b2KIT

Auction Theory Simulator

Simulate English, Dutch, sealed-bid, and Vickrey auctions with multiple bidders. Explore revenue equivalence and winner curse.

Tested tool guide Tested browser tools Checked August 16, 2026

What Auction Theory Simulator does, with a checked example

This simulator takes a set of bidder valuations and runs them through four auction formats side by side: English ascending, Dutch descending, first-price sealed-bid, and second-price sealed-bid (Vickrey). Sealed-bid formats don't take arbitrary typed bids; they apply the symmetric Nash equilibrium bidding strategy for the value distribution selected, shading bids below value for first-price and bidding truthfully for Vickrey. The thing most people get wrong: they expect every format to charge the same price on a single run. Revenue equivalence is a statement about expected revenue averaged over many auctions, not about any one outcome, so first-price and second-price results will legitimately differ trial to trial.

Worked example

A concrete input and expected output from the current implementation.

Input

4 bidders, independent private values drawn from uniform[0,100]: 80, 65, 50, 30. Run first-price sealed-bid, second-price sealed-bid (Vickrey), English, and Dutch on this same value set.

Expected output

Winner is the bidder valued at 80 in all four formats. First-price and Dutch clear at 60 (equilibrium bid = value x (n-1)/n = 80 x 3/4). Second-price and English clear at 65 (the second-highest value).

With n=4 uniform values, the symmetric first-price/Dutch equilibrium bid function is b(v)=v(n-1)/n, so the top bidder bids 80*0.75=60; Vickrey and English are strategically truthful, so the winner pays the second-highest value, 65.

How the result is produced

1

Value input and equilibrium bid shading

You supply each bidder's private value directly, or draw N values from a chosen distribution (commonly uniform). For first-price and Dutch formats the tool converts each value into its symmetric Nash equilibrium bid rather than bidding the raw value, since bid shading is what rational bidders do in those formats. For second-price and English, it bids the value itself because truthful bidding is a dominant strategy there.

2

Format clearing rules and repeated-run revenue tracking

Given the bids, each format's clearing rule determines the winner and price: highest bid wins and pays its own bid (first-price, Dutch), or the highest bid wins but pays the second-highest bid/value (second-price, English). Running the simulation across many repeated value draws accumulates an average revenue per format, which is what actually converges under the revenue equivalence theorem, not any single auction.

Good uses

  • Demonstrating to students why first-price and second-price sealed-bid auctions produce the same expected seller revenue despite different winning bids on any one run.
  • Checking how much a bidder should shade a first-price bid below their true value for a given number of competitors before applying that logic elsewhere.
  • Exploring the winner's curse in a common-value setting by comparing naive bidding against equilibrium bidding when bidders only observe noisy signals of one true value.

Limits and checks

  • The revenue equivalence result assumes risk-neutral, symmetric bidders with independent private values drawn from the same distribution; switching to a common-value or asymmetric setup will correctly break the equivalence rather than indicate a bug.
  • A single simulated auction can show first-price revenue above or below second-price revenue purely by chance; only the running average over many trials approaches the theoretical match.
  • The winner's curse view relies on a common-value model with noisy private signals around one true value, not the independent-private-value model used elsewhere in the tool; reading its output as if values were independent will misstate the recommended bid shading.

Common questions

Why did the second-price auction pay more than the first-price auction on the exact same set of values?

That's expected on a single run. Vickrey's rule charges the winner the second-highest value, while first-price bidders rationally shade below their own value to leave a margin. The two formats only match in expected revenue averaged over many auctions, not bid for bid.

Can I use this to decide which auction format to run for an actual sale?

Not directly. It's an educational simulator built on textbook assumptions - risk-neutral, symmetric bidders with independent private values - that real sales often violate through collusion, budget constraints, or correlated valuations, so treat its comparisons as illustrative rather than a procurement recommendation.

References and verification

The example and behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.

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