Due to its significance, forecasting asset volatility has been an active area of research in recent decades. In this whitepaper we aim to take into account the stylised facts of volatility to improve predictive power of a simple GARCH model. We investigate the power of three GARCH models (GARCH,...

In this study we investigate how the prediction of future volatility is improved by using news (meta)data. We use three input time series, namely: (i) market data, (ii) news sentiment impact scores, as explained by Yu (2014), and (iii) the news volume. We compare the results of predicting...

We report an empirical study of a predictive analysis model for equities; the model uses high frequency (minute-bar) market data and quantified news sentiment data. The purpose of the study is to identify a predictive model which can be used in designing automated trading strategies. Given that...

Oft-cited causes of mini-flash crashes include human errors, endogenous feedback loops, the nature of modern liquidity provision, fundamental value shocks, and market fragmentation. We develop a mathematical model which captures aspects of the first three explanations. Empirical features of...

We prove that the perpetual American put option price of level dependent volatility model with compound Poisson jumps is convex and is the classical solution of its associated quasi-variational inequality, that it is C2 except at the stopping boundary and that it is C1 everywhere (i.e. the...