Convert Mathematical/Statistical/Quant research to c++/other code (Bayesian,Markov,Ha
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Post a project like this$274
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- Proposals: 9
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Description
Experience Level: Expert
Background and Objective:
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We are developing an Ultra High Frequency Trading system based on Bayesian, Markovian models and Hawkes processes, to this effect we have selected approximately 1k+ research papers that are completely or partially relevant to our trading algorithm. These research papers are mostly theoretical and conceptual in nature, hence a background in Physiscs/Statistics/Mathematics is required to study them and convert their math/parameters into c++/other code. We have already implemented a few of these concepts however a major chunk of them still remains. This code will be part of a larger c++ trading system, and eventually will have n > 10e5 hyperparameters (extracted from these papers).
The objective of this job is to take each paper independently, identify the author's algo/formula/concept for trading the LOB and convert the math into c++/other language code, each hyper parameter has to be uniquely defined and the final algo/function has to produce desirable results. This can be done by simply writing a function that gives us an input and output (there is an existing structure for input data). Consolidation of the code will happen at a later stage. We already have a development server where all the code can be placed, run and visualized. Access to LOB/UHFT data will be provided as and when needed .
The code has to be tested/executed and the results have to be verified before a final go ahead. We will try and support you as much as possible with the resources required. After finishing each paper please also make a summary of upto 100 words explaining the working of the function, to make it easier for future developers.
Note:
Please feel free to send us any references or float the word around.
The ideal candidate would preferably have a background in Statistics/Mathematics/Physics and Quant Finance with a Masters or PhD.
We have a preference for c++ however, please let us know your choice of language.
Future Work:
Once we have all the c++/other code/functions in play we will move to the AI and Machine learning part where we will optimize parameters and select relevant features for our model. If you decide to be a regular contributor, we can look at giving you the majoirity of the work based on your interests and skills.
Budget:
Because of the sheer volume of these papers, we have budgeted $125 per paper conversion. Most of the code across these papers is repetitive and intuituve, after the initial few algos/functions the effort to combine and convert the equations will become fractional as compared to the original.
------------------------------------
We are developing an Ultra High Frequency Trading system based on Bayesian, Markovian models and Hawkes processes, to this effect we have selected approximately 1k+ research papers that are completely or partially relevant to our trading algorithm. These research papers are mostly theoretical and conceptual in nature, hence a background in Physiscs/Statistics/Mathematics is required to study them and convert their math/parameters into c++/other code. We have already implemented a few of these concepts however a major chunk of them still remains. This code will be part of a larger c++ trading system, and eventually will have n > 10e5 hyperparameters (extracted from these papers).
The objective of this job is to take each paper independently, identify the author's algo/formula/concept for trading the LOB and convert the math into c++/other language code, each hyper parameter has to be uniquely defined and the final algo/function has to produce desirable results. This can be done by simply writing a function that gives us an input and output (there is an existing structure for input data). Consolidation of the code will happen at a later stage. We already have a development server where all the code can be placed, run and visualized. Access to LOB/UHFT data will be provided as and when needed .
The code has to be tested/executed and the results have to be verified before a final go ahead. We will try and support you as much as possible with the resources required. After finishing each paper please also make a summary of upto 100 words explaining the working of the function, to make it easier for future developers.
Note:
Please feel free to send us any references or float the word around.
The ideal candidate would preferably have a background in Statistics/Mathematics/Physics and Quant Finance with a Masters or PhD.
We have a preference for c++ however, please let us know your choice of language.
Future Work:
Once we have all the c++/other code/functions in play we will move to the AI and Machine learning part where we will optimize parameters and select relevant features for our model. If you decide to be a regular contributor, we can look at giving you the majoirity of the work based on your interests and skills.
Budget:
Because of the sheer volume of these papers, we have budgeted $125 per paper conversion. Most of the code across these papers is repetitive and intuituve, after the initial few algos/functions the effort to combine and convert the equations will become fractional as compared to the original.
Vipul J.
100% (1)Projects Completed
2
Freelancers worked with
2
Projects awarded
27%
Last project
19 Aug 2016
United States
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