offset

hedge your entire P&L via prediction markets.

[offset @offset_xyz]

https://t.co/Wc5rDN585F

[offset @offset_xyz]

Offset is no longer continuing. We're selling our token allocation on @Pumpfun effective in 7 days. Thank you for your support.

[offset @offset_xyz]

@Pumpfun offset's token submission: https://t.co/v8HKitafQU

[offset @offset_xyz]

At Offset, we prefer ice cream when it's cold out.
But if your customers aren't like us, you need a hedge.

Short bad weather through our interface.
Connect your revenue model.
Get paid out on rainy days.

Sunny P&L. Every day.

[Paul Frambot 🦋 @PaulFrambot]

Weather prediction markets will transform financing for ice cream shops.

Model ice cream revenue assuming every day is sunny. Hedge it by shorting bad weather on your location. Clean cashflows. Bankable projections.

Generalize to all seasonal businesses. Who is building this?

[offset @offset_xyz]

Your income is one email away from zero.

Hedge it in a few clicks.

https://t.co/CsvsBiDGbJ

[Polymarket @Polymarket]

BREAKING: Oracle laid off 20,000-30,000 employees this morning with a single 6 am email.

[offset @offset_xyz]

Prediction markets made it possible to price things that were unquantifiable a decade ago. They are the most accurate risk forecasts ever built.

Hedging is the clear next step.

[offset @offset_xyz]

Roy works a 9-5 in accounting.

He wakes up at 8:00 every morning, makes pancakes for his kids, kisses his wife goodbye, and clocks in.

He has not accounted for his whole life depending on that job still being there tomorrow.

Here's what can go wrong:

A war breaks out. The economy tanks. Companies cut costs. Roy gets laid off.

AI gets good enough at spreadsheets or his 70yr old boss discovers Claude Cowork. Roy's out.

His company has a bad quarter. There's no more room for Roy.

Roy has no control over any of these risks. But they all control his income and his life.

He knows this. He just doesn't think there's anything he can do about it.

But what if you could bet on what happens in your life before it happens?

Your job. Your industry. Your specific employment situation. And use those bets as a safety net.

That’s what we are building at Offset.

Here's how it works:

Roy inputs his job title, company, industry, and tenure.
We map the risks that threaten him most (i.e., AI automation, macro recession, sector-wide layoffs).

Then we find the prediction markets that move when those risks hit. Interest rates. Unemployment. War declarations. Legislation. Macro indicators. AI model ratings.

Roy's risk now has a price tag on it.

Then we model what his life looks like across every future. The "everything is fine" world. The "Roy gets a Slack message from HR" world. And every world in between.

Then we build the hedge.

Goal: cut Roy's downside. Keep costs low. Make the worst outcomes survivable.

For context, Roy makes $60k a year. A reasonable insurance allocation is 3% of income. That's $1,800 a year. $150 a month. Less than his car insurance.

Roy's profile flagged three risks. We find three live markets and open a position on each.

Position 1:

"US recession by end of 2026?" on Polymarket. Currently 36% odds. $800 in "Yes" contracts. The same recession that causes his company to cut overhead moves this market.

Pays out $2,222 if it hits.

Position 2:

"Will unemployment exceed 6% in 2026?" on Kalshi. Currently 24% odds. $600 in "Yes" contracts. This is the labor market cracking and white collar finance jobs disappearing in volume.

Pays out $2,500 if it hits.

Position 3:

"Negative GDP growth in 2026?" on Polymarket. Currently 15% odds. $400 in "Yes" contracts. The economy actually shrinks. Companies cut everything that isn't revenue-generating. Roy is overhead, and overhead goes first.

Pays out $2,667 if it hits.

Total cost: $1,800 for the year.

These aren't three independent bets on three separate things. The recession cracks the labor market. The cracked labor market contracts GDP. The same world where Roy gets that Slack message is the world where all three positions are printing simultaneously.

Worst case: recession hits, unemployment blows past 6%, GDP goes negative. Roy gets laid off.

But all three pay out. Roy collects $7,389.

Minus the $1,800 he put in: $5,589 net. That's over a month of salary sitting there before he's updated his LinkedIn. A runway to figure out his next steps.

But there are other worlds too.

Maybe only the recession market hits. Roy gets $2,222 and keeps his job. A small consolation on a scary year.

Maybe none of them hit. Roy is out $1,800 and keeps his job.

He still made the pancakes. Still kissed his wife goodbye. And for $150 a month, he knew that if the floor dropped out, he had something to land on.

That's the trade.

The financial system has always had tools like this. Farmers hedge crops. Airlines hedge fuel. Corporations hedge currency.

But Roy? Roy just hopes.

We’re changing that.

Offset everything.

[offset @offset_xyz]

https://t.co/Wc5rDN585F

[offset @offset_xyz]

Your income is now a layoff derivative.
You just don’t have a hedge.

Yet.

[Claude @claudeai]

You can now enable Claude to use your computer to complete tasks.

It opens your apps, navigates your browser, fills in spreadsheets—anything you'd do sitting at your desk.

Research preview in Claude Cowork and Claude Code, macOS only.

[offset @offset_xyz]

On the first one, we’re building it.

Bitcoin miners are exposed to BTC price, tariffs, power costs, and recessions. Most hedge none of it.

Offset turns prediction markets into a hedge for your entire mining P&L.

BTC price: Revenue hedge
Buy YES on "BTC below $X" at break-even hashprice. If BTC crashes, it pays. If BTC holds, you mine profitably.

China tariffs: CapEx hedge
Buy YES on tariffs staying high. ASIC costs jump 25%, this pays for it.

Gas prices: Energy hedge
Buy YES on "Gas above $X". Power costs spike, this covers the bill.

Recession: Macro hedge
Buy YES on "US recession in 2026". If everything goes wrong at once, this position saves you.

Input your mining operation. Offset evaluates every risk, sizes every hedge, and executes every trade automatically.

Offset everything.

[John Wang @j0hnwang]

sharing a few crypto-specific prediction market research ideas that feel underexplored:
- miners hedging hashprice, operating costs, energy, etc via event markets (not just btc price)
- are prediction markets actually well-calibrated? e.g. brier score
- do markets like ���btc > 100k by X” lead or lag perps/spot in price discovery
- use prediction market probabilities to measure how much the market believes in specific big moves, and compare that to what options/perps are pricing overall

[offset @offset_xyz]

Join the waitlist: https://t.co/CsvsBiDGbJ

[offset @offset_xyz]

Insurance is one of the biggest scams in finance.

For centuries the model hasn’t changed:
You pay premiums.
They pocket the spread.

What are you actually paying for?
- Sales commissions
- Corporate overhead
- Regulatory cushion
- Profit margins
- A claims department incentivized to deny you

The risk itself is only a fraction of the price. Most of it is bureaucracy.

Prediction markets fix this.

They cut out the middleman entirely and let markets price risk directly.

That’s what we’re building at Offset.

Hedge everyday risks through open markets. No forms. No broker. No BS.

The insurance industry had its chance to innovate. We’re not waiting.

[offset @offset_xyz]

waitlist live: https://t.co/CsvsBiDGbJ

[offset @offset_xyz]

Disclosure: We have claimed 15.81 SOL in @Pumpfun creator fees to cover infra, website, and Claude Max subscriptions.

More coming soon.

[offset @offset_xyz]

Your salary is unhedged.

But your job has beta against Tesla earnings, tech layoffs, financial indicators, the Critini paper, and more instruments than you'd think.

We're building the framework so you can use these to hedge your employment.

Article coming soon that explains how we are creating a broadly applicable n-dimensional hedging model that uses stochastic calculus and real-world outcome allocation across correlated markets.

Offset Everything.

[Aaron Guan @aaronguan]

MVP - done

Hedging model - loading...

[offset @offset_xyz]

Excited to share that Offset placed 1st out of 200+ participants and 48 projects at the Tech@NYU Buildathon!

https://t.co/NEd8jQmowD

[offset @offset_xyz]

Mark our words: prediction markets will become a trillion-dollar market when hedging is as easy as placing a trade.

Offset.

[vitalik.eth @VitalikButerin]

Recently I have been starting to worry about the state of prediction markets, in their current form. They have achieved a certain level of success: market volume is high enough to make meaningful bets and have a full-time job as a trader, and they often prove useful as a supplement to other forms of news media. But also, they seem to be over-converging to an unhealthy product market fit: embracing short-term cryptocurrency price bets, sports betting, and other similar things that have dopamine value but not any kind of long-term fulfillment or societal information value. My guess is that teams feel motivated to capitulate to these things because they bring in large revenue during a bear market where people are desperate - an understandable motive, but one that leads to corposlop.

I have been thinking about how we can help get prediction markets out of this rut. My current view is that we should try harder to push them into a totally different use case: hedging, in a very generalized sense (TLDR: we're gonna replace fiat currency)

Prediction markets have two types of actors: (i) "smart traders" who provide information to the market, and earn money, and necessarily (ii) some kind of actor who loses money.

But who would be willing to lose money and keep coming back? There are basically three answers to this question:

1. "Naive traders": people with dumb opinions who bet on totally wrong things
2. "Info buyers": people who set up money-losing automated market makers, to motivate people to trade on markets to help the info buyer learn information they do not know.
3. "Hedgers": people who are -EV in a linear sense, but who use the market as insurance, reducing their risk.

(1) is where we are today. IMO there is nothing fundamentally morally wrong with taking money from people with dumb opinions. But there still is something fundamentally "cursed" about relying on this too much. It gives the platform the incentive to seek out traders with dumb opinions, and create a public brand and community that encourages dumb opinions to get more people to come in. This is the slide to corposlop.

(2) has always been the idealistic hope of people like Robin Hanson. However, info buying has a public goods problem: you pay for the info, but everyone in the world gets it, including those who don't pay. There are limited cases where it makes sense for one org to pay (esp. decision markets), but even there, it seems likely that the market volumes achieved with that strategy will not be too high.

This gets us to (3). Suppose that you have shares in a biotech company. It's public knowledge that the Purple Party is better for biotech than the Yellow Party. So if you buy a prediction market share betting that the Yellow Party will win the next election, on average, you are reducing your risk.

Mathematical example: suppose that if Purple wins, the share price will be a dice roll between [80...120], and if Yellow wins, it's between [60...100]. If you make a size $10 bet that Yellow will win, your earnings become equivalent to a dice roll between [70...110] in both cases. Taking a logarithmic model of utility, this risk reduction is worth $0.58.

Now, let's get to a more fascinating example. What do people who want stablecoins ultimately want? They want price stability. They have some future expenses in mind, and they want a guarantee that will be able to pay those expenses. But if crypto grows on top of USD-backed stablecoins, crypto is ultimately not truly decentralized. Furthermore, different people have different types of expenses. There has been lots of thinking about making an "ideal stablecoin" that is based on some decentralized global price index, but what if the real solution is to go a step further, and get rid of the concept of currency altogether?

Here's the idea. You have price indices on all major categories of goods and services that people buy (treating physical goods/services in different regions as different categories), and prediction markets on each category. Each user (individual or business) has a local LLM that understands that user's expenses, and offers the user a personalized basket of prediction market shares, representing "N days of that user's expected future expenses".

Now, we do not need fiat currency at all! People can hold stocks, ETH, or whatever else to grow wealth, and personalized prediction market shares when they want stability.

Both of these examples require prediction markets denominated in an asset people want to hold, whether interest-bearing fiat, wrapped stocks, or ETH. Non-interest-bearing fiat has too-high opportunity cost, that overwhelms the hedging value. But if we can make it work, it's much more sustainable than the status quo, because both sides of the equation are likely to be long-term happy with the product that they are buying, and very large volumes of sophisticated capital will be willing to participate.

Build the next generation of finance, not corposlop.

[offset @offset_xyz]

@Pumpfun offset's token submission: https://t.co/v8HKitafQU

[offset @offset_xyz]

offset's submission to the @Pumpfun hackathon

[offset @offset_xyz]

https://t.co/rnb32syjr3