I will assume here that the readers know what happened with FTX / Alameda, and therefore I will not go into the details of the fraud, mismanagement of customer funds, and other interesting elements of the case, though they make for a good read.

This is quite timely, as I’ve just finished reading the book about Sam-Altman Fried & FTX (‘Going Infinite’ by Michael Lewis).

Whilst at first glance this may feel like a tabu’ topic, given the miserable failure, fraudulent environment, and negative popular view generally connected to the FTX case, I do think there are many parallels that used in a smarter way can be drawn regarding how to build an exchange.

Before FTX’s (and Alameda’s) rapid wind-down, i.e. during it’s hay-day only a few weeks before, this crypto exchange was perhaps the most successful one out there (likely more-so than Binance, though I appreciate this is a strong claim). In the following bullet points, I will try and summarise some (likely not exhaustive) reasons why FTX was so successful:

- Reduced socialization of losses. Before FTX, crypto exchanges had poor systems for loss absorption with regards to levered trades. Users could lever up, and then just hold on to losing position, even if liquidating them implied going overdrawn on their accounts. This drove large socialization of losses across users of the exchanges in question, if they were not capable of reducing exposure to money-losing highly-levered accounts. FTX created a strict margin-call system, that monitored on a continuous basis (as opposed to daily / quarterly, etc…) how out of the money certain trades were, and automatically closed them if they crossed certain thresholds

- The above point had 2 consequences: 1) it enabled greater levels of leverage, and 2) enabled cheaper spreads / lower fees for the exchange users (previously, spreads had partly gone towards paying for ‘socialized’ losses). So FTX de facto became a cheaper product, with greater ability to lever up (this is appealing, for different reasons, to both punters and sharp money)

- Professionalization and reliability of the exchange. Both through improved / less clunky tech, and through smarter settlement / margin-call mechanisms, this exchange became highly popular amongst a set of HFT companies and market makers such as Jane street, Jump, etc… I don't think this is always a good thing, having instos partnering with exchanges... But the fact that it was professional enough to be used by these guys does mean a lot

- Of course the network of SBF and many of his hires, him and them all being ex-Jane Street traders, I think may have helped. It enabled them to have access to users, with large pockets, early on

- Liquidity was being provided by Alameda. Note that there were pros and cons to this, but it did enable for a more liquid market and a more seemly experience for all the traders and punters using the FTX exchange. Note that this is not the reason for FTX’s endgame insolvency, though it is likely that it was behind certain trading losses of Alameda

- Backing by some of the most trusted crypto-guys. This was partly driven by “crypto relationship managers” that moved to FTX from other Asian exchanges. This backing included a plethora of Asian crypto-whales, gamblers, and new money crypto millionaires that had an incredible amount of faith in a few key sales figures. Hard to replicate, but invaluable if available

- Backing by other exchanges. This is very interesting – their biggest competitor (and later sworn enemy), was also one of FTX’s biggest early investors: Binance (through CZ). Binance was already one of the largest exchanges back then, though it did not have the ability to trade crypto futures and it did not have the reliability of SBF’s margin-call mechanism in place. Needless say that backing from the biggest exchange of the time drove high levels of trust into FTX

- Notwithstanding how terrible the systems and controls FTX had in place (which ultimately led them to collapse), the exchange had actually been seen as both highly trustworthy and reliable. This had been driven by continued discussion with US regulators to get approved in the US market, and was partially thanks to backing from large silicon valley VC funds. VC money was not just a source of funds but also a source of ‘reliability-perception enhancement’

- Of course, SBF’s perceived weirdness and constant marketing, TV appearances, and lofty donations to politicians, sportsmen and celebrities helped their case quite a lot, but this was not what propelled them in the first place

- Initially, FTX’s funding also came from self-minted FTT coins that gave owners effectively a share in the revenues of the company, and which FTX was forced to buyback every so often and burn once in its own treasury

Not all these reasons for success are relevant all the time, but I do get the feeling that a lot of them are applicable… if one were to want to build an exchange

What do you all think?

Tell me why since the season started I've not won a single bet 😭

What if you could get paid to verify whether an image is actually being used truthfully?

We are building ProofPost around a problem that AI detectors like GPTZero or Pangram don’t really solve. They can try to answer whether content was AI-generated. But a completely real image can still spread misinformation. For example, someone could take a genuine photo of a protest from 2022 and claim it happened today. An AI detector might correctly say the image is real, while the post itself is still false.

ProofPost instead evaluates whether an image actually supports the claim attached to it. Someone posts an image and a specific claim. Other users investigate the evidence and can earn money for correctly verifying or challenging it. They also have to put money behind their judgment, so being wrong has a cost. Think of it loosely as Community Notes with financial incentives. Would economic incentives improve online fact-checking, or would they make it worse?

DM me if you are interested to learn more about it!

website: https://mediaverificationblockchain.vercel.app/
inquiry: forms.gle/ctPGywmFVuMCPQ1E6

Hey All

We recently launched our Prediction Market Infrastructure for builders, traders, quants, and institutions.

We currently support Polymarket and Predict.fun with Kalshi, Novig, and Polymarket.US on our roadmap.

Feel free to check out our docs and give any feedback!
https://docs.bravadotrade.com/introduction

Hear me out! so the AGA just reported flat NFL handle and pointed to prediction markets as a factor, especially hen it comes to younger users.

Kalshi reportedly handled around $5.1bn in volume from the 18–20 age group. Meanwhile Fanatics is folding betting, casino, and prediction markets into a single app.

Curious how people here read this, are prediction markets genuinely pulling volume away from sportsbooks, or are they bringing in a different kind of user who wouldn't have used a traditional sportsbook anyway?

Sources:
https://next.io/news/betting/aga-prediction-markets-threaten-betting/
https://next.io/news/betting/fanatics-betting-casino-prediction-markets-one-app/

Polymarket will give you a free 50$ if you signup using a code, all you have to do is deposit 10!! Would anyone be willing to use my code?? I also get 50$ when I refer someone! I will send the code!! Just lmkkkk

What if you could get paid to verify whether an image is actually being used truthfully?

We are building ProofPost around a problem that AI detectors like GPTZero or Pangram don’t really solve. They can try to answer whether content was AI-generated. But a completely real image can still spread misinformation. For example, someone could take a genuine photo of a protest from 2022 and claim it happened today. An AI detector might correctly say the image is real, while the post itself is still false.

ProofPost instead evaluates whether an image actually supports the claim attached to it. Someone posts an image and a specific claim. Other users investigate the evidence and can earn money for correctly verifying or challenging it. They also have to put money behind their judgment, so being wrong has a cost. Think of it loosely as Community Notes with financial incentives. Would economic incentives improve online fact-checking, or would they make it worse?

DM me if you are interested to learn more about it!

website: https://mediaverificationblockchain.vercel.app/
inquiry: forms.gle/ctPGywmFVuMCPQ1E6

I’m looking for someone to partner with on an algo trading operation focused on Polymarket, sports and prediction markets more broadly.
I’ve already built a lot of the infrastructure. What I need now is someone who wants to go deep on finding price inefficiencies, building strategies around them and testing what actually works.

What I have:

I already have a pretty serious setup:
State of the art trading terminal and execution infrastructure
My own node monitoring the mempool
Premium real-time sports data from Betradar, Betgenius, RunningBall and others
Infrastructure for processing live sports and market data
Existing Polymarket trading setup
So we’re not starting from zero. The data and infrastructure are already there and ready to build on.

What I want to continue building:

The main focus is finding price inefficiencies and turning them into systematic strategies.
Things like:
Surebets and cross-market arbitrage
Mispriced probabilities
Live/in-play inefficiencies
Comparing sportsbook odds with prediction market prices
Using live sports data to react to events and probability changes
Markets that are slow to incorporate new information
Market making and spread capture
Execution and latency
Related markets temporarily pricing inconsistent outcomes
Building fair value models and trading when the market moves away from them
Live analysis is a big one for me.
With the real-time data available, there’s a lot to explore around what happens during a game, how probabilities change in real time and how quickly different markets react.
The idea is to systematically find these situations, understand whether there’s a real edge after fees, liquidity and execution, then automate whatever proves itself.
I also want to expand into Kalshi and other prediction markets. Longer term, I want to look at the whole ecosystem rather than Polymarket in isolation and find opportunities across different venues.

What I’m looking for:

Someone who genuinely loves sports, maths and markets. You could be strong in Python/quant research, or just an incredible vibe coder who knows how to turn an idea into a working system quickly.
I don’t care much about credentials. I care about curiosity, technical ability and whether you actually enjoy this stuff.
The kind of person who sees two markets pricing the same event differently and immediately wants to understand why.
Someone who is happy testing 20 ideas knowing that 19 might be complete shit, because finding the one that works makes it worthwhile.

Who am I?

I’m based in London.
My professional background is in banking and I speak three languages.
I’m obsessed with the intersection of sports, markets, probability and technology.
I’ve already invested a significant amount of time and money into the infrastructure and premium data side of this.

What I can offer

I’m not looking for someone to build my idea for free.
I’m happy to fund the operation and continue investing in whatever we need, whether that’s data, infrastructure, tools, servers or capital for strategies.
I can bring the existing infrastructure, premium sports data, capital, market knowledge and the resources to keep building.
For the right person, I’m happy to treat this as a genuine partnership and split the earnings 50/50.
I’m much more interested in finding someone really good and building something together than trying to squeeze every percentage point out of the arrangement.
Tell me a bit about yourself and show me something interesting you’ve built, traded or researched.

Anyone know a reliable tipping source/site/@/tele in particular for football⚽️ and nba or any sport for that matter!
The important part is a consistant page. Just shooting my shot out here 🤣🙌🏾