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This thesis investigates whether a variational autoencoder (VAE) can be trained directly on raw, ir- regularly sampled option quotes rather than on pre-interpolated volatility surfaces. A Raw Set VAE is proposed, combining a Set Transformer encoder with a pointwise decoder to process unordered, variable-length sets of SPX option contracts without requiring prior grid construction. To isolate the c
