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marketmaking

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Illia Runner
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Статия
Hummingbot Update — From “Dead Bot” to Real Execution (SOL/USDT)Yesterday I shared my first results. Today — things got real 👇 📊 What changed: ❌ Before: • 0 trades • Wide spreads → no execution • Bot looked “smart”… but did nothing ✅ Now: • 20+ trades in session • Balanced BUY/SELL cycles • Real market interaction But here’s the twist… 💰 PnL Result: • Trade PnL: positive • Total PnL: slightly negative 🤔 Why? Because of one brutal truth: ⚠️ Fees > Edge Even with perfect execution, small spreads (0.1–0.2%) get eaten by fees. 🔥 Biggest realizations so far: 1️⃣ A bot that doesn’t trade = useless 2️⃣ A bot that trades too cheap = also useless 3️⃣ Execution is step 1… but EDGE is step 2 📉 Market context: • SOL moving in tight range (~82–84) • Low volatility → harder to capture profit • High competition → spreads must be precise 🧠 What I changed: ✔ Removed artificial spread distortion ✔ Fixed inventory skew behavior ✔ Increased effective spread (0.25%+) ✔ Focused on PnL per TIME, not per trade 📊 Current goal: 👉 Fewer trades 👉 Higher profit per cycle 👉 Positive net PnL after fees 💡 My current hypothesis: “More fills ≠ more profit Better edge + controlled fills = profit” 🤔 Question for traders & bot runners: What matters more for you? 1️⃣ High frequency (many trades, small edge) 2️⃣ Lower frequency (fewer trades, higher edge) 📌 Next step: Testing dynamic spreads based on volatility (ATR-based) Will update results soon 👇 #Hummingbot #MarketMaking #SOL #CryptoTrading #AlgoTrading

Hummingbot Update — From “Dead Bot” to Real Execution (SOL/USDT)

Yesterday I shared my first results.
Today — things got real 👇
📊 What changed:
❌ Before:
• 0 trades
• Wide spreads → no execution
• Bot looked “smart”… but did nothing
✅ Now:
• 20+ trades in session
• Balanced BUY/SELL cycles
• Real market interaction
But here’s the twist…
💰 PnL Result:
• Trade PnL: positive
• Total PnL: slightly negative
🤔 Why?
Because of one brutal truth:
⚠️ Fees > Edge
Even with perfect execution, small spreads (0.1–0.2%) get eaten by fees.
🔥 Biggest realizations so far:
1️⃣ A bot that doesn’t trade = useless
2️⃣ A bot that trades too cheap = also useless
3️⃣ Execution is step 1… but EDGE is step 2
📉 Market context:
• SOL moving in tight range (~82–84)
• Low volatility → harder to capture profit
• High competition → spreads must be precise
🧠 What I changed:
✔ Removed artificial spread distortion
✔ Fixed inventory skew behavior
✔ Increased effective spread (0.25%+)
✔ Focused on PnL per TIME, not per trade
📊 Current goal:
👉 Fewer trades
👉 Higher profit per cycle
👉 Positive net PnL after fees
💡 My current hypothesis:
“More fills ≠ more profit
Better edge + controlled fills = profit”
🤔 Question for traders & bot runners:
What matters more for you?
1️⃣ High frequency (many trades, small edge)
2️⃣ Lower frequency (fewer trades, higher edge)
📌 Next step:
Testing dynamic spreads based on volatility (ATR-based)
Will update results soon 👇
#Hummingbot #MarketMaking #SOL #CryptoTrading #AlgoTrading
Статия
Testing Hummingbot on SOL/USDT — real results, no hypeI’ve been running a market making bot on Binance with a small account (~$600) and here’s the honest truth 👇 📊 What actually happened: Several sessionsSome BUY/SELL cyclesNet PnL ≈ breakeven to small profitBut here’s the interesting part… 📉 SOL dropped ~2% 🤖 My bot: almost flat 💡 So yeah… NOT losing money in a downtrend already feels like a win. ⚠️ Biggest mistakes I made (and I see many people repeating): ❌ Spread too wide → 0 fills → “dead bot” ❌ Inventory skew blocking BUY → only selling ❌ Order size too small → Binance rejects bids 👉 Result: bot looks “smart”… but does NOTHING 🔥 What actually started working: ✔ Spreads ~0.6% – 0.8% ✔ Inventory target ≈ 50% ✔ Focusing on PnL per TIME, not per trade 💣 Biggest realization: A bot that doesn’t trade = worst strategy possible Even worse than taking small losses. 🤔 Question to those running bots: Do you prefer: 1️⃣ Wider spreads → higher profit per trade but fewer fills 2️⃣ Tighter spreads → more trades but smaller edge 📊 Right now I’m leaning toward: “More fills > perfect trades” But still testing… Anyone here running Hummingbot or other MM bots on Binance? Curious to hear real experiences 👇 #Hummingbot #MarketMaking #SOL #CryptoTrading #Binance

Testing Hummingbot on SOL/USDT — real results, no hype

I’ve been running a market making bot on Binance with a small account (~$600) and here’s the honest truth 👇
📊 What actually happened:
Several sessionsSome BUY/SELL cyclesNet PnL ≈ breakeven to small profitBut here’s the interesting part…
📉 SOL dropped ~2%
🤖 My bot: almost flat
💡 So yeah… NOT losing money in a downtrend already feels like a win.
⚠️ Biggest mistakes I made (and I see many people repeating):
❌ Spread too wide → 0 fills → “dead bot”
❌ Inventory skew blocking BUY → only selling
❌ Order size too small → Binance rejects bids
👉 Result: bot looks “smart”… but does NOTHING
🔥 What actually started working:
✔ Spreads ~0.6% – 0.8%
✔ Inventory target ≈ 50%
✔ Focusing on PnL per TIME, not per trade
💣 Biggest realization:
A bot that doesn’t trade = worst strategy possible
Even worse than taking small losses.
🤔 Question to those running bots:
Do you prefer:
1️⃣ Wider spreads → higher profit per trade but fewer fills
2️⃣ Tighter spreads → more trades but smaller edge
📊 Right now I’m leaning toward:
“More fills > perfect trades”
But still testing…
Anyone here running Hummingbot or other MM bots on Binance?
Curious to hear real experiences 👇
#Hummingbot #MarketMaking #SOL #CryptoTrading #Binance
Jane Street’s record year is a quiet tell for $BTC 🔎 Jane Street pulled in $39.6B in trading revenue last year, with $15.5B in Q4 alone, a scale that says liquidity and volatility are still paying the professionals. For crypto, that matters because firms like this sit in the middle of flow; when they’re active, the market is usually breathing harder, spreads are alive, and whale intent is still being expressed through execution. Not financial advice. Manage your risk and protect your capital. #Bitcoin #Crypto #MarketMaking #Liquidity ⚡ {future}(BTCUSDT)
Jane Street’s record year is a quiet tell for $BTC 🔎

Jane Street pulled in $39.6B in trading revenue last year, with $15.5B in Q4 alone, a scale that says liquidity and volatility are still paying the professionals. For crypto, that matters because firms like this sit in the middle of flow; when they’re active, the market is usually breathing harder, spreads are alive, and whale intent is still being expressed through execution.

Not financial advice. Manage your risk and protect your capital. #Bitcoin #Crypto #MarketMaking #Liquidity
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