Cost breakdown
| Component | % | $ on your trade size |
|---|---|---|
| Whale's own AMM price impact (inherited, unavoidable) | — | — |
| Your additional impact (trading on top of the moved pool) | — | — |
| Latency drift (volatility-scaled estimate) | — | — |
| Service fee | — | — |
| Your excess cost (impact + drift + fee — the real cost of copying) | — | — |
| Total premium vs pre-trade price | — | — |
How it works
There are three separate cost layers stacked on top of each other, and they behave very differently. The whale's own AMM price impact is the price move their trade causes on a constant-product pool, and it's usually the biggest number in the breakdown by a wide margin — it's a function of their trade size versus the pool's liquidity depth, and there's nothing your bot can do about it because you always trade after them. Your own additional impact is the extra push your copy-trade causes on top of a pool the whale already moved; this is usually small unless your copy size is itself a large fraction of the pool. Latency drift estimates the extra adverse price movement that can accrue during the seconds between the whale's transaction confirming and yours confirming — it's calculated by scaling the token's annualized volatility down to the size of your latency window using a random-walk (square-root-of-time) approximation. That's a statistical estimate of a typical one-standard-deviation move, not a guarantee: real-world price action during any specific window can be considerably larger or smaller than this estimate, especially around news events or thin liquidity moments. Also important — this calculator only models AMM mechanics and latency-driven drift. It does not account for MEV sandwich attacks or front-running by other bots watching the same whale wallet or the same mempool, both of which can add meaningful extra cost that isn't captured here.
Reading the numbers
Take the defaults: a whale trading $500,000 into a $3,000,000 pool, with you copying $10,000 eight seconds later on a token with 80% annualized volatility and a 1% service fee. The whale's own impact is 500,000 ÷ 3,500,000 = 14.29% — that's the price the whale themselves paid, and it's the number you inherit just by trading after them. Your own additional impact, trading $10,000 against a pool now sitting at $3,510,000 combined, is only 10,000 ÷ 3,510,000 ≈ 0.28% — tiny by comparison. Latency drift over 8 seconds, scaled from 80% annual volatility using the square-root-of-time rule, works out to roughly 0.04% — also small, because 8 seconds is a minuscule fraction of a year. Add your impact, drift and the 1% service fee together and your excess cost — the actual premium of using a copy-bot instead of trading nothing at all — is about 1.325%, or $132.52 on a $10,000 trade. But your total premium versus the price that existed before the whale even traded is 14.29% + 1.325% ≈ 15.61%, or $1,561.09. The insight worth sitting with: over $1,400 of that ~$1,561 total cost is the whale's own price impact, not anything your bot did wrong. Copying a large whale trade on a shallow pool is expensive mainly because the trade itself was large relative to the pool — being fast just controls the smallest slice of the bill.
FAQ
Why does the whale's own trade cost me money if I'm the one placing a separate transaction?
Because a DEX pool doesn't reset between transactions — every trade executes against whatever state the pool is in at that moment, and the whale's transaction confirms before yours. In a constant-product AMM, a large trade pushes the pool's price along its curve, and that new, worse price is simply the market price for the next person, which happens to be you. You never get the chance to trade at the price that existed one block earlier; you can only trade at the price the whale left behind. That's why the whale's impact shows up as your cost even though you technically paid your own gas and signed your own transaction — you inherited their price move by definition of trading after them, not because of anything your bot did wrong.
Does a faster copy-trading bot (lower latency) always mean lower cost?
Lower latency shrinks one specific slice of the cost — the drift term — but it doesn't touch the other two, which are usually bigger. The whale's own AMM impact is fixed the instant their transaction confirms, and your own pool-depth impact only depends on your trade size relative to the pool, not on timing. So a bot that confirms in 1 second instead of 8 seconds will meaningfully cut the volatility-driven drift piece, especially on high-volatility tokens, but if the whale traded a huge size against a shallow pool, that impact dominates the total regardless of how fast you are. Faster execution helps most when volatility is high and the whale's trade was relatively small; it helps least when the whale's trade was the dominant cost driver to begin with.
What isn't this calculator modeling (MEV, sandwich attacks, front-running)?
This tool only models the mechanical, unavoidable parts of copy-trading: AMM price impact from constant-product math and a volatility-scaled estimate of price drift during your latency window. It does not model MEV extraction, where searchers detect your pending copy-trade in the mempool and sandwich it with their own buy-before/sell-after transactions to skim extra value from you, nor does it model outright front-running of your bot's known trading pattern by other copy-traders watching the same whale wallet. Both of those can add real, sometimes substantial, additional cost on top of everything calculated here, and they depend on mempool visibility, the chain's MEV infrastructure, and whether your transactions go through a private relay — none of which this calculator has any visibility into. Treat the numbers here as a floor, not a ceiling, on what copying a whale actually costs.
How is this different from the CEX-style copy trading risk calculator already on this site?
RektCalc's existing Copy Trading Risk Calculator models centralized-exchange copy trading, where you allocate capital to a lead trader's strategy on a platform like Bybit or OKX and pay that platform a profit-share fee on realized gains — the cost structure there is entirely about the fee percentage and the lead trader's win rate, with no on-chain mechanics involved at all. This calculator models something structurally different: mirroring a specific wallet's trades directly on a decentralized exchange, where there's no profit-share fee to a lead trader (aside from an optional flat service fee) and the real cost comes from AMM price impact and the latency between the whale's confirmation and yours. If you're allocating to a CEX copy-trading strategy, use the other tool; if you're running or evaluating a bot that mirrors an on-chain wallet's DEX swaps, this is the one that models your actual cost mechanics.