Saturday, 11 June 2016

Ferris Bueller's Day Off (& memories)

18:02 Posted by The Thalesians (@thalesians) No comments

Today is the 30th year anniversary of the release of the film, Ferris Bueller's Day Off. I wouldn't have realised without seeing a plethora of tweets from @grodeau and many others on Twitter. It's one of those films, where the title, is wonderfully descriptive. It is literally about Ferris Bueller's Day Off. Rather than spending a day attending his high school, Ferris Bueller (Matthew Broderick) spends it with his girlfriend Sloane Peterson (Mia Sara) and best friend Cameron Frye (Alan Ruck) generally misbehaving in downtown Chicago and driving around in a classic Ferrari (which is quite spectacular: I've always been somewhat of a car enthusiast!). I'm not quite old enough to remember the film being a cinemas, although, I do recall seeing it on TV in my younger days. However, watching clips of the film back today, memories have come flooding back and I can somehow remember a lot more of the film, than I would have thought. The memories have lain there in my mind undisturbed for years, waiting to be triggered.

In a sense, we probably know a lot more than we think. This is just as true in markets. Our brains are overloaded by masses of market information and events. We might not always be able to recall these in full detail, like my Ferris Bueller example, but they nevertheless often leave an imprint on our mind, that can influence how we behave. One particular example might be how traders interpret Fed meetings. Very often, they will recall how markets might have traded in the past, when similar language was used. Obviously, we can "extend" our memory by doing research and using systematic methods to trade markets. Inevitably experience has a value, which cannot simply be "replicated" by doing number crunching to find patterns. I would argue that the combination of experience and using quantitative techniques does however add massive value.

Experience enhances our ability to see patterns related to past events and can help us understand, where quantitative analysis of markets can be useful. Furthermore, it aids us in splitting the spurious patterns from those which might be significant. Experience helps us prune our search space, and allocate our market research time in the best manner. We unfortunately only have finite time to research markets, so coming up with the right questions to ask is important, we need to be able to end up answering at least some of these questions.

The danger in markets is thinking we know *more* than we think. It's in that situation, that we are tempted to take too much risk. So perhaps from that perspective, thinking we know less than we think might be a good thing!

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)

16 June - New York  - Tobias Adrian - Nonlinearity and Flight-to-Safety
29 June - London - Steve Hutt - Recent Advances in Deep Learning and Applications to Market Data

Saturday, 28 May 2016

Complex simplicity

15:16 Posted by The Thalesians (@thalesians) No comments

Our memories love stories. A narrative finds a place in our thoughts far more easily than some abstract fact. I can remember numerous stories from my university days. However, I might struggle to recall a precise mathematical proof I learnt in a lecture. Indeed, I was recently thinking about the interplay between complexity and simplicity when solving problems (I also recently wrote about a related subject). Thinking about this, made me recall a potentially apocryphal story I had heard a few years ago, told by one of my friends. My friend recalled an interview of Truman Capote, the American novelist, famous for a several books including In Cold Blood, a novel based upon a real crime committed in Kansas, which I've read myself.

The interviewer was berating Capote for the speed of his writing, noting that Capote might sit for hours resulting in only a single word of output. Capote reply was perhaps the best you could think of, along the lines of "But it was the right word". It illustrates how so much time and effort can go into what appears superficially as something very small. Having written a book myself, I can sympathise with the Capote's sentiment. The reader of any book simply sees the output, as opposed to the hours obsessing over sentences, editing and rewriting. Language which simply flows effortlessly from sentence to sentence somehow has the quality of appearing natural and somehow easy to write. The complexity of the process of writing good prose masquerades as simplicity. Of course this masquerade is not purely something seen in writing.

The same can be seen when trading the market. All we want is a binary decision ultimately buy and sell. As we all know the complexity in making this binary decision is enormous. Not only do we need to choose the right direction, we need to understand how much risk we allocate to it, we have to have the right timing, we have to make sure the trade fits into our portfolio etc. The list is unfortunately far from short. It also also something which I've observed in working as an independent. Having the ability to make your own decisions might appear to simplify your work, because you can choose your path. The difficulty is freedom to make your own decisions, also means an outsized ability to make the wrong decisions (something that I have learnt on numerous occasions!)! Within a large organisation, it is of course still possible to make mistakes, but to some extent a lot of your decision making will be shared with other individuals, so there are effectively fewer options to choose.

When something seems simple it might be a lot more complex than we initially think. Making it look easy is the complex part.

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)

09 June - Zurich - Felix Zumstein - Python in quantitative finance
16 June - New York  - Tobias Adrian - Nonlinearity and Flight-to-Safety
29 June - London - Steve Hutt - Recent Advances in Deep Learning and Applications to Market Data

Saturday, 21 May 2016

Celebrating 1000 days of independence

15:42 Posted by The Thalesians (@thalesians) No comments

Time is wonderfully eclectic. The present sprints on, a fleeting flash, the past clings on in memory, the future, that world of the unknown, waits to be fashioned by the sweeping hands of chance, a realm where perhaps fortune or disaster beckons. Repeatedly, the past transcends into present, reminding us of its passing. There is a certain human obsession with anniversaries, the time when the past barges most forcefully into the present. Whilst we might celebrate anniversaries, which coincide with multiples of years, those relating to a multiple of days are usually simply ignored. It is rarely the case that anyone points out when 1000 days have passed since a certain event was plucked from time. After all, it constitutes 2 ¾ years, a duration of time which hardly bears any significance from any astronomical viewpoint. In that case, why do I seek to draw attention to 1000 days as a specific anniversary?

This week, I noticed by pure chance, that it has been 1000 days since my career abruptly changed. It was 1000 days ago, that I resigned from my job at Nomura to embark on being a full time entrepreneur at the Thalesians, an organisation had co-founded several years earlier in 2008, initially to host quant finance talks. I had spent years building up systematic trading strategies in several large institutions. Rather than doing this in an investment bank, I was seeking to do this as an independent entity. How difficult could it be?

There is little I could have predicted on this journey, neither the successes nor indeed the numerous failures. It all seemed so obvious when I resigned from my job. I thought that I knew precisely what I would do to make this endeavour a success. However, what I have learnt in these 1000 days, is that very little is obvious or predictable, when undertaking a totally new project. Whatever vague plans I had inside my head 1000 days ago, have dissolved under the weight of pragmatism. Events are the master of every well intentioned plan (or indeed lack of plans).

I under appreciated the role of chance, for example a chance meeting, and overstated the role of hard work. This is not to say that building a business makes you a servant to chance and hard work is dispensable. A chance meeting with a client will only happen, if you go out and try to engage with people, attend conferences, visit clients and present your work. All of this is indeed hard work, but not necessarily the type of work I had envisaged. I had previously thought that the vast majority of my time would be spent on researching trading strategies, coding them up and testing them. Whilst I do spend a large part of my day doing analytical work, I devote a large proportion of my time interacting with clients, doing marketing and travelling.

If clients are unaware of you, there is no chance of engagement. Marketing in all its forms gives you a better chance of engaging. Yes, social media might be a way to broaden your viewpoint and I would strongly recommend using Twitter and LinkedIn. But ultimately a relationship is not built of 140 characters, but in actually meeting people in real life. At the beginning I was working either at my home or more often, a Starbucks and in retrospect whilst it was ok for the first few months, particularly when I was writing my book, it later became far too much of a hindrance. Later, I was accepted to join Level39, a fintech accelerator based in Canary Wharf. Having other startups developing around you, albeit often with very different business models, has been a fantastic experience and has been a great way to meet folks. It also makes you realise that many other people are in a similar situation to you. The view from Level39 isn’t too bad too (see sunset image above).

There is the cliché which states “failure is not an option”. In practice, failure is the default option. Most of what you try will fail. Through the course of your business, you will meet many potential clients. Most of these people will not become clients. Far from seeing this as failure, it is a necessity to find the clients who really find value in your work. Each meeting is a learning experience, and particularly valuable for getting feedback. From a research perspective, hearing what smart folks think about my work has been crucial in helping to improve it. Also seeking to understand what clients have wanted, has been important. This has led me to pivot from purely offering research on systematic trading to doing bespoke client projects, running workshops and also building a software framework for developing trading strategies (PyThalesians, an open source project available on GitHub). In a sense, I have been lucky that I have been active at a time of the burgeoning data science scene and the use of Python. Many of the projects I have been involved in have involved Big Data, and seeking to understand how it can be used to generate alpha.

Along the way, there were numerous times when I questioned my decision to jettison the relative safety of a bank for a startup, particularly at the initial stages, when most of my time was devoted to building an analytical framework for my work and writing a book about markets.

However, I am glad that I have persisted on this project during the past 1000 days. I have learnt a huge amount during this time and developed new skills. I have built up an array of clients both from hedge funds and a number of data companies. I have now got to a stage where the business is sustainable and growing organically without external funding, save for my own trading income which I’ve used to seed the endeavour.

Yet there is still far more to go in terms of establishing the business and indeed, I suspect there always will be. Would I have done some things differently? I am sure I would have done, although, I am still of the belief that it was the right decision to pursue an independent path, even if has been far more difficult than I had ever envisaged.


Let us see what the next 1000 days hold. Time will pass, it is time to grasp its opportunity. 

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)

25 May - London - Paul Bilokon - How to run electronic market making business?
09 June - Zurich - Felix Zumstein - Python in quantitative finance
16 June - New York  - Tobias Adrian - Nonlinearity and Flight-to-Safety

Tuesday, 17 May 2016

​Teaching others & also learn yourself

13:48 Posted by The Thalesians (@thalesians) No comments

The premise of this article might seem odd. The primary objective of teaching is to teach others and to help them to learn. However, very often the process of teaching itself can also help the teacher to learn. Precisely how, is something I shall elaborate on during the rest of this article!

I recently came back from Budapest (photo above is of St. Stephen's Basilica in Budapest) after teaching with Paul Bilokon at a Thalesians' workshop at on systematic trading and market microstructure. We tried to mix both maths and theory, with some practical examples, including going over how to implement a simple trading model in Python using the PyThalesians library. I enjoyed the whole experience of teaching very much, as did Paul. The workshop was part of the annual Global Derivatives conference, an event which has been part of our annual calendars for several years.

The most important question I wanted to ask the students, was how did they benefit from the course and also to understand both what they liked (and disliked about it). Of course, I would hope there were many more points in the "like" category! Teaching at the workshop did in a way make me want to ask also another less obvious question, this time for myself: what did I learn from the whole experience of teaching?

One of the biggest challenges was in the preparation of the course. Trying to give attendees a crash course in any area which is very broad (eg. systematic trading in this case) is always tricky. The difficulty in preparing the course is not so much in attempting to decide what to put in, but rather what to leave out from areas of my research! In other words, what were the key elements of the subject I wanted students to know? Paul gave me an excellent quotation from Pascal which seemed to capture this point exceptionally well:

If I had more time, I would have written a shorter letter

The whole process of distilling down a subject area into its most important parts is in itself a learning process, and helps to crystallise the subject more clearly in your mind. When delivering the material to an audience, their participation is also important: they will very often ask questions you will have never thought of, which you, the teacher can learn from, even if it's a subject you know well. Different audiences will ask different questions.

The interactive element can also extend to doing worked exercises, for example going through small coding examples from scratch. The whole experience of writing code live can benefit student and teacher alike!

Perhaps, most important of all, teaching is fun and very satisfying when you see your students learning something new. That after all is the main point of it. But if you the teacher can also learn along the way, that's even better!

If the idea of a Thalesians workshop on systematic and electronic trading sounds fun, maybe we'll organise another one soon!

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)

25 May - London - Paul Bilokon - How to run electronic market making business?
09 June - Zurich - Felix Zumstein - Python in quantitative finance
16 June - New York  - Tobias Adrian - Nonlinearity and Flight-to-Safety

Sunday, 1 May 2016

When I (nearly) met Warren Buffett

01:18 Posted by The Thalesians (@thalesians) No comments

"Welcome to Omaha", reads the small sign in the airport which greets you when you land there. Walking through the cobbled streets of the Old Market district, it is hard not to conjecture up images of the saloons of the old west. Shops sell cowboy hats and cow skins. Nebraska steak is the food of choice here and it something for which the state is famous. Dine in a swanky London steakhouse, and it is likely they will serve steak from Nebraska, with a somewhat excessive markup.

Whilst in population terms, it is "small" with around 400,000 inhabitants, it occupies an area quarter of the geographical area of New York City, which boasts nearly 20 times the number of people. When it comes to finance New York City, the image of Wall Street looms large. Most banks have moved out of Wall Street, nearby in downtown or more commonly in midtown. Meanwhile, hedge funds are dotted all around Manhattan and further afield in Connecticut. Yet, it is still Wall Street we associate with the finance industry. Sitting here in a Starbucks in Omaha, writing up this note, Wall Street seems far removed from Nebraska. At the same time it is to this city, that the folks flock to each spring, to hear the Sage of Omaha, Warren Buffett and his business partner, Charlie Munger at the Berkshire Hathaway shareholder meeting talk. Visitors to the meeting included Bill Gates, who is on the board.

This was the first time that I have attended the Berkshire Hathaway meeting. The obligatory downpour whilst queuing to enter did little dampen my spirits, nor my fellow shareholders (to attend, a single stock is sufficient, or you can pick up tickets from eBay). As well as the shareholder meeting, there is also an exhibitor hall, where you can see products from companies owned by Berkshire Hathaway which range from industries as diverse as railroads to candies and buy souvenirs (Warren Buffett is rarely one to give up a business opportunity). The exhibition area is also probably your best chance to catch a glimpse of the great man himself. I managed to sneak in the photo above in the exhibition area, which was the closest I came to actually meeting him (!), amidst a scrum of selfie seekers and photographers.

The shareholder meeting lasts all morning and much of the afternoon, starting with the Berkshire Hathaway movie, which included all sorts of celebrity cameos. Whilst nearly 20,000 shareholders attended the meeting in person, for the first time ever, Yahoo streamed this one online out to a worldwide audience.

The meatier part of the event, began with a brief review of Berkshire Hathaway's performance recently. Throughout, Buffett, stressed that he was always keen to look at long term performance, rather than short term fluctuations in particular with respect to their derivative exposure.

Next, Buffett and Munger answered questions from both journalists and the audience, which discussed a wide range of subjects on their business. What came across was Buffett's enthusiasm to see investing through the prism of owning a business. As Buffett put it:

Figure out what makes sense. when you buy a stock, think about it as a business. Don't get into a stupid game just because it's available.

Both Buffett and Munger relished the microeconomic element, in understanding particular companies rather than macroeconomic element of investing, which obviously still impacted their businesses during cycles. Buffett and Munger confessed that it is very difficult to predict macroeconomic trends. Munger quipped, that "Microeconomics is what we do, macro is what we have to put up with!" For someone with a particular interest in currencies, like myself, if anything, it is the macro part which I find exciting!

In terms of making decisions, Buffett has more often than not, been on the right side. He attributed a lot of this in the ability to pattern recognition both in terms of picking the right investment but also avoid bad ones. He gave a specific example of Valeant, which he did not invest in (and which proved popular amongst some in the hedge fund community). Munger was more blunt calling Valeant a "sewer".

Answering a question on why he believed he was successful Buffett said that:

I owe a great deal to Ben Graham and Charlie. Also been around a lifetime looking at businesses see how some work and some. Yoga Berra said you can see a lot by observing.. Recognise what you can't do (such as department stores in my case)

He also said noted that, smart people are not averse to making mistakes, saying that:

You don't need IQ in investment business that you need. You do need emotional control. Seen very smart people doing something stupid, for example successful people over leveraging.

The difficulty with success in trading that it can lead to overconfidence, and hence the temptation to overleveraging.

In terms of his longer term expectations, listening to Warren Buffett was like hearing the antithesis of Zerohedge! Whilst he noted that his businesses would be impacted by the business cycle, in the long term America's businesses would do well. He noted that during the period of low rates, whilst savers investing would have picked up very little, returns for investing in American businesses had been healthy.

Buffett stressed was importance of compounding returns, which can have a massive effect in the long term, even if in the short term the impact might seem less significant. Indeed, Buffett has benefitted significantly from this. He was also scathing of the use of advisors, who might make suggestions purely for the sake of a change. He noted that changes in the way that he does his due diligence would not have prevented mistakes he has made. Buffett said:

We made plenty of mistakes in acquisitions and in not making them, mistakes about future conditions of economic, sector etc. I've not found a due diligence list that gets at real risks of a business. None of our mistakes would have been cured about doing more due diligence. Bad apples are out there. You won't find these with checklist.

Another element to Buffett's success is being able to use his insurance company as a massive float, has helped to fund the rest of his business, something he discussed at length during the meeting. He did note that persistently low rates could have an impact on his insurance business. He has already reduced exposure to European reinsurers, noting the negative rates at present in the eurozone.

Obviously, not all of us have Buffett's advantages of having a very long term investment outlook. Also everyone has their own way of investing and particular niche, which might not fit the Buffett template (including mine, which are tilted towards macro assets . However, if more investors followed his advice, I suspect they'd be much happier. When asked where both Buffett's and Munger's sense of humour came from, Munger joked:

If you see the world the accuracy it's bound to be humorous because it's ridiculous

I suspect that is the line that I will take away from my visit to Omaha! If you do get an opportunity to go to the 2017 meeting, I would thoroughly recommend going!

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)

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

Saturday, 26 March 2016

Music to benchmarked ears

20:00 Posted by The Thalesians (@thalesians) No comments

There are some days, which I never thought would come. An example of one such day arrived years ago. It was the day, when I simply had no idea which artist was at the top of the music charts. This state of affairs has persisted to the current day: today, I have absolutely no idea who is at the top of either the Billboard 100 or the UK Top 40...

It would however, be wrong to equate this is to a lack of interest with music. I love music just as much as I did a decade ago. Browsing my main playlist, which I have unoriginally called the "Thalesians Mix", which I periodically add my favourite tracks, I see the names Taylor Swift and Ed Sheeran, juxtaposed with David Bowie and Bob Dylan, with a modicum of Tom Petty, The Beatles and topped by a hint of Green Day, interspersed with all manner of musical genres. Is this a "right" playlist? Well, it seems right for me, judging by the fact that I seem to gravitate towards listening to this playlist in its entirety at least several times a week. Whether it is right for everyone else, is an entirely different question, I am quite sure there are some tracks on my playlist, which you the reader, would not like. 

I strongly suspect, that my taste in music seems far more eclectic when judged against the "benchmark" of the music charts. I don't feel the "benchmark" of the current music charts is right for me. Of course, I might like one or two current tracks, but I can never see myself listening entirely to purely new songs and dispensing with the old.

The notion of benchmarks in finance is a fraught subject. Whenever you invest, what should be the yardstick for how you judge your performance? Should investors be purely judged by how they beat (or miss) a benchmark which is the "market"? A recent paper, Curse of the benchmarks, by Dimitri Vayanos and Paul Woolley attempts to answer this question (thanks @george_cooper__ and @PolemicTMM for tweeting this paper to my attention). They suggest that trying to use market cap weighted benchmarks (which is often considered as the market) ends up causing

the inversion of the relationship between risk and return so that high volatile securities and asset classes offer lower returns than low volatile ones

A far better way of judging investors, they suggest, is to try to compare them with their peer group adopting a similar trading strategy, rather than the approach of using market cap benchmarks. More broadly, the matter of precisely how to create targets for your investment, will differ between investors. What is an acceptable drawdown is not acceptable for one investor might well be too much for another. The idea of how much risk a trader should take will differ between mandates. I wrote a chapter on both the matter of risks and investment targets in my book, Trading Thalesians, if you'd be interested in reading more.

So whether it's music or investing, if you do have a benchmark, we first need to consider this: is it the right one? Most important does having the wrong benchmark end up changing your strategy for the worse! In the meantime, I keep listening to the music.

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

Saturday, 19 March 2016

Go-ing with quant trading

15:04 Posted by The Thalesians (@thalesians) No comments

When I think of the word "go", I think of its meaning according to the Cambridge Online Dictionary (written below):

go
verb UK ɡəʊ US ɡoʊ (present participle going, past tense went, past participle gone)
      
go verb (MOVE/TRAVEL)
A1 [I usually + adv/prep] to ​travel or ​move to another ​place:

This week, the word "go" was in the headlines for totally different reasons. Lee Se-Dol the best human player in the world at Go (the Chinese Chinese board game) was beaten by Google's AlphaGo artificial intelligence system. Whilst, chess champions have been beaten in the past, it was thought that it would take at least a decade more for them to accomplish the same thing in Go. Indeed, if you are interested in this topic and are based in London, I recommend you come to Robin Hanson's talk at Thalesians London on economics and robots on March 21st (free tickets)

Perhaps unsurprisingly, it has focused peoples' minds on what other things a computer can do, in areas which have been traditionally required humans. One such area is trading. Trading has seen a massive proliferation of technology. Systematic traders have been trading in markets for many years. Obviously, over the years, the increased processing power of computers and the greater availability of data has increased the types of trading strategies, which can be explored by systematic traders.

What is perhaps a fallacy though is thinking that systematic trading is a matter of computers trading in total isolation from humans! People still have to code up the algorithms executed by computers. Indeed, humans have to come in when a computer's trading algorithm goes wrong.

A computer doesn't understand "why" it is executing code, it simply does it. It can of course calculate all the trading signals, work out the P&L and even execute the trades, without a human touching a system. However, a computer cannot tell you whether you should trade a certain strategy or if there is theoretical basis for a strategy. In a sense, whilst systematic trading reduces the need for day to day decision making for every trade being executed, it increases the process of discretion you need to use on a more strategic level. In particular, this strategic "discretion" comes in, when you are developing the trading strategy and coming up with new ideas to add to your system. Your logic when putting together the model has to be very clear. Any mistakes at this level, will unfortunately persist, when the system goes live.

We sometimes think of systematic and discretionary trading as very different concepts, but in a sense they do share so many similarities. The main difference between them is at which points we employ our discretion.

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)

21 Mar - London - Robin Hanson - Robin Hanson, Economics when robots rule the Earth
23 Mar - Frankfurt - Miguel Vaz -  Finding structure in financial data: from point clouds to graphs
20 Apr - London - Jacob Bartram - Can option trading strategies enhance CTA/trend following
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives
20 May - London - Martin Bridson - Knots and what not

Saturday, 12 March 2016

Excelling with & without Excel

14:18 Posted by The Thalesians (@thalesians) No comments

Travel does many things. The cliche tells us that it broadens the mind. Holidays are the tonic for the whispering monotony of the routine. Yet a holiday is never purely a matter of joy. Within the idea of holiday are bound up the logistics of transportation. None of us book a holiday for the experience of being squeezed on to a flight for hours, at the mercy of delays and heavily processed airline food. However, being able to get to our destination, is a necessary part of any holiday to far away places. Of course we could forgo that long airline journey, but then we'd forgo those sandy beaches, beneath the sunny rays of heat, and instead settle for staying at home.

When trying to analyse markets, we are in a way faced with similar conundrum. We want to find some novel and interesting way to look at market data. However, very often this route is laced with an Excel spreadsheet! Sometimes this approach can work very well, in particular given Excel spreadsheets are the preferred way to share ideas with traders.. but as soon as you have just a bit more data there, a spreadsheet can become unbearably slow to recalculate. Furthermore, when the complexity of your analysis rises, a spreadsheet can become increasingly unstable and easy to break. 

In a sense, there are only certainties in life for a quant researcher: having to use Excel and moaning about having to use Excel. I have to say that I have at times, used Excel far more than perhaps I should have done. One reason is that it makes it easy to explore simple ideas. The difficulty is that very often simple ideas, become very complicated very quickly! Whilst it might save time to use Excel initially, it makes it more difficult to reuse analysis and cost you in the longer term. As for using big datasets like news data, Excel is basically unworkable. Hence, it limits the type of analysis you can do.

To try to get past the issues with Excel, I started writing PyThalesians, an open source Python financial library over a year ago. I wanted to streamline the bulk of my analysis. Rather than reinventing the wheel every single time each time I want to do a new sort of analysis, I've tried to write functions of commonly used financial analysis. These can easily be used again and again, with small modifications. I've now written functions to do basic backtesting of trading strategies, plotting, and market data downloading from many sources including Bloomberg. In particular, I've tried to focus on making the various components interchangeable. Want to change the data source you're using? Just a few lines of code need to be changed, not the the details in your trading algorithm. Want to change how you plot your results? Again, just change a keyword in your code. I've designed the code from the perspective of my experience as a quant researcher and someone who enjoys coding, as opposed to purely looking at it as an IT problem to be solved.

Along the way I've utilised many great open source libraries such as pandas (time series), NumPy (mathematical computations), matplotlib, bokeh and plotly (plotting). Since it's open source, I'm hoping over time, that if users find it useful, they can contribute their own improvements to the library too. We can also blend the two solutions using libraries such as xlwings, which allow us to call complicated calculations in Python and display the results in Excel. In this way, traders who love Excel can still create funky models in Python, but fall back in the familiarity of Excel.

So ok, we often moan about having to use Excel (including me!), but sometimes we can excel both with and without it, if we use a bit of Python (and hopefully PyThalesians!)

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 Mar - San Francisco - Quant Fintech Mixer Event
15 Mar - New York - Thalesians/IAQF - Alex Lipton - Modern Monetary Circuit Theory
21 Mar - London - Robin Hanson - Robin Hanson, Economics when robots rule the Earth
20 Apr - London - Oskar Mencer - FRTB, RWA, XVA, Scenarios, MiFiD II, fast?
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives
20 May - London - Martin Bridson - Knots and what not

Saturday, 27 February 2016

Miami twice as bearish

15:26 Posted by The Thalesians (@thalesians) 1 comment

So why did the title of this article include the words "Miami twice"? I suppose it does sound like the TV show Miami Vice (well, actually that was the main reason). I can't remember much about the show aside from the white suits, sunglasses and the 80s music, perhaps because, I was always much more a fan of the A-Team during that decade of shoulder pads and forgettable music. 

Before I visited Miami over the past week, I already had this vague image in my head of what to expect: the smell of oranges, the sight of the sea and the sound of Spanish, all somehow coalesced into a single snapshot, with the backdrop of whitewashed Art Deco buildings straddling the image. What I had not quite anticipated, was the serenity of the sunrise casting its shifting gaze over the beach. If you ever do go to Miami, I strongly recommend waking up earlier than you might ordinarily do to witness this.

Much of my time, however, was spent inside at the TradeTech USA FX conference, rather than watching the waves roll on beneath the sun. Whilst the sun was shining outside, the mood inside the conference was perhaps less than shining. A bearish mood pervaded most of the conversations during the conference. This was perhaps not unique to conference. In general, within the market, there seems to be a general perception that we've reached a stage where central banks are out of rope, epitomised by the move negative rates, the latest stage of easing. The recent market reaction following the BoJ's move to negative rates seems to tally with this. One interesting point raised by Steven Englander from Citi, during his conference presentation, was that potentially the markets have underestimated the creativity of central banks in coming up with solutions. 

To some extent, I have to agree with Steven's point, particularly when we consider how central banks have reacted following the financial crisis. They have been somewhat more creative than they were during previous crises, notably following the Great Depression. At present, it has become quite fashionable to be outright bearish. The market can often be "right" and it's a reason why trend following is a profitable strategy and why long only strategies have historically been profitable, albeit with some volatility. However, once the cacophony of market bearishness becomes overwhelming, the risks have evolved from being a black swan style event to merely a grey swan type of event and potentially the market will have overpriced the event. If everyone is expecting a disaster, then arguably market positioning will be skewed that way and if anything any "good" news can result in a nasty squeeze the other way. Insurance is most valuable when the market does not really agree about an event, whether it is in the nature of that event or the timing.

One example of this can be seen in Brexit. We of course do not know with certainty the outcome of the event. What we do know, is the timing of the referendum. Hence, knowing the timing means, we can hedge this risk. The likely risk premium which will seep into the market is likely to increase over time, as investors seek to protect themselves from an adverse outcome. Given it is risk that we can hedge, the temptation is for the market to end up overpaying for protection or having an extended exposure in the cash markets. Hence, even if there is a bad result, the risk premium will be so high that it is unlikely to be the case that a hedge would work. It's like buying a Ferrari and having such expensive insurance, that it ends up being the case that the cost of insurance makes up a large proportion of the cost of the car.

Planning for the expected, is perhaps not as important as planning for the unexpected when it comes to hedges. As Hannibal from the A-Team might say "I love it when a plan comes together".

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)

29 Feb - London - Jessica James - FX option trading
14 Mar - San Francisco - Quant Fintech Mixer Event
15 Mar - New York - Thalesians/IAQF - Alex Lipton - Modern Monetary Circuit Theory
21 Mar - London - Robin Hanson - Robin Hanson, Economics when robots rule the Earth
20 Apr - London - Oskar Mencer - FRTB, RWA, XVA, Scenarios, MiFiD II, fast?
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives

Saturday, 13 February 2016

Fashion, trends and CTA strategies

17:12 Posted by The Thalesians (@thalesians) 1 comment

I'll confess, understanding fashion has never been my strong point. My uniform for much of my career working in investment banks was simply an ill fitting suit. I eventually worked out that a suit, which was the right size, might actually be a good idea. In recent years, since quitting banking, working as a full time quant strategist at the Thalesians, my uniform has been the humble t-shirt and jeans. I shall leave that up to you to decide whether I possess a modicum of dress sense....

Despite that, the little that I do know about fashion is that trends play a big part in it. If some such celebrity, who I probably don't know the identify of, suddenly wears an item of unusual clothing, it becomes "trendy" to wear it. If an item appears on the catwalk, high street brands will scramble to produce similar items, and then suddenly everyone is wearing it. Fashion trends seem infectious. Then after a while people tire of a fashion and the trend is extinguished. Fashions move in cycles, punctuated by the seasons, items of clothing seem to come in and out of fashion decade after decade.

Trends are obviously not purely restricted to fashion. Markets exhibit trends. There's that hot IPO, which has attracted lots of media interest, that market participants are desperate to get hold of. There's that new startup, which no one cared about, until a few big venture capital funds decided to invest. There's that currency that was languishing near the lows, till a smart hedge fund manager decided to buy, precipitating interest in that currency, from the rest of the market. We see an asset trend upwards on a chart, and suddenly, human behaviour gets involved and we want to buy, we don't want to miss that move! I could give countless examples of this type of herd behaviour in markets, which mirrors that we see in fashion. We all claim to be immune from it, yet, the fact that there are trends in the market seems to say otherwise.

Even if we ignore the behavioural argument for trends, the presence of an economic cycle gives rise to market trends. At the beginning of an economic cycle, we might expect materials stocks to outperform, as companies begin to invest in infrastructure. Countries which export commodities also tend to benefit. As the economic cycle wanes, commodities become less bid, and investors shift towards preservation of capital as the recession approaches, shifting from equities towards bonds.

Whilst the old maxim says "buy low, sell high", to be a trend follower in markets, you do precisely the opposite. You buy high, on an expectation of price action going higher. Conversely, you sell low, expecting the price to continue drifting lower. CTA, or commodity trading advisors have been around for around for decades. Typically they use systematic trading models, which are trend following, to make trading decisions. But how precisely do they go about it? At Global Derivatives in May, which will be in Budapest for the very first time, I'll be presenting my paper "How to build a CTA?" to help answer this!

I'll be examining the various technical indicators which can be used to generate trend following signals. I'll also be showing, how trading multiple asset classes from a trend following perspective can improve risk adjusted returns, compared to focusing on a single asset class. I'll be looking at historical results which show how trend following can help diversify the returns of long only equity and bond investors. To round off the discussion, there will be an interactive demo of how to implement a simple FX CTA type strategy in Python using my open source PyThalesians library (download the code from GitHub here).

If you want to know more about what a CTA does, hopefully see you at my talk at Global Derivatives in May! I promise I won't be attempting to tell you about my fashion sense at the same time....

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)

16 Feb - New York - Thalesians/IAQF - Harry Mamaysky - Does Unusual News Forecast Market Stress?
29 Feb - London - Jessica James - FX option trading
14 Mar - San Francisco - Quant Fintech Mixer Event
15 Mar - New York - Thalesians/IAQF - Alex Lipton - Modern Monetary Circuit Theory
21 Mar - London - Robin Hanson - Robin Hanson, Economics when robots rule the Earth
20 Apr - London - Oskar Mencer - FRTB, RWA, XVA, Scenarios, MiFiD II, fast?
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives

Sunday, 31 January 2016

Breaking the trading routine

19:11 Posted by The Thalesians (@thalesians) No comments

Routine. The drudgery. The predictability. The sheer monotony. In all my years, I can't recall reading the words, "I dream of routine". No one enjoys the sense that everything they do is routine. However, a modicum of routine helps to give life at least some structure.

Those occasions when we break from our routine, are in a sense what makes it all manageable. A stroll through a new environment, the sight of a painting you've never seen, the sound of song being played on the radio for the first time: the freshness of novelty is intensified when it is a comparatively rare experience. If we are repeatedly surprised by the novel, far from enriching our viewpoint, it suddenly becomes commonplace and routine, a dull and underwhelming experience. Bertrand Russell describes this idea very well, in his book the Conquest of Happiness.

Markets are both routine and novel. At times price action seems boring, range bound and directionless. News seems to do little to move prices. Of course, these periods are never permanent, and are often preludes to a shift in sentiment. I remember, when I quit my job in 2013, FX markets seemed to be on inescapable path to lowering volatility, accompanied by declining lack of interest. The dollar rally started in earnest as Autumn came in 2014. Volatility spiked and currencies actually started to move.

Is a routine or a novel market better? It depends on our strategy! If we are a carry investor, lashings of volatility accompanied by risk sentiment that swings around like a yo-yo are unlikely to be a joy to behold. By constant a trend follower much prefers markets where volatility is picking up, which are often accompanied by the development of trends.

We can complain all we want that the market environment is unsuitable for our specific trading strategy. We unfortunately don't get to choose the market which faces us. It is like complaining that you feel cold whilst strolling through the park during a particularly brutal winter day, when you haven't bothered to wear a coat. Rather than saying the market is unsuitable for our strategy, maybe we should instead think about it the other way round: whatever trading style we are adopting isn't suitable for the current market.

If our time horizon is very long, and we are not massively leveraged, we may well be able to stick it out in an "unsuitable" market. If we have developed a systematic trading strategy we might find that historically that periods of under performance occurs at times, but as a whole, the strategy is still profitable over reasonable time periods. However, with high levels of leverage and very concentrated risk, we don't have this luxury, and need to to think about what we can do to alleviate the situation.

So which is better, the novel or the routine? Sometimes we can't choose between the two, and simply have to deal with it.

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)

08 Feb - London - Saeed Amen/Delaney Granizo-Mackenzie - CTA/Pairs trading (joint Thalesians/Quantopian event)
16 Feb - New York - Thalesians/IAQF - Harry Mamaysky - Does Unusual News Forecast Market Stress?
29 Feb - London - Jessica James - FX option trading
21 Mar - London - Robin Hanson - Robin Hanson, Economics when robots rule the Earth
13 May - Budapest - Saeed Amen/Paul Bilokon - Thalesians workshop on algo trading at Global Derivatives

Saturday, 16 January 2016

Mitigating Risk, Managing Uncertainty

16:21 Posted by The Thalesians (@thalesians) No comments

Happy new year! If you're in markets, the new year has been anything but happy. The markets have greeted the new year with more than a modicum of scepticism. Crude oil has continued to trade very poorly. Equities have sold off significantly since the start of the year, mirroring the behaviour of August's sell off. Elsewhere, in FX, risk aversion has gripped the market. The high beta currencies in G10 FX have got trashed. EM has also been hit hard. The market has also been thinking about "one off" events such as Brexit and also to a lesser extent the breaking of the Saudi peg.

In a sense, this whole period has brought to the fore, the fact that a trader's job is literally to manage risk, trying to minimise downside risks and at the same time being able to capture the upside. The difficulty is that whilst in ordinary times "risk" might seem benign, this job can be much easier, during risk aversion, traders are faced with an explosion in volatility. This can make it difficult for traders to stick to their goals, even if they happen to be on the right side of the trade. Short term volatility can force traders out of positions which are fundamentally sound, but still come under stress, when the markets switch from seeking yield to wealth preservation in periods of risk aversion. When it comes to "one off" events, such as Brexit, we cannot simply use probability tools to understand the risks, we also need to use our judgement and an element of qualitative analysis.

So what should we do? Luckily, on Wednesday at the Thalesians in London, Nick Firoozye, a Managing Director at Nomura International and heads of a global team in cross-product derivatives research, will be doing a presentation on exactly this subject of uncertainty and risk. I must admit it's more a product of coincidence that the talk will be happening at this time of market turbulence, rather than some element of foresight on my part! Nick will be talking about his new book "Managing Uncertainty, Mitigating Risk - Tackling the Unknown in Financial Risk Assessment and Decision Making" and also signing copies. In his book, he stresses that we cannot simply use conventional probability to understand uncertainty in finance, and instead we need to seek understand the mathematics of uncertainty. He introduces concepts such as uncertain value-at-risk (UVaR) in the book, which helps to incorporate expert's insights into a risk framework.

I am looking forward to Nick's talk and hopefully see you there on Wednesday, if you can make it!

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 Jan - London - Nick Firoozye - Managing Uncertainty, Mitigating Risk
29 Jan - Budapest - Robin Hanson - Robin Hanson, Economics when robots rule the Earth
08 Feb - London - Saeed Amen/Delaney Granizo-Mackenzie - CTA/Pairs trading (joint Thalesians/Quantopian event)
29 Feb - London - Jessica James - FX option performance (TBC)
21 Mar - London - Robin Hanson - Robin Hanson, Economics when robots rule the Earth

Saturday, 9 January 2016

I haven't got the foggiest data

16:46 Posted by The Thalesians (@thalesians) 2 comments

The first full week of the year has passed. Christmas decorations have come down. Lazy morning starts are fading from memory. In their place, has come the hectic tempo of early morning commutes to work, the flip of 2015 to 2016 in the calendar, that feeling of starting all over again.

In markets, the volatility which had been absent over the holiday period, has returned. The first week has seen stocks sell off, in particular in China. Whether the Shanghai composite is of key importance for world markets is another question (after all, international markets mostly ignored their bubbly rise last year and Chinese stock market is dominated mostly by local retail investors). Geopolitical tension has increased in the MidEast, which only failed to stop crude oil's continuing decline for a couple of an hours.

Does the first week of the year in markets have any significance on the rest of the year? I recently ran a simple test, plotting the returns from S&P500 during the first week against the rest of the year. Whilst in the past decade there was at least a passable relationship, in the decades before that, it's very difficult to spot any relationship. The difficulty is that we have a comparatively small number of points to test this idea upon, given a trading rule would involve only one trade a year.

We can come up with other examples of this limited data problem in markets. For example, if we are trying to create a model to estimate when (or if) a managed currency might experience a sudden regime change. Rather than attempting to precisely time such a difficult binary event (which is near impossible!), we can instead try to build a probability distribution for that event. In our managed currency instance, we could look at central bank reserves data and other critical economic variables. We can then compare the market pricing for such an eventuality and compare to our model. Indeed, this approach looking at market pricing and also modelling other market variables is the approach I took in recent research on the peg of USD/SAR (see my interview here on the subject).

Should we never do analysis when we have very small amounts of data, given the problems? I would argue not. Once we have a probability assessment of our model, we can then overlay our own judgement on top of that and compare to market expectations. Analysing very small datasets might help us see a bit further into the fog of the future: after all it is likely better than doing nothing! At the same time we need to cast a critical eye on the output of our analysis.

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 Jan - London - Nick Firoozye - Managing Uncertainty, Mitigating Risk
29 Jan - Budapest - Robin Hanson - The Age of Em: Robots
08 Feb - London - Saeed Amen/Delaney Granizo-Mackenzie - CTA/Pairs trading (joint Thalesians/Quantopian event)
29 Feb - London - Jessica James - FX option performance (TBC)
21 Mar - London - Robin Hanson - The Age of Em: Robots