‼️‼️ Early : FCFS 20000 USERS
Claim Early Alpha OAT By @4Dlabs_Official
☆ Free oF Cost ( 0$ )
☆ Limited Availability
☆ Backed By @yzilabs
👉 https://t.co/3YZnODnRAk
👉 Complete Simple Tasks & Claim
📍 Join Me On Telegram For More Updates ( https://t.co/Rcx1iCTd42 )
Something to try on RH
@vibevibefun is a Launchpad currently in testnet phase
ways to participate:
>Testnet :activities 5% of token going to participants
> Raiding : link your X on TG using “Raider”. So many permissions on this so you can use alt (if verified)
1. join https://t.co/JvsAaBQM6o
2. visit raiding & bagworking channel
3. write /login there
then just start raiding
X eligibility criteria:
- all accounts must be verified X accounts
- No spamming
- memebank and visual can rack XP for you
250 (viber) NFTs for top raiders!
use alt X if you’re not comfortable with the flagged permissions
🪂 Best Websites To Find Early Airdrops
Save this list 📌
1. CryptoRank
→ Funding + early projects
https://t.co/EFBQQoVBr4
2. Airdropsio
→ Daily airdrop updates
https://t.co/5HHEkB83s7
3. DeFiLlama
→ New protocols
https://t.co/7YyUfEF91y
4. DappRadar
→ On-chain activity
https://t.co/7XhJK7llUf
5. RootData
→ Funding database
https://t.co/PkPqtRCmYG
6. ICODrops
→ Upcoming launches
https://t.co/p25eQRhlje
7. Cookie3
→ Mindshare tracking
https://t.co/KGYVUMftWz
8. FarmDash
→ Curated opportunities
https://t.co/hsX4AgxRzU
📌 Always research before farming.
Save this list.
Which site do you check daily?
Follow @9Xvenom for more.
How to become a quant from 0 to $650k/year (PLAYBOOK):
by the end, you'll know how to:
- build the exact math foundation top firms actually test
- ship real projects that separate you from every other applicant
- land your first credential and use it to climb the staircase
- crack interviews at Citadel, Jane Street and prop shops
btw i was quantitative backend developer at Liquid Hedge Fund based in Dubai for almost a year, building systematic trading strategies across perp dexes and prediction markets (right now on a break, working on my own projects)
everything below is what actually got me here, in the order it actually worked
here's the full 5-stage roadmap:
---------------
Stage 1 (year 0): build the math foundation in the correct order
the biggest mistake is starting with finance textbooks or trading blogs
you don't need to know markets. you need to know math that markets run on
how to build it:
> probability first - Blitzstein & Hwang, free PDF from Harvard. chapters 1 to 6. conditional thinking is the entire skill
> statistics second - Wasserman, All of Statistics. how to tell signal from noise
> linear algebra third - Strang MIT 18.06, free at > OpenCourseWare. eigenvalues reveal what actually matters
> convex optimization fourth - Boyd & Vandenberghe, free from Stanford. every portfolio problem reduces to this
> stochastic calculus last - Shreve Vol 1 and 2. this is where Black-Scholes comes from
your first year should feel painful, slow, non-linear
most people quit here. that's why the field pays what it pays
metric to watch: can you derive Ito's Lemma from scratch on a whiteboard?
mistake to avoid: skipping layers because they feel abstract
---------------
Stage 2 (year 1): read the papers and implement each one from scratch
this is where I separated from every other backend developer trying to get in
the 5 papers that shaped every quant desk on Wall Street:
> Avellaneda & Stoikov 2008 (market making)
> Engle & Granger 1987 (cointegration)
> Heston 1993 (stochastic volatility)
> Fama & French 2015 (five-factor model)
> Cohen, Malloy, Pomorski 2012 (insider clusters)
read all five. twice. then implement each from scratch in Python. no frameworks
language stack that actually ships:
> Python for research, backtesting and 90% of quant work. pandas, polars, pytorch, cvxpy, statsmodels
> Rust for new systematic infrastructure. this is what Hyperliquid, prediction market engines, and next-gen HFT stacks are built in
> Go for execution infrastructure. broker connectivity, microservices, low-latency APIs
> C++ only if you're targeting elite HFT engineering. Jane Street uses OCaml specifically for their trading stack
the mistake most self-taught quants make is picking one language and defending it, real desks run POLYGOT.
Python for research, Rust or Go for execution
what this gave me:
1: real understanding of how each model breaks
2: code on GitHub that recruiters actually respected
3: the ability to explain any of these in an interview without notes
Heston was the one that changed my thinking. once I understood why volatility itself follows a stochastic process, options started making sense
metric to watch: can you code Heston from a blank file in under 4 hours?
mistake to avoid: reading 20 papers superficially instead of 5 deeply (VERY IMP)
---------------
Stage 3 (year 2): ship 6 real projects with working backtests
this is where most aspiring quants die silently
the 6 projects that will land your first interview:
> pairs trading bot on 5 cointegrated equity pairs
> options pricing engine with Heston implementation
> Fama-French factor decomposition scanner
> insider cluster detector using SEC EDGAR
> mean reversion scanner for S&P 500
> cross-exchange arbitrage scanner for perp DEXs
every project needed:
- clean GitHub repo with a proper README
- working backtest with real historical data
- honest documentation of what failed and why
- one paragraph explaining the math in plain English
the honest documentation is what actually got me noticed. I wrote a section called "what broke" in every README. two recruiters told me later that was the reason they DM'd me
metric to watch: how many recruiters DM you after posting these
mistake to avoid: hiding the projects where the math didn't work
---------------
Stage 4 (year 3): first credential and the interview grind
credential path (what worked for me):
> cold emailed 40 PhD students. 3 responded. 1 took me on
> TA'd a quantitative finance course at a local university
> contributed to open-source quant libraries on GitHub
> the title didn't matter. having real technical work to talk about mattered
interview prep:
- the Green Book (Xinfeng Zhou). 200 real interview problems. spend 15 minutes attempting each before looking at hints
- QuantGuide(dot)io for probability puzzles at interview difficulty
- Brainstellar for brain teasers
- Zetamac for mental math. target 50+ correct per minute before applying
- LeetCode Blind 75 with focus on dynamic programming
the interview is a filter. it's not testing your knowledge, it's testing how you think under pressure with incomplete information
metric to watch: how quickly you can solve fresh problems out loud
mistake to avoid: memorizing solutions instead of understanding patterns
---------------
Stage 5 (year 3-4): compete publicly and climb the staircase
organic applications alone hit a ceiling. now you layer
public competitions:
> Jane Street Kaggle ($100K prize + direct recruiter visibility)
> WorldQuant BRAIN (paid alpha signals + institutional pipeline)
> Citadel Datathon (winners fast-tracked to interview rounds)
the staircase (this is the part nobody tells you):
1: research lab or startup first
2: mid-tier prop shop second
3: elite fund like Citadel, Jane Street, or Two Sigma third
nobody jumps directly from zero to Jane Street. everyone climbs
attempting the vertical jump and failing doesn't mean the field is closed. it means you tried to skip stairs
metric to watch: interview conversion rate at each tier
mistake to avoid: applying to elite firms first, getting rejected and giving up
---------------
CONCLUSION
most aspiring quants die between the math foundation and the first credential because they think they need one more course, one more book, one more year
the truth is: the first 3 stages are slow, painful and non-linear
but they build the foundation that makes stages 4 and 5 feel like gravity
start with probability. read the 5 papers. ship 6 projects. then apply
no MIT. no Stanford. no finance degree required
Citadel entry level pays $336K to $642K. Jane Street average $1.4M. 5-year top prop $800K to $1.2M
the information asymmetry keeping most people out isn't intelligence. it's not knowing what the path looks like.
COMPLETE SUMMARY BELOW:
If I were in my 30s or 40s right now and wanted to leverage AI to retire within 10 years, here's what I'd do:
1. Immediately form an LLC company. Not next month. Not once you're 'ready.' This week.
best thing you'll read all week. read it, internalize it, read it again.
"Getting ahead isn't about working harder than everyone around you. It's about putting your effort in places where it can create disproportionate returns. You don't need every decision to change your life.
You just need a few that change your trajectory. ❤️"
how to get an actual edge against 99% users on fomo
everybody already has guard, scan, api, gmgn, axiom
if you are still getting farmed, use these below
> live tape
- rhtrenches = https://t.co/SqVgPP21ZP
- fomopulse = https://t.co/7ifg3C4QE6
> research / consensus
- fomo radar = https://t.co/k669kHnP8Q
> second screen / alerts
- fomo live feed = chrome side panel (fomo + pump in one timeline)
- fomo tracking bot = https://t.co/2DaMlO38aU
- fomo leaderboard feed = https://t.co/Z3wk3huUh3
> rh chain / wallets that are not a handle yet
- hoodfi = https://t.co/REiOr75Yjj
- stalkchain = https://t.co/dj4nZjHCMD
- hoodwatch = https://t.co/gxrpFQciRv
- hoodstalk = https://t.co/8wPUNotLXm
- robinhood radar = https://t.co/GhpBMd89YG
> other
- fomo etf = https://t.co/9I9gpCB2D4
- fomo sapiens = https://t.co/lY3U1UznL3
- fomofaster ws = https://t.co/7FehGlPavH
tape first. then check if the print is real. then find the wallet that is not a handle yet
do not install all of these. pick one from each section. dyor before using these tools
"27% MORE THAN APR 3 – APR 30, 2026"
that comparison line is under the revenue panel at 0:58. estimated
revenue $32,482.75, subscribers +56.8K.
the pipeline she just built runs on higgsfield's mcp connector — the
"press connect" screen at 0:45 reads https://t.co/7799yJpG6P. higgsfield's
image-to-video only became a claude connector this year.
so the dashboard proving the method compares against april 2026, and the
period it's comparing is april 2026 — a channel that was already earning
$32k/month before the connector in the tutorial existed.
the screenshot isn't the output of this workflow. it's a channel that
was running long before it, borrowed to sell the build.
hook says $20k/month. the receipt on screen says $32k. even the number
she's showing doesn't match the number she's promising.
full breakdown in the article below.