In 1936, Turing proposed the famous Turing Machine idea. In October 1950, he published the paper Can Machines Think? Since then, human beings have gone deeper and deeper on the road of AI research. From the earliest perceptron model to the current popular deep learning, how to apply AI to the financial industry has become a hot topic of discussion. This article starts with the risk sources of options, and describes in detail the current mainstream risk hedging strategies in the financial market. Since option returns are highly correlated with volatility changes, in order to better predict future volatility changes, the text chooses the current popular neural network model to model Bitcoin price volatility, and finds that the neural network model can predict volatility. certain effect.
Summary of the main points of this article
The source of option risk in the capital market—the inconsistency between market judgment and model.
Common strategies for risk hedging. Sellers often use stop-loss trading strategies to hedge against price fluctuations of spot objects, while buyers use more neutral strategies such as Delta and Delta-Gamma, so that investors can benefit from rising or falling prices in the short term. option portfolios with positive returns.
By using the LSTM model to model Bitcoins historical price data, we found that the predicted results did not perform well for the part with relatively large price fluctuations, but the overall trend of the predicted results and the true value of the test set is still very close. To a certain extent, it can be used as a reference for option trading.