The Sharpe Capital Investment Platform brings together a multitude of novel innovations in smart contracts, quantitative trading, machine learning, linguistic analysis and artificial intelligence. Principally, we are issuing Sharpe Platform Tokens (SHP). SHP provides a proof-of-stake that permits platform participants to earn service fees in ETH in exchange for providing sentiment toward global equities and blockchain assets through our web and mobile platforms. Users are rewarded with service fees in proportion to the accuracy of the sentiment they provide, utilising a proof-of-reputation mechanism. The sentiment data collected is complemented with an array of natural language processing (NLP) strategies for performing linguistic analysis, including automated sentiment, emotional response, and contextual frame analysis. These novel approaches to understanding market dynamics, both in equity markets and blockchain assets, have been developed in collaboration with scientists at leading academic institutions. Together, these data provide a valuable source of insight for hedge funds, asset managers and private participants, and therefore a valuable revenue stream through the sale of these insights. Sharpe Capital has developed a proprietary, automated quantitative trading algorithm driven by a hybrid machine learning and artificial intelligence model, bringing together microeconomic fundamentals, macroeconomic data, real-time world events, crowd-sourced market sentiment and NLP-driven linguistic analysis, into an overarching model capable of managing a robust, high alpha portfolio across various asset classes. Sharpe Capital will operate a proprietary investment fund operating much like an automated enhanced index fund to further generate revenue to support the SHP community economy The proof-of-stake metric allows us to infer the level of confidence that platform participants have in the sentiment they provide, which, when coupled with an immutable proof-of-reputation stored on the Ethereum blockchain, permits weighting of sentiment to determine both the size of service fees paid to each user, and the level of confidence to place upon each sentiment indication received. Through direct crowd-sourcing of participant sentiment, we can ensure our automated models continue to capture human, affect-driven & cognitive processes, in addition to microeconomic fundamentalist and linguistic analysis based asset value forecasting. This is unlike a prediction market – there are no losses for incorrect predictions, merely a reduction in the user’s immutable reputation score, and consequently, the size of future payments. Likewise, consistently accurate users will increase their reputation, earning larger and larger payments in exchange for their insight. SHP also provides a mechanism for hedge funds and institutional participants to access our proprietary models, acting as a usage fee.

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