I’m excited to share the call for papers for the upcoming R/Finance conference.  Even if you don’t submit a presentation, I hope to see you there!

Call for Papers:

R/Finance 2012: Applied Finance with R
May 11 and 12, 2012
University of Illinois, Chicago, IL, USA

The fourth annual R/Finance conference for applied finance using R will be held on May 11 and 12, 2012 in Chicago, IL, USA on the campus of the University of Illinois at Chicago. The two-day 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.

I will be traveling to Denver from 10/1-10/5.  Drop me a line if you’re in the area and would like to meet for coffee / drinks.

An updated version of TTR is now on CRAN.  It contains some much-needed bug fixes (most notably to stockSymbols()), some small changes, and a few new functions.  Note that the change to wilderSum() will affect functions that use it (e.g. ADX()).

Here are the full contents of the CHANGES file:

TTR version 0.21-0
  Changes from version 0.20-2

NEW FEATURES:

• Added variable moving average function, VMA().
• Added Brian Peterson’s price bands function, PBands().
• Added David Varadi’s DVI() indicator, DVI().

CHANGES:

As promised in the introduction to quantstrat, here is an example strategy.  I thought I’d start with the obligatory tactical asset allocation (TAA) strategy.  This post will replicate the strategy in the post, tactical asset allocation using blotter.

The “faber” demo in the quanstrat package contains a TAA strategy but it uses a slightly different approach than the code we’re trying to replicate.  There are two major differences:

1. The blotter TAA code initiates a position at the first observation where the close is above the SMA.  The demo only initiates a position when the close crosses the SMA to the upside.

quantstrat provides a generic infrastructure to model and backtest signal-based quantitative strategies.  It is a high-level abstraction layer (built on xts, FinancialInstrument, blotter, etc.) that allows you to build and test strategies in very few lines of code.  quantstrat is still under heavy development but is being used every day on real portfolios.  We encourage you to send contributions and test cases to the project forums.

This post is a joint effort between me and Brian Peterson.  It will describe the underlying philosophy of quantstrat and how quantstrat implements that philosophy.  You may have seen some of this in Brian’s Quantitative Strategy Development in R lightning talk at R/Finance 2011.

This is a guest post by Ilya Kipnis. He blogs at QuantStrat TradeR.

When trading stocks in a single currency, instrument metadata can be safely ignored because the multiplier is 1 and the currencies are all the same.  When doing analysis on fixed income products, options, futures, or other complex derivative instruments, the data defining the properties of these instruments becomes critical to tasks like accounting for value of trades, or comparing notional value between more than one instrument. The FinancialInstrument package provides a construct for storing metadata for tradeable contracts (referred to as instruments, e.g. stocks, futures, options, etc.) and their root representations.  It can be used to create any asset class and complex derivatives, across multiple currencies. 

The most recent issue of The R Journal was recently published.  If you’re not a regular reader, you should at least check out the following three contributed articles (listed in order of appearance).

• Rmetrics - timeDate Package
• Differential Evolution with DEoptim
• Analyzing an Electronic Limit Order Book

For those of you who don’t subscribe to the R-SIG-Finance mailing list:

1. You really should subscribe ;-)
2. Dirk Eddelbuettel announced the R/Finance 2011 presentations are now available.

I’ve included the entire announcement (with some hyperlinks) below.

The organizing committee for the R/Finance 2011 conference is pleased to announce the availability of presentation slides from the 3rd annual R/Finance conference.  This year’s two-day conference once again attracted over 200 participants from across the globe. Academics, students and industry professionals enjoyed almost 30 talks covering trading, optimization, risk management and more — all using R!

Timely Portfolio has been doing some interesting work with Ralph Vince’s Leverage Space Model via the LSPM R package. Here’s a short list of his most recent LSPM-related posts:

1. The Leverage Space Trading Model
2. Bond Market as a Casino Game Part 1
3. Bond Market as a Casino Game Part 2
4. Slightly Different Use of Ralph Vince’s Leverage Space Trading Model
5. Another Use of LSPM in Tactical Portfolio Allocation

I encourage those of you who are interested in LSPM and/or R to check out his blog.  I personally love how much code he shares!

PRESS RELEASE

The Leverage Space Portfolio (LSP) strategy seeks to maximize the probability of equity portfolio profitability by employing a risk-control process focused on capital preservation and drawdown management. Compared to a traditional buy-and-hold portfolio, an LSP-based portfolio aims for more consistent returns with lower risk.

The indexes, scheduled to be launched in the second half of 2011, can serve as the basis of both passive and active investment funds, including exchange-traded funds, mutual funds, and institutional accounts, around the world.