# Market

# R for marketing students

## by KU Leuven Marketing department

KULeuven R tutorial for marketing students […] In this tutorial, we will explore R as a tool to analyse and visualise data. R is a statistical programming language that has rapidly gained popularity in many scientific fields. The main difference between R and other statistical software like SPSS is that R has no graphical user interface. There are no buttons to click. R is run entirely by typing commands into a text interface. This may seem daunting, but hopefully by the end of this tutorial you will see how R can help you to do better statistical analysis. So why are we using R and not one … Read more →

# Data Visualization Project

## by Chiayi Yen

Data Visualization Project […] This study aims at investigating how the change of information dissemination process would affect the window-dressing behaviors of mutual fund managers. By convention, window-dressing is defined as the portfolio manipulations right before the quarter-end date, when all the fund managers are required to disclosure their holding firms of that date. Over the past decades, technological progresses largely change the way how information disseminates, and these further influence the information flow of capital markets. For example, the implementation of “Electronic … Read more →

# 認識 R 的美好

## by 郭耀仁

是郭耀仁，資料科學與推廣教育的愛好者，喜歡使用 R 語言與 Python 做資料科學應用，在台大資工系統訓練班開設多門 R 語言與 Python 的相關課程，亦與企業合作提供客製化的內訓課程；同時也是一個超棒的中文資料科學專欄 DataInPoint 的主編；這個專欄與波士頓的資料科學教學團隊 DataCamp 有行銷合作（Affiliate Marketing）。 如果您有 R 語言、Python、資料科學、教學、專案或顧問的需求，可以 email 與我聯絡：tonykuoyj@gmail.com R 語言是一個高階的統計程式語言，她在 2017 IEEE 調查中排名位於第 6 名，1是以資料分析為主要目的程式語言中的最高位。其他熟為人知的像是 Matlab 排名在第 15 名、SQL 排名在第 23 名、 Julia … Read more →

# Backtesting Strategies with R

## by Tim Trice

Backtesting strategies with R […] This book is designed to not only produce statistics on many of the most common technical patterns in the stock market, but to show actual trades in such scenarios. Test a strategy; reject if results are not promising Apply a range of parameters to strategies for optimization Attempt to kill any strategy that looks promising. Let me explain that last one a bit. Just because you may find a strategy that seems to outperform the market, have good profit and low drawdown this doesn’t mean you’ve found a strategy to put to work. On the contrary, you must work to … Read more →