Research Publications - Working Papers
This page lists working papers on blockchain systems, market microstructure, decentralized finance (DeFi), and cryptocurrency exchange dynamics. All papers are published on Zenodo and available for download.
Publications
1. Price Discovery Dynamics Between Decentralized and Centralized Cryptocurrency Exchanges: An Empirical Analysis of Lead-Lag Relationships and Market Efficiency
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Abstract: This paper presents a comprehensive empirical analysis of price discovery dynamics between decentralized exchanges (DEXs) and centralized exchanges (CEXs) in cryptocurrency markets. Using 1-minute OHLC data from September 4-5, 2025, I analyze 5,000 DEX data points and 3,670 CEX data points across Bitcoin (BTC), Ethereum (ETH), and Solana (SOL) from Binance, Coinbase, and multiple DEX protocols via Bitquery's Crypto Price API.
The analysis reveals remarkably strong price correlations (0.98-0.99) and exceptionally low mean absolute percentage deviations (0.06-0.08%) between DEX and CEX markets, indicating highly efficient price transmission. Lead-lag analysis shows mixed patterns: Bitcoin demonstrates CEX leadership with 5-minute leads across both exchanges, while Ethereum and Solana exhibit DEX leadership, with Solana showing particularly strong DEX dominance (40-minute lead with Binance).
Volume analysis reveals significant disparities, with Binance showing 1.71x higher volume for Bitcoin but comparable or lower ratios for ETH (0.78x) and SOL (0.51x). These findings challenge traditional assumptions about CEX primacy in price discovery, particularly for newer tokens, and suggest that DEXs are becoming increasingly important for price formation in the evolving cryptocurrency market structure.
The research provides quantitative evidence for the growing role of decentralized exchanges in cryptocurrency price discovery and has implications for arbitrage strategies, market surveillance, and regulatory frameworks.
2. Can We Build a Memecoin Index? Building a Financial Index for Internet Jokes with a 10000x ROI
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Abstract: This paper presents a comprehensive analysis of constructing and commercializing a memecoin index, examining two distinct methodologies: volume-weighted and volatility-weighted approaches. Using real trading data from the Solana blockchain via Bitquery API, I analyze 100 memecoins across multiple timeframes (2-week to 1-year) to assess the commercial viability of listing such an index.
Critically, the Return on Investment (ROI) analysis reveals fundamental limitations of historical performance metrics in memecoin markets: only 16-25% of tokens achieve positive returns while 75-84% experience complete loss (-100% ROI). Volume-weighted ROI calculations reveal negative returns (-84.59% to -96.49%), demonstrating the true market impact and unreliability of past performance for future investment decisions.
Will any hedge fund manager be reading about $PIGOS, "snazzy cat" or "Baby MAGA" and thinking "yes, this belongs in my diversified portfolio"? I conclude that while technically feasible, memecoin indexes face significant operational challenges due to their extreme volatility, rapid constituent turnover, and fundamentally unreliable ROI metrics, which make them unsuitable for traditional index products and require specialized risk management approaches that acknowledge their speculative nature.
3. Can On-Chain Liquidity Data Explain Provider Behavior in Uniswap V3?
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Abstract: This article uses on-chain liquidity position data in Uniswap V3 to explain liquidity provider (LP) behavior. Using data extracted from the NonfungiblePositionManager contract, we analyze mint and burn events to characterize how LPs allocate and adjust capital across price ranges, fee tiers, and time.
By modeling how liquidity providers historically adjust positions around market prices and volatility, this methodology aims to provide a framework for using position data as potential indicators of market dynamics. The proposed method can be applied both to historical datasets and real-time data streams to monitor liquidity position ranges, and the players in the AMM space.
4. Deterministic Band Analysis for LPs: Identifying High-Opportunity Price Ranges in Uniswap V3
Abstract: Uniswap V3 introduced concentrated liquidity, allowing liquidity providers (LPs) to allocate capital within specific price ranges rather than across the entire price curve. This increases capital efficiency but introduces new strategic challenges: LPs must determine optimal price bands that balance potential fee earnings, competition levels, and risk exposure.
The liquidity landscape in Uniswap V3 pools is dynamic and complex. Multiple positions may overlap at various price levels, creating areas of high competition where fee earnings are diluted. Conversely, gaps in liquidity often present attractive opportunities for LPs, since fewer competing positions can translate into higher fee capture.
Yet it is still unclear how market makers should decide where to concentrate their capital. Should they allocate liquidity to price levels with consistently high trading volume, or to underpopulated regions where they face less competition?
This work presents a reproducible, deterministic pipeline that combines on-chain data collection, bin-based liquidity analysis, and companion dashboards; it should be viewed as a work-in-progress report rather than a finished product.