Tag Archives: Secret Sauce

probability of a loss secret sauce tricks of Renaissance Technologies HFT masters

 

Sweet Mama. This is the closest I have gotten to this secret sauce eof Ren Tech black swan risk and probability of a loss tricks

From someone who knew all the founders of Ren Tech:

I have known Jim Simons, Bob Mercer and Peter Brown since 1965, 1974, and 1979, respectively.  Renaissance has also hired senior researchers who had formerly worked for me for years.  None of these people has ever told me anything about Renaissance’s investment strategies.  My observations below have been obtained entirely from publicly available records.

In particular, the core strategy is publicly known.  It’s the details that are proprietary.  There are millions of details, and they are essential to the performance.  However, the question was about strategy, so that is what I will try to answer.

The core strategy is portfolio-level statistical arbitrage carried to the limit and executed extremely well.  Basically, portfolios of long and short positions are created that hedge out market risk, sector risk and any other kind of risk that Renaissance can statistically predict.  The extreme degree of hedging reduces that net rate of return but the volatility of the portfolio is reduced by an even greater factor.  The standard deviation of the value of the portfolio at a future date is much lower than its expected value.  Therefore, with a large number of trades the law of large numbers assures that the probability of a loss is very small.  In such a situation, leverage multiplies both the expected return and the volatility by the same multiple, so even with a high leverage the probability of a loss remains very small.

The general properties of the strategy can be deduced from the statement of Renaissance for the Hearing of the Senate Permanent Subcommittee on Investigations, dated July 22, 2014.  [https://www.google.com/url?sa=t&…

Renaissance collects “all publicly available data [they] can that [they] believe might bear on the movement of prices of tradable instruments–news stories, analysts’ reports, energy reports, crop reports, weather reports, regulatory findings, accounting data, and, of course, quotes and trades from markets around the world.”

Their models “use this data to make predictions about future price changes.”

The hearing was specifically about the Medallion fund, about which the statement says “The model developed by Renaissance for Medallion makes predictions that are profitable only slightly more often than not.”

With these properties, there were two reasons that Renaissance would like to have a call option on the portfolio that it has designed: leverage and protection against Black Swan events.

Leverage is needed because, unleveraged, the rate of return of the portfolio is low.  However, because the volatility is much less than the expected return there is no limit to how high the leverage could be without increasing the probability of a loss, at least according to the models.  Through years of use and refinement, Renaissance knows that its models are very reliable.  However, they also know that there is always the risk of something happening that is not covered by the models, in particular something that is outside prior experience, which is called a “Black Swan” event.

Thus, a call option is ideal: it can provide high leverage and can provide protection both against the very low probability of a loss greater than the option premium and also against the unknown probability of a possibly catastrophic loss due to a Black Swan event.

We know all this because these are the business reasons for Renaissance accepting Deutsche Bank’s proposal of barrier options.  Basically, Deutsche Bank, and later Barclays,  sold the equivalent of a call option to Renaissance on the reference portfolio that Renaissance designed.

Of course, writing an uncovered call on the Renaissance portfolio would be equivalent to betting against Renaissance at high leverage, which would seem to be a foolish thing to do.  The banks covered these options by buying all of the securities in the portfolio.  Thus the bank’s position was equivalent to a covered call.  In other words, the banks’ profits and risks were essentially equivalent to writing a put option, which is a bullish position.  Because the volatility was very low the probability of a loss for the bank was low and the probability of a loss greater than the option premium was even lower.

Except for the Black Swan risk.  The probability of a Black Swan risk is unknown.  Part of the premium paid by Renaissance and earned by the banks was equivalent to insurance against Black Swan risk.  I don’t know if the amounts of the premiums were publicly disclosed.

There were many more details in the statements and the testimony at the hearings.  However, discussion of further details would detract from the important points that I have made above.  In particular, the hearings themselves were about tax issues not about investment strategies.  Renaissance explicitly asserted, under oath, that its “models do not factor in tax rates when making trading decisions.”  Therefore, tax issues, although they might be very important, are not part of the “investment strategy” at least as reflected in the models, so they are outside the scope of this particular discussion.

[Edit (added in answer to a comment):  The reference portfolio was highly dynamic.  There were thousands of  trades per day.  To accomplish this, the banks gave RenTech’s computers  direct access to execute trades through the banks’ trading desks.

This  arrangement was part of what created controversy about what should  be the proper tax treatment for this particular case. However, I am not a  tax lawyer and will not try to analyze those issues.  However, if you  want to hear more details on the automatic execution of the trades, and  questions about how much human interaction was present, that is all  discussed in the live testimony before the subcommittee: [Hearings| Homeland Security & Governmental Affairs]

I have copied this in case the Quora link disappears which is from

https://www.quora.com/What-are-the-investment-strategies-of-James-Simons-Renaissance-Technologies-I-understand-he-employs-complex-mathematical-models-along-with-statistical-analyses-to-predict-non-equilibrium-changes

Notes from Senate hearings include:

https://www.hsgac.senate.gov/subcommittees/investigations/hearings/abuse-of-structured-financial-products_misusing-basket-options-to-avoid-taxes-and-leverage-limits

https://www.hsgac.senate.gov/imo/media/doc/STMT%20-%20Renaissance%20(July%2022%202014)2.pdf

Copy attached just in case that disappears

STMT – Renaissance (July 22 2014)2

Latest videos from the legend Jim Simmons

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!

Portfolio optimization secret sauce walkthru staying online until end of Tues Oct 17

Portfolio optimization secret sauce walkthru staying online until end of Tues Oct 17

Here is all the secret sauce walkthrough staying online until end of Tues Oct 17 (Eastern Standard Time)

NOTE Become a Quant Analytics member by purchasing here

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!

30K/yr for hedge fund secret sauce winning trade

30K/yr for hedge fund secret sauce winning trade

Are you the gambling kind? I will be taking a course to assess my value which I am sure I way below I currently offer

From Bloomberg, Sep 15, 2016, 7:00:05 PM

Jens Nordvig, one of the hottest prognosticators in finance, will sell anyone his secret sauce for winning trades for $30,000 a year.

To read the entire article, go to http://bloom.bg/2cqUeTi

Join my FREE newsletter to learn more about other secret sauce tricks for automated trading

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!

SecDB and SLang secret sauce to Goldman Sach’s profit and saving grace of the 2008 financial crisis? Quants rules the roots now!

SecDB and SLang secret sauce to Goldman Sach’s profit and saving grace of the 2008 financial crisis? Quants rules the roots now!

I like to use Goldman Sachs as a good role model for building out a tech operation built around being indie with your own source code.

About investment banks, Goldman Sachs is your #1 investment banks in the world:

http://en.wikipedia.org/wiki/List_of_investment_banks

https://www.quantnet.com/threads/former-goldman-quant-spills-secret.4316/

http://stackoverflow.com/questions/3392636/slang-goldman-sachs-proprietary-programming-language

http://www.cnbc.com/id/38584613

When you post the sort of items it is always decisions decisions.

After learning from others in various place, it seems your database is key to all your successes. Not models, but software architecture and design patterns to give you the edge. Math strategies and and other technologies are secondary. Just read me my links to see what I mean:
(As always lend me your ears for fedback)

http://news.efinancialcareers.com/ca-en/147434/inside-goldman-sachs-secret-sauce/

http://dealbreaker.com/2013/04/goldman-had-a-quarter/

http://dealbreaker.com/2013/04/mf-global-report-shows-limits-of-the-just-write-all-your-positions-on-post-its-method-of-risk-management/#fn06

http://www.secdb.com/

http://news.efinancialcareers.com/ca-en/174323/rise-quants-goldman-sachs/.

…teams, to the point where it’s the uber-technical guys who are gaining ground at the top. Since the shake-up of Goldman’s senior technology ranks at the tail end of last year – when R. Martin Chavez took over from Steve Scopellite as chief information officer, and Don Duet and Paul Walker were installed as co-heads of technology – the ‘strats’ have been taking over, suggest our sources.

Chavez heralded from Goldman’s ‘strats’ team, which is largely a quantitative function with the ‘core strats’ building complex models across the bank’s trading desks. So did Walker, who joined the bank as a vice president in the FICC strats team in 2001. Most are not pure technologists – heralding from a science, maths and engineering background – but are still very computational.

Nonetheless, Goldman continues to offer a lot of opportunities for technologists – at least 25% of its employees work in tech. Lloyd Blankfein says that the bank is a “technology firm nowaday”, while Walker’s LinkedIn profile invites technologists to get in touch with the bank’s HR teams.

How Math Quants Rule the World: High Frequency Trading

PHD psychologist article?

http://www.psychologytoday.com/blog/good-thinking/201405/how-math-quants-rule-the-world-high-frequency-trading

More SecDB and othe tech stuff:

 

“Best and brightest, SecDB is king ”

http://www.glassdoor.com/Reviews/Employee-Review-Goldman-Sachs-RVW1073827.htm

Former Employee – Equities Trading Strategist in New York, NY

I worked at Goldman Sachs

Pros

– best & brightest + very nice people
– SecDB, major competitive advantge, no other firm has this (altho they tried)
– exceptional quant talents (way smarter than traders)

Cons

– political on top (esp. the business side)
– like all banks, constant hustling
– some useless work just to get exposure or satisfy short term needs

Advice to Management

– better performance review procedure: it’s called 360 degree but in reality still one sided from manager
– make it a true meritocracy and reduce politics

 

http://www.wilmott.com/messageview.cfm?catid=16&threadid=59857

Slang seems to be integrated into C++ on Linux/UNixL

Some job notice descriptions:

http://www.simplyhired.com/job/slang-c-developer-job/performance-resources/tm7j2zx4oi?cid=ioazsyviorodfzazbsmmhfarqfjtjmbu

I will make a HUGE assumption this is for Goldman Sachs in Company: Performance Resources ??

 

Slang/C++ Developer 10666

Location: New York , NY

Group Summary

The Credit Technology team is responsible for systems that facilitate negotiation, approval and capture legal terms that govern counterparty risk. The risk can include trades with increased exposure to a counterparty or to certain events that can cause significant financial or reputational impact to either party. The technology includes building out tools to streamline business processes and modeling of terms in such a way they can be easily integrated with other systems in the firm for the purposes of operations, control, and management of counterparty risk.

The group is a talented mix of developers, architects, and functional analysts who maintain a technology friendly environment where quality of software is given prime importance and align with firm s initiatives on managing counterparty risk. We leverage test-driven development and other agile development practices to deliver quality software the first time out.

We do most development in Java and other proprietary platforms.

Role Summary

We are looking for talented developers interested in finance to build and maintain the applications which manage the firm s counterparty risk and satisfy regulatory requirements. You will gather functional requirements, participate in technical design sessions, and interact with other technology teams within Sales, Trading, Legal, and Controller areas to accurately model the terms and implement efficient workflows to streamline the business processes in the firm. The role will allow you to gain an understanding of various business processes at firm, the funding terms that affect pricing of OTC derivatives and suitability of the client to engage in such transactions. The successful candidate will participate in all phases of a project lifecycle and work with extremely bright and motivated individuals.

The successful individual will develop a UI application to capture client profile by presenting a form or questionnaire to sales and compliance. The application will be developed in slang/secdb and interacts with other systems via messaging, server calls, SQL queries etc. for storage, retrieve reference data and feed into operational flows.

In addition, the project also includes writing batch scripts (mostly in slang ) to reconcile data across multiple systems, notify alerts to users by email, generate reports etc.

Required skills:

Solid programming skills with good algorithmic thinking and data modeling

Programming languages: Slang, C++

Unix/Linux experience

Demonstrated history of technical projects successfully deployed to production

Must be able to gauge and define technical specs for applications supporting the business processes

Ability to understand business processes and make judgments in the technical complexity needed for the application that will support the business processes.

Good communication skills and organizational skills to understand and keep track of requirements as part of interacting with peers.

Some RDBMS experience

 

—-

Is Python used at Goldman?

http://www.goldmansachs.com/a/data/jobs/28392.html

Technology – FICC Technology – Commodities Franchise Front Office Developer (Java, C#, .NET, C++, Python)- Analyst, London

Job id

28392

Location

London

Full/Part Time

Full-time

Apply Now

Job Summary & Responsibilities

The Commodities Technology team in London is seeking a dynamic, entrepreneurial and hands-on individual. The candidate will have the opportunity to work directly with Traders, Sales, Operations and Strategists. This is a great role to get an insight into the commodities business and work closely with end users. The role involves working on a variety of projects such as new products set up, market driven changes, tools to improve productivity/support new business and re-engineer existing applications.

Problem solving ability and good communications skills are the key requirements.

The successful candidate will work on SecDb/Slang with elements of Java/C#/Web Development. This powerful object oriented database and interpreted language is similar to Python, and underpins front office pricing and upstream trade processing across the firm. Full training will be given.

Basic Qualifications

MANDATORY
•4-6 years of commercial experience
•Strong analytical skills
•Good knowledge of Object-Oriented Programming (Java, C#, .NET, C++, Python)
•Excellent communications skills

Preferred Qualifications

•Commodities knowledge
•Experience of a front office / client facing role
•Experience of programming in Python

—–

http://www.goldmansachs.com/a/data/jobs/30291.html

Technology – Trading Shared Services – Analyst Developer (Java, C#, .NET, C++, Python)- Analyst, London

Job id

30291

Location

London

Full/Part Time

Full-time

Apply Now

Job Summary & Responsibilities

Analyst Developer (Java, C#, .NET, C++, Python)

The newly formed Trading Shared Services team in London is seeking a dynamic, pro-active and hands-on individual. The candidate will have the opportunity to work on a broad set of functions across post execution services. Including Clearing & Middleware, Regulatory Reporting and our Core Matching and Trade processing services. The team is functionally aligned so gives the individual a great opportunity to go deep as well as gain a broad exposure across all major OTC derivative asset classes.

With this being a newly formed BU it’s also a great opportunity for the right individual to help shape our future and bring in new expertise as we harmonize teams across the functions we support. Problem solving ability and good communication skills are the key requirements. A strong interest in Agile & Test driven development are also welcome.

The successful candidate will primarily work on SecDb/Slang. This powerful object oriented database and interpreted language is similar to Python, and underpins front office pricing and upstream trade processing across the firm. Full training will be given.
There will also be opportunities to use Java.

Basic Qualifications

• 3+ years of commercial experience.
• Strong analytical skills.
• Good knowledge of an Object-Oriented Programming (Java, C#, .NET, C++, Python).
• Excellent communications skills.
• Pro-active and takes initiative.

Preferred Qualifications

• Degree in an analytical subject. (CS, Maths, Engineering, Finance etc)
• Previous experience in financial technology.

 

 

About investment banks, Goldman Sachs is your #1 investment banks in the world:

http://en.wikipedia.org/wiki/List_of_investment_banks

 

 

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!

I just posted Secret sauce trick to make your trading platform up to twice as fast with .NET and C Sharp

I just posted Secret sauce trick to make your trading platform up to twice as fast with .NET and C Sharp

This comes from the London Quant. It also shows why the software engineering can be more important than anything else in this whole world of trading.

These are for my QuntLabs.net Premium Member

–> JOIN NOW FOR ACCESS <–

Join my FREE newsletter to learn more secret stuff like this

 

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!

HFT Secret sauce videos revealed with memory management, MongoDB NOSQL, and ZeroMQ message queuing

Hi there

So what makes a HFT blitzkrieg lightning fast? I just posted this for my QuantLabs.net Premium Members:
“More secret sauce tricks for the ultra fast HFT system I saw in Microsoft .NET C# and Visual C++”
I am not a fan of supervision but I am very ok with this situation. I guess you could say I am be directed by a very technical REAL WORLD quant who has developed an amazingly fast HFT system. You could say I am replicating it at a very low level. Listed below are the latest technologies with video which makes this  thing scream in terms of speed:
1. Youtube video Demo overview of MongoDB NOSQL with Microsoft .NET C# and MonguVue GUI Client
2.  How to install ZeroMQ with C# and .NET binding and example on Microsoft Visual Studio 2012 or 2010
3. Youtube video Demo ZeroMQ with Microsoft .NET C# with Pipeline communication pattern
I hope you recognize the value of this. I just need to integrate all of these with my Matlab Simulink mode that can be code generated. If successful, I am off to the races with a potentially fast system.
The real secrets to these systems is in memory management and the data types chosen. It is not so easy as you think but I am learning it from a world class quant. Want to learn more about the secret sauce of these system?
Thanks Bryan
P.S. I may post the source code once complete but this system will be worth a LOT of money once completed. As a result, there will be a hefty amount to value in my membership.
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!

Youtube video on open mpi open source project vs mpi for C++ and Linux secret sauce for propietary HFT hedge funds

Here are some tutorial and video at end.

Join my march to HFT platform development

Open MP tutorial:

http://bisqwit.iki.fi/story/howto/openmp/

Decent comparison:

http://mc.stanford.edu/cgi-bin/images/7/78/Hybrid_MPI_openMP.pdf

Often hybrid programming (MPI+OpenMP) slower than pure MPI

– why? (pg 5)

–> USE OPEN-MPI.ORG <-

http://stackoverflow.com/questions/2427399/mpich-vs-openmpi

Standard MPI tutorial:

https://computing.llnl.gov/tutorials/mpi/

http://www.lam-mpi.org/tutorials/ <– Includes LAM for clustering machines within Linux and MPI

LAM MPI is abandonded

http://stackoverflow.com/questions/8770005/differences-between-lam-mpi-and-openmpi

OPEN MPI

http://hpcprogrammer.com/mpi-vs-openmp

However, if you are going to launch a single job across multiple nodes,
MPI is the de facto standard for parallelizing on clusters…

. Conversely, with MPI the entire code is launched
on each node and you control what each code executes based its node
number in the MPI universe along with an algorithm that distributes work,
eg, a master/slave model.

http://lists.apple.com/archives/mt-smp/2004/Mar/msg00002.html

 

MPI is based on local memory and message passing, and is intended for problems where moving data around is a key part of the domain. High-performance computing is very much about taking the dataset for a problem, and splitting it up among a host of compute resources. And that is pretty hard work in a message-passing system as data has to be explicitly distributed with balancing in mind. Essentially, MPI can be viewed as a grudging admittance that shared memory does no

http://stackoverflow.com/questions/185444/why-is-mpi-considered-harder-than-shared-memory-and-erlang-considered-easier-wh

**MPI Seems best for our HFT needs

To be really brief, MPI is not a shared memory model and is targeted to very highly parallelized systems. OpenMP is a shared memory model (as simple pthreads) and one of its advantages is that the parallelization process is easier with respect to MPI. So it’s harder to convert a serial program into a MPI parallelized version, but if you’d plan to run the program on thousands of nodes, you’ll probably have better performance with MPI.

http://askubuntu.com/questions/145119/what-is-the-difference-mpi-vs-openmp

 

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 ‘Secret Sauce’ tricks of Matlab, bridge to C++/C#, .NET open source HFT trading platform, backtesting MYSQL historical database

Quant ‘Secret Sauce’ tricks of Matlab, bridge to C++/C#, .NET open source HFT trading platform, backtesting MYSQL historical database

I am doing this Meetup and will be demoing the following only ONCE EVER in public! I have been researching for the last few years with some ‘secretive’ techniques and tools to help in me in quant.  I will reveal as I move forward on this model/strategy development cycle and quant development stack. I will reveal the following:

  1. Matlab’s powerful toolbox that enables you to generate C++ source code from your M file script models that you develop for quant analysis and trading decisions.
  2. How to bridge your C++ generated code using a Dynamically Linked Library which can be plugged into your .NET trading application. This can also be used in a Linux/Unix based platform as well. This technique is not openly documented anywhere I have seen.
  3. The superior TRUE open source trading platform I believe is the best in the world for leading quant based trading firms and prop shops. I do know many secret hedge funds and prop shops are using this very effectively. The best part is it is free and I can also say the support is quite decent. It can also scale very well and is blazingly fast.
  4. A brief demo of how to retrieve free Yahoo Finance end of day market data to capture for your Matlab data sets. I know Yahoo as a source is not the best but who really can afford Bloomberg or Reuters? There are better options as well which we can discuss including down to the minute real time tick data.
  5. How to use Matlab to record market data and automatically insert into a MYSQL database for historical back testing. Other major commercial databases can be easily implemented as well.

 

A small donation of $3-5 is asked to cover the cost of the room. We can also take the discussion into a more social setting across in the street in a restaurant/bar after we close. I do think GOOD beer encourages wishful thinking of owning fleets of Lamborghinis and have a jet setting lifestyle!!

Details at:

http://www.meetup.com/quant-finance/events/42092262/

 

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!