Author Updates
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Blog postIt 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 of instruments. Combine those with a couple of simple trading rules, and you'll have a pretty decent system. Adding additional rules will improve your expected return, but with rapidly diminishing returns.
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Blog post"Today the VIX traded below 10 briefly intraday. A pretty rare occurrence. Since 1993, there have been only 18 days where it traded below 10 intraday and only 9 days where it closed below 10." (source: some random dude on my linkedin feed)
... indeed 18 observations is a long.... long... way from anything close to a statistically significant sample size. (my response to random dude)
You can't move on the internet these days for scare stories about the incred -
Blog postAs you'll know if you've been following any of my numerous social media accounts I spent the weekend in New York at QuantCon, a conference organised by Quantopian who provide a cloud platform for python systematic trading strategy backtesting.
Quantopian had kindly invited me to come and speak, and you can find the slides of my presentation here. A video of the talk will also be available in a couple of weeks to attendees and live feed subscribers. If you didn't attend this will cos -
Blog postIt's now almost three and a half years since I got my last pay cheque and started on my new career as a speculator (also sometime writer, and itinerant consultant), and exactly three years since I started running my fully automated futures trading system, for which my accounting period is the UK tax year ending on 5th April. Which means it's the third in this trilogy of which the first two instalments were:
http://qoppac.blogspot.co.uk/2015/04/futures-trading-performance-year-one.ht -
Blog postThis 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 positions we have. Although the code is rather trivial, interpreting the results requires some understanding.
This is an update of the following post where I used the non native swigib -
Blog postThis 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, but otherwise the post is pretty similar.
We are nearly at the end of our journey of simplistic examples of how to get the swigibpy package to mediate between the -
Blog postThis 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 not the poor attempts at humour.
In my last post we looked at getting a single snapshot of historical prices. In this one we will look at streamed prices - 'm -
Blog postThis is the second in a series of posts on how to use the native python API for interactive brokers. This post is an update of the post I wrote here, which used the 3rd party API swigibpy.
Okay so you have managed to run the time telling code in my last post.
Now we will do something a bit more interesting, get some market prices. Arguably it is still not that interesting, and this stuff will never be as interesting as a decent book or a good bottle of red win -
Blog postUntil quite recently interactive brokers didn't offer a python API for their automated trading software.
Instead you had to put up with various 3rd party solutions, one of which swigibpy I use myself. Swigibpy wrapped around the C++ implementation. I wrote a series of posts on how to use it, starting here.
Although swigiby has been very good to me its always better to use official solutions if they exist. And lo and behold after many people begging them we finally -
Blog postThis post is about a slightly obscure, but very important, issue. Should we use geometric or arithmetic means of returns to evaluate investments?
This might seem boring, but answering this will help us with some other serious problems: Does diversification increase the expected value of your portfolio or just reduce the volatility? If so can we then afford to pay extra costs to get diversification? Does adding a small amount of bonds to an all equities portfolio increase your likely -
Blog postThis post is about using Docker - a containerisation tool - to run automated trading strategies. I'll show you a simple example of how to use Docker with my python back testing library pysystemtrade to run a backtest in a container, and get the results out. However this post should hopefully be comprehensible to non pysystemtrade and non python speaking people as well.
PS: Apologies for the long break between posts: I've been writing my second book, and until the first dra -
Blog postAs the casual reader of this blog (or my book) will be aware, I like to delegate my trading to systems, since humans aren't very good at it (well, I'm not). This is quite a popular thing to do; many systematic investment funds are out there competing for your money; from simple passive tracking funds like ETF's to complex quantitative hedge funds. Yet most of these employ people to do their risk management. Yes - the same humans who I think aren't very good at trading.
As I noted in -
Blog postThis is a two part post which blends my favourite subjects: finance, economics, and politics. It's about the stunning victory of the "leave" campaign that has left the UK facing a period of serious uncertainty.
Part one is an ex-post update on whether my portfolio was as robust to Brexit as I hoped it would be in my last post. This is based on market moves on Friday; of course things will continue to move as the full ramifications are digested.
Part two explai -
Blog postI've had a few questions along the lines of "what are you going to be doing to prepare your trading system for Brexit?" (and I'll admit there is a strong element of bandwagon jumping here). The short answer is nothing. The slightly longer answer forms the rest of this post.
(This is not a post about whether we should be in or out. If you're interested, I'm voting to remain. Rather than retread all the arguments about this I can't do any better than recommend you read -
Blog postThis post is about how should you adjust the trading capital you have at risk given the profitability (or not) of your trading account.
I'm posting this for three reasons. Firstly it's a pretty important topic. I address, in some detail, how to set your risk target for a given amount of trading capital in chapter 9 of my book. I only briefly discuss what you should do thereafter, once the size of your account changes*.
* There was actually a lot more on this in an early -
Blog postBreakout. Not the classic home arcade game, seen here in Atari 2600 version, but what happens when a market price breaks out of a trading range.
The Atari 2600 version was built by Wozniak with help from Jobs exactly 40 years ago. Yes that Wozniak and Jobs. Source: wikipedia
In this post I'll discuss a trading rule I use to look at breakouts. This will be an opportunity to understand in more general terms how I go about designing and testing trading rules. It will be fascinati -
Blog postIn a previous post I showed you how to use my open source python backtesting package, pysystemtrade, to estimate forecast weights and instrument weights. At the time I hadn't included code to calculate costs. Now that has been remedied I thought I should also write some code to demonstrate the different ways you can optimise in the presence of costs.
You can see what else has been included in pysystemtrade since you last checked, here. If you're not a fan of pysystemtrade, don't wor -
Blog postWell time flies. It's a year since I wrote this post:
http://qoppac.blogspot.co.uk/2015/04/futures-trading-performance-year-one.html
... which means it's time I reviewed my second year of systematic futures trading.
Executive summary: Last year was amazing, this year was just excellent.
The money shot
Or to put it in the context of the full period:
So basically a 40% increase, on top of the 57% last year (I don't com -
Blog postI get occasional emails asking me to cover subjects in my blog (keep them coming! I will eventually get round to them). A pretty common one runs something like this:
"I understand that diversification over instruments is the best way to improve returns- you trade almost 40 futures markets, and the likes of AHL and Winton trade hundreds. But how can someone with a small account trade enough instruments?"
This post will try and answer that question. It will also -
Blog postOr why you aren't, and will never be, John Paulson
The systematic versus discretionary trading argument is alive and well; or if you prefer, computers versus humans*. In this post I pose the question - who is better the average systematic trader, or the average discretionary human?
* Though even fully discretionary traders will be relying on a computer at some point; fully manual trading and back office settlement systems not available in modern market.
My -
Blog postThis post serves three main purposes:
Firstly, I'm going to explain the main features I've just added to my python back-testing package pysystemtrade; namely the ability to estimate parameters that were fixed before: forecast and instrument weights; plus forecast and instrument diversification multipliers.
(See here for a full list of what's in version 0.2.1)
Secondly I'll be illustrating how we'd go about calibrating a trading system (such as the one in ch -
Blog postI've just added the ability to estimate forecast scalars to pysystemtrade. So rather than a fixed scalar specified in the config you can let the code estimate a time series of what the scalar should be.
If you don't understand what the heck a forecast scalar is, then you might want to read my book (chapter 7). If you haven't bought it, then you might as well know that the scalar is used to modify a trading rule's forecast so that it has the correct average absolute value, normally 1 -
Blog postThere are already many python packages where you can back test trading strategies. Some of them also include a framework for automatic execution and complete position management.
I can't give an exhaustive list but I'll pick out:
- Quantopian's zipline
- BT
- pythalesians
- pyalgotrade
There is a longer list here.
Does the world really need another one? Well, probably not, but today I've released one anyway (thi -
Blog postEveryone knows that the usual naive method of portfolio optimisation is, well, a bit rubbish. This isn't because the method is flawed, but it relies on the inputs being 100% accurate, or to put it another way we need to know precisely what the mean, volatility and correlation of future returns are going to be. But most peoples crystal balls are somewhat foggy.
Fortunately there are a few methods we can use to deal with this problem. Some of these are straightforward; like the handcr -
Blog postJust a quick post today. As most of you know until a couple of years ago I worked for a large systematic hedge fund. Now I manage my own money. I'm doing similar things (systematically trading futures, with a holding period averaging a few weeks, and a variety of trading rules with a trend following bias).
An interesting question, which I'm often asked, is can a little guy like me compete with a giant behemoth of a fund? Should we little guys just give up? After all surely a huge fu
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