“Financial Economics, I argue, did more than analyze markets; it altered them. It was an ‘engine’ in a sense not intended by Friedman: an active force transforming its environment, not a camera passively recording it.” Donald MacKenzie, “An Engine, Not a Camera”, 2006.
Donald Mackenizie’s wonderful book, “An Engine, Not a Camera”, was referred to us by a couple of our most respected mentors, who regularly appear referenced in our Updates, after we published our February 2025 Update – “Rational Accounting Man”. It is a wonderful book that goes through the history of the evolution of what the author refers to as “financial economics”, what we refer to as “Sharpe World”. There is a great deal within it that aligns with our own efforts that we may come back to in future updates, but for now we will just note the core premise of “financial economics” not just snapping a photograph and passively (pun intended!) recording markets. No, we would portend that those very models, tools, maths, Nobel Prizes, regulations, practices have driven market structure and dynamics. They are fundamental in the ever-evolving determinants of initial conditions and, as such, our own frequent refrain that “positioning is all that matters”.
This conclusion, obviously to regular readers, parallels our own philosophical view of how markets and economies work. We take it maybe a step further with the introduction of Rational Accounting Man as the agent of manipulation for those imposing the rules on the regulated Sharpe World institutions. We suspect that this is how you get major market players to lever zero, even negative, yielding bonds, or how you make it ok for retail investors to take endless unbounded tail risks in the form of embedded short volatility, under the guise of enhanced yield, in unexplainably complex structured products, or even how central bankers use suspect models to justify ZIRP and QE as regulatorily ignored asset (leverage) bubbles build systemic fragility. We put it thusly in our February 2025 Update – “Rational Accounting Man” Convex Strategies | Risk Update: February 2025 – “Rational Accounting Man”.
“Meanwhile, central planners, in the form of central bankers and other like-minded policy makers, use these models to not just try to predict economic outcomes but, even more dangerously, to try to manipulate economic outcomes. They try to play God in their own fantasy metaverse of conjured rules and participants, fiddling with their scientistic models, ala the famed Dynamic Stochastic General Equilibrium model. Obviously, in the broader world of reality, we know that markets and economies behave like Complex Adaptive Systems (CAS), where the basic assumptions undergirding traditional economic and financial models simply do not exist. In reality, there is no such thing as Rational Economic Man, so what exactly are the policy makers trying to manipulate to guide things to the outcomes they desire?
The answer to that is our “Rational Accounting Man”. If markets and economies, and the agents participating in them, won’t behave like the models say they should, the solution became to create a subset of reality that would march to the beat of the central planners’ drum – Sharpe World in the form of regulated financial fiduciaries, aka Rational Accounting Man.”
We are certainly not alone in our ongoing refrain on these issues. One of the true leaders in the business of regularly pointing out, and mathematically proving, the flawed nature of Sharpe World practices is physicist turned hedge fund manager Jean-Philippe (JP) Bouchaud. Robin Wigglesworth, deserving of much credit, published a wonderful article in the FT in his semi-regular lunch conversation series. Huge kudos to Mr. Wigglesworth, the FT isn’t exactly known for venturing into advocacy of complex systems, in other words criticism of Sharpe World. We wish the article had dug a bit deeper into JP’s thoughts, and a bit less into the delicacies of their chosen dining venue, but we will take what we can get!
Investor Jean-Philippe Bouchaud: ‘The whole bull run is because of an influx of money’
JP’s response to the notion that somehow markets are efficient:
“It’s all wrong. It’s not weakly wrong – it’s badly wrong.” Jean-Philippe Bouchaud, September 2025.
Amen. Noting one of the cornerstones of Sharpe World, the Nobel winning Black-Scholes model, and the inherently flawed assumptions, JP had this to say:
“Black-Scholes was useful and misleading at the same time. It gave a very clear formula for option writers to hedge their position, which could be coded and followed blindly. Unfortunately, it tells you that if you do so quickly your risk is zero, which is wrong. Secondly, and perhaps most importantly, it creates feedback loops.” Jean-Philippe Bouchaud, September 2025.
Ah yes, again back to Sharpe World models not just defining markets but actually impacting how they function, namely feedback loops, or redefined initial conditions. JP goes on to reference some work near and dear to our hearts, what is known as the “Inelastic Markets Hypothesis”. This hypothesis, obviously, sits in rather sharp contrast to the Sharpe World stalwart, Nobel prize winning, “Efficient Market Hypothesis” (EMH). The article, in a move that truly shocks us, even links to the core academic paper introducing the inelastic markets hypothesis from Gabaix and Koijen, “In Search of the Origins of Financial Fluctuations: The Inelastic Markets Hypothesis”.
https://www.nber.org/system/files/working_papers/w28967/w28967.pdf
The authors make a very compelling case that markets (they focus only on equity markets in this paper) are in fact inelastic. Their key conclusion, given said inelasticity, is that flows have a much larger impact on markets than would be the case if markets were efficient, as assumed by your basic Sharpe World models. Their efforts tend to show that their hypothesis much more closely aligns to how markets actually behave: not something that has been of particular concern to the high priests of Sharpe World.
Their attention-grabbing conclusion is that the inelastic nature of markets leads to the scenario where $1 of additional purchases of stocks adds a whopping $5 of value to the market’s aggregate value. Further, those flows don’t generate a temporary dislocation of price that mean reverts, as is assumed in EMH as equilibrium prices adjust to some previously unknown information, but rather makes long-lasting price impacts.
“Importantly, the data are consistent with a quite long-lasting price impact of flows. Indeed, in the simplest version of the model, the price impact is perfectly long-lasting. This is not necessarily because flows release information, but instead simply because the permanent shift in the demand for stocks must create a permanent shift in their equilibrium price.” Gabaix and Koijen, June 2021.
While the paper is focused very much on the impact of flows, the point is that inelasticity of positioning is what makes the flows so impactful. It is the evolving initial conditions that then make the markets susceptible to the impact of shifts in supply and demand. Still, if one were to insist, we would revive our above statement to “positioning and flows are all that matters”.
One of the loudest voices in support of this thesis has been friend of Convex Michael Green, aka the Cassandra of Passive Investing. https://www.institutionalinvestor.com/article/2e5um1swovwbm3x5yyk1s/corner-office/why-michael-green-is-known-as-the-cassandra-of-passive-investing.
To be fair, we have never referred to Mike with that moniker, nor have we ever heard anybody else use it, so it may just be the author of this article that came up with it. We had the wonderful opportunity of spending some time with Mike when our paths crossed recently. No doubt he gets some credit for planting the seed that tilted us towards the theme of this month’s Update.
Those interested can follow along with Mike’s thoughts at his Substack page, “Yes I give a fig”. Yes, I give a fig… thoughts on markets from Michael Green | Michael W. Green | Substack
Mike takes the inelastic market hypothesis to an obvious next step. If markets as a whole are inelastic, then obviously subsets of markets, and the relevant flows that act upon them, are also inelastic. This leads to the implications of the massive expansion of passive investing and, in particular, passive index investing in market cap weighted indices. The biggest weights in the index consistently attract the largest weights of the persistent incoming flows and are the largest recipient of “permanent shift in their equilibrium price”, as noted above.
It is easy enough to pop online and find pictures showing the scale with which passive flows have been taking over total market activity.
Figure 1: Share of Total US Equity Fund Assets
Source: Yahoo!finance
Pardon our laziness, but we will use a previous picture to explain what might be some of the implications of this significant shift over to passive strategies. We used figure 2 in our July 2025 Update – “Preservation” Convex Strategies | Risk Update: July2025 – “Preservation”. The point then was to show the misrepresentation of an investor justifying the intentional trade-off of explicitly foregoing upside to probabilistically reduce downside. They showed the first set of like for like normal distributions to try to justify their cause.
Figure 2: GIC Proposed Portfolio Diversification Benefit
Source: GIC Report on the Management of the Government’s Portfolio for the Year 2024/25
We then showed a reconstructed version of this representation with a normally distributed distribution based on the risk and return metrics of their Actual Portfolio, presumably adapted with their enhanced diversification, and compared it with the normal distribution drawn from the performance metric they provided for their own Reference Portfolio.
Figure 3: GIC 5yr Portfolio Distribution Actual vs Reference
Source: GIC Report on the Management of the Government’s Portfolio for the Year 2024/25, Convex Strategies
Figure 3, which could be explained by the passive effect on equity market valuations, is at least a good pictorial expression of what that impact might look like (we know this because it looks very much like a picture that we saw Mike Green draw!). The persistent passive flows into equities has, in essence, shifted the return distribution to the right, meaning that anybody trying to be clever in a Sharpe Ratio targeting activity, i.e. explicitly foregoing upside to probabilistically reduce downside, has been punished by the superior performance of passive equity. A punishment that couldn’t be made up by supposed diversification across other naïve Sharpe Ratio optimizing strategies. This is why active is losing out, they aren’t solving for the correct problem, i.e. compounding.
JP Bouchaud wrote his own follow up to the inelastic market hypothesis paper, “The Inelastic Market Hypothesis: A Microstructural Interpretation”.
[2108.00242] The Inelastic Market Hypothesis: A Microstructural Interpretation
“If order flow is the dominant cause of price changes, ‘information’ is chiefly about correctly anticipating the behaviour of others, as Keynes envisioned long ago, and not about fundamental value. The notion of information should then be replaced by the notion of correlation with future returns, induced by future flows.” Jean-Philippe Bauchoud, January 2022.
JP and Mike, as should be obvious, also point out that the implications of flows go in both directions.
“The 2007 quant crunch and other recurrent deleveraging spirals are also extreme consequences of the impact of order flow on prices.” Jean-Philippe Bouchad, January 2022.
Here JP touches on the “flow” that is, to our opinion, the most significant one. That being the application of leverage. This, as we have discussed so often, is what sets up the fat-tailed, negative-skewed, distribution that is the number one detriment to compounding paths. It is the application of leverage, both explicit and implicit in the form of volatility selling, that makes the inelastic market so vulnerable to “deleveraging spirals”. The utilization of leverage is, in a sense, like adding steroids to the core flows that are both impacting and redefining initial conditions.
We have often discussed the concept of correlation as leverage and the flaw of relying on assumptions of stable correlations in the process of building supposedly diversified investment portfolios, only to be let down time and again as correlations prove to be anything but steady when you need it the most. This is another of those chicken-or-the-egg conversations that we engage in regularly. Does correlation become unstable because markets crash? Or, do markets crash because correlation becomes unstable? Our experience leads us to lean towards the latter. Kindly, JP has done some wonderful work related to this topic in two papers that he and his coauthors put out this year.
[2206.10419] Multivariate Quadratic Hawkes Processes — Part I: Theoretical Analysis
Multivariate Quadratic Hawkes Processes — Part II: Non-Parametric Empirical Calibration
There is some pretty geeky mathematics (multi-fractal stuff) underlying these notes, but the explanations provided are very easy to keep up with. In a nutshell, dependence on stable correlations is leverage. This leads to notable findings that volatility on one asset can and does have a direct result into volatility on other assets. These understandings provide explanations for the empirical realizations of things like volatility clustering and power-law distributed return dynamics.
We can go back to our simple visual of the football pitch to show the empirical implications of what all the high-level mathematics from these papers are showing. To paraphrase the godfather of showing the shortcomings of Sharpe World, Benoit Mandelbrot, it is magnitude, not frequency, that matters. Worth noting that Chapter 4 of the MacKenzie book covers a good bit of Mandelbrot’s history as he was developing his criticism of the traditional models of finance.
Figure 4: Frequency vs Magnitude. Normal Distribution (black) and Shannon’s Entropy Curve (yellow). Shading by Percentile Contribution to SPX Index 40yr CAGR. Oct 1985 – Sept 2025.
Source: Bloomberg, Convex Strategies
Those unfamiliar with the construction of this wonderful visual representation can go back to our June 2023 Update – “One Thing” Convex Strategies | Risk Update: June 2023 – One Thing. It reveals, fairly starkly, the obvious benefits to our persistent refrain that it is the divergences from the mean that drive the compounding path, not the mean.
Those using the tools of Sharpe World are not asking the right questions, are not pursuing the right objectives. Sadly, very much aligned with the theme of MacKenzie’s book, the tools and models of Sharpe World have been allowed to align benchmarks and incentives to the statistical analysis of frequencies. As Charlie Munger observed, “Show me the incentive, and I will show you the outcome.”
Seriously, how does optimizing to the mean expected return make any sense? Look at this real-world frequency distribution of S&P 500 returns.
Figure 5: Frequency Histogram of S&P 500 Annual Returns. 1929 – 2024
Source: Bloomberg, Convex Strategies
Over 95 years, the mean annual return of the S&P 500 is 7.9% (we are ignoring dividends here, which does not alter the point). The width of the blue bar that captures the mean is circa +/-0.9%, so the range of that bar is approximately 7.00% to 8.80%. There are three occurrences inside that range. The error estimate, aka standard deviation, is 18.80%, a little over 2x the mean. This is before we even get into the nature of large numbers on multiplicative, geometric, long-term compounding paths. See figure 4 / football pitch above! As we so often say, it’s just math.
Serendipitously, Nassim Taleb just dropped on his X feed a screenshot of a revised version of one of his papers, along with co-author Pasquale Cirillo, on just this topic. The initial paper, from 2019, is titled “Branching Epistemic Uncertainty and Thickness of Tails” and the revised version is titled “The Regress of Uncertainty and the Forecasting Paradox”. All we have seen of the revised one is the screen shots from Nassim’s twitter feed. There is enough difference between the two versions that we would advocate reading both, for those so inclined.
https://arxiv.org/pdf/1912.00277
From the initial 2019 paper, the authors give us this conclusion on their work:
“The results have relevant implications for forecasting, dealing with model risk and generally all statistical analyses. The more interesting results are as follows:
- The Forecasting Paradox: The future is fatter tailed than the past. Further, out of sample results should be fatter tailed than in-sample ones.
- Errors on errors can be explosive or implosive with different consequences.”
Nassim Taleb/Pasquale Cirillo, 2019.
We love the term errors on errors. In market parlance, standard deviation becomes volatility (both, the square root of variance). Errors on errors becomes volatility of volatility. As the authors put it:
“…one can keep nesting uncertainties into higher orders, with the dispersion of the dispersion of the dispersion, and so forth. There is no reason to have certainty anywhere in the process.” Taleb/Cirillo, 2019.
The revised paper is absolutely full of nuggets, many of which align with our own works and comments.
Aligning with our own “Probability vs Possibility” Convex Strategies | Risk Update: March 2023 – Probability vs Possibility, Nassim gives us:
“One of the central problems of knowledge concerns the gap between representation and truth (that is, between map of reality and reality)…” Taleb/Cirillo, 2025.
Aligning with our own “Reverse Polanyi Paradox” on the shortcomings of today’s AI, which we coined as “It (AI) can tell more than it can know” Convex Strategies | Risk Update: May 2024 – “Polanyi’s Paradox”, Nassim gives us:
“In machine learning, the problem resurfaces in the tendency of modern AI systems to be overconfident: despite good predictive accuracy (on the short run), they often lack calibrated and reliable estimates of their own uncertainty…our ignorance about our ignorance structurally reshapes predictive distributions.” Taleb/Cirillo, 2025.
As we so often say, history alone is a poor measure of risk. Using it to forecast, or model, future risk and opportunity is a fool’s errand.
“Our approach highlights that this hierarchy of uncertainty is the true, deep structure of model risk: uncertainty propagates recursively, and the structure of this regress thickens tails across domains. Practitioners often halt this regress after the first step, treating their own statements of uncertainty – such as confidence intervals – as if they were themselves known with certainty. This is a profound mistake that leads to the monumental underestimation of risk from higher moments.” Taleb/Cirillo, 2025.
That is very well said. Going back to Wittgenstein, understanding is contextual Convex Strategies | Risk Update: April 2024 – “Wittgenstein’s Ruler”. The future is not explained by the past; it is defined by current initial conditions and a whole bunch of unknowability.
Of course, you wouldn’t know that, from listening to those pontificating from the ivory towers of Sharpe World. Take for example the ongoing sham that is the exchange of letters between the Governor of the Bank of England (BOE) and the Chancellor of the Exchequer, whenever the BOE fails to meet its price stability target, not exactly a rare event these days as shown in figure 6.
Letter from the Governor to the Chancellor
“More generally, the restrictive stance of monetary policy is expected to return inflation towards the 2% target next year… A gradual and careful approach to further withdrawal of monetary policy restraint remains appropriate. The restrictiveness of monetary policy has fallen as Bank Rate had been reduced. The timing and pace of future reductions in the restrictiveness of policy will depend on the extent to which underlying disinflationary pressures continue to ease.” BOE Governor Andrew Bailey, September 2025.
Figure 6: UK CPI yoy% (white) vs BOE Bank Rate (blue). Price Stability Target Range (yellow dashed). Aug1995 – Aug 2025
Source: Bloomberg, Convex Strategies
About the only thing in there that we would assign any credence to is that they have reduced restrictiveness, if there ever was any, as they have lowered the Bank Rate. They have reduced their policy rate by 125bp over the last year. Meanwhile, their price stability measure has risen a little over 200bp from its recent low. Thus, real policy rates have indeed loosened by circa 300bp, yet we are supposed to believe this will return CPI back within their target range. One must take the whole letter writing requirement as either a total charade or as proof that there is truly no path to impose accountability on BOE leadership.
All they give us is that they expect the rise in CPI inflation to be temporary. There is no real explanation of why they believe that to be so. There is no explanation of why, at 0.25%, we should accept that real policy rates are restrictive. They just tell us it is so. There is nothing about the context within which they have consistently failed to spend any sustained period whatsoever inside the wide range by which they define their mandate. Do they know what they are doing? Do they have a realistic, useful, model of the economy? We doubt it.
We would love to know how they are factoring in our relentless point about the population demographics issue. Are they following our suggestion and ending every discussion on the topic of the economy with this addendum: “and for every year going forward there will be fewer taxpayers”? In that scenario, is it accurate to persistently forecast that rises in the measure of inflation will always be temporary?
The Financial Times published a little note on the issue – “France and Britain are in thrall to pensioners” – touching on the rising costs of pensioners and the shrinking overall earnings of the working age population, highlighting the particular challenges for France and the UK.
https://www.ft.com/content/d419bd2d-a6ba-44a5-a93a-1276f3e5d2d7
Figure 7: Growing Share of GDP spent on old-age benefits and health care: France and UK
Source: Financial Times
Figure 8: Cumulative real-terms increase in median income by age group: France and UK
Source: Financial Times
Figure 9: Relative income level of over-65s (working-age average = 100)
Source: Financial Times
We would certainly like to hear more from the policy making elites explaining how they are viewing this key structural dynamic to the current state of initial conditions.
Broadly speaking, where are initial conditions? We’ve talked a lot about our feelings of déjà vu, comparing recent market circumstances with our memories of 1995-1999 Convex Strategies | Risk Update: December 2024 – “Deja Vu”. The main vein of similarity is the exceptional performance of a portfolio of long US equity beta, protected by global multi-asset opportunistic long volatility, over the respective periods. So far, this year, this continues to be the case. Reviving a proxy of a chart we showed back in that December 2024 Update, gives some sort of a visualization.
Figure 10: GS US Financial Conditions (white), Fed Funds Rate (blue), Nasdaq 100 Index (papaya, log-scaled). LTCM event (green circle). Liberation Day (purple circle). Fed Hiking Cycle June1999-May2000 (white rectangle). Jan1991 – Sept2025
Source: Bloomberg, Convex Strategies
Much like those heady days of the late 1990s, the equity markets keep chugging along. Meanwhile, lots of stuff is going on around the world. We’ve highlighted in the above pictures the very brief tightening of financial conditions, one in 1998 around the LTCM attributed event, and the recent one in purple, generally attributed to the Liberation Day imposition of tariffs. In both cases, financial conditions very quickly eased thereafter, aided by easing by the Federal Reserve. We have also highlighted, with the shaded white rectangle, the period that saw the Fed jump back in and attempt to tighten conditions back up a little. You can see, the final real melt up of the Nasdaq occurred over the period the Fed was hiking, right up until the final jumbo 50bp hike in May of 2000. That seemingly was enough, finally the equity markets broke, financial conditions tightened, and we saw a decade of poor overall equity market returns.
Of course, so many things are different with today’s initial conditions compared to back then. US debt/GDP was much lower than it is today. The US government, amazingly, started running fiscal surpluses, a far cry from today’s seemingly perpetual fiscal deficits. Back then nobody was talking about fiscal dominance. The bulk population cohort was right in the middle of their peak earnings, taxpaying capacity, and savings years. Now they are moving into retirement. The Euro didn’t exist. China was not a major player on the global stage. Globalization was pulling massive amounts of cheap labour into the global pool, versus today where population demographics is shrinking working-age labour supply across virtually all of the developed world, and much of the developing world.
From an investment perspective, again paraphrasing Mandelbrot, everybody’s risk is subjective. Everybody’s initial condition and future path is their own. We cannot know all of the future curves and straightaways of the not yet revealed future laps of our long-term race to superior terminal capital. All we can do is focus on the resilience of our race car, give it really good reliable brakes and get out there and explore the ways you can drive faster.
Below is a good representation of where various racers might be after almost 8 laps/years of racing. We set as our target reference the return of a simple 60/40 portfolio (60% in S&P500 Total Return: SPXT Index and 40% in US Treasuries Total Return: LUATTRUU Index). We include just one other Sharpe World-styled participant, Risk Parity (S&P Risk Parity Index – 10vol: SPRP10T). Then we toss in a selection of some of the various hypothetical “Barbell Racers” that we have discussed over the years:
- Dream Portfolio: 70% S&P500, 10% Gold (GLD US Equity), 20% LongVol (EurekaHedge Long Volatility Index thru 2024 then bootstrapped into the WITH Long Volatility Index)
- Always Good Weather (AGW): 40% S&P500, 40% Nasdaq (NDX 100 Total Return Index: XNDX Index), 20% LongVol.
- MegaBell: 70% S&P500, 10% Bitcoin (XBT Currency), 20% LongVol.
- Preservation Portfolio: 50% Nasdaq, 25% Gold, 25% LongVol.
Figure 11: 60/40 (dark blue), Risk Parity (light blue), Dream Portfolio (gold), AGW (fuschia), Preservation Portfolio (brown), MegaBell (red). Jan2018-Sept2025. Compounding paths
Source: Bloomberg, Convex Strategies
After 7 and ¾ years in our theoretical look at history, the compounded capital and, as such, current initial conditions of the Barbell Racers are all ahead of the target path set by the reference portfolio of 60/40. Those with better brakes, better convexity, are distancing themselves by pursuing opportunities to explore. They have distanced themselves away from their target, they have learned how to drive aggressively knowing they have the convexity of good brakes and, ideally, have continually been building that braking ability.
The Risk Parity racer, who thought levering assumptions of low volatility and stable correlations would somehow allow him to achieve superior returns with improved risk, continues to get educated on the concept of volatility drag. It has achieved the opposite, having the worst returns and the highest downside volatility, i.e. it drives the slowest in the best parts and the most reckless in the dangerous parts. The Risk Parity car has the worse current initial conditions, it has a bunch of leverage, around a bunch of assumptions, that are just not true and constructed around a philosophy that is optimized to something other than compounding wealth. That car is seriously in need of an overhaul.
Back to Mike Green with one last link. This is Mike interviewing David Einhorn at the annual Simplify Entering the Fall Conference. It is a great overall discussion, well worth having a thorough listen.
Entering the Fall 2025 | Still Broken? More Broken? Never Broken?
We would, however, direct everyone to the David’s very final response, at about the 1:00:00 mark, to an audience question enquiring if the advent of AI LLMs would eliminate the need for analysts like himself, given everyone can just access an app to ask what’s the attractively valued stock. He gives a wonderful response that very much parallels our thoughts about both LLMs and Sharpe World methodologies, which Mike summarizes perfectly.
“…it depends on what the question they’re asking is”
If you are asking AI the wrong questions, or applying Sharpe World tools towards the wrong objectives, they won’t do you any good, and may be causing unseen harm.
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