A Method for Comparing Hedge Funds

📝 Original Info

• Title: A Method for Comparing Hedge Funds
• ArXiv ID: 1303.0073
• Date: 2013-05-14
• Authors: Researchers from original ArXiv paper

📝 Abstract

The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The paper describes further the implementation of the methods on a financial search engine system to identify behavioral similarities among time-series representing monthly returns of 11,312 hedge funds operated during approximately one decade (2000 - 2010). The presented approach of cross-category and cross-location classification assists the investor to identify alternative investments.

💡 Deep Analysis

Deep Dive into A Method for Comparing Hedge Funds.

The paper presents new machine learning methods: signal composition, which classifies time-series regardless of length, type, and quantity; and self-labeling, a supervised-learning enhancement. The paper describes further the implementation of the methods on a financial search engine system to identify behavioral similarities among time-series representing monthly returns of 11,312 hedge funds operated during approximately one decade (2000 - 2010). The presented approach of cross-category and cross-location classification assists the investor to identify alternative investments.

📄 Full Content

Reference