This note explores machine learning based modelling approach over classical quantitative methods with a focus on modelling realized volatility of asset price over time. Initially, a few modelling assumptions of classical quantitative finance are examined using recent market data. Daily stock...

The aim of this paper is to present novel tests for the early causal diagnostic of positive and negative bubbles in the S&P 500 index and the detection of End-of-Bubble signals with their corresponding confidence levels. We use monthly S&P 500 data covering the period from August 1791 to August...

We examine how traders react to two prominent stock market regulations. Under a constant fundamental value (FV) process, price limits and trading restrictions significantly reduce the price level and mispricing size when traders are inexperienced. Under a Markov-process FV, there is no evidence...

We investigate the effects of engagement auditor industry specialization on stock price crash risk. Although research on audit partners has been growing, we are not aware of any prior studies that investigate partner-level specialization and crash risk. Using a large sample of Chinese stocks...