Sim

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Sim

@simpelyfe

Building @bkdplx

Katılım Aralık 2019
2.6K Takip Edilen27.3K Takipçiler
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Sim@simpelyfe·
Real world example of relative market microstructure. Please follow @bkdplx for updates! :D
Book Duplex@bkdplx

Book Duplex here - This is our 'Hello World!' We're diving right into liquidity dynamics for ratio assets with an example of ETH/BTC absorption. A) Ratio price rising, but log ratio depth for asks remain positive near mid (yellow rounded peak). B) ETH buyers are actively taking liquidity while BTC leg is absorbing the pressure. C) That means, someone is selling into the HERD ENTRY instead of lifting liquidity. D) Static books won’t show this. Ratio liquidity dynamics will. That's all for now. But we're just getting started... Happy Wednesday, folks!

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Sim@simpelyfe·
Lunch! :3
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Sim@simpelyfe·
Gimme da foot.
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Sim@simpelyfe·
I told the guy that works at the gas station where I frequent -- gave him... 60% of the recipe on receipt paper. I think I'll proposition him: if you do the research and figure out the rest or come close, I'll give you a job. Because this is like, serious mental cross referencing of academic studies. It shows incredible soft skills and desire + curiosity.
Sim@simpelyfe

I solved the age-old adage of: 'How does price, open interest, and funding rate' quantitatively inform state? And all you guys are just writing X articles on 'feeling' out these primitives while I solved this problem on a beer. Ask me how; go ahead... ask me how, and I'll give you hints.

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Sim@simpelyfe·
@RenjieGaming It's not ready until I am damn well happy that you guys will be happy!
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Sim@simpelyfe·
I solved the age-old adage of: 'How does price, open interest, and funding rate' quantitatively inform state? And all you guys are just writing X articles on 'feeling' out these primitives while I solved this problem on a beer. Ask me how; go ahead... ask me how, and I'll give you hints.
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Sim
Sim@simpelyfe·
I got a great question: > how would you approximate the fill/kill ratio(I have a somewhat tackey method which I have very low confidence in) cause depth updates every lets say 100ms,while trades are streamed almost real time. asking cause without it,it becomes difficult to quantize the effects you were talking about in the tweet Response: this is a good question — but I wouldn’t try to estimate true FOK directly because like you said... book = 100ms snapshots; trades = near real-time so you’re always missing state instead I’d reframe it: Don’t ask “was it filled or killed?”; Ask “did it move the mid?” if aggressive buys consistently → mid lifts after that’s effectively “high fill / low resistance” if not? Absorption... so your metric becomes: P(mid follows trade direction) -- that's the real signal. ----------------- Can we jumpstart a REAL discussion? Tag microstructure-KOL's, RT for visibility if you are interested in elucidating this topic... Let's go folks.
Sim@simpelyfe

I figured out why the tape always shows fake and shallow flow: It's a means to probe whether informed participants have entered the market. The milliseconds after a trade is matched can tell you so much. If the mid is higher, for example, 200ms after a buy trade gets matched, that buyer might know something. If the mid is continually above subsequent buys, asymmetric information has hit the market; and it's time to take liquidity. Also, if you're interested in microstructure: monitoring book speed -- the shelf-life of quotes: this will tell you much more than tape speed ever will. Tape speed is stale information. By the time tape speed spikes, market makers have already shifted liquidity surface curves, and taking liquidity in the direction of move has a high probability of being toxic fills. These two metrics: fill-to-move ratio and quote lifetime, IME, are the most actionable when combined with OBI, CVD, etc. etc. Anyways, I still prefer my retarded TA diagonals and Elliot Waves lol

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Sim@simpelyfe·
So I’m watching last episode of Hells Paradise and the juxtaposition was like the hug I needed from Nuru… this is such a good show for the soul…
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Sim@simpelyfe·
Someone stop me from xeeting unruly things. That was a former lyfe… I am now just. Another NPC…
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Book Duplex
Book Duplex@bkdplx·
New layout just dropped. Scanner → bottom. Context → above. Execution → faster. You can now: • scan pairs • validate microstructure • act — all in one frame No tab switching. No mental overhead. This is how flow should feel.
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Book Duplex
Book Duplex@bkdplx·
There’s a layer beneath price most people never see. Not candles. Not indicators. Execution geometry. We started mapping it. Clusters don’t lie: - where size actually trades - where participants get forced - where moves are born… before they show up on price The chart didn’t get more complex. It got honest. Once you see this, you can’t go back. BkDplx.
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Sim@simpelyfe·
Excitement. 11/10.
Book Duplex@bkdplx

We just shipped something that changes how you scan markets. Pair Scanner → now runs on recipes, not just metrics. Not: “highest z-score” “strongest imbalance” But: Trend alignment Exhaustion Liquidity vacuum Traps Structural divergence 10 microstructure states. Ranked. Live. Across all pairs. Instead of staring at numbers… You scan for behavior. Markets aren’t just moving — they’re expressing structure. This is how you see it. BkDplx.

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Book Duplex
Book Duplex@bkdplx·
This is why microstructure matters. Net imbalance wasn’t just confirming price — it was driving it. • Persistent sell-side flow → sustained drawdown • Flip to buy-side → immediate expansion But the real signal: • Liquidity gravity was already negative • SLS structure leaned bearish before price moved • High fragility → small flow = large impact When flow + structure + fragility align, price becomes trivial.
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Book Duplex
Book Duplex@bkdplx·
It’s not NYO, but DOGE/SOL is giving us some great microstructure data this weekend. Both book + flow are active, and the expanding trade profile at the bottom is doing exactly what we hoped during stress tests. Traditional feeds (time & sales, vertical trade streams) have an inherent problem: they come at you too fast to parse in real time. You end up doing mental compute. Book Duplex approaches this differently. We deconstruct liquidity and flow into aligned time-series, so volatility regime shifts become visible the moment they start forming. Example in this clip: As price descends into larger bins and extends left/right in the trade profile, that flow is very often retail participation. Now combine that with the book. If the opposite side doesn't empty — walls remain in the direction of the block flow — you're often looking at the setup for volatility expansion. In this case it's the weekend, alt ratios, and the opposite book did clear → mean reversion as retail targets liquidity. The bigger point: There’s a lot of mental computation traders do that is slow and error-prone. Book Duplex is built around a core principle: deconstruct the metadata so you can understand market structure at a glance. One-look analysis.
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Sim@simpelyfe·
In all seriousness, this has applications in portfolio assessment. You have benchmarks, roe, and weights. You create a right triangle out of all three of them and compare the juxtaposition and magnitudes of thetas.
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Sim@simpelyfe·
@MrChiefExec If I don't partake, I sleep... then I stop breathing; and I die... lol
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Chief@MrChiefExec·
@simpelyfe You’re lowkey cracked, god had to nerf you by making you an S++ tier gooner
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Sim@simpelyfe·
So, I worked in biotech. Not that kind of biotech, but legit oncology drug development. My grad school curriculum contained advanced statistics courses, drug kinetics, pharmacodynamics, pharmacoeconomics -- the works. I was a B- student. That said, that coveted biotech position I landed after my first year allowed me to see GROUND ZERO of drug development. All the moving parts, and I got to review all the study protocols for phase 2-3 clinical trials. Honestly, it burnt me out, but I'm starting to see there's a silver lining. Because making a lateral move into crypto markets, quantitative finance, and all associated disciplines forces me to find parallels in my university knowledge-base. Combined with learning via high-level abstraction and though experiments, I don't know the academic jargon and terminology that quants throw around. This is where LLM's have been incredibly complementary for me. While using it as a learning tool, I'll instinctively try to find parallels to my current knowledge-base, and ask it a question if this 'is a thing'; does it have a use-case. Sometimes the response is: 'Yes — what you’re describing is not only valid, it’s actually a very common quantitative technique.' But then, I get this, The LLM gives this response/feedback:
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