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Dynamic-Hedging-using-LSTM

A new and more effective method for dynamic hedging, developed during my research internship at Tsinghua University. The LSTM neural network outperformed 5 baseline models in several markets. Please see the project presentation slides.

The code is implemented in Python with Tensorflow, and the baselines were implemented in R.

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A new and more effective method for dynamic hedging

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