<![CDATA[Quantitative Finance Collector]]> http://www.mathfinance.cn/index.php en-US http://www.mathfinance.cn/interview-patrick-burns-quantitative-finance-r/ <![CDATA[Interview: Patrick Burns Quantitative Finance in R]]> abiao <> Mon, 05 Mar 2012 12:03:05 +0000 http://www.mathfinance.cn/interview-patrick-burns-quantitative-finance-r/ Dr. Patrick Burns is the founder of Burns Statistics, providing consulting and bespoke software specializing in quantitative finance, programming in the S language, and optimization via genetic algorithms and simulated annealing. Patrick has written many papers on quantitative finance and statistics, he is also the author of the book The R Inferno and the R package BurStFin.  

Tell us a little background info about yourself. Where are you from? What’s your education background?


I was born on the edge of a wheat field in the Empty Quarter.  I made my way to Seattle for university where I received a PhD in statistics (with an emphasis on computing and a smattering of economics).  Much later I moved to London.

In graduate school one of my office mates was Robert Gentleman, who would a few years later be half of the team that originated R.

How long have you been using the R language and to what extent? What are the main reasons you choose to run analysis in R rather than other languages?


I first touched R in the early 90's when Robert came around with it on his laptop.  However I didn't seriously make the switch from S-PLUS to R until I started Burns Statistics in 2002.

A big reason I use R is because I used to be a developer of S-PLUS (R's sibling) and so I'm naturally fluent in R.

But there are what I think are good reasons why others should also use R.  The key thing is that the S language – and so R – was specifically designed for data analysis.  A lot of experience, thought and arguments have gone into creating what R is now.  Data analysis is really what quantitative finance is about, hence R was designed for quant finance.

Another reason is that it is looking like R will soon be the dominant data analysis platform.  I continue to be astounded at the growth of R, especially in finance.  It's not good to use an inferior tool just because everyone else uses it (read Excel).  But if you have a selection of reasonable tools, then there are advantages to using the most popular of the good choices.
One of the advantages that R has over Matlab is that it is free.  You can think about installing R on all the machines on a trading floor so that everyone on the floor can use some functionality (probably without knowing that it depends on R).  Such a scheme would be very expensive with a commercial language.

An advantage that R has over other free languages is its wealth of functionality.  There are over 3000 packages in the main R repository. The development of packages specific to finance is quite active.  R most definitely has the attention of the statistics community, so new statistical techniques are most likely to appear first in R. Also R tends to play nice with others – you can often easily mix R and tasks done in other languages.

In short sentences, what are the major differences between Portfolio Probe developed by Burns Statistics and other free or paid packages / software?


The most important thing in Portfolio Probe is the generation of random portfolios.  That is, sample from the population of portfolios that obey some set of constraints (for example: sector constraints, weight constraints, number of names).  Generating random portfolios is a general quant tool  that has many uses, most of them yet to be discovered.  I think their main impact will be in performance measurement. Currently they are mainly used to test risk models.

The other thing that Portfolio Probe does is portfolio optimization.  The optimization uses a form of genetic algorithm.  This has the advantage of flexibility over optimizers that use mathematical algorithms.  The optimizer can adapt to the problems people actually have rather than trying to make the problem adapt to the optimizer.  The Portfolio Probe optimizer is better than other heuristic optimizers because a lot of work has gone into making it work well.  Some of that work was successful.

What’s the biggest change you feel the credit crisis has brought to the development of quantitative finance?

  
One change is that it has pushed quants away from the illusion that their models are true.  That's a good thing, but unfortunately probably temporary.  People will be lulled into complacency once their models have worked well for a while.
The other major change I see is that it has prompted more thought on hard but important problems.  I'm thinking of things like understanding herding risk, and the real dynamics of markets.

Correlation between assets has become higher since the breakout of financial crisis, which makes portfolio management more difficult (for example, less diversification), what’s your advice for an investor to better manage his portfolio? What’s the impact on portfolio optimization?

  
I don't have advice for investors – at least none that they should take.  However, this is an example where random portfolios can be informative.  The actual opportunity that a fund manager had over historical periods can be seen by generating a set of random portfolios that satisfy the fund's constraints and then getting the distribution of returns for the portfolios over time.  The opportunity given a certain set of constraints may not follow average correlation very well.

As for its effect on portfolio optimization, that's a good question to which I don't know the answer.  Perhaps you'll see a blog post on that some day.

What accomplishments so far are you the most proud of?


My greatest technical achievement is probably the speed of optimization and random portfolio generation in Portfolio Probe.  I of course want it to be still better, but I think it's pretty good now.

One of my best conceptual achievements has been realizing the immense potential of random portfolios.  The achievement that I'm still missing is convincing the rest of the world of that.

What is the single toughest challenge you’ve had to face in your past projects, and how did you get through it?


I'm not convinced I'm “through it” but I've made progress.
Consulting has a technical component and a social component.  I'm okay with technical, but human society is a foreign language to me.  Some people take that to mean that I'm anti-social.  That's not it – I like people, I just don't understand the rules of interaction very well.  Things that seem to be innate to elementary school children are mysterious to me.  However, I'm massively better than I used to be.  The less observant might even confuse me for normal now.

What have you been up to recently? What projects are you working on?


I'm in the final phases of putting out the official release of the new version of Portfolio Probe.

Can you describe a typical work day? How do you like to spend your free time?


My typical day begins by waking up to the battle with Alfred – the cat who owns the house where I live – over strategic territory on the bed.  Once I admit defeat, I brace myself for the arduous commute of going one flight down the stairs.
I spend the morning playing with the buttons on my computers.  I have lunch with my wife (and of course Alfred).  Then I go for a walk in the park, and say hello to my dog friends.  This is often the most productive part of the day.  Once back, I have another session of playing with computer buttons.

How can people contact you for business? Do you have a website or Twitter account or Facebook “Like” page?


There is a website for Burns Statistics: http://www.burns-stat.com
Among other things, this has information on using R including an introductory set of pages and The R Inferno.
There is also the Portfolio Probe website: http://www.portfolioprobe.com that includes the blog.

On Twitter I'm @portfolioprobe  – this is mainly announcements of blog posts, but sometimes has something about R, and occasionally a joke that hardly anyone gets.
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Read the full post at Interview: Patrick Burns Quantitative Finance in R. ]]> http://www.mathfinance.cn/interview-donald-van-deventer-risk-management/ <![CDATA[Interview: Donald R. van Deventer Risk Management]]> abiao <> Tue, 28 Feb 2012 11:14:06 +0000 http://www.mathfinance.cn/interview-donald-van-deventer-risk-management/ edge financial theory to solve critical financial risk management problems. He was elected to the 50 member RISK Magazine Hall of Fame in 2002. Dr. Donald R. van Deventer has served on the editorial board of the Journal of Credit Risk since 2005, and has written numerous papers and several books covering a wide range of risk management.  

Tell us a little background info about yourself. Where are you from? What’s your education background?


I grew up in Los Angeles and was a double major at Occidental College in mathematics and economics.  I went to Harvard University and earned my Ph.D. in business economics in 1977.  The business economics program is a joint program of the Department of Economics and the Harvard Business School.

You had worked for a few financial institutions before founding your own company, what are the advantage and disadvantage of working in a risk solution provider over in the risk management group of a big financial firm, especially for a junior?


If one has the chance to work for a very innovative firm like Kamakura, there’s the challenge and the pleasure of making the state of the art better every day.  Within large financial institutions, a junior risk analyst is often trapped using an old fashioned legacy risk system purchased years before from a mediocre vendor.  That’s bad for one’s career for two reasons.  First, you don’t learn state of the art risk management and you run the risk of turning into a risk dinosaur at a young age. Second, if the firm is not using best practice risk management, the odds of failure are high even at a large bank as we’ve seen in the last five years.

A lot of people blame Copula or Black-Scholes formula for the current financial crisis, what’s your opinion on this debate?


My partner Prof. Robert Jarrow has a nice paper on the misuse of financial models and a video on the front page of the Kamakura web site www.kamakuraco.com on exactly this topic.  Black and Scholes certainly shouldn’t be blamed if an analyst uses the Black model (which assumes interest rates are constant) to price interest rate options.  The incorrect usage of financial models is astonishingly widespread.

You recently wrote a series of articles on CDS trading volume, and questioned that the CDS quoted spreads are highly likely to have been affected by collusion (unfamiliar readers may refer to http://www.kamakuraco.com/Blog/tabid/231/EntryId/362/Collusion-and-CDS-Dealer-Volume.aspx for detail), what’s the direct motivation of this research? Does this issue commonly exist for other assets as well?


One of the issues we deal with daily at Kamakura is the steady improvement in the accuracy of our KRIS default probability models.  We have spent a decade looking at the CDS market and analyzing whether or not to add CDS spreads to our models as inputs.  We’ve concluded that there is minimal trading in individual reference names after analyzing the DTCC warehouse trade data.  The market is dominated by a few dealers, many of which have been named in lawsuits alleging manipulation of Libor.  One would be naïve to assume the same firms would not manipulate the CDS market.

What’s the biggest change you feel the credit crisis has brought to the risk management?


The credit crisis eliminated many dinosaurs from the financial services business and brought smarter people into senior management and into risk management.  It was a tough lesson for many but in the long run the financial services industry will be smarter.

What accomplishments so far are you the most proud of?


I am very proud of the extremely strong staff we have at Kamakura and at their continued push for absolute excellence.  It’s exciting to be surrounded by so many brilliant and self-motivated people who love what they do.

What is the single toughest challenge you’ve had to face in your past projects, and how did you get through it?


Mack McQuown, one of the co-founders of KMV, once said “This business is like surfing; if you are too far out in front of the wave you stall and get pounded by the wave.  If you are too far back in the wave you get pounded too.”  In the risk business anyone with a new idea is by definition “in front of the wave” and it’s been amazing to me how long it has taken people to realize there’s a better way to do things. That being said, we’ve been very successful in both risk information and risk management software and we’re extremely grateful to the “lead steers” who have shown the world what Kamakura can do.

What have you been up to recently? What projects are you working on?


We’re enhancing both our interest rate analytics and our credit models in a very significant way that is very exciting. A new edition of my book with Kenji Imai and Mark Mesler “Advanced Financial Risk Management: Tools & Techniques for Integrated Credit Risk and Interest Rate Risk Managements” is coming out later this year as well.

How do you like to spend your free time?


I like to spend time with my three daughters. I’m an aspiring ukulele player and I’m a director of the Hawaii Bicycling League, so I ride as much as I can.

Do you have other suggestions you like to share with us?


I know that people who read this website are very smart, and I strongly urge the readers to be smart and get smarter every single day of their career.  Those who stop learning become dinosaurs.

How can people contact you for business? Do you have a website or Twitter account or Facebook “Like” page?


Please feel free to contact us in either English or Chinese at info@kamakuraco.com or at the Beijing or Shanghai offices listed on our website www.kamakuraco.com.  The company twitter account is @KamakuraCo and my twitter account is @dvandeventer.
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Read the full post at Interview: Donald R. van Deventer Risk Management. ]]> http://www.mathfinance.cn/interview-ernest-chan-quantitative-trading/ <![CDATA[Interview: Ernest P. Chan Quantitative Trading]]> abiao <> Mon, 13 Feb 2012 11:03:36 +0000 http://www.mathfinance.cn/interview-ernest-chan-quantitative-trading/ "Quantitative Trading: How to Build Your Own Algorithmic Trading Business".

Ernest Chan quantitative trading

Tell us a little background info about yourself. Where are you from? What’s your education background?


I was born in Hong Kong, and I moved with my family to Toronto, Canada, when I was 17. I studied physics as an undergrad at U of Toronto, and received a Ph.D. in theoretical condensed matter physics from Cornell University. But after graduation, I never did any work in physics. I first worked as a researcher at IBM T. J. Watson Research Center’s Human Language Technologies group, where I designed statistical pattern recognition algorithms. Quite a few of my colleagues in that group moved on to become hugely successful algorithmic traders. (The current heads of Renaissance Technologies, Robert Mercer and Peter Brown, were both managers of that group.) After a few years, I too moved on to a career in finance, beginning at Morgan Stanley.

How long have you been as a quantitative trader? We know you had worked for a few big investment banks and hedge funds, what are the pros and cons of working as an independent traders and a manager of your own fund, instead of in a big firm?


I started researching algorithmic trading strategies in 1997, began trading my own strategies for a hedge fund in 2003, becoming an independent trader in 2006, and started my own hedge fund in 2008. The obvious benefit of working for large institutions is that you will receive a very decent salary, whether or not your strategies ultimately work. And if they work, the compensation can be large, if not astronomical. The drawback is that you have to deal with the politics, and more problematically, the traded strategy is often a product of compromise or consensus among various parties, which is rarely optimal. So it is actually rather hard to find a strategy in this environment that will make money for your institution. Working as an independent trader, or starting your own fund, is very demanding on your intellectual as well as emotional energy. But actually, it is easier to find profitable strategies that work for a small amount of capital, though the profits will also likely be much smaller due to limited capital, and there is no guaranteed salary to fall back on if they fail. Of course, success in this case can be more satisfying than just receiving a big bonus from your boss. On the whole, from a purely financial point of view, working in a large institution probably generates a higher expected lifetime income for you. But if you take into account the psychological rewards of being your own boss, and if you truly have the skills necessary to trade successfully, then the expected satisfaction, or “utility” in economists’ parlance, of being an independent trader or fund manager is higher.

What are the main types of assets you are trading? Equity, futures, or other derivatives? I read from your blog you started with equity, and then traded futures, so what characteristics do you feel is the most different for these types of assets in terms of trading strategies generation?


I used to trade only equities, though now I trade mainly foreign currencies. I dabbled in various futures strategies from time to time, but those have not formed a big part of my portfolio. Equity strategies are becoming less profitable because of the lower volatility in the market (notwithstanding August 2011), higher correlation among stocks, and the rise of high frequency trading. The first two factors do not present problems to FX strategies in general, and there are not as many high frequency traders in FX yet, so profitability can be high, especially since leverage can be higher as well.

What do you think it takes to be successful as a Quant trader? What is the best advice you’ve been given and you like to share with Quant traders?


The most important characteristic of a successful trader is to realize that the signal to noise ratio is very low in financial markets, so keeping one’s models simple is essential. The best advice I have been given is that high leverage kills.

2011 was a tough year for many traders, especially for those trend-following traders, what is the outlook for 2012 algorithm trading?


I don’t pretend that I can predict volatilities! But so far, the environment has returned to the favorable condition prior to August, 2012.

What accomplishments so far are you the most proud of?


Not having a personal down year since 2007.

What is the single toughest challenge you’ve had to face in your past trading, and how did you get through it?


There were a few days when the intraday drawdown was over 10% of my net worth. Those were scary times, but luckily the end-of-day P&L weren’t as bad. The important lesson to learn is to have confidence in your models during crisis, and not to manually intervene.

What have you been up to recently? What projects are you working on?


A publisher has asked me to write another book, so I am organizing some ideas that I have learned in the past few years. Of course, research into new strategies is always on-going. Also, once every few months, I teach trading workshops in London and Singapore. But my first priority, of course, is to operate my fund and generate profits for my investors.

Can you describe a typical work day of an independent Quant trader? How do you like to spend your free time?


Typical workday begins at around 7am, which is when I start various programs for data downloading and  trading. Then research and discussions with colleagues over emails took up the best part of the day. I spend very little time marketing my fund – typically investors know me from my blog or meet me through my workshops. I take long walks in the middle of the day: I live in a fairly rural area, so this can be quite pleasant. And in the winter, singing in the choir has become a major pastime as well.

How can people contact you for business? Do you have a website or Twitter account or Facebook “Like” page?


Prospective clients can reach me through epchan.com, or through my blog epchan.blogspot.com.
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Read the full post at Interview: Ernest P. Chan Quantitative Trading. ]]> http://www.mathfinance.cn/interview-thijs-van-den-berg-from-sitmo-com/ <![CDATA[Interview: Thijs Van Den Berg From Sitmo.com ]]> abiao <> Tue, 07 Feb 2012 13:09:50 +0000 http://www.mathfinance.cn/interview-thijs-van-den-berg-from-sitmo-com/ Standing on the shoulders of giants allows us to see further, from now on we will invite experts to share with us their valuable experience and lessons.

It is our great pleasure to have Thijs van den Berg joining this week's interview session, Thijs is the manager of Sitmo B.V founded in 1998, which was initially a derivative market-making firm operating on the European Options Exchange (now Euronext), but soon building customized derivative models and risk management software development became an important activity. In 2003 Sitmo started consultancy services in Energy trading and quantitative modeling.

Tell us a little background info about yourself. Where are you from? What’s your education background?


I’m from The Netherlands. As long as I can remember I’ve been curious: math, physics. I got my first computer when I was 10 and things became magical: I had my personal desktop lab to experiment with! About that time my family decided to move to a sunny island. I had a great time windsurfing, surfing and skating, but education was a bit 2nd place. I went a year to a local Spanish school but didn’t speak much Spanish and so the only thing I could follow was the math classes. The second year I went to a British International school and that was very intense and good. Every morning sausages and beans etc. After that we moved back to The Netherlands, I skipped a school year, and eventually went to the Delft Technical University when I was 17 to study Computer Science. The first year was perfect -I was in the top 5-, but then I started to doubt my choices... I ended up working in a popular bar and was really enjoying that, ..until a professor knocked on my door and said he wanted to talk to me. He’s now a very good friend. After that I quickly finished university, did a thesis at a bank on forecasting with Wavelets.

Do you have any experience with quantitative finance? If yes, how long have you been in the quantitative finance industry and to what extent?


I ran into QF when I started trading (equity) derivates on the floor in the 90s. I’d build our own option pricing models and risk management tools, those were great times, we always had different prices than other traders, but we got it right... After that I got a job running a quant department at an energy Company. Energy trading was in its infancy: there was extremely much to do from a modeling perspective. The commodities have very complex dynamics, exotic assets, optimization, load forecasting, credit, data warehouses. We managed to get a couple of good PhD on board who delivered good models on fundamental activities. It was a true startup: when I joined the company the trade floor was just 6 people, when I left 250 with full blows specialized departments.

I left there in 2003 and I started my consultancy firm and have been doing that ever since. I took one year off in 2008 setting up an algo trading firm with two partners. It was very heavy on computing, scalability, reliability, data mining, stream processing, exactly replicating exchange matching engines etc,.. lots and lots of C++. It was great fun, very long days, but we made a fatal mistake at the beginning with the contract. It ended up being a big write-off, and an expensive lesson learned.

What is your specialty? Equity, fixed income, derivatives or others, and to what extent?


I think my specialty is more my drive to perform and solve. I enjoy learning new things very much, and I seek new types of problems whenever I can. In general I do a lot of strategic advice, energy, coding and trading related projects. My last project was completely different: a 7 month fixed income model validation and liquidity modeling task.

What accomplishments so far are you the most proud of?


I’ve build a modeling framework that can learn complex non-linear dynamic from observation data. It performs extremely well and it has a very elegant mathematical foundation. It’s very versatile and I use it to model complex time-series like energy spot stochastic, volatility term structures, intra-day FX, even weather dynamics like temperature, wind speed and light –intensity. I think I’ve invested at least 4 years in developing the math and coding.

Why did you choose this career? What are the pros and cons of working as an independent consultant instead of in a big company?


My parent had their own firm, and that’s one of the first reasons. Another reason is probably my personality: I enjoy initiating things, I thrive on new knowledge and solving complex issues, and I’m not risk adverse, I like to challenge things and innovate. The cons are the unclear distinction between work and home. Clients are expecting a lot of performance, and there are always tight deadlines. Socially it’s of-course also a bit different, you come and go. My colleagues are probably my peer consultants I regularly team up with on projects.  

What do you think it takes to be successful as a quantitative analyst?


Be honest to yourself. Never bend figures towards a predefined goal by anyone. When modeling: know about model error and over fitting, always try to validate results with common sense back-of-the-matchbox bounds and simple proxy models. Know the difference between accuracy and precision. Another aspect of being honest to yourself: when you’re wrong directly say that you were wrong, it takes guts to do that. People will respect that, and it allows you to move forward faster.  Time management is also very important. Continuously try to deliver small increment, don’t hide in a closet for half a year.

What is the single toughest challenge you’ve had to face in your past projects, and how did you get through it?


The toughest challenge was working in an extremely political war-type of environment and try to be productive. Almost all divisions at my client were in serious conflicts with each other, managers trying to get each other fired, lying, put the blame of failures on each other, there were coupes. No one was looking after the company. I had to pick a couple of battles and those were mainly on establishing clear boundaries professional and making clear that I don’t accept certain type of behavior.

What is the future of quantitative finance in your opinion, especially after the financial crisis?


My opinion is that there will always be need for improving things. Saving money for a company, helping make better decisions, help them value things more precisely, help reduce risk and save on capital needs. These activities will always be valuable.

What have you been up to recently? What projects are you working on?


Many things in 2011. For a bank I’ve done model validation, setting up swap curves and building liquidity management models. I’ve done a strategic advice for a large international utility that wanted to quantify their strategic lobby possibilities. I’ve started an open-source Quantitative Finance Code Library Platform with Paul Wilmott and Daniel Duffy. I’ve build optimization and risk models for a large group of CHP owners to help them optimize their operation and manage their risk. Another optimization modeling project was for the water utility. They have storage buffers, strict safety bounds and use lots of energy to process water and pump it around the country.

What is the best advice you’ve been given and you like to share with Quant wannabe?


During  a review, ask your managers about the things you are not good at and then don’t try to get upset about that but instead think and talk about it. These things typically transcendent the workplace and not many people tell you about your flaws in your life.

How do you like to spend your free time?


My family is vey important to me, I like to not just work 24/7 but also be at home, I value that highly. I run to keep fit, I still have a skateboard and there is a skate park around the corner.  I enjoy playing pool with my friend, go with then to camp at festivals and see bands. Another thing I like it those relaxing spa’s with my wife -but I hardly do that-.

Do you have other suggestions you like to share with us?


Try to be happy and have a diversified identity, you only live once.

How can people contact you for consulting business? Do you have a website or Twitter account or Facebook “Like” page?


Website: www.sitmo.com, email: thijs@sitmo.com, twitter: sitmo_com

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Read the full post at Interview: Thijs Van Den Berg From Sitmo.com . ]]>