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Name: hj
Type: User
Name: hj
Type: User
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
An R package to help manage R projects (e.g. Sweave reports) where multiple versions are created based upon a single source repository. For example, a monthly report where each versions is identitcal with the exception of easily definable parameters (e.g. date ranges for data extraction, title, etc.). This package is not meant to assist with package development or more complex data analysis projects. For those types of projects, consider devtools or ProjectTemplate, respectively.
Long-term analysis of Fama-French factors (momentum, value, size, equity risk premium).
FiveThirtyEight replica
Machine learning strategies for multi-step-ahead time series forecasting
Record My Curiosity
openAlgo is a public repository for various work product relavant to algorithms and the high frequency low latency electronic trading space with a bias toward market microstructure as well as exchange traded futures and options.
Optimal Rebalancing Strategy Using Dynamic Programming for Institutional Portfolios
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.
Estimation of parsimoniously time-varying parameter VARs
Portfolio Analysis, Including Numerical Methods for Optimization
Official Repository for Code associated with 'Practical Natural Language Processing' book by O'Reilly Media
Study relationship between technical indicators and future Forex price
mirror of qmao on R-Forge; quantmod add-on: some quantmod-like functions
A repository that houses example code, applications and teaching material related to QuantEcon
The code for the Markov Switching model with constant transition probabilities shiny app in my R/Finance 2015 presentation.
All graphs in “Creating More Effective Graphs”, made with R package ggplot2.
Raphael Rendered, Data Driven Documents
R package to create D3.js Visualisations
R-Adamant is a collection of functions and algorithms for processing of Financial Time Series, Risk Management and Econometrics.
Business analytics using R and Shiny
Repository for my R (Shiny) web applications.
an api to fetch data from a certain vendor which has a habit of asking for its name to be redacted
rCharts + shiny + dygraphs -> maybe a good combination
An `rCharts` extension. Run `dygraphs` from R - interactive visualizations of time series using JavaScript and HTML canvas. See: http://dygraphs.com/ and
Resources for doing data journalism with R.
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.