This is a summary of links featured on Quantocracy on Wednesday, 08/17/2022. To see our most recent links, visit the Quant Mashup. Read on readers!
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Geometric Brownian Motion Simulation with Python [Quant Start]Generating synthetic data is an extremely useful technique in quantitative finance. It provides the ability to assess behaviour on models using data with known behaviours. This has a myriad of applications, such as testing backtesting simulators for correct functional behaiour as well as allowing potential "what if?" scenarios to be evaluated, such as for simulated crises. Synthetic data
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Protected equity fund: Split your portfolio to better fit your hedging instruments [DileQuante]Imagine you are an European insurer. One of your funds is an equity portfolio of EMU stocks. Under Solvency II framework, you might want to reduce your Solvency Capital Requirement (SCR) thanks to the use of derivatives to hedge some of your equity risk. However, due to your size, the only sufficiently liquid contracts that you can use are Euro Stoxx 50 (E50) options. The problem is that your fund