transformation of the economy, which in turn will reduce the risk of offenses and crimes that constitute threats to the security of …

Model, to identify the risk factors discussed in 10-Ks. We apply this algorithm to a US REIT sample between 2005 and 2019 to … assess whether the probability of appearance of the extracted risk factors helps to explain the perceived risk on the stock … market. We find that the majority of risk factors is significantly associated with volatility indicating that our machine …

We investigate the stock return volatility predictability using firm’s fundamental risk with machine learning … fundamental risk in forecasting future volatility. The nonlinear models, especially the neural networks, outperform the linear … types. Firms with high expected volatility have higher fundamental risk and commonality in fundamental characteristics …