Regular listeners to the podcast I ocasionally co-host will know that I enjoy some light hearted banter with some of my fellow podcasters, many of whom describe themselves as 'pure' trend followers, whilst I am an apostate who deserves to be cast into the outer darkness. My (main) sin? The

Another brief post this month; the deadline for the first draft of my latest book is only a couple of months away and I haven't got much free time! But I was asked an excellent question on twitter recently, which was how the various types of trading rule have contributed to my p&l this

Eight years! Wow. In late 2013 I walked out of an office for the last time where I had been working for AHL, a large systematic futures trading fund. A few months later, in April 2014, I had my own very small systematic futures trading account, and I started doing these performance reviews. And this

Very brief blog post this month; I'm deep into book writing mode at the moment. Chanelling Clif Assness, I'm just going to present a few charts and lead you to draw your own conclusions. Excess / futures returns from portfolio of 60% S&P 500, 40% US Ten year treasuries (Authors own

This is a short follow up post to one I did a couple of years ago, on "Exogenous risk management". This was quite an interesting post which dug into why expected risk changes for a typical diversified futures trading system. And then I introduced my risk overlay: "Now we have a better

Happy new year! A very quick post from me this month - I'm trying to get ready for teaching next week and also cracking on with my latest book. On the Systematic Trader podcast I recently discussed using a clustering algorithim to group instruments. Using my software, pysystemtrade, I can get a

I realise that I've never actually sat down and described my fully automated futures trading system in all it's detail; despite having runit for around 7.5 years now. That isn't because I want to keep it a secret - far from it! I've blogged or written books about all the various

My last blog post was about a new method for a daily dynamic optimisation of portfolios with limited capital, to allow them to trade large numbers of instruments. (Although I normally write my blog posts to be self contained, you'll definitely have to read the previous one for this to make any

This is the sixth (!) post in a (loosely defined) series about finding the best way to trade futures with a relatively small account size. This first (old) post, which wasn't conciously part of a series, uses an 'ugly hack': a non linear rescaling of forecasts such that we only take

This will be a bit different from my normal posts. It's basically some personal reflections on the LIBOR fixing scandal, prompted by having just read this book written by Stelios Contogoulas: This post isn't really a book review, although I will say that the book is definitely worth

This post is something that I've banged on about in many presentations at several conferences* (most complete slides are here), and in various interviews, but never actually formally described in a blog post. In fact this post has existed in draft form since 2015 (!). * you know, when you leave

Over the last few posts I've been grappling with the difficulties of trading futures with a retail sized account. I've tried a couple of things so far - a complex dynamic optimisation (here and here) where I try and optimise the portfolio every day in the knowledge that I can only take

In a couple of recent posts (here and here) I explored the idea of using dynamic optimisation to deal with the following problem: diversification across markets is good, but requires more capital. That didn't work out so well! I can also appreciate that this is *way* beyond most peoples idea of

This is part two in a series of posts about using optimisation to get the best possible portfolio given a relatively small amount of capital. Part one is here (where I discussed the idea). You should read that now, if you haven't already done so. In this post I show you and explain the code and

This is part one of a series of posts about using optimisation to get the best possible portfolio given a relatively small amount of capital. In this short post I present the idea, and discuss some issues that I need to resolve. It's a bit of a stream of conciousness! It's less of a blog

I've long been a critic of the sort of people who think that one should run a different trading system for each instrument that you trade. It is the sort of thing that makes intuitive sense; surely the S&P 500 is a completely different animal to the Corn future? And that's probably

For the last seven years since I started trading my own account I've pretty much kept the same set of futures markets: around 40 or so, with very occasional changes. The number is limited, as to trade more markets I'd need more capital. The set of markets I have is a compromise between

It's April, which means the birds are singing, the trees are leafing, and I'm doing my annual review of my investing and trading performance. The format will be familiar from previous years, but I'm going to be using the fact I've upgraded my live trading system to include a lot

A few days ago I was browsing on the elitetrader.com forum site when someone posted this: I am interested to know if anyone change their SMA/EMA/WMA/KAMA/LRMA/etc. when volatility changes? Let say ATR is rising, would you increase/decrease the MA period to make it more/less sensitive? And the bigger

When I was a spotty teenager I was a walking nerd cliche. I liked computers; both for programming and games. I was terrified of girls. I was rubbish at nearly all sports*. And I played D&D (and Tunnels and Trolls, and Runequest). * Nearly all: Not, I'm not talking about the

One of the upsides of having a (very, very minor) public profile is that you get a lot of people asking you for advice, which is flattering (and if you say otherwise, you need to consider just how first world that particular 'problem' is). The only downside of this is you get asked the

Risk. Love it or hate it, well as a trader you have to deal with it even though none of us really like it. No, we'd all prefer to be one of those mythical traders you hear about on youtube or instagram who consistently make $1000 a day, and never lose any money. Sadly I am not in that unicorn

As most of you know I have a regular(ish) gig talking on the Top Traders Unplugged systematic investor podcast, every month or so with Niels Kaastrup-Larsen and Moritz Seibert. Anyway on the most recent episode we got chatting about whether open or closed equity should matter when trading a

Remember the handcrafting method, which I described in this series of posts? Motivating portfolio construction Methodology Implementing Testing Adjusting portfolio weights for Sharpe Ratios All very nice, all very theoretically grounded, except for one thing: the 'candidate matrices'.

This is a blog post which has been coming for a while. It relates to a lot of themes I've discussed before, and a recurring conversation I've had with a few people. As most regular readers will know, I run my trading strategy to hit a particular risk target. That risk target is expressed

This is a blog post about forecasting vol. This is important, since as sensible traders we make forecasts about risk adjusted returns (as in my previous post), which are joint forecasts of return and volatility. We also use forecasted vol to size positions. A better vol forecast should mean we end

This is a post about forecasts in trading systems. A forecast is a calibrated expectation for future risk adjusted returns. In more layman like terms, it is a measure of how confident we are about a bullish (positive forecast) or bearish (negative forecast). Perhaps it is easiest to think about

"How does your risk management work?" ... is a question I'm frequently asked. In fact this is actually a difficult question, if you were to look at my open source python backtesting project pysystemtrade, you would struggle to point at a piece of code and say "Behold! Right

Time for the annual review post, as my reviews follow the UK tax year which ended on the 5th April. And what a year it has been; well 10 months or so of fairly normal stuff, followed by several weeks of stomach churning market chaos. Previous updates can be found here, here, here, here and here.

This is the final post in a series aimed at answering three fundamental questions in trading: How should we control risk (first post) How much risk should we take? (previous post) How fast should we trade? (this post) Understanding these questions will allow you to avoid the two main mistakes made

This is the second of three posts aimed at answering three fundamental questions in trading: How should we control risk (previous post) How much risk should we take? (this post) How fast should we trade? (TBC) These questions are extremely important, IMHO much more important than the question of

Stop losses are the most common method used by traders to control risk. However, they're often used inappropriately. In this post I'll quickly bust some of the myths around them, and explain how to use them properly. This is the first of three posts aimed at answering three fundamental

This is part X of my series of blog posts on skew and kurtosis, where 2 A post on skew: measuring, and it's impact on future returns A post on kurtosis: measuring, it's impact on future returns, and it's interaction with skew. A post on trend following and skew (which I actually wrote

In my recent posts on skew and kurtosis I've put together a large number of ideas for possible trading strategies. The next step will be to create and test these ideas out. However I already know from my initial analysis that many of these ideas will probably have poor performance. This leaves

In my last post, I stated my intention to write a series of posts about skew. Slight change of plan, since one loyal reader suggested that I write about kurtosis. I thought that might be fun, since I haven't thought about kurtosis much, and the literature on kurtosis isn't as well

Some bloke* once said "The most overlooked characteristic of a strategy is the expected skew of it's returns, i.e. how symmetrical they are" * It was me. "Systematic Trading" page 40 Skew then is an important concept, and one which I find myself thinking about a lot. So

This month* marks the release of my third book, with the snappy title "Leveraged Trading", and the slightly less snappy subtitle "A professional approach to trading FX, stocks on margin, CFDs, spread bets and futures for all traders". Photo courtesy of Harriman House. As you can

(Both) regular followers of this blog will have been on tenterhooks for many months now, waiting for my next post. I have been busy! First of all, I've been finishing my third book. More detail on that later, in the next post. I've also had a fair bit of holiday time. But mainly over the

Hard to believe, but it has been five and a half years since I had to go to an office to manage other peoples money, and exactly five years since I began systematically trading my own. Time then for another annual review. Perhaps it is confusing for overseas readers, but these reviews follow the UK

Quite a few of my recent blog pieces have been picked up by the lovely folk at allocate smartly. So I thought I'd write an asset allocation piece, as the readers of my second book "Smart Portfolios" probably feel neglected with the lack of articles on investment rather than trading.

In this post I discuss a well known stylised fact of the investment industry: "Trend following is a positively skewed strategy". Spoiler alert: yes it is (sort of), but it's much more complicated (and interesting!) than you might think. A quick primer on positive skew So what actually

This post is all about handcrafting; a method for doing portfolio construction which human beings can do without computing power, or at least with a spreadsheet. The method aims to achieve the following goals: Humans can trust it: intuitive and transparent method which produces robust weights Can be

This post is all about handcrafting; a method for doing portfolio construction which human beings can do without computing power, or at least with a spreadsheet. The method aims to achieve the following goals: Humans can trust it: intuitive and transparent method which produces robust weights Can be

This post is all about handcrafting; a method for doing portfolio construction which human beings can do without computing power (although realistically you'd probably need a spreadsheet unless you're some kind of weird masochist). The method aims to achieve the following goals: Humans can

I've talked around a type of portfolio construction called "Handcrafting" for some time now, in both of my first two books, and in the odd blog post. I thought it would be useful to explain how the technique works in a more thorough and complete series of blog posts, and also share

Let's begin this post with a gross generalisation: Professional traders tend to measure risk and target risk using standard deviation. Amateur traders tend to use a funky little number called the ATR: 'Average True Range'. Both try and achieve the same aim: summarise the typical

I get asked this question at least once a week. As those of you that have met me IRL ('in real life') will know I have limited patience and I'm easily bored. I'm definitely bored of answering this question. This post is the last time I'll answer it. There are broadly two

First an apology. It's been quite a few months since my last blog post. I've been in book writing mode and trying to minimise outside distractions. Though looking at my media page since my last blog post I've done two conferences, a webinar, a book review, a guest lecture, a TV panel

I was moved to write this by a post on LinkedIn, which you can find here, and which is worth quoting (and thanks to Helder Palaro for pointing me at this): "Volatility tends to “cluster”. Recent high(low) volatility is followed by high(low) volatility in the near-term (ARCH). VT says lever

Since I was a young lad there has been an ongoing fight in Financial Academia 'n' Industry between two opposing camps: In the red corner are the Utilitarians. The people of classical finance, of efficient frontiers, of optimising for maximum return at some level of maximum risk. In the