Portfolio managers can now research like a quant in a fraction of the time it takes to use traditional tools. At our webinar on 14 September, we’ll show how.
Chief investment officers and portfolio managers are under immense pressure to increase returns, improve productivity, and reduce costs.
The question on their minds is, “how can we scale and systematize fundamental research so that we get results in less time?”
This challenge has been made all the more urgent by the asset management industry’s global performance in 2016.
Watch video — Introducing Thomson Reuters QA Point
For the first time since the 2008 financial crisis, the revenue pool of traditional managers fell worldwide, along with their profits.
In 2017, the environment remains just as challenging, amid further signs of outflows from active products and increasing competition from passive strategies.
Quant techniques without needing a deep quant skill set
Asset managers who make investment decisions based on fundamental research recognize that they need to look at data analytics to gain a competitive edge.
In particular, non-quant portfolio managers want ways to empower their decision making with newer methods and using the best data and tools in order to avoid being left behind.
One of the many approaches is using quant techniques to augment the research process when coming up with investment ideas.
In this instance, the decision will ultimately be made by a discretionary manager, but with better analytics to help them make that decision.
Portfolio managers and research analysts are increasingly looking to leverage quantitative tools for a number of workflows, from building more dynamic and robust screening to full-scale model building and backtesting.
Intuitive model building
At our webinar on 14 September, you’ll see how to use pre-built data mapping and intuitive multi-factor model building to get results in minutes, not weeks.
All of this can be achieved without the need to hire an expensive team of quants.
Our industry experts will discuss key topics including:
- How to incorporate quantitative, data-driven approaches to augment your current investment workflow
- The leveraging of quantitative tools for building factor models and backtesting
- The use of model diversification as a means of risk diversification
There will be an opportunity to find out about Thomson Reuters QA Point.
Powered by Elsen, this cloud-based platform allows you to easily build, modify, and backtest complex financial models — helping you take advantage of advanced investment techniques and data science without requiring a quant skill set.
Who is on the panel?
- Saeed Amen is the founder of Cuemacro. Over the past decade, he has developed systematic trading strategies at major investment banks. He is also a systematic FX trader, running a proprietary trading book trading liquid G10 FX since 2013.
- Tim Gaumer is the Director of Fundamental Research at Thomson Reuters, having held the same position at StarMine, a company acquired by Thomson Reuters in 2008. He has more than 20 years of experience conducting fundamental analysis.
- Zac Sheffer is the CEO and founder of Elsen, the Platform-as-a-Service company for large financial institutions allowing anyone to harness vast quantities of data to make better decisions and quickly solve the most complex problems. Zac is a mechanical engineer with a passion for finance.
The webinar will be moderated by Austin Burkett, Global Head of Quant and Feeds at Thomson Reuters. He has developed investment tools and financial data visualization products for over 10 years.