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ToDoList.txt
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ToDoList.txt
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############
# ToDo list in C:\Develop
### everyday tasks to-do
# Key Link signup
# BofA set email for Oksana
# Change Verizon primary email to dirac2010@gmail.com
# Jonnett email about TA for DataCamp
# request 2015 NYU check
# pay master Bruce
# verify NYU tax withholding amounts
###########
### explore
Internal and Primitive Functions
internal C functions
http://www.zerohedge.com/news/2013-09-27/when-bubbles-fail-albert-edwards-what-happens-when-fed-can-no-longer-contain-fury-99
http://www.zerohedge.com/news/2013-09-13/bernankes-helicopter-warming-larry-summers-first-pilot
# interview with Jim Simons
https://www.youtube.com/watch?v=U5kIdtMJGc8
###########
### tasks NYU to-do
- [ ] Arman first steps:
I spoke with professor Barry Blecherman about your capstone project
need to apply to professor Agnes Tourin in October
send updated script: load design matrix and roll pca
ask Arman to create project repository
what do I need to install?
- [ ] get student to create DataCamp courses
- [ ] obtain Professional Development grant
- [ ] apply for Professional Development Funds
- [ ] apply for Professional Development Funds
###########
### tasks NYU teaching to-do
- [ ] invite winners to course
http://engineering.nyu.edu/news/2015/12/21/triumphs-trading
- [ ] ask Barry to waive prerequisite FRE6123 for FRE7241
- [ ] ask students to take Datacamp courses
- [ ] take Portfolio Analysis Datacamp course
- [ ] upload to NYU Classes: Gandrud book Reproducible Research with R and RStudio.pdf
- [ ] ask students to answer question on stackoverflow
- [ ] ask students to publish in R Markdown on rpubs
- [ ] ask students to publish their plotly interactive plots on plotly
- [ ] ask students to publish their CV in R Markdown on GitHub Pages
https://plot.ly/r/github-getting-started-for-data-scientists/
- [x] Create LinkedIn group for jobs for students
- [x] Send email invitation to LinkedIn group for jobs for students
- [x] give names to students: Joe Pimbley, Naresh, Ken Walker kwalker@newoak.com
Jonathan Stein jstein@hess.com
- [ ] create Datacamp courses - developed by Filip Schouwenaars and Vincent Vankrunkelsven
martijn.theuwissen@datacamp.com
https://github.com/filipsch
https://github.com/vincentvankrunkelsven
https://www.datacamp.com/teach/
https://www.datacamp.com/community/
https://www.datacamp.com/community/blog/create-your-own-r-tutorials-with-github-datacamp
https://www.datacamp.com/community/blog/building-your-own-datacamp-course-with-github
https://github.com/datacamp/datacamp-light
# create new branches of courses
https://www.datacamp.com/teach/documentation#tab_repository_overview
# legacy datacamp R package
https://github.com/datacamp/datacamp
- [ ] create datacamp group
https://www.datacamp.com/groups/business
###########
### tasks quant models to-do
- [ ] create github repository develop
- [ ] read Norman Matloff book Parallel Computing for Data Science in R C++ and CUDA
VitalSource book reader
https://www.vitalsource.com/
jp3900@nyu.edu
Tw!nkle16
- [ ] create simple example using package RcppRoll
Kevin Ushey packages RcppRoll and RcppParallel
https://github.com/kevinushey/RcppRoll
https://kevinushey.github.io/
- [ ] create simple example using package RcppParallel
Kevin Ushey packages RcppRoll and RcppParallel
https://github.com/kevinushey/RcppRoll
https://kevinushey.github.io/
- [ ] PCA and regression analysis
https://www.analyticsvidhya.com/blog/2016/03/practical-guide-principal-component-analysis-python/
https://www.analyticsvidhya.com/blog/2016/07/deeper-regression-analysis-assumptions-plots-solutions/
https://www.analyticsvidhya.com/blog/2016/07/making-predictions-test-data-principal-component-analysis/
https://www.analyticsvidhya.com/blog/2016/05/h2o-data-table-build-models-large-data-sets/
- [ ] Jason Foster package roll
https://cran.r-project.org/web/packages/roll/index.html
https://github.com/jjf234/roll
- [ ] create .Rmd document for analyzing periods around volatility spikes
- [x] create interaction terms from most significant factors in design matrix
- [x] select only those design matrix columns that are most significant
- [x] apply function roll::roll_scale() to normalize (demean and standardize) the design matrix using past data
apply rolling dimensional reduction (PCA)
http://quant.stackexchange.com/questions/7921/how-to-normalize-technical-indicators-for-machine-learning
http://quant.stackexchange.com/questions/4434/gradient-tree-boosting-do-input-attributes-need-to-be-scaled
- [x] create design matrix called SPY_design containing multiple columns of aggregations using package HighFreq
use differences of volume, variance, and skew
- [x] develop forecasting model using principal component regressions (PCR)
- [ ] create forecasting model using LASSO
https://gist.github.com/alexchinco/467325abbf11d5c8f565
http://www.alexchinco.com/using-the-lasso-to-forecast-returns/
https://quantmacro.wordpress.com/2016/04/26/fitting-elastic-net-model-in-r/
https://quantmacro.wordpress.com/2016/01/07/lasso-model-example-lmes-aluminium-futures-price/
- [ ] develop backtesting system as follows:
create forecasting model: produce xts of forecasts
create learning meta-model: adjust parameters of forecasting model
https://timtrice.github.io/backtesting-strategies/
- [ ] apply package kernlab for Support Vector Machines
- [ ] analyze Feng Zhang backtest project
- [ ] analyze Fan Wang projects
C:\Lecturing and Conferences\Polytech\recruit\Fan Wang projects\Momentum
C:\Lecturing and Conferences\Polytech\recruit\Fan Wang projects\Stat Arb
C:\Lecturing and Conferences\Polytech\recruit\Fan Wang projects\Text Mining
- [ ] adapt code from: investment_strategies.Rnw
- [ ] implement Constrained Critical Line Algorithm
http://rnfc.org/2015/06/05/Markowitz/
- [ ] create data project called high_freq_data, using ProjectTemplate for importing WRDS data
http://projecttemplate.net/
http://blog.rtwilson.com/in-praise-of-projecttemplate-for-reproducible-research/
# ProjectTemplate/Markdown/RStudio/knitr Routine
http://nksbarker.blogspot.com/2013/07/my-projecttemplatemarkdownrstudioknitr.html
# Customising ProjectTemplate in R
http://jeromyanglim.blogspot.com/2014/05/customising-projecttemplate-in-r.html
https://github.com/johnmyleswhite/ProjectTemplate
- [ ] introduce unit testing to all packages
https://github.com/hadley/testthat
https://rpubs.com/manishb/t345
https://cartesianfaith.com/2016/06/30/how-to-write-good-tests-in-r/
- [ ] implement simple Shiny app and take tutorial
http://shiny.rstudio.com/
http://rmarkdown.rstudio.com/authoring_shiny.html
http://shiny.rstudio.com/articles/
- [ ] create simple ggvis
https://github.com/rstudio/ggvis
http://patilv.github.io/Interactive-Anscombe-Viz/
http://blog.ouseful.info/2011/08/30/the-visual-difference-%E2%80%93-r-and-anscombe%E2%80%99s-quartet/
- [ ] set up RSS reader
- [ ] contribute to:
https://bl.ocks.org/
https://bl.ocks.org/mbostock/1353700
- [ ] create R notebook
http://data-steve.github.io/setting-up-r-notebook/
- [ ] publish interactive plots on rpubs
https://rpubs.com/
- [ ] demonstrate how to run R from Google sheets and Excel: package excel.link
https://cran.r-project.org/web/packages/excel.link/vignettes/CallingRFromExcel.html
https://www.linkedin.com/pulse/integrating-r-solutions-excel-russ-penlington
http://stackoverflow.com/questions/11597626/running-r-scripts-from-vba
http://stackoverflow.com/questions/19170237/running-r-from-excel-vba-without-rexcel
http://sharpstatistics.co.uk/stats/more-than-macros/
http://sharpstatistics.co.uk/sharp-r/
http://blog.revolutionanalytics.com/2015/09/using-the-googlesheets-package-to-work-with-google-sheets.html
- [ ] read
https://www.quandl.com/blog/interview-with-a-quant-part-one
https://www.quandl.com/blog/interview-with-a-quant-part-two
https://www.quandl.com/blog/interview-with-a-quant-part-three
- [ ] write SSRN paper and send emails to:
Keren Shen, The University of Hong Kong
- [ ]
https://about.me/
- [ ]
http://metacademy.org/
- [ ] H2O prediction engine, sponsored by Stephen Boyd, Rob Tibshirani, Trevor Hastie
http://0xdata.com/
- [ ]
https://www.instapaper.com/
- [ ] Pocket for Chrome
https://getpocket.com/
- [ ] create weekly development diary
- [ ] study tenor (maturity) dependence of mean, variance, skewness, and kurtosis
show that skewness and kurtosis decay with time
- [ ] calculate tail shape of return frequency distribution and demonstrate power law
- [x] analyze code in functions:
rmOutliers
loadInstruments
getSymbols.FI - done
- [x] adopt .Rdata file and directory conventions
- [x] analyze code in:
scripts_hist.R - done
Rhistory 07-12-14.txt - done
copy anything useful and then delete files - done
###########
### tasks finished
- [x] install Ruby devkit
- [x] install gcc
- [x] create IB account