before proceeding with this one. We lay most of the explanatory and

You’ll recall, I had Andy Kershner on the podcast a few episodes back. Towards the end of that episode, Andy briefly mentioned a cloud-based algo development platform and fund, CloudQuant, which is a subsidiary of Kershner Trading Group… I mention this, because with me on this episode is Morgan

This article is the final project submitted by the author as a part of his coursework in Executive Programme in Algorithmic Trading (EPAT™) at QuantInsti™. Do check our Projects page and have a look at what our students are building. Introduction The Dispersion Trading is a strategy used to

Motivation Trading has gotten a lot faster over the last two decades. The term “short-run trader” used to refer to people who traded multiple times a day. Now, it refers to algorithms that trade multiple times a second. Some people are worried about this new breed of short-run trader making

Why Ferrari or Rolex does not price their products at 149.999 or 12.999 but most of the items you see in your supermarket is priced like 4.99? Because Ferrari never likes to position itself as a bargain. Did you know that we tend to chose the price with less syllables even if the two prices have the

I’m very pleased to announce my DataCamp course on Visualizing Time Series Data in R. This course is also part of the Time Series with R skills track. Feel free to have a look, the first chapter is free! Course Description As the saying goes, “A chart is worth a thousand words”. This is why

We've recently been considering the field of deep learning as a modelling methodology for forming new quantitative trading models. Such models have been shown to be 'unreasonably effective' in the fields of computer vision, natural language processing and games of strategy. This

In a rising rate environment, conventional wisdom says to shorten duration in bond portfolios. Even as rates rise in general, the influence of central banks and expectations for inflation can create short term movements in the yield curve that can be exploited using systematic style premia. Value,

What are the research questions? Are crowdsourced earnings forecasts from a source such as Estimize, useful in the capital markets by capturing new information about future earnings? Does a site such as Estimize add incremental accuracy when combined with the conventional, sell-side earnings

STRUGGLING QUANT episode 1: How I lost USD 500.000 while figuring out the link between questions, math, stats, coding and trading Say that you are 30 years old and you have a good 25 years to work hard. Instead of going down the easy way of working for someone else during the day and killing time in

Density estimation using regression? Yes we can! I like regression. It is one of those simple yet powerful statistical methods. You always know exactly what you are doing. This post is about density estimation, and how to get an estimate of the density using (Poisson) regression. The “go-to”

Let’s start an experiment! This post will be the first in a series on going through the process of creating a trading strategy. It will not only detail the steps that I myself curently follow when I am building a strategy, what I’m hoping for is that others contribute to the process by adding

It is a common misconception that the most important thing to have when you're trading, or investing, systematically is good trading rules. In fact it is much, much, much more important to have a good position management framework (as discussed in my first book) and to trade a diversified set

This is the fourth in a new advanced series of posts written by Imanol Pérez, a PhD researcher in Mathematics at Oxford University and an expert guest contributor to QuantStart. In this post Imanol applies the Theory of Rough Paths to the task of predicting which country a company belongs to based

I will be talking on the Factor Investing panel at the upcoming Evidence-Based Investing Conference in Dana Point, CA next Sunday –Tuesday. I am excited for the opportunity to chat, and figured I would highlight a few thoughts we have on the topic going into the event. First, what is “evidence

Last week I posted an article, which formed the first part in a series on Linear Algebra For Deep Learning. The response to the article was extremely positive, both in terms of feedback, article views and also more broadly on social media. Many of you commented that there was "an appetite"

In the last article we looked at the backtest results from 600,912 iron condor trades entered between January 2007 and September 2016. The focus in that article was on win rate and normalized P&L per day for each of the 3024 variations tested. Recall that we looked at combinations of: Trade

Mean reversion strategies rely on the premise that extremes in price eventually revert to the mean price over time. They are effective during established markets – bull, bear or sideways – but unfortunately do not perform well during market regime changes or tail events. Tail events are outcomes

I am frequently asked if I do out-of-sample testing. The short answer is not always and when I do, it is not how most people do the test. There are lots of considerations and pitfalls to avoid when doing out-of-sample testing. Out-of-sample testing is not the panacea it is made out to be. There are

I'm excited to announce my DataCamp course on importing and managing financial data in R! I'm also honored that it is included in DataCamp's Quantitative Analyst with R Career Track! You can explore the first chapter for free, so be sure to check it out! Course Description Financial

Factor investing has experienced a resurgence in popularity under the moniker “smart beta.” Several traditional factors, such as value, size, momentum, and low beta, are well defined and have been heavily researched in academia as return anomalies for many decades. These factors have also been

The first part of this post is a quick update on Tony Cooper’s of Double Digit Numerics’s volatility ETN momentum strategy from the volatility made simple blog (which has stopped updating as of a year and a half ago). The second part will cover Dr. Jonathan Kinlay’s Beta Convexity concept. So,

In our last post, we covered the importance of a well-designed investment universe as a precondition for thoughtful diversification. In this second article on Dynamic Asset Allocation for Practitioners we will explore several methods for measuring price momentum to compare and contrast their utility

That headline was a response I received from a handful of friends regarding my last post on buying puts as tail risk insurance. And I agree. Well, sort of. It’s been long known that there exists a premium for selling insurance…hey, otherwise why would anyone do it? Now what if you could combine

Continuing our exploration into the smart beta segment (Part 1, Part 2), in this third post we introduce a simple “IQ Test” that can help investors and managers measure the “smartness” of the increasing number of non-cap-weight rules-based products on the market. There are numerous arguments

Title: FURTHER EVIDENCE ON THE STRATEGIC TIMING OF EARNINGS NEWS: JOINT ANALYSIS OF WEEKDAYS AND TIMES OF DAY Authors: RONI MICHAEY, AMIR RUBIN, ALEXANDER VEDRASHKO Publication: JOURNAL OF ACCOUNTING AND ECONOMICS, 2016 (version here) What are the research questions? Do managers act to strategically

The term “multi-asset” appears in many investment strategies and applies to both balanced funds and target date retirement funds. However, multi-asset strategies may be concentrated in a limited set of asset classes, and the performance of these asset classes may be driven by an even more

At the end of my last blog, I had asked a few questions. Now, I will answer them all at the same time. I will also discuss a way to detect the regime/trend in the market without training the algorithm for trends. But before we go ahead, please use a fix to fetch the data from Google to run the code

In this second part of the Algorithmic Options trading series we’ll look more closely into option returns. Especially into the methods of combining different option types for getting user-tailored profit and risk curves, which gives options an interesting advantage over other financial

When the tech bubble collapsed back in 2000, the Nasdaq fell from 5,132 to just 1,470 a few months later. Many popular stocks found their market prices gutted. For example, Cisco lost 86% of its market cap, while Amazon fell over 90% from $107 to $7. Losses such as these decimated investor

Monetary Policy Uncertainty and Bond Risk Premium Fuwei Jiang (Central University of Finance and Economics) and Guoshi Tong (Renmin University) October 1, 2016 We show that uncertainty of monetary policy (MPU) commands a risk premium in the US Treasury bond market. Using the news based MPU measure

The Holy Grail for mutual fund investors is the ability to identify in advance, which of the active mutual funds (or ETFs nowadays) will outperform in the future. The evidence suggests this task is almost impossible. To date, the overwhelming body of academic research has demonstrated that past

Back in March we ran a content survey and found that many of you were interested in a refresher course for the key mathematical topics needed to understand deep learning and quant finance in general. Since deep learning is going to be a big part of this year's content we thought it would be

I. Trading Strategy Developer: John Ehlers. Source: Ehlers, J., FRAMA: Fractal Adaptive Moving Average. Concept: Trend following trading strategy based on adaptive price filters. Research Goal: To verify performance of the Fractal Adaptive Moving Average (FRAMA). Specification: Table 1. Results:

Purely passive investing is theoretically plausible, but practically impossible. That said, the practical implementations can often be “good enough.” As a theoretical index investor, you deploy capital, take a long snooze, and wake up some day to consume your portfolio. Unfortunately, the world