Credit Suisse has launched the Credit Suisse RavenPack Artificial Intelligence Sentiment (AIS) Index, a result of a collaboration with big data analytics provider RavenPack to create quantitative investment strategies from news analyses leveraging RavenPack's artificial intelligence algorithms.
The AIS Index tracks the notional performance of an algorithmic US large-cap sector-rotation strategy, harnessing the power of big data analytics to make sector allocation decisions in a tradable and systematic way.
According to Elaine Sam (pictured), head of equity derivative sales for the Americas at Credit Suisse, in New York, the index offers 'an innovative means to obtain exposure to asset allocations that are systematically selected by sophisticated data-driven analysis' based in 'a quantitative approach to information gathering'.
The strategy is based on sentiment scoring extracted from news data by RavenPack's artificial intelligence algorithms, and it represents Credit Suisse's entry into the growing field of big data-driven investment analysis. It is the bank's first quantitative investment strategy resulting from its collaboration with RavenPack.
A Credit Suisse spokesperson said this is the first Credit Suisse index that relies on artificial intelligence's interpretation of news data but declined to "go on the record or comment on future products linked to the index at this time".
According to Armando Gonzalez, president and chief executive at RavenPack, the new index is testimony of the increasing opportunities in the development of underlying strategies that can be deployed using index-linked and structured products "especially around those using quantitative investment techniques, artificial intelligence (AI) including machine learning, and alternative data sources like news and social media sentiment".
"Big data and artificial intelligence present a huge opportunity for the financial services industry, and this milestone collaboration with Credit Suisse shows the increased value our news analytics can provide to equity investors," said Gonzalez, adding that as investors adopt these new technologies, the market will start reacting faster and increasingly anticipate traditional data sources (e.g. quarterly corporate earnings, macroeconomic indicators, etc.).
"This will give an edge to investors willing to adopt these indexes, while eventually, the 'old' techniques and datasets will lose most predictive value and new datasets that capture Big Data will increasingly become the norm," said Gonzalez. "Likewise, investors today get diversification benefits and exposure to products that are built using orthogonal alpha sources."
SRP data shows that Credit Suisse has used 35 own-branded proprietary indices in 215 structured products sold across 20 retail markets. Some of the most featured indices developed by the bank's QIS team include the Credit Suisse FX Factor SEK Excess Return, Credit Suisse RALL Holt Index, Credit Suisse HOLT European Dividends Synthetic Return Index, Credit Suisse / Tremont Long-Short Equity Sector Invest Index, Credit Suisse / Tremont Investable Index, Credit Suisse / Tremont Hedge Fund Index, Credit Suisse / Tremont Event Driven Sector Invest Index, and Credit Suisse / Tremont Emerging Markets Sector Invest Index.
The Swiss bank has also sold eight products in the US market featuring a number of proprietary indices from its LAB series of indices which seek to represent the aggregate risk and return characteristics of hedge fund strategies using liquid, tradable instruments such as the Credit Suisse Global Alternative Energy Index, Credit Suisse FX Factor USD Excess Return, Credit Suisse Commodities Benchmark Index and Credit Suisse Emerging Markets Index, all of which have reached their maturity date.
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