Dr Sadik has an MSc Degree in Computational Mathematics with Modelling at Brunel University, London (2012). Dr Sadik completed his PhD in Applied Mathematics with a thesis on the ‘Asset Price and Volatility Forecasting Using News Sentiment’ at Brunel University, London (2018). His current research interests lie in the areas of empirical finance and quantitative methods and, in particular, the role of news sentiment in financial markets.

A Hybrid Approach to Multi-Equity Daily Trading

• Short term market movements (mini-regimes) predicted by AI & ML
• Long/Short Limits (parameters) adjusted in response
• News Factored in Asset Universe Filters
• Trade Portfolio of Multiple Stocks
• Daily Trade Signals for Adjusting Asset Allocations

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