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> Initialising...
> BSc (Hons) Finance & Investment | UOG First Class>
> Statistical Arbitrage thesis | 92%>
> Trading Support Analyst | Energy markets
> Data Analysis | Data Science | Networking Protocols
> Programming Languages | Python(pandas, numpy, matplotlib, streamlit), C++(beginner), SQL
> Languages | English (Native), British Sign Language (Level 2), Mandarin (HSK 3 equivilant)
> Hobbies | Mixed Martial Arts, Gym, Running
> System Ready. Explore projects, research, and computational insights.
Challenge of the month
A researcher is estimating the unknown probability p that a trading signal produces a profitable trade.
Before examining the latest backtest, their prior belief about p is represented by p∼Beta(4,2).
The strategy is then tested on 94 independent trades, of which 63 are profitable and 31 are unprofitable.
Assume that, conditional on p, each trade outcome follows an independent Bernoulli distribution.
Question: After incorporating the backtest results, calculate the posterior predictive probability that the next trade generated by the strategy will be profitable.
Submit your answer as a whole-number percentage.