Tim Muirhead is a highly experienced trader who has been trading full time since 2005. He has worked in several proprietary trading firms as an options market marker, a spread trader and corporate advisor for private equity raisings.
With a background in Systems Engineering and Computer Science, Tim has also been at the core of development of proprietary automated high frequency trading (HFT) systems. These systems used complex algorithms to analyse markets are able to capture small arbitrages in fractions of a second. Over the last decade, Tim has drawn on this knowledge of markets to develop his own proprietary trading framework that combines fundamentals, technical, macro and sentiment, which is the system he now deploys as Portfolio Manager for Gleneagle’s Equity Fund.
Tim’s background lies at the intersection between engineering and finance. With bachelors degrees in Systems Engineering and Computer Science, he spent the first 10 years of his career as an automation engineer, working across the globe. In 1997 he was part of the team that won the Institute of Engineers Australia Project Excellence Award for Automation, Control and Instrumentation for BHP Engineering.
He has lived and traded through multiple market cycles and was living in Thailand for the 1997 Asian Financial crisis. Having traded through the dot.com bubble, the GFC, the Covid crash and all the market cycles to date, he has a wealth of market experience combined with real world knoweldge of how businesses operate.
Tim’s trading strategy can broadly be broken down into three stages:
Conduct top-down analysis of markets to identify new trends by using global macroeconomics data, industry shifts, major monetary policy changes and geopolitical factors.
Identify technical trends in country and industry benchmarks, and analyse specific industry specific drivers such as commodity supply and demand.
Identify assets that meet the proprietary technical criteria and develop target lists. Fundamental analysis is then performed to validate the best candidates for trade selection.
Trades are then placed within a portfolio risk framework to control aggregate exposure. A number of other factors are also considered such as event risk, counterparty risk and the impact of underlying market conditions.