Auction Bidding Strategist
by @quochungto
Apply the complete game-theoretic auction framework to determine the optimal bid in any auction format. Use this skill when a user is preparing to bid in an...
Example 1: Vickrey Auction (Corporate Software License)
Setup: A government agency is auctioning a multi-year software contract to the lowest bidder. This is a second-price procurement auction (winner pays the second-lowest bid). Your cost to deliver is $800K. You estimate one strong competitor at roughly $700K-$900K.
Apply the rule: In a Vickrey (second-price) procurement auction, the dominant strategy is to bid your true cost exactly. Bid $800K.
Why: If you win, you pay the second-lowest bid (competitor's bid). If competitor bids $750K, you lose β correct, because they can do it cheaper. If competitor bids $850K, you win and get paid $850K for $800K work: $50K profit. Bidding below $800K (say $750K) might win but you'd be paid $750K or less for $800K work β a guaranteed loss. Bidding above $800K (say $850K) only changes the outcome if the competitor bids between $800K-$850K, in which case you lose wins you would have profited from.
Recommended bid: $800K (your true cost).
Example 2: First-Price Sealed-Bid (Real Estate Offer)
Setup: You are in a competitive offer situation on a house. True value to you: $620,000. You believe there are 3 competing bidders, all with values roughly similar to yours.
Apply the formula: N = 4 (you plus 3 others). Optimal bid = $620,000 Γ (4-1)/4 = $620,000 Γ 0.75 = $465,000.
Sanity check: This seems very aggressive shading. In practice, real estate values are not uniformly distributed across [0, V] β they cluster near the asking price. The formula is exact only under symmetric uniform beliefs. Adjust: if you believe competing values cluster around $580K-$620K, the effective range is narrow and shading should be modest (perhaps $595K-$605K). The formula gives a floor on shading; judgment about competitor value concentration adjusts from there.
Recommended bid: $600,000 (approximately V Γ 0.97, given tight competitor value clustering) with a clear ceiling at $620,000.
Example 3: Winner's Curse Correction (Company Acquisition)
Setup: Your team estimates a target company is worth $50M-$90M today. You can improve operations by 40%. You are in a sealed-bid acquisition process.
Naive calculation: Average value $70M Γ 1.4 = $98M. "I can bid up to $98M."
Winner's curse analysis: If accepted at $98M, current value is between $50M and $98M β average $74M. Your 40% improvement: $74M Γ 1.4 = $103.6M. Profit: $103.6M - $98M = $5.6M. Still slightly positive.
Find the breakeven bid B: Accepted at B β current value between $50M and B β average (50+B)/2. Your improvement: 1.4 Γ (50+B)/2 = B. Solve: 70 + 1.4B/2 = B β 70 + 0.7B = B β 70 = 0.3B β B = $233M.
Wait β this is above the stated range. This means within the range $50M-$90M, your 40% improvement always generates enough value to justify winning. The winner's curse is not binding here because your operational uplift is large. In this case, bid your full expected-value calculation up to $98M, but confirm your improvement assumptions β they are doing all the work.
When the winner's curse is binding: It binds when your improvement multiplier is small (say 1.05Γ) and the value range is wide. In that case, the accepted-bid calculation reveals expected losses.
clawhub install bookforge-auction-bidding-strategist