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abf99d05fc
Restructured from flat .tex/.pdf files into per-paper subdirectories. Added Antje Worring as co-author on all papers. Synced PDFs to pdfs/ for download site.
81 lines
1.9 KiB
TeX
81 lines
1.9 KiB
TeX
\section{Marketplace Features}
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\subsection{Collection Listings}
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Collection pages provide per-collection analytics:
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\begin{itemize}
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\item Floor price tracking with 24h/7d/30d changes
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\item Volume metrics and liquidity depth
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\item Holder distribution and unique owner count
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\item Trait rarity analysis and price correlations
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\item Activity feed with real-time updates
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\end{itemize}
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\subsection{Bidding System}
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The bidding mechanism supports multiple order types:
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\begin{algorithm}
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\caption{Bid Matching Algorithm}
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\begin{algorithmic}
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\STATE \textbf{Input:} Bid $B$, Asks $A$
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\STATE \textbf{Output:} Matched order or null
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\STATE
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\IF{$B.type = \text{Collection}$}
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\STATE $A_{eligible} \leftarrow$ FilterByCollection$(A, B.collection)$
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\ELSIF{$B.type = \text{Token}$}
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\STATE $A_{eligible} \leftarrow$ FilterByToken$(A, B.tokenId)$
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\ELSIF{$B.type = \text{Trait}$}
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\STATE $A_{eligible} \leftarrow$ FilterByTrait$(A, B.traits)$
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\ENDIF
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\STATE
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\FOR{each ask $a \in A_{eligible}$}
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\IF{$B.price \geq a.price$}
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\RETURN Match$(B, a)$
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\ENDIF
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\ENDFOR
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\RETURN null
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\end{algorithmic}
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\end{algorithm}
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\subsection{Dutch Auctions}
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Dutch auction implementation follows a linear decay model:
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\begin{equation}
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P(t) = P_{start} - \frac{P_{start} - P_{end}}{T_{duration}} \cdot t
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\end{equation}
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where $P(t)$ is the price at time $t$, bounded by:
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\begin{equation}
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P_{end} \leq P(t) \leq P_{start}, \quad 0 \leq t \leq T_{duration}
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\end{equation}
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\subsection{Bundle Sales}
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Bundle pricing optimization:
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\begin{equation}
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P_{bundle} = \sum_{i=1}^{n} P_i \cdot (1 - \delta_{bundle})
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\end{equation}
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where $\delta_{bundle}$ is the bundle discount factor, typically:
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\begin{equation}
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\delta_{bundle} = \min(0.1 \cdot \log(n), 0.25)
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\end{equation}
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\subsection{Rarity Ranking}
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Rarity scores are calculated using statistical rarity:
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\begin{equation}
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R_{token} = \sum_{t \in traits} \frac{1}{f_t}
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\end{equation}
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where $f_t$ is the frequency of trait $t$ in the collection.
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