GOIH Capital Markets: Quantitative Finance Theory ---Apple and Google up sharply.

Our Quantitative Finance Group (QFG) correctly predicted based on our in-house developed stochastic models and based on a Monte Carlo dynamic programming using the results of a Game Theory simulation as the input variable the direction of both Google and Apple. Our simulation receives proprietary data from HS Econometrics & Financial Theory which we process through a filtering mechanism before input into our models.


Last Friday on the close we picked up 200,000 shares of AAPL and also last week acquired 600,000 shares of Google at an avg. price of $648.25 and Apple at $170.44 per share. In the premarket GOOG is trading at $661.75 and Apple at a new all-time high of $187.40

We have received an overwhelming number of questions concerning how we are able to correctly predict the macro and micro structure of the market. Our answer is our QFG group uses revolutionary techniques on the frontiers of knowledge in the fields of behavioral finance, economic finance theory, macro-economics, and dynamic stochastic econometrics.

In particular our staff has uncovered several errors in the traditional market metrics which are used to price most of the S&P 500 market sectors as well as most of the companies listed in the S&P 500 Index. These errors were most likely the source of the subprime credit crisis as well as most likely the source of several hedge fund implosions.

We believe there are fundamental errors in the models of most of the Wall Street investment banks quantitative finance systems which under a period of market stress, the models give inaccurate results, and the models are subject to manipulation.

The models contain several inflections points based on the current knowledge base in financial theory, and which when designed with those inflection points leads to inaccurate predictions under what would be statistically considered as a 4 sigma event, when in actuality the event is more likely a 2 sigma event leading the large investment banks to think their position is hedged, when the position is really exposed and subject to being manipulated by those that know where the inflection points are located.

We have staff trained in the above disciplines and we utilized the latest in advanced dynamic programming using the global economic markets as isolated variables for our models.

Our models are calibrated using a modified filtered data set derived from more than 10 separate sources primarily sourced through HS Financial Data and Econometrics.

We consult with tax specialists, economists, programmers, legal specialists, financial theorists, and psychologists that design and develop our quantitative models and make our market predictions.