Welcome to the WC, where you’re trapped in my mind for eight to twelve minutes weekly.
I’m back from holiday and thoroughly enjoying my well-air-conditioned European home.
Lots to cover this week despite the lazy summer days including art forgery, how AI is transforming film investments, and a deep dive into the horse race industry.
Let’s get to it.
Genuine fakes
While on holiday this summer, I read Provenance, a book about legendary modern fraudster John Drewe and his forger, John Myatt.
Drewe sold millions worth of forged paintings in the 1990s before eventually getting caught and serving time in prison. Like many conmen, the money was necessary, but it was more about the prestige.
The high a poor kid gets when he gets one over on the ruling class — beating them at their own rarified game.
Drewe’s story isn’t unique.
Just a day or two after I finished Provenance, I read about Matthew Christopher Pietras, who recently passed away.
Pietras had crafted perhaps the most audacious art world fraud of recent years. At just 40, he’d positioned himself as one of New York’s most generous young patrons, securing a spot as one of the youngest managing directors on the Metropolitan Opera board.
He cultivated friendships with the cultural elite, including Courtney Ross (widow of Time Warner’s co-founder) and Gregory Soros (George’s son). His donations were substantial, his taste impeccable, his checks… fictional.
When institutions tried to deposit his multi-million-dollar “gifts,” they bounced. Pietras was found dead in his apartment just as the fraud unraveled, leaving behind a web of stolen funds and fabricated wealth that had fooled Manhattan’s most sophisticated cultural gatekeepers.
The art world is uniquely susceptible to prestige-driven fraudsters.
Consider Wolfgang Beltracchi, who ran Germany’s biggest postwar art forgery operation for nearly 40 years.
He didn’t see himself as a criminal but as an artist whose “lost masterpieces” by famous painters were so convincing that major museums competed to acquire them.
Then there’s Han van Meegeren, whose fake Vermeers were so coveted that he became a national hero after World War II.
He sold a “priceless” Vermeer to Nazi Reichsmarschall Hermann Göring. His defense? The Dutch court had to decide whether he was a traitor or just a very successful forger.
The British Greenhalgh family turned forgery into a cottage industry, with son Shaun creating masterpieces in his garden shed while his elderly parents handled sales. Their “ancient” sculptures fooled the British Museum, and Shaun now claims credit for what experts believe is a $100 million Leonardo drawing.
How do you protect yourself in a market where even institutions with unlimited resources and expert curators get fooled?
The uncomfortable truth is that provenance can be faked almost as easily as the art itself. Drewe proved this by infiltrating museum archives and creating entirely fictional documentation.
Smart money focuses on purchasing from established auction houses with robust authentication processes and comprehensive insurance policies.
When dealing with private sales, insist on multiple independent expert opinions and consider scientific analysis. Remember: if a “lost masterpiece” surfaces with a too-good-to-be-true backstory, it probably is.
Here’s where things get interesting from an investment perspective.
Some forgeries have become valuable in their own right. Van Meegeren’s fake Vermeers now sell for hundreds of thousands at auction—not as Vermeers, but as van Meegerens.
Beltracchi has parlayed his notoriety into a legitimate art career, with collectors paying premium prices for works openly labeled as “Beltracchi originals.”
John Myatt, the forger from the Drewe operation, now legally creates “genuine fakes.” The clearly labeled reproductions sell for thousands.
Some forgers end up making more money after getting caught than they ever did while operating in the shadows.
Nice work if you can get it.
AI in films – not what you think
While Hollywood writers struck over AI stealing their jobs, savvy investors are using AI to generate alpha in film finance. James Cameron recently predicted AI could cut film production costs in half, but the real disruption isn’t in what AI creates: it’s in how it’s transforming the money behind the movies.
AI is reshaping film finance from multiple angles.
VFX costs are plummeting, budget optimization tools are democratizing high-quality production, and streaming platforms like Netflix are deploying algorithms to guide their $17+ billion annual content spend.
Meanwhile, new regulations around AI usage (from WGA strike outcomes to digital likeness rights) are creating fresh legal and insurance considerations.
But AI isn’t just changing how films are made. It’s changing how they’re financed, which creates opportunities for investors who understand the new landscape, particularly if you’re willing to dive into the weeds.
Our film bridge loan fund occupies a specific niche: providing 8-14 week bridge loans during critical financing gaps – we get actors and crew on set while producers are waiting for tax credits or other finance to arrive.
Box office performance is irrelevant to us, because Film I gets paid before the first ticket sells. So our risk isn’t whether a film succeeds creatively.
The question is whether our counterparties fulfill their obligations.
We’ve already built an AI-powered “FICO score” for producers, analyzing court records and news for defaults and derogatory information.
But we can go deeper.
By mapping producer networks through IMDbPro, LinkedIn, and corporate filings, AI can identify relationship patterns that predict reliability. Which producers consistently close financing on time? Who works repeatedly with successful collaborators? This network analysis could help us identify reliable partners before competitors even know they exist.
Our biggest risk isn’t film failure. It’s counterparty failure. AI can help us track which primary financiers actually close deals versus just commit to them, building a proprietary database of financing reliability.
Similarly, not all completion bonds are created equal. AI analysis of bond company financial strength, payout history through court filings, and claims patterns can guide our selection process.
Real-time monitoring of corporate structure changes, financial health signals, and related entity stress provides early warning systems for potential workout situations.
Much of this data exists now: corporate filings, court records, industry databases. The challenge is systematic analysis and pattern recognition, exactly what AI excels at. Over time, we can build proprietary datasets combining public information with our loan performance history, creating compounding competitive advantages.
Our little niche of the entertainment industry is a tiny example of how AI is changing film, but I think it’s illustrative.
And it will both make money for our investors and open finance up to previously uncreditworthy borrowers.
A happy ending for everyone.
Have horses run their race?
When an entire industry reaches a universal consensus that it’s dying, I start paying attention. Sometimes (usually) the industry is right, but when it’s not, that’s usually when the real money gets made.
Let’s talk about horse racing.
2024 U.S. Thoroughbred handle dropped 3.35% to $11.27 billion. Attendance is soft across most circuits. The media has declared racing DOA, pointing to sports betting cannibalization and demographic headwinds as evidence of terminal decline.
But here’s what caught my attention: while total handle declined, Derby Day online betting jumped from $92.1 million in 2024 to $108.0 million in 2025. TwinSpires set records even as Churchill Downs attendance dipped 6%. This isn’t the behavior of a dying industry.
It’s the signature of an industry in transformation.
The pessimists have valid points. Sports betting competition is real.
- Why take 20% takeout on a horse race when you can bet NFL spreads at 4.5% hold?]
- Racing’s core audience skews older with limited Gen Z adoption.
- Smaller field sizes make races less attractive to bet.
But these concerns are already reflected in asset prices.
The structural changes are complete: in Illinois, on-track betting has collapsed to just 6% of total handle, while advance deposit wagering (ADW) now comprises over 60%. This isn’t a decline. It’s digital transformation.
The question isn’t whether racing will return to 1970s popularity. The question is whether current asset prices rationally assess cash flows from a smaller, more efficient industry.
To invest profitably, I don’t need racing to grow. I need it to stabilize at a lower equilibrium with better margins and less competition for quality assets.
Here’s where it gets interesting…
North American foal crops have declined steadily, creating supply constraints at the top end just as international demand from Middle Eastern and Asian buyers provides price floors for elite bloodstock.
We’re seeing classic consolidation dynamics. While weak hands get shaken out, strong hands are accumulating quality at discounts.
Technology is accelerating this separation.
Better veterinary screening, stride analytics, and genetic testing create transparency premiums. The spread between “A” and “B” horses is widening as buyers reward measurable advantages. At March OBS sales, horses with clean scopes and strong under-tack shows commanded significant premiums over those with question marks.
Geographic arbitrage adds another layer. Kentucky’s Historical Horse Racing (HHR) machines and New York’s subsidies create stable purse environments independent of wagering handle. These circuits maintain strong end-user demand even as handle-dependent tracks struggle.
Smart pinhookers can target horses suited for these robust purse programs while others chase shrinking opportunities elsewhere.
The setup reminds me of other “dying” industries that consolidated profitably.
- Newspapers didn’t disappear. They digitized, and the survivors captured more value with less competition.
- Music didn’t die; it moved to streaming, and the platform winners thrived.
Racing’s downside appears limited since assets already reflect pessimistic assumptions.
But multiple upside catalysts exist: technology efficiency gains, international market expansion, and platform consolidation favoring scale players. The asset class also provides portfolio diversification benefits with low correlation to traditional investments and inflation hedge characteristics through real asset ownership.
The playbook here is pretty clear.
- Focus on high-end pinhooking targeting proven sires, clean veterinary records, and commercial appeal aligned with stable purse jurisdictions.
- Time purchases for maximum liquidity windows such as March and April 2YO sales where global buyers congregate.
- Use syndication structures to reduce risk while maintaining upside exposure.
We’re keeping a close eye on this space as we explore potentially launching a bloodstock pinhooking fund in early 2026. The opportunity set is compelling: an unloved sector with expertise barriers, asymmetric risk/return profiles, and clear catalysts for value realization.
Peak pessimism rarely lasts. In racing, as in film finance, we’re not trying to save an industry; we’re trying to profit from its evolution.
That’s all for this week; I hope you enjoyed it.
Cheers,
Wyatt
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