Saturday 11 June 2016

Ferris Bueller's Day Off (& memories)

18:02 Posted by The Thalesians (@thalesians) 35 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) 9 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) 13 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) 21 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) 7 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) 9 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) 2 comments

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