MT4 to R interface ... - page 2
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An Introduction to Analysis of Financial Data with R by Ruey S. Tsay : the book
Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research.
The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including:
Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison
Different approaches to calculating asset volatility and various volatility models
High-frequency financial data and simple models for price changes, trading intensity, and realized volatility
Quantitative methods for risk management, including value at risk and conditional value at risk
Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression
Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques.
An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.Practical Data Science with R by Nina Zumel : the book
Practical Data Science with R shows you how to apply the R programming language and useful statistical techniques to everyday business situations. Using examples from marketing, business intelligence, and decision support, it shows you how to design experiments (such as A/B tests), build predictive models, and present results to audiences of all levels.
This book is accessible to readers without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed.
What's Inside
Data science for the business professional
Statistical analysis using the R language
Project lifecycle, from planning to delivery
Numerous instantly familiar use cases
Keys to effective data presentationsHi all,
Although this threat isn't often visited I find it very interesting.
Thank Mladen, thanks Seekers to have enlighten me about this knowledge.
For those who wish to draw future, here is
The R Project for Statistical Computing
Moreover there is something new:
https://www.mql5.com/en/articles/1103
In these currency war times, digging fx knowledge could be an edge for better times.
Have a good trading week
Sincerely.
Tomcat98
We are just a cannon meat in the currency wars, but I agree with you : using R for calculations instead of mt could be an edge we are looking for
Thanks for the links
If we only could use mt just as a sort of shell - an avoid all the nonsense of mql
Clifford Ang, "Analyzing Financial Data and Implementing Financial Models Using R" : the book
This text aims to overcome several common obstacles in teaching financial modeling. First, most texts do not provide students with enough information to allow them to implement models from start to finish. In this book, we walk through each step in relatively more detail and show intermediate R output to help students make sure they are implementing the analyses correctly. Second, most books deal with sanitized or clean data that have been organized to suit a particular analysis. Consequently, many students do not know how to deal with real-world data or know how to apply simple data manipulation techniques to get the real-world data into a usable form. This book will expose students to the notion of data checking and make them aware of problems that exist when using real-world data. Third, most classes or texts use expensive commercial software or toolboxes. In this text, we use R to analyze financial data and implement models. R and the accompanying packages used in the text are freely available; therefore, any code or models we implement do not require any additional expenditure on the part of the student.
Demonstrating rigorous techniques applied to real-world data, this text covers a wide spectrum of timely and practical issues in financial modeling, including return and risk measurement, portfolio management, options pricing, and fixed income analysis.Haven't noticed this thread till now
Nice. Thanks
Worth a try - R is a different story from mql
Thanks for the post