Our pre-built, ready-to-deploy thematic portfolios employ the latest alternative data analytics and can supplement any investment offering.
Explore a wide array of pre-built algorithmic strategies varied by asset type and investment style.
The model seeks to generate alpha over the S&P 500 using sentiment from Dow Jones Newswires. We use an NLP Transformer trained on a financial text corpus to score articles and buy stocks that have strong positive sentiment.
The model invests in stocks selected from the S&P 500 index based on OWL Analytics ESG scores. An aggregated ESG strategy gives more weight to stocks with the most E, S, G representation. Scores are industry neutralized to avoid industry biases.
The model invests in a subset of the Russell 1000 Index constituents according to the 100 highest ranking stocks from ISS EVA Spread factor. EVA Spread is a measure of of corporate profitability useful in determining a firm's true earnings.
The multi-strategy model is constructed from multiple portfolio sleeves including Adaptive News Sentiment, Adaptive ESG and Adaptive Corporate Metrics. Portfolio Hedges are constructed with liquid ETFs.
The multi-strategy model is constructed from multiple portfolio sleeves including Adaptive News Sentiment and Adaptive corporate metrics. Individual positions are subject to an 11% trailing stop loss.
Asset managers across the globe are challenged to outperform their benchmarks.
Traditional fundamental analysis using common data sources and techniques results in an increasing difficulty to outperform.
We help to create a competitive advantage by bringing together adaptive AI, alternative data sets and new ideas that set you apart from the competition.
We are putting our own money to work by deploying capital within our thematic portfolios to showcase their performance in real-time and provide full transparency into how the underlying portfolios perform with real capital in live market conditions.
Through our strategic data partnerships, we can deliver a portfolio unique to your firm – focused on specific dynamics such as carbon emissions and alignment with temperature goals, employee satisfaction, workplace safety, board diversity, human rights — or all of the above.
