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machine-learning-for-algorithmic-trading-second-edition

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

maker

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.

mcaa

Long-term analysis of Fama-French factors (momentum, value, size, equity risk premium).

mlb-payroll-and-wins

FiveThirtyEight replica

mlforecasting

Machine learning strategies for multi-step-ahead time series forecasting

my_story

Record My Curiosity

openalgo

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

Optimal Rebalancing Strategy Using Dynamic Programming for Institutional Portfolios

optimal_transaction_execution

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.

parsimonious

Estimation of parsimoniously time-varying parameter VARs

portfolioanalytics

portfolioanalytics-1

Portfolio Analysis, Including Numerical Methods for Optimization

practical-nlp-code

Official Repository for Code associated with 'Practical Natural Language Processing' book by O'Reilly Media

project_forexstudy

Study relationship between technical indicators and future Forex price

qmao

mirror of qmao on R-Forge; quantmod add-on: some quantmod-like functions

qmj

quantecon.applications

A repository that houses example code, applications and teaching material related to QuantEcon

r-finance-2015-mscp

The code for the Markov Switching model with constant transition probabilities shiny app in my R/Finance 2015 presentation.

r-graph-catalog

All graphs in “Creating More Effective Graphs”, made with R package ggplot2.

r2d3

Raphael Rendered, Data Driven Documents

r2d3-1

R package to create D3.js Visualisations

radamant

R-Adamant is a collection of functions and algorithms for processing of Financial Time Series, Risk Management and Econometrics.

radiant

Business analytics using R and Shiny

rapps

Repository for my R (Shiny) web applications.

rblpapi

an api to fetch data from a certain vendor which has a habit of asking for its name to be redacted

rcharts_d3_cpi

rcharts_dygraphs_shiny

rCharts + shiny + dygraphs -> maybe a good combination

rcharts_factor_analytics

rchartsdygraphs

An `rCharts` extension. Run `dygraphs` from R - interactive visualizations of time series using JavaScript and HTML canvas. See: http://dygraphs.com/ and

rddj

Resources for doing data journalism with R.