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Research · Algorithms
Quantitative technology is unforgiving: a wrong number is worse than no number. This direction studies the engineering of quantitative systems — data integrity, statistical honesty, backtesting discipline and the computation behind algorithmic strategies.
Active direction
How should a system communicate the freshness and provenance of every value it displays?
Which backtesting practices most reduce the gap between simulated and live behaviour?
How can statistical summaries disclose their sample size and method without cluttering the interface?
No findings have been published in this direction yet.