REVEALING THE HISTORICAL ACCURACY OF 100 POPULAR TECHNICAL INDICATORS (APPLICATION IS NOT LIVE YET) WWW.OLAPTRADER.COM

OLAPTRADER MISSION STATEMENT

Online Analytical Processing - or OLAP is an approach to quickly provide answers to analytical queries that are multi-dimensional in nature. OLAP

is part of the broader category - Business Intelligence (BI), which also encompasses relational reporting and data mining. The typical applications

of OLAP are in business reporting for sales, marketing, management reporting, budgeting and forecasting, financial reporting, and similar areas.

By their very nature, databases configured for OLAP allow complex analytical and ad-hoc queries with rapid execution time. Vast amounts of

data can be sifted and analyzed by virtue of “pre-aggregated” queries. This lends itself very well to an application which looks to validate or

invalidate the most trusted technical indicators currently employed to determine entry and exit points for equity purchases/sales. History

dictates that the investor should rely on more than one indicator for making buy and sell decisions. This is where the power of multi-dimensional

analysis gives him the information he needs in order to make more informed decisions.

Conventional means of technical analysis tends to emphasize comparing two or more indicators, possibly in conjunction with pattern analysis.

Armed with this information, he will feel sufficiently confident to invest in a company, index, or fund. Were the investor provided with the

historical performance of the indicator(s) and patterns, he may choose to continue using them as before, fine tune them, or switch to others.

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The purpose of this application is to provide an unprecedented level of both quantitative and qualitative historical analysis by using new and

novel techniques to reveal those indicators which have historically been the most accurate in predicting price movement. Thousands of stocks,

funds, and indexes, and decades of price data form the foundation upon which Business Intelligence operates in order to pull historical

performance metrics from the raw data. While many indicators have proven to be more predictive of future price movement, it has not

heretofore been possible to quantitatively determine the exact percent price increase over time for multiple, disparate indicators which all tend

to agree upon one thing: namely, this is a good time to buy or sell.

Armed with such information, I believe that the investor’s ability to make informed trades is significantly enhanced.

Video Series, Part I of V This video - part I of V details the basic premise behind the OlapTrader application. Namely, that historical technical indicator data can be mined for the historical performance of a group of mutually related technical indicators. This is done by scanning for Stocks which met these criteria in the past and then summing and averaging out the percent change in price over the course of time.

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Video Series, Part II of V

TELECHART 2007

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Video Series, Part III of V

STOCKFINDER.COM

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Architecture of an OLAP Based Historical Stock Market Application - Part 4 of 5

This video - part 4 of 5 details the basic foundation of the OlapTrader application. Namely, the SQL Server relational database upon which OLAP

cubes, dimensions, and measures are built. Tremendous numbers of complimentary technical indicators will be compared using twenty years of

historical stock market data. There is historical data for over 100 technical indicators, 65 Japanese Candlestick Patterns, 10 Fibonacci ratios,

Darvas Boxes, and more. In part two of this video series I will delve into more of the theory behind combining the indicators in order to derive

the historical percent change over time for groups of stocks which had, in the past, the same bullish or bearish criteria on the same day.

Video Series, Part IV of V

HARMONIC TRADING RECOGNITION SOFTWARE

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Video Series, Part V of V

ADDITIONAL INFORMATION

I AM LOOKING FOR AN EXPERIENCED MS SQL SERVER DBA TO PARTNER WITH!!