I assume that you’re reading this because you are one of many people who were affected by the changes to Yahoo Finance data in May (2017). Not only did the URL change, but the actual data changed as well!
The most noticeable difference is that the adjusted close column is now only split-adjusted, whereas it used to be split- and dividend-adjusted. Another oddity is that only the close prices is unadjusted (strangely, the open, high, and low are split-adjusted).
A quantmod user asked an interesting question on StackOverflow: Looping viewFinancials from quantmod. Basically, they wanted to create a data.frame that contained financial statement data for several companies for several years. I answered their question, and thought others might find the function I wrote useful… hence, this post!
I called the function stackFinancials() because it would use getFinancials() and viewFinancials() to pull financial statement data for multiple symbols, and stack them together in long form. I chose a long data format because I don’t know whether the output of viewFinancials() always has the same number of rows and columns for a given type and period. The long format makes it easy to put all the data in one object.
R/Finance 2017: Applied Finance with R
May 19 and 20, 2017
University of Illinois at Chicago
The ninth annual R/Finance conference for applied finance using R will be held on May 19 and 20, 2017 in Chicago, IL, USA at the University of Illinois at Chicago. The conference will cover topics including portfolio management, time series analysis, advanced risk tools, high-performance computing, market microstructure, and econometrics. All will be discussed within the context of using R as a primary tool for financial risk management, portfolio construction, and trading.
The team at DataCamp announced a new R/Finance course series in a recent email:
Subject: Data Mining Tutorial, R/Finance course series, and more!
R/Finance - A new course series in the works
We are working on a whole new course series on applied finance using R. This new series will cover topics such as time series (David S. Matteson), portfolio analysis (Kris Boudt), the xts and zoo packages (Jeffrey Ryan), and much more. Start our first course Intro to Credit Risk Modeling in R today.
You can find registration information and agenda details on the conference website. Or you can go directly to the Cvent registration page.
Note that registration fees will increase by 50% at the end of early registration on May 6, 2016.
The conference will take place on May 20 and 21, at UIC in Chicago. Building on the success of the previous conferences in 2009-2015, we expect more than 250 attendees from around the world. R users from industry, academia, and government will joining 50 presenters covering all areas of finance with R.
This post is in response to Michael Harris’ Price Action Lab post, where he uses some simple R code to evaluate the asymmetry of returns from the day’s close to the following day’s open. I’d like to respond to his 3 notes, which I’ve included below.
- The R backtest assumes fractional shares. This means that equity is fully invested at each new position. This is important because it affects drawdown calculations.
- When calculating the Sharpe ratio, the “geometric = FALSE” option must be used otherwise the result may not be correct. It took some time to figure that out.
- The profit factor result in R does not reconcile with results from other platforms or even from excel. PF in R is shown as 1.23 but the correct value is 1.17. Actually, the profit factor is calculated on a per share basis in R, although returns are geometric.
I completely agree with the first point. I’m not sure Mike considers the output of SharpeRatio.annualized with geometric=TRUE to be suspect (he doesn’t elaborate). The overnightRets are calculated as arithmetic returns, so it’s proper to aggregate them using geometric chaining (i.e. multiplication).
We have been working on a new charting engine for xts::plot.xts for the past couple years. It started with Michael Weylandt’s work during the 2012 Google Summer of Code, and Ross Bennett took up the torch during the 2014 GSoC.
This new engine improves the functionality, modularity, and flexibility of plot.xts by building off the framework Jeff Ryan began with quantmod::chart_Series. The modular framework allows users to plot an xts object and incrementally build custom charts by adding panels of new data (including transformations of the original xts object).
You can find registration information and agenda details (as they become available) on the conference website. Or you can go directly to the registration page. Note that there’s an early-bird registration deadline of May 15.
The conference will take place on May 29 and 30, at UIC in Chicago. Building on the success of the previous conferences in 2009-2014, we expect more than 250 attendees from around the world. R users from industry, academia, and government will joining 30+ presenters covering all areas of finance with R.
The R Project has once again been selected as a mentoring organization for this year’s Google Summer of Code (GSoC). If you’re not familiar with GSoC, it’s a global program that offers students a stipend to write code for open source projects, under the direction of a mentor. Mentors get code written for their project, but no money. Students get something like a paid summer internship, with open-source contributions they can reference on their resume.
Call for Papers:
R/Finance 2015: Applied Finance with R
May 29 and 30, 2015
University of Illinois at Chicago
The seventh annual R/Finance conference for applied finance using R will be held on May 29 and 30, 2015 in Chicago, IL, USA at the University of Illinois at Chicago. The conference will cover topics including portfolio management, time series analysis, advanced risk tools, high-performance computing, market microstructure, and econometrics. All will be discussed within the context of using R as a primary tool for financial risk management, portfolio construction, and trading.