Yesterday Quantopian rolled out an update which added a few very nice features. All you really need to know is that you can now design your own custom filters and the 500 stock universe limit has been lifted. The following model uses these new additions to rank and buy 50 stocks according to their(...)

The VIX and VXO have dropped sharply over the last 7 days. These are measures of options premium. When they are falling it means premium is declining, and options traders are less fearful. The study below looks for times when the VXO becomes stretched more than 20% below its 10-day moving average.(...)

In this article I want to show you how to apply all of the knowledge gained in the previous time series analysis posts to a trading strategy on the S&P500 US stock market index. We will see that by combining the ARIMA and GARCH models we can significantly outperform a "Buy-and-Hold"(...)

Today I was trying to investigate short interest in the Energy sector: the group as a whole has rallied hard over the last few days and I suspect a short covering rally is at play, so some testing is in order. Much to my dismay, my searches didn’t return an easy way to do this in Python. Lots of(...)

Standard mean-variance optimized momentum outperforms the traditional equally weighted momentum strategy if the expected return vector used reflects momentum's top and bottom only characteristic. This top and bottom only characteristic is the phenomenon that only the stocks in the top decile(...)

Since writing about my experience writing the CFA Level I exam in June, I have received many emails from people interested in finding out how to become a quant. To some extent, this post will answer that question. That said, this post is actually not about how to become a quant, it is about how to(...)

Modelling of financial markets is usually undertaken using stochastic process. Stochastic processes are collection of random variables indexed, for our purposes, by time. Examples of stochastic processes used in finance include GBM, OU, Heston Model and Jump Diffusion processes. For a more(...)

How Do Investors Measure Risk? Jonathan Berk and Jules H. Van Binsbergen October 1, 2015 We infer which risk model investors use by looking at their capital allocation decisions. We find that investors adjust for risk using the beta of the Capital Asset Pricing Model (CAPM). Extensions to the CAPM(...)

This post will review the DIY Financial Advisor book, which I thought was a very solid read, and especially pertinent to those who are more beginners at investing (especially systematic investing). While it isn’t exactly perfect, it’s about as excellent a primer on investing as one will find out(...)

Back-testing of a trading strategy can be implemented in four stages. Getting the historical data Formulate the trading strategy and specify the rules Execute the strategy on the historical data Evaluate performance metrics In this post, we will back-test our trading strategy in R. The quantmod(...)

Selecting the indicators to use is one of the most important and difficult aspects of building a successful strategy. Not only are there thousands of different indicators, but most indicators have numerous settings which amounts to virtually limitless indicator combinations. Clearly testing every(...)

Last month I tested random rebalancing strategies based on dates and found that searching for optimal points through time to reset asset allocation may not be terribly productive after all. Let’s continue to probe this line of analysis by reviewing the results of randomly changing asset weights for(...)

I've had a request for the code used to do the optimisations in chapter 4 of my book "Systematic Trading" (the 'one-period' and 'bootstrapping' methods; there isn't much point in including code to the 'handcrafted' method as it's supposed to(...)

Any trading strategy can be broken down into a set of events and the reaction to those events. The reactions can get infinitely complex and varying but essentially strategy writing is quite simply put exactly that. The kind of events and their frequency would depend on the markets and the(...)

The index had a strong September, continuing the “Summer uptrend” started in mid-July. This has now resulted in the YTD performance returning to positive territory, after the “Spring slump” took the index from the “Winter highs” to negative performance. Let’s see what Autumn (or Fall depending on(...)

September 2015: Trend Following UP +4.64% — YTD: +13.98% Third month in a row of the index producing a positive return. The YTD and 12-month figures — well in the black (over 10% and 35% respectively) — show that trend following has been a good strategy to invest or trade in these past market(...)

Readers of Scott’s Investments know I am a proponent of do-it-yourself investing solutions. I am also a big fan of Alpha Architect, so I was excited when I was asked to review a book which combines the best of both worlds, DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth(...)

Meb Faber tweeted an interesting question related to taxes, dividend payers, and the value premium the other day. I’ll summarize the heart of the question: How do dividend payers affect the value premium? Instead of pontificating on the issue, we decided to directly address the question via(...)

Summary Backtests should be, and frequently are, evaluated with scrutiny and skepticism While hypothetical results – backtested or live – are reported as a single, precise number, investors will have different performance based on In most hypothetical results, this execution factor is often(...)

The market is off to a strong start today and is posting short-term highs. Below is a study that examines similar situations when short-term highs occurred on a Monday during a long-term downtrend. 2015-10-05 image2 As you can see the numbers are quite bearish. Down-gaps outnumbered up-gaps by a(...)

Friday had an exceptionally weak start and strong finish. Such reversals during long-term downtrends have often failed to see further buying the next day. This can be seen in the study below. 2015-10-05 image1 The numbers here are solidly bearish. 70% of the time SPY has closed down the next day(...)

The best quant mashup links for the week ending Saturday, 10/03 as voted by our readers: Empirical Finance: Meeting Fiduciary Standards Through Skepticism, Not Cynicism [GestaltU] Forget “Active vs. Passive”: It’s All About Factors [GestaltU] Strategy Replication – Evolutionary Optimization based(...)

The days of Richard Dennis and his “turtles” with their alleged 100% per year profit are long gone, but their mystique lives on. And with it comes one attempt after the other to emulate them, to create trading systems that will knock the socks off the competition. Robert Carver is more modest—and(...)

I read a post on Mebane Faber’s blog a few months back about something he calls the “Three-Way Model.” It’s a simple trend following model that uses 3 ETFs: Stocks, Bonds and Gold. The rule is simply: Invest equally in whatever is going "up" (ie. 3 month moving average > 10 month(...)

A bunch of people got in touch about the recent 'Duality' strategy. Frankly, I see a result and post it up here, thinking these ideas through as I write and as you read 'em. I used current DJIA constituents to backtest the strategy, but mentioned the need to test with random(...)

The below analysis was purely an accident. I was actually looking into periods the U.S. stock market "suffered" a 10% drawdown for the absolute opposite reason; to show that a buy and hold investor should likely ignore these regularly occurring events. How regular? The always interesting(...)

Yesterday I wrote up a post, and immediately after, was sure I got something wrong. This is the offending chart. Volatility increases linearly as we add more positions to the equally weighted portfolio. What I failed to mention is that each position was weighted by 100% of the portfolio. So two(...)

The portfolio manager of a large, active dividend fund was recently interviewed by Morningstar. (“What Active Management Can Bring To Dividend Investing” http://www.morningstar.com/cover/videocenter.aspx?id=716392). The portfolio manager argues that simply looking for stocks with high dividend(...)

We will now repeat our experiment with the 900 trend trading strategies, but this time with trades filtered by the Market Meanness Index. In our first experiment we found many profitable strategies, some even with high profit factors, but none of them passed White’s Reality Check. So they all would(...)

This paper focuses on momentum strategies based on recent and intermediate past returns of U.S. industry portfolios. Our empirical analysis shows that strategies based on intermediate past returns yield higher mean returns. Moreover, strategies involving both return specifications exhibit(...)

Over the last five blog posts we looked at the backtest results for 4080 options straddles sold on the S&P 500 Index (SPX) at 45 days-to-expiration (DTE). Eight different loss approaches were tested on these straddles. On top of these eight loss approaches, tests were conducted with no profit(...)

The Ivy Portfolio spreadsheet track the 10 month moving average signals for two portfolios listed in Mebane Faber’s book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10, and 20 security portfolios that have trading signals based on long-term(...)

In the post, Maximum Loss Stops: Do you really need them?, we looked at how maximum loss stops changed the results of a mean reversion strategy. At the end of the post I asked the readers to vote for what to try next. Let us see how these are ideas turn out. The rules from the original post Setup(...)

I wrote last week that many different measures of risk can be used to demonstrate that low risk stocks outperform high risk stocks, and illustrated this by sorting stocks according to the Hurst exponent. Today we are going to offer another example of this by using entropy as the measure of risk.(...)

This is a brief post aimed at those who have already bought a copy of "Systematic Trading" (by the way thanks!) As you've probably noticed I've included excel sheets here explaining the two trading rules I describe in the book - exponentially weighted moving average crossover(...)

I recently enrolled in the QuantInsti Executive Program in Algorithmic Trading and one of the areas in quantitative finance that interests me greatly is the analysis of financial time series. During the course we will take on a massive project to build our own trading strategy with the help of a(...)

Months ago I came up with an idea. How about building a portfolio where choosing positions and a holding period is interchangeable? Weird right? Let me explain. Academics assume day over day returns have little to do with each other and that markets are more or less efficient. So increasing your(...)

Robert Carver introduces his 2015 book, Systematic Trading: A Unique New Method for Designing Trading and Investing Systems, by stating that: “I don’t believe there is any magic system that will automatically make you huge profits, and you should be wary of anyone who says otherwise, especially if(...)

The Efficient Market Hypothesis (EMH) has been widely called into question in the investment literature, through two main anomalies: timing and low-volatility anomalies. In this paper, we aim to combine the predictive power of timing and low-volatility strategies to deliver better risk-adjusted(...)

The WSJ blog had a recent article The VIX Market Suggests It’s Not Yet Time to Buy the Dips outlining: Typically, longer-dated VIX futures are more expensive than VIX futures expiring in the current month, as there’s a greater chance of stock swings over a longer time period. That makes for a an(...)

We just love a good debate, and there seems to be quite a heated debate at the moment about the relative utility of passive versus active investing. Perhaps this debate is as timeless as investment management itself, but a flurry of recent studies may have finally armed passive advocates with(...)

As noted through our previous posts, we are big proponents of Value investing and Momentum investing strategies. We even highlight the best way to combine value and momentum. However, there is a new paper by Toby Moskowitz titled “Asset Pricing and Sports Betting” which examines how size, value and(...)

Summary We often hear trend following being referred to as “market timing” In all active strategies, timing is an important concept Market timing is a distinct process whereby investors try to predict the future Momentum is reactionary, not predictive, and is therefore no more a form of market(...)

Approach to Designing Amazing Strategies “Add a SMA(30)! No add an EMA(18). Optimise it to find the best parameter value. Ok we’ll stick to EMA(15). Throw in 3 date and time filters, 3 optimised price indicators and 3 volume indicators (that are essentially saying the same thing in different ways)(...)

Robert Carver is an independent systematic trader, freelance writer and research consultant. He spent more than seven years working for AHL, one of the worlds largest systematic hedge funds. Robert was responsible for the inception of AHL's fundamental strategies group and subsequently managed(...)

Michael Edesses is out with a scathing article lambasting the field of empirical finance. He draws inspiration from Harvey, Liu and Zhu's (HLZ) recent article, entitled "…and the Cross Section of Expected Returns", but extends HLZ's conclusions to an absurd limit. In this(...)

Wow, I enjoyed replicating this neatly written paper by Ronald Hochreiter. Ronald is an Assistant Professor at the Vienna University of Economics and Business (Institute for Statistics and Mathematics). In his paper he applies evolutionary optimization techniques to compute optimal rule-based(...)

Following on from my last post I thought I would, as a first step, code up a "straightforward" Runge-Kutta function and show how to deal with the fact that there is no "magic mathematical formula" to calculate the slopes that are an integral part of Runge-Kutta. My approach is(...)

Momentum and Risk Adjustment

Market Condition and Momentum