Asymmetries in volatility spillovers are highly relevant to risk valuation and portfolio diversification strategies in financial markets. Yet, the large literature studying information transmission mechanisms ignores the fact that bad and good volatility may spill over at different magnitudes....

This paper suggests how to quantify asymmetries in volatility spillovers that emerge due to bad and good volatility. Using data covering most liquid U.S. stocks in seven sectors, we provide ample evidence of the asymmetric connectedness of stocks at the disaggregate level. Moreover, the...

Noisy markets need extensive descriptions that are noisy themselves, such as deep regression trees that capture many data-local nonlinear anomalies and that do not require arbitrary weighting schemes like traditional linear multifactor models often do. Simple tools allow extraction of general...

The Prediction of a dynamic, volatile and unpredictable stock market has been a challenging issue for the researchers over the past few years. This paper discusses stock market related technical indicators, computing mathematical models , most preferred algorithms used in data science industries...

Backtesting stock market investment strategies is fraught with danger – for example, overfitting. The signal to noise ratio in stock markets is so low that overfitting is inevitable. Simulation offers a means of assessing and compensating for the dangers. It is not obvious at first how...

Social media can help investors gather and share information about stock markets. However, it also presents opportunities for fraudsters to spread false or misleading statements in the marketplace. Analyzing millions of messages sent on the social media platform Twitter about small...

Traditionally the price discovery is measured by information share (IS) and component share (CS) measures. Recently, Putnins (2013) proposed another measure called information leadership share (ILS) measure based on IS and CS measures. This paper performs an evaluation of ILS and finds some...

This paper studies the US equity market during the COVID-19 period in the first half of 2020. There is a record rise, then a record fall in prices and then a record recovery. Throughout the period there was extreme volatility and much short term momentum with fear and greed alternating. The VIX...

A prominent factor used in most models predicting stock returns is firm size. Yet no consensus has emerged on the magnitude and stability of the size premium, with some researchers even questioning the usefulness of the factor. To take stock of the voluminous academic literature on the size...

We investigate whether there are systematic jumps in stock prices using the Brownian motion approach and Poisson processes to test diffusion and jump risk, respectively, on Johannesburg Stock Exchange and whether these jumps cause asset return volatility. Using stock market data from June 2002...