We demonstrate a computer program that designs a portfolio consisting of common securities, such as the constituents of the S&P 500 index, that achieves any desired profile via in-sample backtest optimization. Unfortunately, the program also shows that these portfolios typically perform

What is an Order book? With the growing popularity of Algorithmic and High Frequency Trading, study of order books has grown manifolds. “Order book” is essentially an electronic list of all Buy and Sell orders, arranged as per price time priority. This means that a person having higher price on

Summary As a stand-alone asset class, dividends may make an interesting alternative to fixed income: they offer low volatility, are generally robust to market crises, and may serve as an inflation hedge. Accessing dividend strips was previously restricted to institutional investors, using

A hedge fund is simply a go anywhere investment vehicle that attempts to provide excess returns to cash with a low correlation to traditional asset classes (i.e. vehicles that provide alpha). Hedge funds and liquid alternatives have taken a lot of heat recently, much of it deserved, but in this post

It’s hard enough deciding which Machine Learning technique to use, but after selecting an appropriate clustering algorithm the next challenges begin: how good is the separation and into how many groups should you divide the data? Maybe three is not always a crowd… First, let’s set the scene We

I recently came across a graph similar to the following while doing some market research. 1 Source: Yahoo! Finance. Analysis by Newfound Research. Data from January 1951 – December 2015. The argument was that the markets are getting more volatile. While this certainly looks to be the case based on

This is more of a "How to build your own algotrading strategy - the Ethereum edition" and not a "make money fast" blog post. It is also a real example with real returns (and real production errors that cost me money) where you can see how to identify opportunities, why

We present extensive evidence that "risk premium" is strongly correlated with tail-risk skewness but very little with volatility. We introduce a new, intuitive definition of skewness and elicit an approximately linear relation between the Sharpe ratio of various risk premium strategies

The range over the last week has been extremely tight. On 7/20/16 SPY closed at a 50-day high. Every SPY close in the 5 days since 7/20 has been within the intraday range of that 7/20/16 bar. (And it wasn’t even that big of a range.) It is said that consolidations are often resolved in the

I had the pleasure of finally meeting Gary Antonacci earlier this year. Gary is the creator of the momentum strategy that I follow and have been discussing on this blog. I first came across his work in 2011 on the blog Abnormal Returns (which should be a daily read for investors). Gary and I have

The majority of machine learning posts to date on QuantStart have all been about supervised learning. In this post we are going to take a look at unsupervised learning, which is a far more challenging area of machine learning. Supervised learning involves taking a number of data observations, each

During the 1600s, the Dutch had a large merchant fleet and the port city of Amsterdam was a dominant commercial hub for trade from around the world. Based on the growing influence of the Dutch Republic, in 1602 the Dutch East India Company was founded, and its evolution into the first publicly

One of my favorite classes during EPAT was the one on statistical arbitrage, so the pair trading strategy seemed a nice idea for me. My strategy triggers new orders when the pair ratio of the prices of the stocks diverge from the mean. But in order to work, we first have to test for the pair to be

In 2004 I enjoyed my 15 minutes of fame for an article I wrote called The Tao of Alpha, in which I explained the concept of alpha as a zero-sum game. Sources of alpha in 2004 were much different than those available in the mid-1990s when I started my career and they are also different from

Let’s say one sets out to design a portfolio, knowing everything we know today about investing. Where would a logical, evidence-based investor even start? Investors today have access to more market data and strategic information than at any other time in history. While beneficial in some ways,

Most academics and practitioners tend to compare momentum or trend-following strategies to a buy and hold investment strategy. They do so by comparing the results of the strategies to a benchmark that is a proxy for buy and hold. From this type of analysis many ‘experts’ justify why the

To prepare for the previous episode on system trading through the Brexit, I had to dig through some of the past podcast episodes for background information. As I was going through them I realized there was so much great information there, some that I had already forgotten about. Such a shame, all

Mar Vista Investment Partners has a really interesting research piece out The Price You Pay which has a great table outlining the benefit of an asymmetric return profile (i.e. having more market exposure during up markets than down markets). It is a mathematical truism that superior down capture in

The trending value strategy buys the top 25 stocks by their 6 month price momentum among the top decile of stocks ranked by value composite 2 (VC2), a combination of price-to-earnings ratio, price-to-sales ratio, price-to-book ratio, earnings before interest tax depreciation and amortization to

I have had the pleasure of getting to know and work with Brian Peterson of late building out the blotter::mcsim function in the blotter package. I will be writing about this function soon and where it is headed, but in this post i wanted to share a presentation Brian gave the CapeR User Group last

Well, despite some recent market turmoil from the Brexit, the S&P 500 is still hovering near its high from last year on a price basis. If we include the reinvestment of dividends, then we have already seen new highs in April, May, and June of this year. As we wrote about previously, a bear

Investors talk a big game when describing how they evaluate mutual funds. They say they consider things like the objectives of the fund, its size, and the longevity of its managers. But there’s one factor that looms larger than all the others: Performance. We wrote here about how investors tend to

Many assets exhibit bull or bear trends which persist for long periods of time. This presents an interesting problem for anyone trying to predict the future return of an asset: a lack of diversity in your training set. This problem is known as unbalanced classes in the machine learning field. The

Last night it was my pleasure to present at the Tyro Fintech Hub in Sydney on the topic of using machine learning in algorithmic trading systems. Here you can download the presentation Many thanks to all who attended and particularly for the engaging questions. I thoroughly enjoyed myself! In

Developer: Alan Hull. Source: Kaufman, P. J. (2013). Trading Systems and Methods. New Jersey: John Wiley & Sons, Inc. Concept: Trend following trading strategy based on low lag moving averages. Research Goal: To verify performance of the Hull Moving Average (HMA). Specification: Table 1.

Using a simple sign test, we report new empirical evidence, taken from both the US and the German stock markets, showing that trading behavior substantially changed around Black Monday in 1987. It turned out that before Black Monday investors behaved more as in the momentum strategy; and after Black

Jegadeesh and Titman (1993) popularized a simple idea: "past winners outperform past losers." Post JT, the relative strength, or "momentum anomaly," was forever ingrained in the minds of academic researchers (which is odd, since the idea had been around 50 years prior to JT 1993,

Python has emerged as one of the most popular language for programmers in financial trading, due to its ease of availability, user-friendliness and presence of sufficient scientific libraries like Pandas, NumPy, PyAlgoTrade, Pybacktest and more. Python serves as an excellent choice for automated

According to the just-published 2016 Rich List of the World's Top-Earning Hedge Fund Managers by Institutional Investor's Alpha magazine, eight of the top ten earners fall into the "quant" category, and half of the 25 richest of the year are quants. The firms listed include the

Momentum can be calculated in a number of different ways. As long as you are measuring the strength of price appreciation over an intermediate time horizon most logical calculation methods will work to one degree or another. The standard, academic definition of momentum usually means taking the

A simple tutorial demonstrating how to train a neural network to square root numbers using a genetic algorithm that searches through the topological structure space. The algorithm is called NEAT (Neuro Evolution of Augmenting Topologies) available in the RNeat package (not yet on CRAN). The training

I made a recent short-term case for bonds in a recent post given my view that low rates may be disinflationary, despite my view that they have a "horrific risk / return profile" over the longer-term. This post will highlight that what matters over the longer term is the level of inflation

We are really excited that we can announce, that Quantopian started to publish series of articles where they will really deeply analyze some of Quantpedia's suggested strategies. We think, that Soeng Lee from Quantopian did a really good job with a first article, so we just wanted to point that

Asset Allocation: A Recommendation for Resolving the Collision between Theory and Practice Larry J. Prather (Southeastern Oklahoma State University), et al. April 26, 2016 We examine the creation of a low-cost optimal risky portfolio that individual investors can easily construct and manage. We

This is the second and concluding part of our interview with Artur Sepp. Q: If you had an account of $100k, what would you trade? A: Well, if I had $100k I would manage it using the three strategies. The core strategy is based on the dividend growth. I would be very conservative with the companies I

By way of introduction we begin by reviewing a well known characteristic of the iPath S&P 500 VIX ST Futures ETN (NYSEArca:VXX). In common with other long-volatility ETF /ETNs, VXX has a tendency to decline in value due to the upward sloping shape of the forward volatility curve. The chart below

After every crash or major geopolitical event that roils the market we are exposed to graphics like this one containing sigma numbers: Black Swan The message associated with these charts is usually, "We should be very worried because the events that just occurred were really unlikely." The

In the last two posts (here and here) we looked at the performance of a simple 60 day momentum rotation system. In this post, we will look at variations on that simple system, and how these variations performed during the same time period, using the same 10 ETF products. The 10 ETFs used by all of

Often one runs a optimization of a testing idea, then using some set metrics from these results, one picks a variation to trade. What often comes as a surprise to people, and myself the first time I saw this, is that your optimization runs are often mean reverting. What do I mean by this? For

1. Motivating Example This post shows that, if traders face convex transaction costs (i.e., it costs them more per share to buy 2 shares of stock than to buy 1 share of stock), then it is possible to infer traders’ investment horizons from trading-volume data. To see why, imagine you are a trader

This post will introduce component value at risk mechanics found in PerformanceAnalytics from a paper written by Brian Peterson, Kris Boudt, and Peter Carl. This is a mechanism that is an easy-to-call mechanism for computing component expected shortfall in asset returns as they apply to a portfolio.

I was emailed yesterday with an interesting career question about working in High Frequency Trading (HFT). The question posed was "Is it possible to get a HFT-related job in a big company without a formal degree?". The short answer is that yes, it is possible. The longer answer is that it

The idea that one can predict stock market movements is somewhat insane. The major problem with stock market forecasting is the lack of evidence that it is possible. I am unaware of any market commentator that has been successful–on a consistent basis–at predicting the future direction of the

If you don’t know who you are, the stock market is an expensive place to find out – George Goodman In the previous post, I had a conversation with a few experts in the field of Algorithmic Trading to gain some insights into this seemingly “black-box”. That conversation not only helped me

Recently a paper was published by AQR where the authors advocate for an integrated approach to multi-factor portfolios, preferring securities that exhibit strong characteristics across all desired factors instead of a mixed approach, where securities are selected based upon extreme exposure to a

Artur Sepp is a rare example of a quant who combines excellent technical skill with a practical understanding of markets. If you can't learn from his presentations the fault is more likely to be yours rather than his. He recently agreed to do an interview for us. Here is the first part. Q: What

We evaluate the robustness of momentum returns in the US stock market over the period 1965 to 2012. We find that momentum profits have become insignificant since the late 1990s partially driven by pronounced increase in the volatility of momentum profits in the last 14 years. Investigations of

Remarkable about Friday’s 50-day high close is that it came just 8 trading days after SPX closed at a 50-day low. That’s quite rare to see. The study below is from this weekend’s Quantifiable Edges Subscriber Letter. It looks at all the instances since 1950 of a move from a 50-day closing low

What an eventful few weeks we’ve had since the last episode. The results of the Brexit decision took a lot of people by surprise and the markets reacted accordingly. What was interesting about this market event is that we all knew the date and time period when the Brexit votes would start rolling

The best quant mashup links for the two weeks ending Saturday, 07/09 as voted by our readers: Backtesting Based on Multiple Signals – Beware of Overfitting [Alpha Architect] Cloud-Based Automated Trading System with Machine Learning [Quant Insti] Alpha’s measurement problem [Flirting with