Signals:31/Aug/2012

Date: 31 Aug 2012
Strategy:MEOM

Action: Buy MOC (Market on Close)
Ticker: XLY
#Shares: 50% of equity

Action: Buy MOC (Market on Close)
Ticker: IYR
#Shares: 50% of equity

Signals:30/July/2012

Date: 30 July 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: XLF
#Shares: 339

Date: 30 July 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: XLV
#Shares: 128

Signals:30/May/2012

Date: 29 June 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: IYR
#Shares: 78

Date: 29 June 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: XLU
#Shares: 135

Signals:30/May/2012

Date: 31 May 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: IEF
#Shares: 46

Date: 31 May 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: XLP
#Shares: 147

Review of Quantpedia.com

I was recently approached by one of the founders of QUANTPEDIA.com – “The Encyclopedia of Quantitative Trading Strategies”. As he is a frequent reader of my blog, he asked if I would be willing to do a review of the Service they are offering. I seem to focus on researching new strategies these days so I thought it would be interesting to see what the service is bringing.

From my mail exchange with the co-founder I learned that Quantpedia.com is a start-up founded by a team behind the screener Finviz.com. Their goal is to systematically map financial academic research and derive trading systems out of the most usable research papers. They do so by extracting trading rules in a plain language, performance, risk and various other characteristics and then categorize all systems together with related research in a database that can be accessed through the service.

According to the co-founder: “Quantpedia.com currently contains more than 40 relatively well known trading strategies in a publicly accessible free section. The premium section, priced at $299 for a 3 months- or $499 for a 1 year subscription, contains more than 140 mainly uncommon and high performing strategies.”

Website Overview

At the home page of the service you are offered various menu sections. The actual screener let’s you search the database with strategies and filter on several aspects of a trading strategy like trading frequency, instruments, return/risk factors, Sharpe ratio, complexity etc. The results of the screener are presented in a table for which 4 different pre-defined views can be selected varying from basic overview to all filter criteria.

A second feature is the Charts section. This section offers five pre-defined graphical summaries of strategies in the database. The overview charts show histograms for each of the main filter criteria, e.g. the amount of strategies for the different instruments (see picture below).

The other summaries in the Charts section show extensive graphical summaries of the strategies in the database for areas of complexity, performance and risk. The Summary section finally shows all 187 strategies at time of writing sorted by Performance (including the estimated confidence range), returns and Sharpe ratio. I liked this screen as it gives in one glance the best performing strategies.

Other sections of the website include a Blog in which new additions to the strategy database are announced and a section summarizing the principle behind Quantpedia.com. This principle is based on the team continuously scanning various sources of information (research portals, financial journals, universities and conferences) and dissecting the information for relevance. In case a paper is selected a strategy is extracted and added to Quantpedia.com.

Strategy Database

The added value of Quantpedia is that for each strategy in the database the team has summarized and extracted the key information. After selecting a strategy from the output screen, the following information is presented in a structured format:

• Short description of the Strategy
• The fundamental reason why the strategy should work
• Characteristics of the strategy (frequency, markets, instruments, keywords, etc)
• Trading rules in plain language
• Source Paper that describes the strategy
• Relevant related papers
• A simplified performance chart indicating the

Below is a snapshot of the first 4 bullets for a strategy that can be accessed in the free section of the website:

I have reviewed several of the strategies in the database. My main findings are:

• Though I did not read all the source papers, I did read some of them in the past and I recognized the simple trading rules that were extracted. Quantpedia does a good job in extracting the characteristics of the strategy. An improvement could be to elaborate on variations.
• Where strategy information is lacking (e.g. estimated volatility) Quantpedia will fill in this void, clearly indicating how the data was determined /calculated.
• The trading rules in plain language are easy to understand, however are not always a 100% match with the rules described in the paper. This happens mainly when the strategy has a higher complexity and is understandable.
• The strategies in the database cover a wide range of fundamental reasons, instruments, markets and complexity. To me at least 40% of the strategies looked relatively new to me. So it brought a lot of new ideas.

Summary

These days I find myself spending a lot time reading papers, journals, websites identifying potential new trading strategies trying to understand if these would work for my portfolio. My personal belief is that Quantpedia is a service that would save me a lot of time in this research process and free up a significant amount of my time.

The website works very user friendly and I have found some interesting strategies that are new to me and interesting for further exploration. The price of $299 for a membership of 3 months or $499 for 1 year, may be at the high side for some potential users, however I belief this is easily covered if one would consider the time spend in the research process to get the same level of information.

FULL DISCLOSURE: I was given temporary access for free to the premium part of the service in exchange for writing a survey.

Signals:30/Apr/2012

Date: 30 Apr 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: XLY
#Shares: 377

Date: 30 Apr 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: QQQ
#Shares: 74

Signals:30/Mar/2012

Date: 30 Mar 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: EWT
#Shares: 377

Date: 30 Mar 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: EWH
#Shares: 288

Custom Backtest file available at Download page

Requested my several readers, I post here the Custom Backtest File that I use.
It includes features like go-in-cash, export stats, multiple entries etc.
Credits go to Frank Hassler at engineering-returns.com that has shared his CBT and from which I took several code snippets.
Download OutputStatistics.afl (rename file extension to .afl)

QD

Signals:29/Feb/2012

Date: 29 Feb 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: XLK
#Shares: 172

Date: 29 Feb 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: EWT
#Shares: XLY

Signals:31/Jan/2012

Date: 31 Jan 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: EWZ
#Shares: 76

Date: 31 Jan 2012
Strategy:MEOM
Action: Buy MOC (Market on Close)
Ticker: EWT
#Shares: 399