🎯 Arb Desk Report

🏆 Top 5 Arbitrage Opportunities

Note: all entries below come directly from the provided data. "Available volume" and "Window length" are not specified in the dataset, and the TOTALS indicate no actual liquidity at present, so executable status is contingent on live order books and transfer times.

• Buy exchange and price: Bitunix, $0.025520
• Sell exchange and price: Bitget, $0.026200
• Available volume: Not disclosed
• Window lasted: Not disclosed
• Risk factors: Liquidity depth on Bitunix and Bitget; cross-exchange transfer times; potential withdrawal constraints for AZTEC token; market microstructure risk during narrow windows
• Executable status (my take): The dataset shows zero pump/dump volumes, so there is no realized liquidity. While the theoretical spread is large, execution requires visible depth and timely settlement. In the current data view, this is not executable until liquidity appears on both sides.

• Buy exchange and price: Bybit Spot, $0.037160
• Sell exchange and price: Coinbase, $0.042700
• Available volume: Not disclosed
• Window lasted: Not disclosed
• Risk factors: On Bybit Spot, depth for CHZ; Coinbase liquidity and withdrawal times for CHZ; potential fee drag on both sides; withdrawal/transfer pacing between Bybit and Coinbase
• Executable status (my take): The theoretical margin is substantial, but without visible volumes, it remains non-executable in this snapshot. If liquidity appears, expect a meaningful but potentially time-sensitive window before price convergence.

• Buy exchange and price: Bitget, $0.026911
• Sell exchange and price: OKX, $0.028625
• Available volume: Not disclosed
• Window lasted: Not disclosed
• Risk factors: Bitget depth for AZTEC, OKX liquidity on the sell side; cross-chain withdrawal timing; possible futures vs spot timing mismatches
• Executable status (my take): The spread is noteworthy, but execution requires concurrent liquidity on both Bitget (buy) and OKX (sell). In this snapshot, not guaranteed.

• Buy exchange and price: OKX Spot, $0.136478
• Sell exchange and price: Coinbase, $0.154000
• Available volume: Not disclosed
• Window lasted: Not disclosed
• Risk factors: Depth on OKX for OP; Coinbase’s price stability and withdrawal timing; potential slippage during rapid legging; cross-exchange transfer cycles
• Executable status (my take): Strong theoretical margin, but no current liquidity data. If a trader can access both legs with adequate volume, this could be a high-returns window, otherwise it remains on paper.

• Buy exchange and price: OKX Spot, $2.739000
• Sell exchange and price: Coinbase, $3.060000
• Available volume: Not disclosed
• Window lasted: Not disclosed
• Risk factors: OKX’s RPL depth; Coinbase withdrawal/settlement timing; token liquidity gaps between spot and fiat gateway; slippage risk if volumes appear
• Executable status (my take): The margin is sizable per unit, but this window is not guaranteed to be executable in the absence of confirmed volumes. It’s worth monitoring as liquidity builds.

Notes on the five selections: Across these top opportunities, the common thread is cross-exchange price dislocation with spot-to-spot or spot-to-futures mismatches. The absolute spreads are sizable, but the practical path to profit requires prompt liquidity access, reliable withdrawal/transfer timing, and minimal counterparty risk during transfer windows. In this dataset, all top-5 entries share the characteristic of zero live volumes, so they are currently theoretical rather than executable.

📊 Exchange Spread Patterns

• Consistent counterparty roles: Coinbase frequently appears as the sell venue in several opportunities (CHZ, RPL, NEAR, etc.), suggesting it often quotes higher relative prices on certain assets, creating favorable sell legs for arbitrageurs. This pattern is visible in CHZ (Bybit Spot buy, Coinbase sell) and RPL (OKX Spot buy, Coinbase sell), among others.
• Bitget as a recurring buy leg: AZTEC entries show Bitget as the buy leg in multiple windows (Bitget buy in the 13.53% and 11.25% examples). The presence of Bitget as a bid-side venue is a recurring hot spot for AZTEC spreads to the OKX or Gate Futures sell legs.
• OKX as sell anchor on larger deltas: The 13.53% AZTEC window pairs Bitget buy with OKX sell, illustrating OKX as a common high-sell counterpart when other venues supply the lower bid.
• Bybit as both sides in separate opportunities: Bybit surfaces as a buy leg (CHZ 14.91% CHZ window uses Bybit Spot buy) and as a sell counterpath in other AZTEC patterns (AZTEC 9.72% uses Bybit as the sell leg). This dual role highlights Bybit’s liquidity presence across both legs in different assets.
• Limited direct Binance-like pairings: The dataset shows a network of exchanges including OKX, Gate Futures, Bitget, Bitunix, Bybit, Coinbase, and Bybit Spot, but no explicit Binance pairings. The arbitrage graph appears to hinge on a cross-section of prominent spot and futures venues rather than a single hub exchange.

Overall pattern takeaway: The spreads tend to hinge on a mix of spot-to-spot cross-venue disparities and spot-to-futures (Gate Futures and OKX) dislocations, with Coinbase frequently acting as a liquidity sink on higher-priced sell quotes. This implies that the most robust opportunities in real liquidity would arise where market depth is deepest on the buy leg and where the counterparty can rapidly settle on the sell leg with minimal withdrawal friction.

⚡ Speed vs Size Analysis

• Speed (smaller, quicker windows) vs size (larger, slower windows): The dataset’s high-spread opportunities imply attractive per-unit margins, but many of these windows will be sensitive to order-book depth and inter-exchange transfer times. Faster execution tends to favor smaller, near-market spreads where depth is deep and slippage is minimal; larger spreads usually come with thinner liquidity, increasing the risk of partial fills and longer max fill times.
• Slippage considerations: In low-volume, high-spread windows, slippage can erode a large portion of the gross margin if you chase aggressively. Opt for conservative sizing on a first-pass fill and then scale as depth confirms.
• Position sizing recommendations: Given the lack of disclosed volume in the dataset, a cautious approach is prudent. Start with small nominal exposure (e.g., dozens to hundreds of thousands of token units in assets with robust liquidity) to validate cross-exchange transfer times and immediate fill behavior. As liquidity confirms, scale in measured steps.
• Practical rule of thumb: In a 0-volume snapshot, any approach should assume potential 0- to low-visibility fill. Favor venues with consistent depth for both legs and minimal withdrawal friction, and limit exposure until both legs display depth in real time.

💰 Profit Calculations

Here is how to think about profits given the quoted prices, assuming typical fee structures, and illustrating with a conservative framework. The numbers below treat the per-unit profit in USD terms for a single unit of each asset.

• Common formula per unit
• Gross profit per unit = P_sell - P_buy
• Fees (assume 0.1% taker on each leg as a baseline): Fee_buy = 0.001 × P_buy; Fee_sell = 0.001 × P_sell
• Total fees per unit = 0.001 × (P_buy + P_sell)
• Net profit per unit = (P_sell - P_buy) − 0.001 × (P_buy + P_sell)

Top-5 live-quote-based calculations (per-unit basis). For illustration, we use the precise prices from the dataset and a baseline fee of 0.1% on each leg.

• P_buy = 0.025520; P_sell = 0.026200
• Gross per unit = 0.000680
• Fees per unit = 0.001 × (0.025520 + 0.026200) = 0.000051720
• Net per unit ≈ 0.00062828
• Example scale (1,000,000 units): ≈ $628.28 net

• P_buy = 0.037160; P_sell = 0.042700
• Gross per unit = 0.005540
• Fees per unit = 0.001 × (0.037160 + 0.042700) = 0.000079860
• Net per unit ≈ 0.00546014
• Example scale (1,000,000 units): ≈ $5,460.14 net

• P_buy = 0.026911; P_sell = 0.028625
• Gross per unit = 0.001714
• Fees per unit = 0.001 × (0.026911 + 0.028625) = 0.000055536
• Net per unit ≈ 0.001658464
• Example scale (1,000,000 units): ≈ $1,658.46 net

• P_buy = 0.136478; P_sell = 0.154000
• Gross per unit = 0.017522
• Fees per unit = 0.001 × (0.136478 + 0.154000) = 0.000290478
• Net per unit ≈ 0.017231522
• Example scale (1,000,000 units): ≈ $17,231.52 net

• P_buy = 2.739000; P_sell = 3.060000
• Gross per unit = 0.321000
• Fees per unit = 0.001 × (2.739000 + 3.060000) = 0.005799
• Net per unit ≈ 0.315201
• Example scale (1,000,000 units): ≈ $315,201.00 net

Notes on profit calculations:

• The per-unit nets above assume symmetrical taker-fee exposure on both legs. If a venue offers maker rebates or slightly different fee tiers for high-volume participants, the net profit per unit could shift modestly.
• Withdrawal fees and cross-exchange transfer times are not included in the per-unit net. If a token withdrawal incurs a nontrivial cost or a bridge delay exists, the effective net profit could drop, especially for smaller spreads.
• With the dataset reporting zero liquidity, the practical profitability of any of these opportunities hinges on real-time depth and fast cross-exchange settlement.

Minimum spread worth chasing:

• A spread is worth chasing when the net per-unit profit after fees remains positive at the intended trade size, and the expected fill rate across both legs is high enough to realize the margin within a reasonable window.
• Theoretical break-even per unit (assuming 0.1% taker fees on both legs) is any positive gross delta, since the fees subtract a small amount from the delta. In practice, a more conservative threshold would require the net per-unit profit to comfortably exceed withdrawal costs and any slippage risk.
• From the five best quotes, all show positive net per-unit profits under the baseline assumption. The higher the price delta and the deeper the liquidity, the larger the practical profits for a given trade size. However, zero volumes in the dataset mean actual realized profits cannot be stated here; only the per-unit economics stand as a guide.

⚠️ Risk Alerts

• Withdrawal delays: Cross-exchange transfers can introduce delays that widen the window for price moves against you. Some tokens have higher withdrawal times and sometimes require manual approvals.
• Liquidity gaps: Even if prices look attractive, real liquidity may be asymmetric between the buy and sell venues. Partial fills or failed fills can erode margins quickly.
• Exchange issues: Network congestion, API outages, or maintenance windows can disrupt arbitration trades and produce unanticipated slippage.
• Counterparty risk and KYC: Some venues require updated verification tiers; cross-border or cross-asset transfers may be subject to withdrawal fees, limits, or rolling 24-48 hour holds.
• Settlement risk: If one leg settles later than the other, price drift may reduce or reverse expected profits.
• Market regime risk: Spreads can vanish in minutes as market participants rebalance or as new information flows in.

🔮 Tomorrow's Setup

• Assets to watch: CHZ, OP, RPL, NEAR, and AZTEC remain the most active in these top pools due to clear cross-exchange mismatches and higher nominal spreads.
• Best times to monitor: Overlaps in US/EU session transitions and Asia-to-US liquidity windows tend to reveal the most aggressive cross-exchange opportunities. Specifically, watch for price re-pricings during session starts (roughly each day's opening hours) and during period of heightened Coinbase activity for asset pairs that tend to print higher sell quotes there.
• Exchange pairs to monitor:
• AZTEC: Bitunix (buy) vs Bitget (sell); Bitget (buy) vs OKX (sell); Bitget (buy) vs Gate Futures (sell)
• CHZ: Bybit Spot (buy) vs Coinbase (sell)
• OP: OKX Spot (buy) vs Coinbase (sell)
• RPL: OKX Spot (buy) vs Coinbase (sell)
• NEAR: Bybit Spot (buy) vs Coinbase (sell)
• Practical watch plan: Set alerts for the exact quotes listed above and verify depth on both legs before attempting any execution. Validate that withdrawal timelines from the buy venue and on-ramp liquidity at the sell venue can accommodate the intended size in one cohesive cross-exchange move.

Sign Off

Arbitrage markets evolve in real time, and what’s printed here is a snapshot—distinct from a live-order opportunity. The clearest takeaway is the presence of sizable per-unit margins on several high-profile cross-exchange dislocations, tempered by the lack of disclosed liquidity in this dataset. When liquidity does appear, these windows can convert into meaningful trades. Until then, proceed with disciplined risk controls, confirm depth and withdrawal paths on both legs, and size positions adaptively.