Monday, 25 April 2016

The skill of New York

01:07 Posted by The Thalesians (@thalesians) No comments

Buildings race with one another, aiming to touch the sky. Joggers throng the park, the feet tapping down one after the other. Spring blossoms, the park lives once more. Horns beep, the sounds crisscrossing the grid of streets. Food carts on street corners, with the smell of warm pretzels and kebab in the air. Yellow reflections of taxis sprint along the windows of shops. Ocean waves curl up to spring aboard the shore. Pedestrians walk, a certain purpose appears in their step. This is New York.

What makes New York, this amalgam of people, images and sounds so successful? I'm far from an expert on New York (I've never lived there, although I've visited on numerous occasions and am writing this note from there). Potentially one reason is simply that the city is so varied. There are so many diverse groups of people who live in New York. It is a truly international city. The geography of the city is diverse. Yes, it might be a city which is well known for finance, but it also has other industries supporting the economy, with a strong tech startup scene.

Within a trading environment, it might seem that being good at one thing, namely trading is the way forward. However, trading in itself requires many different skills. If we focus on systematic trading, it cannot simply be defined as a technology problem. Yes, a good systematic trader needs to be able to code. For more complex strategies, such as high frequency trading, the ability to write very fast code becomes paramount. However, approaching it purely as at a technology problem, ignores the fact that trading is about markets, and interacting with markets. In a way, it's like suggesting that if you are very dextrous and have strong hand eye coordination today, you should be able to perform surgery, somehow ignoring, the matter of needing medical knowledge!

Systematic trading needs a diversity of skills. Is having a strong background in coding and markets difficult? Yes it is! Just as New York's success might be explained by its differences, a successful systematic trader needs to have a diversity of skills.

Like my writing? Have a look at my book Trading Thalesians - What the ancient world can teach us about trading today is on Palgrave Macmillan. You can order the book on Amazon. Drop me a message if you're interested in me writing something for you or creating a systematic trading strategy for you! Please also come to our regular finance talks in London, New York, Budapest, Prague, Frankfurt, Zurich & San Francisco - join our Meetup.com group for more details here (Thalesians calendar below)

12 May - New York - Luis Seco - Are Negative Hedge Fund Fees on the Horizon?
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives
20 May - London - Martin Bridson - Knots and what not

Sunday, 17 April 2016

Proof's in the data scientist pudding

15:25 Posted by The Thalesians (@thalesians) 1 comment

I am defenseless in the face of those titans of confectionery, chocolate and cake: the sweetness of sugar, the butteriness of butter, the milkiness of milk (I was attempting to choose words to make you, the reader, as hungry as possible). The cause I presume, is my sweet tooth. I realise that this is a somewhat circular argument, yet it nevertheless helps to absolve myself of a certain modicum of responsibility.

Whilst I am more of an expert at consuming sweets, I also occasionally dabble in their creation, with varying levels of success. Usually, I stick to the easier to bake items, such as cookies or brownies. Admittedly, I have yet to master the more visual element of baking, a particularly polite of saying whatever I bake does not really look that nice. However, the end result of my baking efforts seem at least to be successful from a taste perspective.

Does that mean, that I could try my hand at baking macarons, with an automatic guarantee of success? I know the answer is no. The complexity of baking macarons is far greater than that of the humble brownie (from personal experience). Whilst, there are common skills in baking, at the same time there are often specific skills that need to be honed for specific bakes. In other words, these skills are very domain specific.

Data science is a fashionable new term for a mixture of several disciplines, including statistics and programming, as well the ability to display results in an innovative manner, using visualisation tools. Very often data scientists can end up working with unstructured datasets, which take time to clean up and process. Data science is precisely like baking (well in some ways, just bear with me for a few sentences). A few days ago, I tweeted what I thought a data scientist was, namely someone who is both excellent at statistics, but is also adept at coding. There can be a misconception that a data scientist, can simply get by with a bit of stats and the ability to cobble up a bit of Python. I strongly disagree with that notion!

However, in response, one my Twitter followers (@macroarb) noted that data scientists also need some domain specific knowledge, a point that I had casually overlooked. Thinking about this a bit more, if anything, domain specific knowledge is perhaps the most important part of a data scientist's toolkit. After all, it is domain specific knowledge which enables you to ask the right questions from your dataset. In my case, my domain specific knowledge is centred towards systematic trading.

Hence, before even indulging the number crunching of a specific dataset, I form a hypothesis of what I am trying to find in it. Of course, sometimes my hypothesis can be totally discounted by some statistical work, which can actually be an important result. It's far better to know that a trading strategy doesn't work, than mistakenly thinking it is profitable and end up losing money on it. On other occasions, I will be able to find results, which can confirm my initial hypothesis.

If you have no hypothesis, where do you even begin to start when analysing data? Of course, you can keep searching through the data, and perhaps you'll eventually find something. However, is that result going to be robust? I suspect not. If you have no domain specific knowledge, it can be difficult to ask the right questions! Just because I can bake brownies, it doesn't imply I can make macarons successfully!

So next time you try your hand at baking, remember, in some ways you're exactly like a data scientist, the proof's in the data scientist pudding!

Like my writing? Have a look at my book Trading Thalesians - What the ancient world can teach us about trading today is on Palgrave Macmillan. You can order the book on Amazon. Drop me a message if you're interested in me writing something for you or creating a systematic trading strategy for you! Please also come to our regular finance talks in London, New York, Budapest, Prague, Frankfurt, Zurich & San Francisco - join our Meetup.com group for more details here (Thalesians calendar below)

20 Apr - London - Jacob Bartram - Can option trading strategies enhance CTA/trend following
12 May - New York - Luis Seco - Are Negative Hedge Fund Fees on the Horizon?
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives
20 May - London - Martin Bridson - Knots and what not

Sunday, 3 April 2016

When learning was history

19:14 Posted by The Thalesians (@thalesians) 1 comment

Lounging about on Saturday afternoon, my mind seems less honed to thinking, and more adept at wondering away the hours, a boat seemingly poised to eventually land at the shores of the asleep. However, rather than surrender to sleep, I thought it best to try my hand at writing this blogpost.
As ever, the main challenge is not so much writing it, but working out the subject! Rather than thinking up a subject myself, I tweeted suggestions for ideas. One of my followers @grodaeu suggested writing about a historical figure (although, I think the suggestion was somewhat tongue in cheek). His reply nevertheless (together with the book I'm reading) gave me an idea, why not write about history in an abstract sense. Why do we write so much about history?

In a sense, understanding our past might well shed light on our future. Whilst, technology might change from age to age, there is often a common thread which binds us with our ancestors. I'm currently reading a book on the French Revolution and Robespierre. I can hardly claim to be an expert on this period of history, or indeed any. However, what struck me was that many of the motivations which drove the revolution, would not be out of place today.

From the point of view of markets, we could argue that motivations for investors has not changed over the years. Investors actively seek to make a profitable return. How this is achieved is obviously a different question!

The notion of high frequency trading has only come about through the widespread adoption of electronic trading for example. However, one thing that hasn't changed is the need to have a well thought out hypothesis behind a trade. We also use our own histories (or perhaps better put our experience) to view the market. Statisticians use historical data to generate more quantitative descriptions of the past.

Indeed why investors should look to history is a subject which I wrote about extensively in my book Trading Thalesians - What the ancient world can teach us about trading today. Your experiences will impact how you see future events. A trader who experienced the Lehman crisis is likely to behave in a different way when stocks fall, compared to a trader who hasn't.

History might not be able to tell us precisely what the future holds (and perhaps lead us to mistakenly believe that the future will be identical to the past), but it can help us to understand in more abstract way to approach problems.

Like my writing? Have a look at my book Trading Thalesians - What the ancient world can teach us about trading today is on Palgrave Macmillan. You can order the book on Amazon. Drop me a message if you're interested in me writing something for you or creating a systematic trading strategy for you! Please also come to our regular finance talks in London, New York, Budapest, Prague, Frankfurt, Zurich & San Francisco - join our Meetup.com group for more details here (Thalesians calendar below)

14 Apr - New York - Lawrence Glosten - Limit Order Book Tail Expectations (Thalesians/IAQF)
20 Apr - London - Jacob Bartram - Can option trading strategies enhance CTA/trend following
12 May - New York - Luis Seco - Are Negative Hedge Fund Fees on the Horizon?
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives
20 May - London - Martin Bridson - Knots and what not