The recent Future of Investment Management Conference, held on 12 July 2023, brought together industry experts to discuss Australia’s economic outlook, portfolio construction challenges, risk management techniques, and the role of technology in investment.
The conference covered a range of topics, including the impact of inflation, geopolitical shifts, portfolio diversification strategies, operational risk management, model evaluation, machine learning applications, and the importance of ESG factors in corporate credit ratings. Let’s explore some of the key presentations from the conference.
Short and Long-Term Forces Impacting Australia’s Economy
Warren Hogan, the Managing Director of EQ Economics and Economic Advisor at Judo Bank, highlighted the challenges Australia faces in the next few years. He emphasised the importance of bringing inflation under control while minimising disruption to the economy. Additionally, Hogan discussed the need to enhance productivity by leveraging new technologies. Despite uncertainties in the global economic and political environment, he expressed confidence in Australia’s robust economic fundamentals, including its abundant natural resources, social cohesion, and favorable political, economic, and legal structures.
Navigating a New Investment Order
Ben Samild, Deputy Chief Investment Officer at the Future Fund, discussed the paradigm shift occurring in global markets. He noted the upsurge in foreign direct investment in the USA and Europe, contrasting with the decline of foreign investment in China. Samild highlighted the impact of geopolitics and national security concerns on investment decisions. The investing environment was described as complex, with risks of sluggish growth, high unemployment, and rising prices. Notably, the energy transition was identified as a factor that could fuel inflationary pressures.
Panel Discussion: Vanguard vs. Australian Retirement Trust
A panel discussion featuring Aidan Geysen from Vanguard and Andrew Fisher from Australian Retirement Trust centered around portfolio construction strategies beyond the traditional 60/40 allocation. The speakers shared their views on inflation and identified assets they believe will offer value in the near term. The discussion shed light on diversification approaches and the evolving investment landscape.
Leveraging Data for Risk Management
Nikki Cornwell presented on the benefits of a data-driven approach to operational risk management. She emphasised that analytic techniques offer clarity, consistency, and continuous monitoring of risks compared to traditional qualitative methods. Leveraging advanced analytics allows for increased predictive power and a forward-looking approach.
Exploring Uncertainty in Model Evaluation
Dr Laura Ryan highlighted the importance of considering uncertainty when choosing and evaluating models for unknown data-generating processes. She discussed aleatoric and epistemic uncertainties and suggested methods such as resampling, multi-model inferencing, and clustering to improve the reliability of models’ estimates.
Machine Learning for Earnings Forecasting
UBS research analyst Oliver Antrobus shared insights into using gradient boosting models to forecast forward earnings. This machine learning approach provides an alternative view of a company’s growth profile, overcoming biases in consensus estimates. Antrobus found that high-growth companies, as predicted by the model, were not fully priced by the market.
ESG Factors in Credit Ratings
Associate Professor Rand Low explored the relevance of ESG factors in determining corporate credit ratings. By using clustering techniques, he identified several industry classification, credit, and governance metrics that could help estimate ESG scores. This approach provides an alternative to vendor data and offers accurate and tailored ESG ratings.
Source: UBS data