Web3 market maker | 6y exp | 50+ CEX/DEX | Exchange setup in 1 day | 24/7 ops, 99%+ uptime
Dubai, Global
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@bitmakerfi has a new home online.
We’ve rebuilt our website to give a clearer view of how we approach market making, from preparation and trading infrastructure setup to live deployment, optimization, monitoring, and expansion.
→ 6 years in the market
→ 50+ integrated exchanges
→ 40+ active clients
→ 35 professionals
→ 99% uptime
→ 24/7 execution
All brought together in one place.
Explore the new Bitmaker website ↓
🌐 bitmaker.fi
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A 24/7 market keeps trading across time zones, weekends, and periods when the underlying market may have limited hours. Perps, tokenized assets, and onchain venues therefore place continuous demands on execution infrastructure.
Three areas determine whether this market can operate with discipline.
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3. A clear account of trading performance
Volume alone says little about the result of continuous trading. Performance attribution needs to show how realised and unrealised PnL, fees, funding, inventory exposure, and execution quality contributed to the outcome.
That visibility gives teams a basis for reviewing a strategy over a full trading cycle.
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At @bitmakerfi, these requirements are reflected in the operating layer around execution: market-data freshness monitoring, pre-trade risk checks, venue-state reconciliation, exposure and PnL tracking, and real-time dashboards.
Continuous markets require the same continuity from the infrastructure that supports them.
Read the full article by Bitmaker co-founder Roman Korotchin: finextra.com/blogposting/320…
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On September 18, @coinbase said it had sought approval to list perpetual futures tied to 50 to 60 large-cap U.S. stocks. Earlier in the month, Kalshi was preparing a filing for a perpetual WTI crude oil contract after filing for products tied to equity indices, metals, FX, and interest rates.
@HyperliquidX already gives traders access to crypto, commodities, indices, and other markets through the same perpetual trading environment.
The common feature is continuous leveraged exposure to instruments whose underlying markets still have their own trading hours, reference venues, and liquidity rhythms.
This makes price formation part of the product. Once the underlying market closes or reprices sharply, the perpetual contract still needs a reference price participants can trust, funding and margin rules suited to the conditions, and enough depth for traders to enter and exit.
A new perp market becomes meaningful once it meets volatility, gaps in underlying pricing, and live order flow.
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Liquidity becomes real after a market goes live, when order flow, infrastructure, and risk all meet in the same book.
We’ll be in Seoul on September 30 to discuss this with LPs, protocols, and infrastructure teams. See you at @ProofOfLiq
Looking for the best event at @kbwofficial? Look no further.
Our Seoul Edition connects LPs, protocols/chains and the infrastructure layer between them.
Co-hosts: @monad, @Shift_DeFi, @apyx_fi, @frankencoinzchf
Event partners: @EmberProtocol, @zama, @bitmakerfi
Sep 30, Seoul
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Live markets rarely fail as a clean outage. A connection can stay open while orders are rejected, a balance can look current while it is stale, and a venue can reopen before exposure is fully reconciled.
Kraken’s recent status updates show why this matters.
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Usable infrastructure has to connect these events into one operating view.
Execution shows what the venue accepted. Visibility connects orders, fills, positions, balances, and PnL. Control provides alerts, audit trails, and a safe route through degraded conditions.
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At @bitmakerfi, exchange connectors, an execution router, reconciler, and real-time dashboard are built around that operating problem.
The important moment is when an operator can see the state clearly enough to continue, reduce risk, or pause.
Source: status.kraken.com/
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A new article by @bitmakerfi co-founder Roman Korotchin @korrom18 on Hyperliquid’s emerging market structure.
HIP 3 has separated market creation from the exchange layer, while independent terminals are beginning to shape how traders manage accounts and strategies across venues. The question is whether Hyperliquid can remain the preferred execution layer as new deployers and access points emerge.
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When someone opens an order book, there is a simple question behind every trade: can I enter or exit this position at a price I can rely on?
The answer starts with information the market needs to share:
• executable bids and offers
• available depth across price levels
• recently completed trades
These signals allow participants to assess liquidity, estimate price impact, and form a view on value.
Behind those quotes sits a second view of the market.
The team managing liquidity needs to understand:
• current inventory and market-risk exposure
• quote parameters and execution logic
• balances, credentials, and counterparty information
This information defines how a trading operation manages risk. Its access belongs with the people and systems responsible for execution, oversight, and audit.
Market infrastructure has to serve both views at the same time. Participants need clear market information to make informed trading decisions. Risk teams need controlled visibility into the positions and processes behind that liquidity.
At @bitmakerfi, execution infrastructure combines market-data processing and order-book analysis with tenant isolation, encrypted credential storage, role-based access, and audit trails for strategy and order actions.
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Glad to join Proof of Liquidity in Seoul during @kbwofficial and Singapore during @token2049
See you there 🇰🇷 🇸🇬
A full-stack Web3 market maker providing liquidity across all major CEXs and perpDEXs.
@bitmakerfi joins Proof of Liquidity as an Event Partner for both Seoul and Singapore Editions.
yieldnetwork.io/events
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A useful example of why liquidity parameters need to follow the market regime.
Funding normalized within two days, while the trading range remained several times wider than BTC on the same venue.
For a market maker, that changes fill probability, inventory exposure, spread requirements and risk limits even when funding already looks normal.
Funding on the solana:Dz9mQ9NzkBcCsuGPFJ3r1bS4wgqKMHBPiVuniW8Mbonk perp hit 330% annualized on listing day, then dropped to Hyperliquid's 10.95% baseline by day two and has held there since on @HyperliquidX
Carry traders got their window and it closed in about 36 hours.
What didn't normalize is the candle range. Average hourly bar spans 373 bps. BTC on the same venue runs roughly 53.
So when you clone a working bitcoin:native grid and swap the ticker, a 15 bps step that filled a few times an hour there now crosses 25 levels in the same window. Every one of those fills pays a spread you sized for a different book.
The leverage field will also reject whatever you had set. HL caps this market at 3x.
Funding tells you what the crowd is paying. Candle range tells you whether your step size makes sense. They move independently and only one of them is in your config.
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Crypto ETFs have now recorded six consecutive weeks of inflows. The latest week brought $1.3 billion after $3.3 billion the week before, according to @KobeissiLetter. Across the full six-week period, the total reached $6.8 billion.
Flows like these form part of the wider market environment in which an order book operates. A market can trade in a stable range for days, then begin to carry a different pattern of demand as price and positioning adjust.
Market conditions change the risk carried by every quote in the book.
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Perpetual markets offer a useful illustration of how quickly this can change. As @MrGigaWhale noted this week, rising open interest needs to be read alongside funding. When open interest builds while price remains flat, leverage can accumulate before the market has resolved in either direction.
Once the price breaks, that positioning can make the next phase move much faster.
Highly volatile periods compress the time available for adjustment. Fair price can shift quickly, and the order book can change before earlier conditions are still relevant.
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Liquidity management requires live market data, fast execution infrastructure, and continuous monitoring of orders, balances, and market-risk exposure.
At @bitmakerfi, dynamic model parameters use signals from trades, order-book imbalance, order-flow characteristics, and broader market dynamics to adjust quote skew, spread width, and balance limits in real time.
Across different market regimes, the objective remains the same: keep liquidity continuous while keeping risk controlled.
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