The market is an ecosystem of millions of participants, each acting on their own information, incentives and beliefs, and constantly adapting to one another. Behaviour of this kind is intrinsically difficult to predict, because the parts depend on each other and on the environment around them. Traditional, linear financial models were never built to capture it.
This is the field of complex adaptive systems, pioneered at the Santa Fe Institute under several Nobel laureates. Savana is among the first to apply its principles directly to financial markets. It gives us a first-principles understanding of how prices form, where they are reliable, and where they quietly break down.
A Fundamentally Different Approach to Active Investing
Active Investing, Built on Science.
Our approach is grounded in more than a decade of research into how investment markets actually behave. Rather than attempting to outsmart the market, we seek to understand it. By studying the forces that drive market efficiency and inefficiency, we identify areas where market prices are temporarily disconnected from underlying value. We believe this disciplined framework delivers a consistent and repeatable source of long-term outperformance.
complex adaptive systems
Markets Are Living Systems
Collective intelligence
Why Markets Are Usually Right
Within a complex adaptive system, collective intelligence is an emergent property. It is the scientific principle that large groups tend to make better decisions than individuals.
Every day, millions of investors contribute information, opinions and insights through their trading activity. Together, these perspectives are aggregated into market prices. The result is a powerful form of collective problem-solving. Markets may not be perfect, but their ability to process vast amounts of information explains why most securities are priced surprisingly accurately most of the time.
The accuracy, however, is conditional rather than guaranteed. It rests on the structure of the crowd, specifically on the independence and diversity of the views being aggregated. Where that structure holds, prices are reliable. Where it degrades, the aggregation breaks down in ways that are systematic and, in principle, identifiable in advance.
Every day, millions of investors contribute information, opinions and insights through their trading activity. Together, these perspectives are aggregated into market prices. The result is a powerful form of collective problem-solving. Markets may not be perfect, but their ability to process vast amounts of information explains why most securities are priced surprisingly accurately most of the time.
The accuracy, however, is conditional rather than guaranteed. It rests on the structure of the crowd, specifically on the independence and diversity of the views being aggregated. Where that structure holds, prices are reliable. Where it degrades, the aggregation breaks down in ways that are systematic and, in principle, identifiable in advance.
The Foundations of Collective Intelligence
Three Conditions For An Intelligent Crowd
Collective accuracy is not automatic. It depends on three conditions holding at once. When they do, the crowd is wise. When any one of them weakens, accuracy degrades in a predictable way.
01
Diversity
Enough participants, with a genuine variety of perspectives, models and assumptions. Different viewpoints produce errors that point in different directions and cancel out.
02
Independence
Each participant forms a judgement on their own, free of undue influence. This guards against the correlated errors caused by herding and groupthink.
03
Skill
Each view carries some genuine signal, closer to the truth than pure chance. A crowd of informed, varied estimates tends to beat any single expert.
Savana's Engine
Pioneering Collective Intelligence in Investing
Savana was built to harness the principles of Collective Intelligence through technology.
Our proprietary investment engine evaluates thousands of companies simultaneously using a collection of diverse and independent valuation signals. Each contributes a unique perspective on value, creating a synthetic form of Collective Intelligence that is objective, scalable and free from emotion.
The result is a valuation framework that broadly agrees with market prices most of the time, but systematically identifies the rare situations where the crowd's judgement appears impaired. By combining cloud-scale computing, sophisticated data infrastructure and disciplined portfolio construction, Savana transforms the science of Collective Intelligence into a repeatable investment process designed to identify and exploit market mispricing.
Our proprietary investment engine evaluates thousands of companies simultaneously using a collection of diverse and independent valuation signals. Each contributes a unique perspective on value, creating a synthetic form of Collective Intelligence that is objective, scalable and free from emotion.
The result is a valuation framework that broadly agrees with market prices most of the time, but systematically identifies the rare situations where the crowd's judgement appears impaired. By combining cloud-scale computing, sophisticated data infrastructure and disciplined portfolio construction, Savana transforms the science of Collective Intelligence into a repeatable investment process designed to identify and exploit market mispricing.
the empirical evidence
Validating the Signal
Savana's proprietary valuation models are built on 10+ years of research and development. Our research demonstrates a statistical relationship between our valuations and forward stock price returns.
Average bi-monthly returns by Savana’s valuation outputs, spanning all NYSE and NASDAQ companies over a 10-year period from 1-Jan-15 to 1-Jan-25. Companies are assigned a valuation score between 0 and 1, with 0.5 representing intrinsic fair value. Scores are grouped into eight evenly spaced buckets from undervalued (left) to overvalued (right). Two-month are returns are consistent with the bi-monthly rebalancing frequency of Savana’s portfolios. Return distributions are winsorized (clipped) at the 1st and 99th percentiles to control for extreme outliers.
from theory to portfolio
Real Portfolios, Tested in Real Time
Savana continues to manage more than 100 contemporaneous paper-trade portfolios across the world's major equity markets, validating that the framework translates into real-world outcomes and building a ready-made pipeline for future products.
Our paper-trade inventory includes the Savana US Small Caps Strategy, which was managed as a contemperaneous paper-trade portfolio between 1 July 2022 to 7 November 2024. The performance of this Strategy validated our core investment hypothesis that our unique investment approach delivers a powerful and differentiated solution to alpha, and supported our conviction to launch the Strategy on the ASX in November 2024.
The Savana US Small Caps Paper-Trade Strategy
2+ Years
US Small Cap Paper-Trade track record from 1 July 2022 to 7 November 2024
+42.6% p.a.
Annualised Return
+26.7% p.a.
Annualised outperformance of the S&P 600 Small Cap (AUD) benchmark
2.26
Information Ratio
The performance data represents a contemporaneous paper-trade simulation of SVNP's investment strategy, with no actual money invested. Performance range is from 1 July 2022 to 7 November 2024. Total returns are calculated in Australian dollars and do not include any assumptions of fees or costs. The simulation assumes that dividends are reinvested. The simulated performance data aims to provide investors with an approximate indication of SVNP's extended track record. However, hypothetical performance results have inherent limitations. No representation is made that any account will achieve profits or losses similar to those shown. In reality, there are often significant differences between hypothetical performance results and the actual results achieved by a specific trading program. Hypothetical trading does not involve financial risk, and no hypothetical trading record can fully account for the impact of financial risk in real-world trading.
independent validation
"The evidence suggests that Savana is not just a factor or smart-beta manager but also a skilled stock picker, which is evident from their consistent outperformance of factor benchmarks. Its strong stock selection was persistent and pronounced even after adjusting for the market, sector and style."
- Foresight Analytics, February 2024
This is the engine now running inside ASX:SVNP. Since listing in November 2024, SVNP has continued to outperform its benchmark.
research & reading
Reading the Market Differently
Our investment process is grounded in a distinct way of thinking about how markets work. Below is a selection of our own writing and the external research that shapes our perspective.
savana research
essay · Livewire markets
Markets are wise, but not always
An introduction to Savana's investment philosophy. Learn how Collective Intelligence shapes market behaviour, and how Savana seeks to identify opportunities when the crowd's judgement breaks down.
wHITE PAPER
Valuation Decoded
Outlines Savana's valuation framework and presents empirical evidence that mispricings can be used to predict future returns. Discover how Savana transforms Collective Intelligence theory into a repeatable investment process.
wHITE PAPER
Beyond Human Limits
Details the philosophy, style and performance behind the Savana US Small Caps Strategy, paper-traded from July 2022 to November 2024. Explore the extended track record of our US Small Cap strategy before it launched as ASX:SVNP.
further reading
Revisiting Market Efficiency: The Stock Market as a Complex Adaptive System
Michael J. Mauboussin
Explaining the Wisdom of Crowds
Michael J. Mauboussin
Some Microfoundations of Collective Wisdom
Lu Hong and Scott E Page
Reframing Financial Markets as Complex Systems
Genevieve Hayman, PhD and Raymond Ka-Kay Pang, PhD