Tag Archives: Mathematica

Pay rates for doing maths in banks, Matlab in Computational Finance, Mathematica In London,Paris, Frankfurt & Zuerich, Daniel Duffy in London, and Attilio Meucci in NY

Subject: Pay rates for doing maths in banks, Matlab in Computational Finance, Mathematica In London,Paris, Frankfurt & Zuerich, Daniel Duffy in London, and Attilio Meucci in NY
Do you use (or misuse) maths in your finance job ?
We’re surveying pay levels for quants, quant developers, algo traders, asset managers, risk people, strats, structurers, analytics developers, risk developers etc. because it’s ironic that those who do numbers for banks have such poor quality numbers to work out how they are paid relative to others.

http://bit.ly/koFj1Q

It is completely confidential because we use a 3rd party SurveyMonkey to collect results. It’s 3-5 minutes, yes really, we’ve tested it.

We’ve have >4,500 responses so far but the reason *you* need to fill this form is that this is a field with lots of specialisations, and one factor can make a significant difference in your pay, so contributing your numbers means you get better information.

We will of course be publishing interesting results on Wilmott.com and through the Trading Tech group. This is the last week before we start publishing final results so you may want to act sooner rather than later,
http://bit.ly/koFj1Q

Dates for Your Diary
Computational Finance with Mathematica -New technologies for accelerating quantitative analytics,
http://bit.ly/k1imgk
Wednesday 14 June Zurich
Wednesday 15 June Frankfurt
Speakers
Efficient Valuation of Complex Derivatives on the GPU
Dr. Andreas Binder, MathConsult GmbH
In the pricing and risk analysis of structured financial instruments, numerical methods for valuation, as well as calibration of the model parameters, have to be implemented very carefully. The calibration often leads to optimization problems for which local algorithms do not converge. We present an efficient hybrid global/local algorithm and compare them to global optimization.

Daniel Duffy author of several major books on financial programming, is running the following workshops in London

One-day Master Class: The Alternating Direction Explicit (ADE) Finite Difference Method. Fast, Unconditionally Stable, High-Order Schemes for Derivatives Pricing and Hedging (8 July, London)
http://bit.ly/fFikUq

Creating Trading and Quant Applications in C# and Excel (September 20, 21, 22 London)
http://bit.ly/dHnXPz

Advanced Risk and Portfolio Management Bootcamp
by Attilio Meucci
August 15-20, 2011, Baruch College, New York City
http://bit.ly/jDv3nq

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Pay Survey, Matlab in Computational Finance, Mathematica In London,Paris, Frankfurt & Zuerich, Daniel Duffy in London, and Attilio Meucci in NY and The Thalesians are doing FPGAs in NY

Do you use (or misuse) maths in your finance job ?
We’re surveying pay levels for quants, algo traders, asset managers, risk people, strats, structurers etc. because it’s ironic that those who do numbers for banks have such poor quality numbers to work out how they are paid relative to others.

http://svy.mk/letqkA

It is completely confidential because we use a 3rd party SurveyMonkey to collect results. It’s 3-5 minutes, yes really, we’ve tested it.

The reason *you* need to fill this form is that this is a field with lots of specialisations, and one factor can make a significant difference in your pay, so contributing your numbers means you get better information.

We will of course be publishing interesting results on Wilmott.com

Dates for Your Diary
MATLAB Computational Finance Virtual Conference – June 9th, 2011

Presentations from Deutsche (on HFT), Dexia (on Basel II, Credit Risk & back-testing), Banc Sabadell (on enterprise deployment of pricing & trading analytics), IMF (on economic forecasting), Bank of Canada (on Systemic Risk), Attilio Meucci (on PRAYER framework), Model IT (on Solvency II and insurance risk) and CamraData (on the threat of the Pythagorean cult)

http://matlab.my/mrBAbH

Computational Finance with Mathematica -New technologies for accelerating quantitative analytics,
bit.ly/k1imgk
Monday 6th June London
Tuesday 7th June Paris
Wednesday 14 June Zurich
Wednesday 15 June Frankfurt
Speakers
Efficient Valuation of Complex Derivatives on the GPU
Dr. Andreas Binder, MathConsult GmbH
In the pricing and risk analysis of structured financial instruments, numerical methods for valuation, as well as calibration of the model parameters, have to be implemented very carefully. The calibration often leads to optimization problems for which local algorithms do not converge. We present an efficient hybrid global/local algorithm and compare them to global optimization.

Daniel Duffy author of several major books on financial programming, is running the following workshops:

One-day Master Class: The Alternating Direction Explicit (ADE) Finite Difference Method. Fast, Unconditionally Stable, High-Order Schemes for Derivatives Pricing and Hedging (8 July, London)
http://bit.ly/fFikUq

Creating Trading and Quant Applications in C# and Excel (September 20, 21, 22 London)
http://bit.ly/dHnXPz

Thalesian Seminar (NYC) Rakesh Joshi:FPGAs in HFT
6:30, Wednesday May 25
3rd Floor Playwright Tavern
202 W 49th St, NYC
http://bit.ly/iwzPqy

Advanced Risk and Portfolio Management Bootcamp
by Attilio Meucci
August 15-20, 2011, Baruch College, New York City
http://bit.ly/jDv3nq

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Events for Data Management , Daniel Duffy, Mathematica , GPU FPGAs, High Frequency Trading Dinner with the Real Time Club

Data Management in NY, Daniel Duffy in London, Mathematica / GPU in Paris, Frankfurt, Zurich & London, FPGAs in NY and High Frequency Trading Dinner with the Real Time Club in Whitehall. Dates for your Diary Data Management for Risk, Analytics and Valuations – New York City, May 17 http://bit.ly/iXIphY Apparently there is a lot of data in banks. Keeping track of it all, trying to work out if it’s correct and then working out what (if anything) it means is a pain. The question is whether it is your pain ? If a bank is paying you to do this then those nice people at A-Team are holding a one day conference with speakers who have shared your pain and offer some solutions, and even opportunities to look good to your boss. These people come from The Fed, Commerzbank, S&P, EMC, Oracle, Citi etc and there will be the chance to pick their brains as well as those of your peers over coffee, the day finishing with a well earned glass of wine. Computational Finance with Mathematica -New technologies for accelerating quantitative analytics, bit.ly/k1imgk Monday 6th June London Tuesday 7th June Paris Wednesday 14 June Zurich Wednesday 15 June Frankfurt Speakers Efficient Valuation of Complex Derivatives on the GPU Dr. Andreas Binder, MathConsult GmbH In the pricing and risk analysis of structured financial instruments, numerical methods for valuation, as well as calibration of the model parameters, have to be implemented very carefully. The calibration often leads to optimization problems for which local algorithms do not converge. We present an efficient hybrid global/local algorithm and compare them to global optimization. Dr. Michael Kelly, Wolfram Research Significant profits in finance are determined by the power, scope, ease, and speed of the computational toolset available. Mathematica has built upon its world-famous suite of mathematical, statistical, and computational functions to deliver a new range of financial capability. Whether it is the evaluation of bonds, cashflows, annuities, or derivatives or the estimation of underlying distributions,Mathematica has a diverse suite of functions to determine prices with ease and flexibility. John Ashley, NVIDIA Find out how the latest technology is shaping the modern finance industry talks from Nvidia, Wolfram Research and UnRisk, including live benchmarking of the speed-ups achieved. events-europe@wolfram.co.uk Daniel Duffy author of several major books on financial programming, and holds the following workshops: 2-day workshop PDE/FDM Methods in Computational Finance: Theory, Algorithms and Applications (May 19, 20 London) http://bit.ly/hqj9Ba One-day Master Class: The Alternating Direction Explicit (ADE) Finite Difference Method. Fast, Unconditionally Stable, High-Order Schemes for Derivatives Pricing and Hedging (8 July, London) http://bit.ly/fFikUq Creating Trading and Quant Applications in C# and Excel (September 20, 21, 22 London) http://bit.ly/dHnXPz Thalesian Seminar (NYC) Rakesh Joshi:FPGAs in HFT 6:30, Wednesday May 25 3rd Floor Playwright Tavern 202 W 49th St, NYC http://bit.ly/iwzPqy Real Time Club Dinner : Debate on High-Frequency Trading: A Formula for Liquidity or a Recipe for Meltdown? May 23, 6:00-9:00 PM am been a member of the Real Time Club, London’s oldest technology dining club; established in 1967 we hold regular dinners at the National Liberal Club in Whitehall to discuss the technology issues of the day. It won’t shock you that HFT is an issue that deserves not only our attention but also a rather good dinner and bottle of wine to get right. RTC members are an eclectic mix of academics, practitioners, bankers, techies, entrepreneurs and regulators; but for this event you do not have to be a member of either the RTC or the Liberal Club If you would like to book online go to http://bit.ly/f04i7C

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Quant analytics: Matlab is my now my focus! Lower priority for Mathematica, Octave, Scilab, even R and Python

Quant analytics: Matlab is my now my focus! Lower priority for Mathematica, Octave, Scilab, even R and Python

First off, let me say these other technologies including for Mathematica, Octave, Scilab, even R and Python are no worst. I just believe Matlab is very, very powerful for my needs. It also delivers as a standard in what large institutions use in terms of researching and prototyping. Also, Matlab’s vendor MathWorks has proven to deliver excellent documentation, software central, online videos and education, and so much more. It is expensive especially when you consider the required toolkits as well. It seems to be well worth spending. If you are about to launch a business, I see this investment no different when a store or restaurant invests thousands before they launch. It is just the cost of doing business especially my kind of business.

It seems these other tools, languages, and platforms may be fine, but I find Matlab always is mentioned in any of the above along with Matlab. As said, it is proven to be the standard. As for the open source versions of both Octave and Scilab, I have not seen the extensibility you get out of Matlab. I mean Matlab is fantastic there as well.

Also, it seems many argue that Matlab is slow. Have you ever heard of parallel computing? I mean that toolkit should deliver those needs. I also have seen metrics for both Python and R are painfully slow. Also, some say you can add Python with another framework to speed things up. Well, I get that out of the box with Matlab. Also, it seems there a fantastic supportive community out there but judging from other open source communities, I just don’t think neither will bring what Mathworks brings to the table.

I also I have not even mentioned Simulink, Matlab’s data connectivity features, compiling capabilities, or even the built in reporting documentation capabilities. Seriously, why would I use anything else?

As for Mathematica, I am sure it is fine but Matlab seems to deliver everything I need. Thanks to Matlab, I am very happy to part of what they deliver. Matlab seems to be greatest invention for us Quant wannabes.

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

A mathematical approach to order book modelling

We present a mathematical study of the order book as a multidimensional continuous-time Markov chain where the order flow is modelled by independent Poisson processes. Our aim is to bridge the gap between the microscopic description of price formation (agent-based modelling), and the Stochastic Differential Equations approach used classically to describe price evolution in macroscopic time scales. To do this, we rely on the theory of infinitesimal generators. We motivate our approach using an elementary example where the spread is kept constant (“perfect market making”). Then we compute the infinitesimal generator associated with the order book in a general setting, and link the price dynamics to the instantaneous state of the order book. In the last section, we prove the stationarity of the order book and give some hints about the behaviour of the price process in long time scales.

http://arxiv.org/abs/1010.5136

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Are these advantages enough to want use Mathematica over Matlab for quants using Java, .Net, and C++?

Someone posted this on Linked In. Are these advantages enough to want use Mathematica over Matlab for quants using Java, .Net, and C++?

Mathematica is extremely powerful. Those who believe it is only a program to perform symbolic calculations probably have never used Mathematica. Parallel processing capabilities are built-in and standard. So calculations spanning multiple cores using multiple machines can be set up simply by just pre-pending the word “Parallel” to a standard command. Furthermore, using the built-in MathLink Mathematica interfaces seamlessly to C, C++ or using the built-in J-Link it interfaces seamlessly with JAVA.

Key Advantages of Mathematica as a Programming Language:
Immediate built-in access to the world’s latest math and other algorithms
Automatic algorithm selection, typically vastly outperforming custom-written code
Consistent symbolic syntax and semantics across all data, functions and interfaces
Stable language on all platforms with consistent development since 1988 »
Symbolic paradigm maximizing code modularity, analyzability and testability
Fully integrated visualization, interface building, document generation and data interchange
Unified environment for model generation, analysis, execution and deployment
Symbolic structure allowing derivation and representation of code as well as data
Formulas entered in traditional math notation, for enhanced readability and verifiability
Built-in complex numbers, arbitrary-precision and automatic-precision tracking »
Immediate vector, matrix, and arbitrary-array programming »
Wide range of optimized data structures (e.g. sparse arrays and interpolating functions) »
Integrated full-function code documentation system, with document programmability
Immediate pure Mathematica interface to arbitrary Java and .NET classes »
gridMathematica with full parallel programming & debugging capabilities
World-class in-house QA and broad usage ensuring high algorithm reliability
Mathematica Player free runtime environment

Key Advantages of Mathematica for Statistics:
Support for gigabyte-sized datasets »
Built-in industrial-strength linear algebra and optimization »
Full coverage of mathematical special functions »
Symbolic statistics, giving formulas as results
Full integration of broad computational capabilities
Integrated input and output of traditional mathematical notation
Immediate creation of interactive interfaces for all computations »
Built-in fully programmable dynamic formatted document generation »
Ability to extract data from web pages, documents and many specialized formats »
Built-in curated data sources for scientific, socioeconomic, financial, etc. data »
Built-in automated typeset table layout »
Computational aesthetics automation of all aspects of visualization
Full multiparadigm programming language for data manipulation
Full programmable extensibility for adding arbitrary functionality
Capability for symbolic specification of statistical models »
Seamless support for exact- and arbitrary-precision computation »
Uniform high-quality language, with full professional development tools »
Deployment with webMathematica
Broad statistics coverage in The Wolfram Demonstrations Project
Integration with statistics information in Wolfram MathWorld

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Best quote: "C++ is my wife, but Mathematica is my mistress." — Anonymous

Best quote: “C++ is my wife, but Mathematica is my mistress.” — Anonymous

Acutally second best quote. The best quote is:

“C++ is my wife, but Matlab is my mistress.” — Bryan Downing

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Is this the classic debate of Matlab vs Mathematica for quants? Wilmott has great opinions!

Is this the classic debate of Matlab vs Mathematica for quants? Wilmott has great opinions!

Here is a very classical debate. As I posted my thoughts on Matlab, I seem to be piss off of some old dude who built his whole business on Mathemtica and Java. Can you doh!?!? Here is some responses of the Matlab versus Mathematica debate from Wilmott:
For Mathematica:
Mathematica’s document-oriented front-end (programmable hierachical documents, called Mathematica notebooks) allows you for creating reports that look like a “paper” but work like “programs” (“typeset documents which can do math”).

There is a bit of a learning curve, but there are plenty of examples in the documentation and other publications, especially for displaying options pricing data.

Mathematica handles X and Y plot graphics is easier.
Symbolics computation gives Mathematica an edge over Matlab.
It offers C++, C#, or Java solvers to be linked in Mathematica code. This could be used in examples of numerical schemes to solve
– uniform expression model (the input language for the Mathematica kernel). It handles mathematical formulae, lists, logical expressions, graphics objects,.. with the same underlying structure

– task-oriented super functions, like NDSolve (for numerical DE solvers). It analyses the DE and selects the solver. You do not need to select from ode23, ode113, ….pdepe,.

Matlab:
Matlab is much faster than Mathematica. A comment was posted try doing a Monte Carlo simulation in both and see. The Matlab GUI is much better while the Matlab is better for general development as well.
Matlab is easier but Mathematica is more powerful

The Statistical toolbox has been described as a treasure trove. This is for PCA, decision trees, and more.
Matlab’s compiler and parallel computing power offers a new look at Matlab as compared to Mathematica
Matlab can start simple with matrixes and gets into complex stuff like structures, pointers,
classes with private member functions

Some claim the data miner toolbox is the main workhorse of Matlab.
Matlab can compile into standardized components.
Matlab focuses on numerical computation. Mathematica focuses on symbolic computation.
We learned in business school that sunk costs (e.g., all the hair I’ve pulled out over Mathematica) shouldn’t influence future capital investment. Since I’m all over economic rationality, I’ll probably switch to Matlab rather than buying the next major release of Mathematica or any additional Mathematica add-ons. I do know that if I were making the same decision today, I’d value practical considerations over technical (and seldom used) capabilities. Hope this helps someone.

We can post more but go ahead and post your opinions below:
From:
http://www.wilmott.com/messageview.cfm?catid=10&threadid=34261&FTVAR_MSGDBTABLE=&STARTPAGE=2

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!