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Name: James
Type: User
Company: ABC
Location: Henan
Name: James
Type: User
Company: ABC
Location: Henan
Acm Cheat Sheet
Notes on Advances in Financial Machine Learning
This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver. Therefore, much of the analysis are correct and give an indication how these methods work.
An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.
Barra CNE6 因子构建
虚拟货币(BTC、ETH)炒币量化系统项目。币安交易所-量化交易-网格策略实践。火币、OKEX热门交易所未来都支持。最简单收益最靠谱的项目,包教包会。
Chartbuilder 2.0 (for test)
This is for cloud computing project
Recovers passwords from pixelized screenshots
Enhanced Index Tracking Strategy with application of Machine Learning and Tracking Error Optimization
Ultra-fast exchange engine
利用Wind API更新周频与月频因子
This journey accesses a Financial Risk Management API published on IBM Bluemix with Machine Learning on z/OS running on the mainframe through a simulated retail bank system called MPLbank.
A list of helpful front-end related questions you can use to interview potential candidates, test yourself or completely ignore.
Python web crawler to pull fund holdings from the SEC EDGAR database
A project of using machine learning model (tree-based) to predict short-term instrument price up or down in high frequency trading.
沪深300指数增强模型
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Algorithm Trading
A java client for Microsoft Lync 2013 Server Unified Communications Web API(UCWA) which is a REST API that exposes Lync Server 2013 Instant Messaging and Presence capabilities.
This algorithm was developed under the research project
OpenCV人脸捕捉和识别
This entry contains two topics The first item is entirely based on the following paper: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2011-056.pdf It contains 2 MATLAB demonstrating script : DATA_preprocessing.m & VAR_modeling_script.m DATA_preprocessing.m uses the LOBSTER framework (https://lobster.wiwi.hu-berlin.de/) to preprocess high frequency data from the NASDAQ Total View ITCH (csv files) allowing us to reconstruct exactly at each time the order book up to ten depths. Just look at the published script ! VAR_modeling_script.m contains the modeling of the whole order book as VEC/VAR process. It uses the great VAR/VEC Joahnsen cointegration framework. After calibrating your VAR model, you then assess the impact of an order using shock scenario (sensitivity analysis) to the VAR process. We deal with 3 scenarii : normal limit order, aggressive limit order & normal market order). Play section by section the script (to open up figures which contain a lot of graphs). It contains a power point to help you present this complex topic. The second item is entirely based on the following paper : http://www.courant.nyu.edu/~almgren/papers/optliq.pdf It contains a mupad document : symbolic_demo.mn I did struggle to get something nice with the symbolic toolbox. I was not able to drive a continuous workflow and had to recode some equations myself. I nevertheless managed to get a closed form solution for the simplified linear cost model. It contains a MATLAB demonstrating script : working_script.m For more sophisticated cost model, there is no more closed form and we there highlighted MATLAB numerical optimization abilities (fmincon). It contains an Optimization Apps you can install. Just launch the optimization with the default parameters. And then switch the slider between volatility risk and liquidation costs to see the trading strategies evolve on the efficient frontier. It contains a power point to help you present this complex topic.
An open source library for portfolio optimisation
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.