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The main focus of BrainBrane is the research of statistical arbitrage and other investment opportunities. Our investment strategies can be divided into two broad categories: quantitative strategies based on mathematical and computational models and cognitive strategies based on the analysis of human behavior and mind process. Quantitative strategies are the main focus of our activities, and are used to identify underpriced and overpriced securities. These strategies are based on mathematical models embodied in computer software (java and c++). On the other hand cognitive strategies are based on the detailed financial analysis which applies scientific research on human and social behaviour and on, cognitive and emotional factors. The goal is to better understand the economic decisions made by consumers, borrowers, investors, and how these decision affect market prices, returns and resources allocation. Our quantitative models and strategies are based on: • the use of mathematical techniques to identify profit opportunities based on statistical mean reversion property; • the application of proprietary models designed to limit portfolio risk exposure; • the use of quantitative techniques to hedge our portfolio and minimize the transaction costs; • the utilization of proprietary technologies to trade dynamically vanilla options and other derivatives. In the course of identifying profit opportunities, BrainBrane analyzes a great amount of data in different frequency, from tick by tick data to month returns. Our researches and strategies are also based on multifractal volatility, the study of fat tail events, market reflexivity and decisions making in a context of uncertainty. We use options and other derivatives to trade along all moments of market distribution. We collaborate with many phd and professors in Maths, finance, Bioinformatic, Signal processing and Informatic.