Can you do better than cap-weighted equity benchmarks?

April 28, 2011
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

We're on our way to Chicago for the annual conference for R users in Finance, R/Finance 2011. Revolution Analytics is proud to once again sponsor this conference, and during the sponsor lunch session at noon on Saturday, we're honoured to have Guy Yollin show how the big-data capabilities of Revolution R Enterprise can be used for quantitative finance. Here is the abstract for the talk:

Can you do better than cap-weighted equity benchmarks?

Guy Yollin, Visiting Lecturer, University of Washington
Krishna Kumar, Financial Consultant
Scott Payseur, PHD, Quantitative Analyst, UBS Global Asset Management

Indexing and passive benchmarking has been sold by pension consultants as an efficient allocation to endowments and pension plans. Index tracking and ETFs around them have had spectacular growth in AUM. However, cap-weighted indices are unintuitive and inefficient from a CAPM.

In this presentation we review several large universe equity indices (Russell 1000, S&P 500 etc). We propose an alternative efficient benchmark to the underlying indices. After constructing an intuitive measure of risk we construct alternative indices with robust optimization techniques using the RevoScaleR package of Revolution R Enterprise.

Here's more information about the session, from Yahoo! Finance:

WHAT: “High-Frequency Financial Data Analysis with R,” a session at R/Finance 2011
WHO: Guy Yollin, Principal Consultant, R-Programming.org
WHEN: Saturday, April 29 at 12:00 p.m. Central Time
WHERE: University of Illinois at Chicago

Financial institutions rank among the most cutting edge companies when it comes to data analytics. Increasingly, their tool of choice is the open source R statistics language. Thanks to R’s powerful computation ability, extensibility and openness, data analysts at banks, investment firms, insurance organizations and other financial institutions can create and run virtually any algorithm to unlock intelligence that keeps them ahead. Today’s data analysts however must tackle larger data volumes than ever before and are tasked to analyze it faster then ever.

In this session, Guy Yollin will present some of the latest optimization techniques for the financial sector using the RevoScaleR package for big data analysis from Revolution Analytics. RevoScaleR is a framework for fast and efficient multi-core processing of large data sets.

Revolution Analytics is pleased to be a sponsor of R/Finance. Organized by members of the R community, R/Finance is a specialized forum focused on the use of R in the financial services industry for applications such as portfolio management, time series analysis, advanced risk tools, high-performance computing and econometrics. Register to attend the R/Finance Conference.

R/Finance 2011: Agenda

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