Explore how Kalman filtering refines trading algorithms' risk and return estimates, with insights from Ben Trubshaw, Quantitative Trader at Tibra Capital.
Improving capital allocation to trading algorithms using Bayesian techniques (Ben Trubshaw, Tibra Capital)
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Wollongong Campus
39c 174
National Institute for Applied Statistics Research Australia (NIASRA) is hosting a seminar on Thursday 22nd August, 2024
Time: 11:30 – 12:30
Speaker: Ben Trubshaw (Tibra ambassador)
Venue: room 39c-174
One of the biggest challenges in trading is managing the low signal-to-noise ratio in the market. Therefore, we use Kalman filtering to estimate the risk and return of trading algorithms based on historic data. We can then use the posterior distribution to appropriately weight newly researched algorithms against those that are proven. Finally, we assess the performance of these estimates using real algorithms that have potentially been overfitted.
Speaker
Ben Trubshaw is a Quantitative Trader currently working in the portfolio management team after spending seven years on signal research in Tibra Capital. Additionally, he works alongside Professor Sumeetpal Singh, to improve on the statistical techniques used within Tibra.