首页|Reports Outline Machine Learning Study Findings from Shanghai University (Deep L earning Option Price Movement)
Reports Outline Machine Learning Study Findings from Shanghai University (Deep L earning Option Price Movement)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in artific ial intelligence. According to news reporting out of Shanghai, People's Republic of China, by NewsRx editors, research stated, "Understanding how pricevolume i nformation determines future price movement is important for market makers who f requently place orders on both buy and sell sides, and for traders to split meta -orders to reduce price impact." Funders for this research include National Natural Science Foundation of China. The news editors obtained a quote from the research from Shanghai University: "G iven the complex non-linear nature of the problem, we consider the prediction of the movement direction of the mid-price on an option order book, using machine learning tools. The applicability of such tools on the options market is current ly missing. On an intraday tick-level dataset of options on an exchange traded f und from the Chinese market, we apply a variety of machine learning methods, inc luding decision tree, random forest, logistic regression, and long short-term me mory neural network. As machine learning models become more complex, they can ex tract deeper hidden relationship from input features, which classic market micro structure models struggle to deal with. We discover that the price movement is p redictable, deep neural networks with time-lagged features perform better than a ll other simpler models, and this ability is universal and shared across assets. "
Shanghai UniversityShanghaiPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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