Quant Insight, a macro research firm providing discretionary managers with actionable investment ideas, has launched an Analytics Dashboard, which brings together the ability to analyse and visualise patterns between asset prices and the macro forces driving them, and tools to identify the best trading expression across all asset classes.
Discretionary portfolio managers face an ever more challenging environment: capital flight and margin compression due to the threat from passive strategies makes it more important than ever that active managers deliver superior performance. An explosion of data, greater cross-asset correlations and geographical inter-connectedness make alpha generation tricky. Moreover, even when managers have the right call on their macroeconomic or Central Bank policy view, they face the issue of choosing the right trade expression.
The new QI Analytics Dashboard provides an ultra-quick, user-friendly way for investors to access data and analytics relevant to their trading activity, in one single view. Discretionary managers are now able to easily visualise sensitivities to macro factors and valuation gaps to find the best trade expression of their view or chosen theme. Where an investor already has a pre-determined view, the QI Analytics Dashboard can rank by sensitivity to their chosen theme, thereby presenting the user with the optimal trading expression across all asset classes. Alternatively, users can quickly detect which equity index, sector or stock, which FX cross or part of the yield curve displays the biggest price deviation from the model; this affords the user an immediate snapshot of when a security is trading rich or cheap to QI model value.
Launched in January 2017 following three years of technological development, Quant Insight (QI) is a macro research firm that combines investment expertise with high-quality data, proprietary algorithms and AI driven machine learning models, to help institutional investors analyse and make sense of complex trading environments, make better trading and investment decisions, and ultimately improve performance.
Mahmood Noorani, Founder, Quant Insight, says: “What we have set out to do, is transform macro views and themes into actionable trade ideas. We do this by combining our investment expertise with AI and machine learning technology to improve our clients’ investment strategies.”
“The QI analytics dashboard was designed in response to client demand and will further improve the user experience for portfolio managers, significantly reducing the time required to assimilate necessary information, find the best trade expression and enhance overall performance.”
