Tim is the application specialist in Technical Analysis at Bloomberg LP in London, where he manages the rapidly increasing demand for charting and data visualization tools in EMEA.
He has over 30 years’ experience in financial markets, in trading, sales and research at major international banks, including State Street, UBS, BNP Paribas and Lloyds. He uses diverse but complementary technical methodologies, based on behavioural finance, to help Bloomberg clients to analyse sentiment in all asset classes and all conditions of volatility and liquidity.
In 2018 he additionally took an MSc in Financial Investigation, including a dissertation examining the dependency of financial markets on illicit flows from money laundering. He previously took a BA in Classics and is a full member of the Society of Technical Analysts in London and of IFTA.
Bloomberg has long offered back-testing of trading strategies based on technical indicators (both mainstream and customized), complete with optimization to find the best settings. Bloomberg now extends this into two key areas:
- Back-test technical trading strategies in relative terms, e.g. pairs trading or relative to an index or portfolio (benchmark & customized). Buy-side users can now quantify optimum trading strategies relative to actual portfolios, while sell-side users can offer recommendations which are carefully tailored to their clients’ investment parameters.
- Back-test trading strategies using Bloomberg’s vast library of global economic and corporate data. The value of macroeconomic research can finally be compared directly with technical analysis. Back-test equity brokers’ analyst recommendations, together with the impact of corporate activity (e.g. stock-splits or dividends), all on both an individual and relative basis.
This presentation demonstrates how Bloomberg technical analysis meets the practical needs of modern trading and investment, with direct comparison with macroeconomic research, analyst recommendations and corporate activity.