We solve for the complexity of global capital markets through our continuous investment in research and innovation, identifying market inefficiencies both for alpha generation and to reduce the undesirable impacts from sequencing and longevity risks caused by tail risk events. Our data scientists and quantitative researchers employ contemporaneous analytical techniques leveraging our technology to solve complex portfolio and risk management challenges.

By taking a deeply scientific, eclectic and empirical data-driven approach to our research, we formulate hypotheses, build data models and test our ideas for their fragility and robustness, then select the best ideas for future product development. We utilise low-latency distributed computational power to enable real-time insight into volatile market behaviour for alpha generation and risk mitigation.

Collaboration with academia

Our capacity for idea germination is enhanced through long-term collaborative research engagements with academia. Our focal areas of research with academia include quantitative finance, such as the development of new models and frameworks for risk management, advanced AI analytics, data science and big-data visualisation.

Delivering tailored solutions

Our research-based collaboration naturally extends to our clients. We engage our clients with a solutions mindset, working collaboratively with them to gain a deeper understanding of their investment objectives and risk management challenges. We focus on developing tailored solutions that address their unique requirements.

Active Currency Hedging

Problem set: Investors vary in their approach to currency hedging of their international growth asset portfolios, some choosing not to hedge, others choosing to passively or actively hedge. Considerations in decision-making include the implications on/for risk diversification, for example providing an element of downside protection during tail events without negatively impacting liquidity.

Objective: The objective of this case study is to determine whether Edge/Wise’s active AI-driven currency hedging strategy can achieve superior risk diversification when compared with traditional passive and active PPP (Purchasing Power Parity-based) currency hedging strategies. Hedging strategy comparisons are based on an AUD-denominated US Equities portfolio (S&P500).

Approach: The benchmark for comparison for the three scenarios is the S&P500 price index AUD Unhedged. The hedge instrument applied is AUDUSD. The hedge ratio applied in all three cases is 50% of the total investment.

Return correlations were compared between:

(i) the S&P500 benchmark portfolio vs the 50% passively hedged portfolio

(ii) the S&P500 benchmark portfolio vs the 50% active PPP-based portfolio,

and

(iii) the S&P500 benchmark portfolio vs the active Edge/Wise portfolio.

Observations and outcomes: We observed meaningful reductions in return correlation between the benchmark portfolio and the Edge/Wise actively hedged portfolio in all cases – ie for the periods leading up to the GFC and Covid tail events, as well as through the tail event periods themselves. The risk diversification objective in those periods were fulfilled, and appreciably improved over traditional passive and PPP-based hedging strategies.