Paul Colagrande

Kaspa Ambassador
Dev student at Epitech Paris
Passionate about blockchain & DAG technology

[Paul Colagrande @ColagrandePaul]

I’m thrilled to officially join the #Kaskad team after six inspiring weeks of collaboration! Thank you to everyone for the warm welcome and for the opportunity to develop the Oracle. Excited to keep pushing the boundaries together. 🚀

[Kaskad @AppKaskad]

After 6 weeks challenging @ColagrandePaul on the modelling of the algorithm of our Oracle with @eliottmea, we are excited to share that he has exceeded expectations. Today we are officially welcoming him to the #Kaskad team, where he can continue putting his talents to work.
Welcome to the crew, Paul!

[eliott @eliottmea]

Have spent two weeks annoyed at an attack vector on my HFT oracle, nicely pointed out by someone in the #kaspa discord. Specifically on illiquid exchanges.

will detail this later, but essentially there should be a way to make it such that people keeping their #kas (or later other assets) on CEXs, have a win-win situation.

we distribute software (essentially automating arb bots for people on a specific CEX), so that anyone can
1. profit if someone tries to manipulate the oracle (one specific attack in mind, ie a huge arbitrage).
2. help secure the oracle through filling this arbitrage.

this probably won't be a constant profit because we'll frontrun you on small arbs, but if someone tries to attack the oracle, the whole community becomes rich.

Y'all in ?

[eliott @eliottmea]

Wannabe @michaelsuttonil & @hashdag with our oracle infra

[Paul Colagrande @ColagrandePaul]

@eliottmea @Chewie_xo @kaspaunchained @WolfysBar @remao155 😂😂

[Paul Colagrande @ColagrandePaul]

@KaspaLens Also, does your backend implement any kind of oracle or pricing mechanism?

And for the orderbook view, is it sourced live from exchanges or reconstructed on your side?

Thanks in advance for the clarification.

[Paul Colagrande @ColagrandePaul]

@KaspaLens Great work, the tool looks impressive!

Quick question regarding the price displayed on https://t.co/4983AxrjCR: what’s the source of your KAS price feed? Is it aggregated across multiple exchanges, or taken from a single market?

[Kaskad @AppKaskad]

Unveiling our Fundraising Campaign through the $KSKD token

A lot has been brewing behind the scenes, and it is time we start opening the doors.

📣Behold! The official Kaskad Campaign starts today: a full month of learning, discovery and community participation. It will be the first time we share the full picture of the protocol, including the role of the $KSKD token in the platform, and how the community can take part in the project’s next chapter.

At #Kaskad, we do not take education lightly. In fact ,we believe that educating our participants at this stage is an absolute need.

Here is what to expect by clicking on the link below:

• Building the best lending platform on Kaspa - our approach and long-term vision

• Understanding the Kaskad tokenomic.- interactive tools and guided explanations

• Community Fundraising - a chance to take part in the early growth phase

• Deep dive into Kaskad - interviews, events, technical sessions and Q&A

• ...and a few more surprises!

Kaskad is built by Kaspa lovers, for Kaspa lovers, which is why our fundraising campaign will be open to communities and DAO VCs only.

Ready? Let the campaign begin!

Rendez-vous here: https://t.co/vBaplGjyLS
Invitation code: KASKADR1

[3SEARCH Capital @3searchcapital]

We’re thrilled to announce our strategic partnership with @AppKaskad - the first compliant lending protocol on #Kaspa 🔒

Their expertise in oracles, verified price feeds, and institutional-grade infra brings DeFi one step closer to Kaspa’s future.

[eliott @eliottmea]

Coming to @AppKaskad (and more generally to #kas)

tldr; oracle inspire from the NA (no arbitrage) from math fin theory (which obv doesn't hold).

Idea : if there were a single LOB across the market, oracles wouldn't make any sense. We need them only because of fragmented liquidity.

Thus at a fixed time t, we aggregate snapshots from all CEX LOBs (assume for now kas only trades on CEXs). We use websockets such that, when an LOB updates (an order hits/cancels in the book), we receive the info sub 50ms or faster. Given there is natural arbitrage (no perfect market), the oracle simulates arbitrage in order to understand what the fair value is : the value above (resp. under) which there is net excess supply (resp. demand). Maybe our engine will try to fill the arb itself, didn't think about that yet.

Ok we got fair value, is our oracle robust ? No. Although illegal, nothing prevents a CEX from manually overriding their API and displaying #KAS/USDT=0.000001, as well as setting a huge sell wall at 0.000002 with volume larger than all buy orders across venues. We let the reader understand how this would successfully manipulate the oracle.

Two outlier detection methods that only work well when used together. The first, using survival analysis in order to detect if an arbitrage is lasting longer than usual (conditioned on market conditions such as volatility). Eg. usually an arb of 2% between MEXC and kraken is filled within 1s, weirdly it's taking 5s and the arb is still here : why is nobody taking the free money ? Hence we observe something we'll call epsilon-events (V_t being the volume of arb at time t):
Problem w. the above, the same attack mentioned still works, because there is a huge arb (by a CEX creating fake sell wall), but the oracle will necessarily take a positive amount of time to flag the outlier. In that window, it will account for it and get wrecked.

Second detection : Wasserstein-1 distance between exchanges. An LOB histogram can be seen as a pile of sand, and the distance from one lob to the other is the amount of energy (or trades) needed to move one pile of sand to the next.

If for eg., in 1 update, kraken reports a change that we deem too large (has to be VERY carefully defined), we flag it as an outlier. The oracle should then attempt to profit from that HUGE arb opportunity, and if it doesn't manage to within eg. 50ms, successful flag. If it does manage, we profit huge money, we're/I'm rich and unflag.

Now the only thing that needs to be really studied, apart from what parameters we use (will need @remao155 ML skills for this), as well as what can happen under collusion. Although imo collusion won't change much.

challenge the idea and find some flaws cc. @maxibitcat, @emdin, @xximpod, @quex_tech, @madenis, @JC_G33K etc.

@Kaspa_KEF will send report soon, on this as well as my work with yonni (both related anyways), @ColagrandePaul there is much work ahead, pls implement all the above ;)

[Paul Colagrande @ColagrandePaul]

Congrats @remao155 ! Thrilled to see you joining the Kaskad team, your background and research focus sound like a perfect fit. Excited to build together!

[Kaskad @AppKaskad]

We are glad to welcome Rémi Khani @remao155 as an Applied Researcher at Kaskad!

He will be focusing on the tokenomics game theory behind Kaskad’s protocol. Rémi has recently graduated with a Master’s degree in Applied Mathematics and Machine Learning from ETH Zurich and holds a Bachelor’s degree in Pure Mathematics from EPFL Lausanne.

Currently in the process of writing a research paper, he is conducting a proof of concept for the protocol’s tokenomics under @BagayokoJack supervision, exploring the mathematical foundations of its key features.

Building on Kaskad's tokenomic model, Rémi is analyzing optimal incentive structures to promote sustainable TVL growth, long-term participation, and responsible leverage, all aimed at maintaining the platform’s stability and efficiency.

Together with @eliottmea , our Lead Oracle Architect, he will also be responsible for developing the Research and Development Department at Kaskad.

Rémi’s previous work experience in machine learning ranges from medical imaging for stroke detection to early decision making in time series environment using reinforcement learning models.

Strongly passionate about DeFi and Kaspa, he is keen on finding a way to contribute to the Kaspa ecosystem by joining our team.

Please give that man a follow and welcome to #Kaskad, Rémi! 🚀
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[Paul Colagrande @ColagrandePaul]

@KrcBot @eliottmea Thanks, I’ll take a look at DruidDB, Rabbit Stream, NATS JetStream, and QuestDB

[Paul Colagrande @ColagrandePaul]

@KrcBot @eliottmea We process all data in real time, then store both the order books and computed results at T+1 after processing. Currently evaluating Kafka and Elastic for scalable storage and analytics.

[Paul Colagrande @ColagrandePaul]

@eliottmea @KrcBot Thanks for the CCXT link, great resource.

We’re using Rust with WebSockets instead of REST to stream L2 order book data live, testing aggregation every 50 ms, and detect subtle market changes with lower latency.

Still, CCXT is handy for backtesting and managing API calls.

[Paul Colagrande @ColagrandePaul]

@TheLoadedLounge Heard about your project and got inspired. I built a quick front-end demo. Would you be open to discuss this further in DMs so I can hear more about your ideas for the app?

[Paul Colagrande @ColagrandePaul]

@Radical_Ed_Bad @AppKaskad @eliottmea Totally agree. With the team’s energy and vision, I’m confident Kaskad will achieve great things

[Paul Colagrande @ColagrandePaul]

@hopp_quentin @AppKaskad @eliottmea Thank you! I’m glad to be here and looking forward to contributing

[Paul Colagrande @ColagrandePaul]

@MonsieurMarius @AppKaskad @eliottmea Appreciate it! Happy to be part of the team and to contribute

[Paul Colagrande @ColagrandePaul]

@moxypixy15683 @AppKaskad @eliottmea Haha not a wizard yet, but working on it 😉 Thanks for the support!

[Paul Colagrande @ColagrandePaul]

@ErwanHenry3 @AppKaskad @eliottmea Merci beaucoup !

[Paul Colagrande @ColagrandePaul]

@BagayokoJack @AppKaskad @eliottmea Thanks Jack! Really happy to join and start contributing with the team