Abstract
Nowadays, market volatility prediction is the most prominent terms you will hear in the trading market. Realized volatility is the representation of price movements, market's volatility and the trading risks. A little change happened in volatility will affect the expected return on all assets. In this article, we will use the dataset provided by Kaggle platform to predict the volatility. As a leading global electronic market maker, Optiver is dedicated to continuously improving financial markets, creating better access and prices for options, ETFs, cash equities, bonds and foreign currencies on numerous exchanges around the world. The prediction model we used in our paper is LightGBM, which is an iimproved version of XGBoost. We conclude some related work about the prediction of volatility. And we compute our model with others, the result shows that our model LightGBM has a lowest RMSPE score that is 0.211. And compared to it, the RMSPE of other models such as logistic regression, SVM and XGBoost are respectively 0.099. 0.076, 0.034 higher than LightGBM.
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