Last updated 18 February, 2025. To see current performance, visit our live case study page.
This case study examines the effectiveness of LENSELL’s Asset Allocation Optimisation Service in a real-world scenario.
This live case study examines the impact of portfolio optimisation on a real investment portfolio consisting of 27 ASX-listed securities managed by an Australian Wealth Manager. Building a well-diversified portfolio is crucial for long-term investment success. However, even with a carefully constructed portfolio, periodic review and adjustments are essential to optimise returns and manage risk.
Starting with an initial value of AUD 100,000 in July 2024, we analyse the portfolio’s performance over a six-month period.
Portfolio Allocation — Original vs. Optimised
We compare the original asset allocation with an optimised allocation, demonstrating the potential gains achieved through strategic portfolio optimisation and rebalancing.
This case study will detail the specific changes made to the portfolio’s weightings, showcasing how optimisation can lead to greater expected returns and a significant difference in CAGR, in this instance, a 4.65% improvement.
For confidentiality reasons, the actual portfolio holdings are represented proportionally, starting from a base of AUD 100,000.
The optimisation process is rooted in the principles of Modern Portfolio Theory (MPT), developed by Harry Markowitz. MPT emphasises the importance of diversification across different asset classes to manage risk and maximise potential returns. LENSELL’s Asset Allocation Optimisation Service uses MPT principles to analyse the portfolio’s holdings, considering factors such as expected returns, volatility (risk), and correlations between assets. The service then identifies an optimised allocation that aims to maximise returns for a given level of risk (i.e. an “efficient portfolio position”). In this case, the optimisation considered the specific characteristics of the 27 ASX-listed securities, aiming to create a portfolio that had the highest expectation of return while minimising the level of risk (“Optimal Portfolio”).
By comparing the pie charts above, we can visualise the construction of the portfolio’s original and optimised asset allocation, while the table allows for a comparison of how each holding’s weight has changed after optimisation.
After 6 months, the portfolio in LENSELL’s Optimised Allocation sees a significant difference in CAGR, a 4.65% improvement.
Portfolio Performance
To assess the effectiveness of LENSELL’s Asset Allocation Optimisation Service, we compared the Wealth Managers’ actual realised returns to the Optimised Allocation Returns.
The strategy informed by LENSELL’s calculations yielded impressive results during a volatile market, with the portfolio valued at $104,743 from an initial value of $100,000, compared with $102,135.72 that would have been yielded by the same portfolio in the original (Wealth Manager’s) allocation. This represents a substantial increase of $4,743 in 6 months, or an extra CAGR of 4.65%.
Conclusion
By leveraging LENSELL’s Asset Allocation Optimisation Service, the Optimised Portfolio emerges as the clear option. This data-driven approach took advantage of market fluctuations to construct a portfolio with optimal asset allocation that delivered a significantly higher expected portfolio value of $104,743.02 after 6 months, translating to a 4.65% increase in CAGR when compared with a no change scenario.
This case study demonstrates the power of data-driven investment strategies and the value of LENSELL’s portfolio optimisation tools.
See more Optimisation Live Case Studies from LENSELL, here.
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Note: This analysis is based on the provided data and does not constitute financial advice. All data accurate as of February 2025. Investors should conduct their own research and consult with a financial advisor before making investment decisions.