Let's say you have conditional access, condition X, to a piece of information, condition Y. If Y is met there is a catastrophic change in modern portfolio theory's efficient frontier. Let's further say that the change is not only catastrophic, but, given Y, so extremely obvious that executives in a large number of major corporations, as well as institutional investors, will be liable as individuals, for failure of due diligence under fiduciary responsibility to make even the disappearingly small investment requird to obtain access to Y. In other words, there would be no "safety in numbers" for executives and institutional portfolio managers.
Note, the definition of "obvious" as used above, was not remotely met by the introduction of the web 2 decades ago. I'm talking about something more qualitatively analogous to the market demand for breathable oxygen in the atmosphere -- THAT obvious and while not really that catastrophic to life itself, it may as well be for portfolio management and executive decisions.
In such a scenario there very low, but non-zero, motivation to make investments conditioned on Y until Y is known. And, indeed, there are many such low, but non-zero investments that make rational sense for institutional investors given the magnitude of their portfolios.
However, let's say that condition X requires nothing more than the signing of a CDA with reciprocal disclosure of investment plans conditioned on Y -- but the existence of such plans is a requirement for disclosure of Y.
This requires obtaining the small amounts required to do preliminary investments in speculative planning. Where do you go for such preliminary investments?
When seeking sources of information on Black Swan Bayesian investments, you might explore the following:
Books and Academic Papers:
"The Black Swan: The Impact of the Highly Improbable" by Nassim Nicholas Taleb provides foundational knowledge on Black Swan events and their implications.
"Antifragile: Things That Gain from Disorder" by Nassim Nicholas Taleb explores concepts related to Black Swans and their impact on investments.
Scholarly articles and papers on Bayesian methods in finance, which may be available through academic databases like JSTOR, Google Scholar, or SSRN.
Financial and Investment Journals:
Publications such as the Journal of Finance, Financial Analysts Journal, and Quantitative Finance often feature articles on advanced investment strategies, including Bayesian approaches.
Investment Research Firms and Think Tanks:
Firms specializing in quantitative finance or risk management, such as AQR Capital Management or Bridgewater Associates, may publish research or insights related to Bayesian methods and Black Swan events.
Online Courses and Lectures:
Platforms like Coursera, edX, and Khan Academy offer courses on Bayesian statistics, risk management, and advanced investment strategies. Look for courses that cover Bayesian analysis and its applications in finance.
Professional Networks and Forums:
Engaging in discussions on platforms such as LinkedIn, specialized finance forums, or professional groups can provide insights and updates from industry experts.
Financial News and Media Outlets:
Reputable financial news sources like Bloomberg, Reuters, and The Financial Times occasionally cover advanced investment strategies and their applications.
Consulting Firms and Advisory Services:
Consulting firms that specialize in risk management and investment strategy may offer insights and case studies on Bayesian approaches and Black Swan events.
These sources will provide a well-rounded view of how Bayesian methods can be applied to understand and manage Black Swan risks in investment strategies.
With a background in corporate finance, portfolio risk, and strategic investment frameworks, here’s how I’d approach your question:
What you’re describing — conditional access to transformative information (Y), with extremely small initial capital requirements (X) — essentially falls into the category of information-driven optionality. These “Black Swan Bayesian” opportunities don’t behave like standard investments. Instead, they rely on identifying situations where asymmetric upside exists because the market systematically underestimates low-probability/high-impact events.
In practice, the earliest capital for these opportunities almost never comes from institutional investors, because institutions typically cannot justify deploying funds based on information that is not yet fully validated. Instead, preliminary investment usually comes from individuals or very small funds who specialize in speculative optionality: angel investors with high risk tolerance, boutique macro funds, or family offices that intentionally allocate a small percentage of capital to speculative, information-driven plays. These groups can move quickly, have flexible mandates, and don’t require the full institutional due-diligence cycle that would otherwise prevent acting before Y is confirmed.
Once Y is known — and if the thesis is correct — institutional money then follows, because the opportunity becomes visible and defensible. But the earliest dollars almost always come from investors whose mandate explicitly allows them to fund scenarios where probability is uncertain but payoff potential is extremely asymmetric.
If you’d like, I can help you think through how to structure, validate, or raise for this type of Bayesian/optionality-driven thesis. Feel free to schedule a call anytime.
