OVVO Labs @OVVOLabs
Apps: {Portfolio Construction, Options Pricing, MacroNow Nowcasting} Better Tools → Better Insights ovvolabs.com Joined October 2023-
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Group think with human experts: 10/10 AI agents: Hold my beer…
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@OriginalDudeMan 1000%: x.com/OVVOLabs/statu… x.com/OVVOLabs/statu… x.com/OVVOLabs/statu…
If YOU can launch an AI trading agent and YOU bring NOTHING to the table, then neither does your AI trading agent. Slop in. Slop out. #shortthemall #nonstationaritymeteor
Fred Viole (OVVO Labs) has a strong, defensible claim to provenance here—not as the inventor of partial moments, but as a key figure who developed them into a unified, practical, open-source statistical framework with direct quantitative finance applications.
@RudyHavenstein x.com/ovvolabs/statu…
Given his Ayn Rand discipleship, the supremely ironic “Fed put” Greenspan ushered in was one of the worst policy mistakes of all time. We have only further institutionalized moral hazard since.
@KobeissiLetter Maybe they're pricing in peace... x.com/OVVOLabs/statu…
“Buy when the cannons are firing, and sell when the trumpets are blowing” — Nathan Rothschild
@Barchart It helps to be able to fully analyze the Russell 2000 security universe and generate a portfolio that satisfies your risk preferences* in under 10 seconds! 😉 *With an actual generalized portfolio theory, not some AI bastardization of mean-variance
@bennpeifert x.com/ovvolabs/statu…
WWII version: Let’s All Fight — Buy War Bonds 2026 version: Be Our Exit Liquidity — Buy War Stocks Seems a little less patriotic today.
@KobeissiLetter There is no passive, just degrees of active however infrequent
@RudyHavenstein ABYSS - Automated Bailout Yielding SpaceX Subsidies
The more difficult choice is often the right one.
You can have every variable, every tick, every earnings call transcript and still lose money. Feed enough data into a model and it'll find a pattern in anything. Including noise... especially noise. You don't have alpha, you have a coincidence with good backtests. 40 year old paper still relevant: github.com/OVVO-Financial…
In finance, every algorithm that issues an order is a forecaster in terms of risk exposure, but not every algorithm is a forecaster in terms of epistemic ambition. The purely reactive error-driven method is a forecaster by compulsion, the world forces it to hold a position over a gap. While the structural model is a forecaster by design. One absorbs risk as a penalty for being reactive; the other deploys risk as the price of a structural belief. This is why position sizing is everything. Forecasting may enter through the front door as structural belief, or through the back door as unavoidable exposure. But in both cases, size determines the consequence of being wrong. It is the conversion rate between epistemic humility and financial survival.
@TheStalwart x.com/OVVOLabs/statu…
“When a measure becomes a target, it ceases to be a good measure.” ~ Charles Goodhart
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