Antonio Briola,Silvia Bartolucci,Tomaso Aste
Antonio Briola
We exploit cutting-edge deep learning methodologies to explore the predictability of high-frequency Limit Order Book mid-price changes for a heterogeneous set of stocks traded on the NASDAQ exchange. In so doing, we release 'LOBFrame', an o...
Walter Distaso,Antonio Mele,Grigory Vilkov
Walter Distaso
Many asset pricing models assume that expected returns are driven by common factors. We formulate a model where returns are driven by a string, and no-arbitrage restricts each expected return to capture the asset's granular exposure to all ...
DeepVol: volatility forecasting from high-frequency data with dilated causal convolutions [0.03%]
基于扩张因果卷积的高频数据波动率预测模型
Fernando Moreno-Pino,Stefan Zohren
Fernando Moreno-Pino
Volatility forecasts play a central role among equity risk measures. Besides traditional statistical models, modern forecasting techniques based on machine learning can be employed when treating volatility as a univariate, daily time-series...
Are missing values important for earnings forecast? a machine learning perspective [0.03%]
缺失值对于收益预测重要吗？一种机器学习视角
Ajim Uddin,Xinyuan Tao,Chia-Ching Chou et al.
Ajim Uddin et al.
Analysts' forecast is one of the most common and important estimators for firms' future earnings. However, it is challenging to fully utilize because of the missing values. This study applies machine learning techniques to impute missing va...
Philipp J Kremer,Damian Brzyski,Małgorzata Bogdan et al.
Philipp J Kremer et al.
Index tracking and hedge fund replication aim at cloning the return time series properties of a given benchmark, by either using only a subset of its original constituents or by a set of risk factors. In this paper, we propose a model that ...
Calibration to American options: numerical investigation of the de-Americanization method [0.03%]
基于美式期权的校准问题：去美式方法的数值研究
O Burkovska,M Gass,K Glau et al.
O Burkovska et al.
American options are the reference instruments for the model calibration of a large and important class of single stocks. For this task, a fast and accurate pricing algorithm is indispensable. The literature mainly discusses pricing methods...
A semiparametric graphical modelling approach for large-scale equity selection [0.03%]
一种大规模股票选择的半参数图模型方法
Han Liu,John Mulvey,Tianqi Zhao
Han Liu
We propose a new stock selection strategy that exploits rebalancing returns and improves portfolio performance. To effectively harvest rebalancing gains, we apply ideas from elliptical-copula graphical modelling and stability inference to s...