Nowcasting
Explain a fund's returns through broad market factors.
Nowcasting explains and predicts a fund's returns using broad market forces (more than 25 cross-asset market factors) rather than just its individual holdings. It shows which market dynamics are driving performance. It answers: which market factors explain this fund's returns, and is today's move in line with them?
How it works
It explains and predicts a portfolio's return through broad market forces rather than its individual holdings. Extending the classic factor approach, it uses more than 25 cross-asset factors (such as carry, momentum, value, quality, size, and low volatility) across equity, fixed income, commodity, foreign exchange, and credit, and a regression estimates how much each factor drives the return. Once calibrated, the model predicts the expected daily return and an acceptable range, and flags a potential anomaly when the actual return falls outside those bounds.
What you get
- A breakdown of how much each market factor (carry, momentum, value, quality, size, low volatility, and more) contributes to the fund's return, across equity, fixed income, commodity, foreign exchange, and credit.
- A daily predicted return with expected bounds, from a regression of returns against those factors and a tailored benchmark.
- Anomaly flags when actual returns fall outside the predicted range.
How to use it in Spark
The factor breakdown and predicted returns arrive as data in your workspace. Visualize the drivers on a canvas, and let a workflow or the Agent surface days that move against their expected range.