Chapter 10 Further Reading

Foundational Academic Papers

Market Microstructure Theory

  1. Glosten, L. R., & Milgrom, P. R. (1985). "Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders." Journal of Financial Economics, 14(1), 71-100. - The foundational model of how bid-ask spreads arise from adverse selection. Essential reading for understanding why spreads exist. The model directly applies to prediction markets where informed traders are common.

  2. Kyle, A. S. (1985). "Continuous Auctions and Insider Trading." Econometrica, 53(6), 1315-1335. - Introduces the concept of market depth and the lambda parameter (price impact per unit of order flow). Complements Glosten-Milgrom by modeling a strategic informed trader rather than competitive market makers.

  3. Stoll, H. R. (1978). "The Supply of Dealer Services in Securities Markets." Journal of Finance, 33(4), 1133-1151. - Early decomposition of the spread into adverse selection, inventory holding cost, and order processing cost components. Provides the theoretical basis for the three-part decomposition discussed in Section 10.1.

  4. Huang, R. D., & Stoll, H. R. (1997). "The Components of the Bid-Ask Spread: A General Approach." Review of Financial Studies, 10(4), 995-1034. - Empirical methodology for decomposing spreads into their components. The techniques can be adapted for prediction market data.

Market Impact and Execution

  1. Almgren, R., & Chriss, N. (2001). "Optimal Execution of Portfolio Transactions." Journal of Risk, 3, 5-40. - The definitive framework for optimal execution that balances market impact against price risk. The Almgren-Chriss model is the basis for the execution strategies discussed in Section 10.6.

  2. Bouchaud, J. P. (2010). "Price Impact." Encyclopedia of Quantitative Finance. - Comprehensive survey of price impact models, including the square-root law. Accessible overview of why impact scales sub-linearly with order size.

  3. Gatheral, J. (2010). "No-Dynamic-Arbitrage and Market Impact." Quantitative Finance, 10(7), 749-759. - Theoretical constraints on market impact functions. Shows that the square-root law arises naturally from no-arbitrage conditions.

Prediction Market-Specific Research

  1. Manski, C. F. (2006). "Interpreting the Predictions of Prediction Markets." Economics Letters, 91(3), 425-429. - Discusses how to interpret prediction market prices as probabilities, including the role of transaction costs and the overround in distorting prices away from true probabilities.

  2. Wolfers, J., & Zitzewitz, E. (2004). "Prediction Markets." Journal of Economic Perspectives, 18(2), 107-126. - Comprehensive overview of prediction markets, including discussion of market microstructure issues like spreads and fees that affect price accuracy.

  3. Arrow, K. J., Forsythe, R., Gorham, M., Hahn, R., Hanson, R., Ledyard, J. O., ... & Neumann, G. R. (2008). "The Promise of Prediction Markets." Science, 320(5878), 877-878.

    • Influential short paper arguing for the value of prediction markets, with acknowledgment of transaction cost barriers.

  4. Berg, J. E., Nelson, F. D., & Rietz, T. A. (2008). "Prediction Market Accuracy in the Long Run." International Journal of Forecasting, 24(2), 285-300.

    • Analysis of Iowa Electronic Markets accuracy, including how transaction costs and fee structures affect market efficiency.

  5. Rothschild, D. (2009). "Forecasting Elections: Comparing Prediction Markets, Polls, and Their Biases." Public Opinion Quarterly, 73(5), 895-916.

    • Empirical analysis of prediction market accuracy that accounts for bid-ask spreads and overround in interpreting market prices.

Transaction Costs in Practice

  1. Harris, L. (2003). Trading and Exchanges: Market Microstructure for Practitioners. Oxford University Press.

    • The definitive practitioner-oriented textbook on market microstructure. Covers spreads, market impact, execution strategies, and market maker economics in exhaustive detail. Highly recommended as a companion to this chapter.

  2. Hasbrouck, J. (2007). Empirical Market Microstructure. Oxford University Press.

    • More technical and econometric approach to measuring transaction costs, spread decomposition, and market quality. Good for readers who want to do their own empirical analysis.

  3. Kissell, R. (2013). The Science of Algorithmic Trading and Portfolio Management. Academic Press.

    • Comprehensive treatment of execution algorithms, market impact models, and transaction cost analysis from a practitioner's perspective.

Fee Structure Design and Market Design

  1. Budish, E., Cramton, P., & Shim, J. (2015). "The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response." Quarterly Journal of Economics, 130(4), 1547-1621.

    • Innovative analysis of how market structure and fee design affect trading costs and market quality. Relevant to understanding how prediction market platforms could improve their design.

  2. Malinova, K., & Park, A. (2015). "Subsidizing Liquidity: The Impact of Make/Take Fees on Market Quality." Journal of Finance, 70(2), 509-536.

    • Empirical analysis of how maker-taker fee structures affect spreads, volume, and market quality. Directly relevant to the fee design analysis in Case Study 2.

  3. Colliard, J. E., & Foucault, T. (2012). "Trading Fees and Efficiency in Limit Order Markets." Review of Financial Studies, 25(11), 3389-3421.

    • Theoretical analysis of how trading fees affect market efficiency. Shows that fee structure matters as much as fee level.

Blockchain and DeFi Transaction Costs

  1. Capponi, A., & Jia, R. (2021). "The Adoption of Blockchain-Based Decentralized Exchanges." Available at SSRN.

    • Analysis of transaction costs on decentralized exchanges, including gas fees, MEV (Miner Extractable Value), and AMM-specific costs. Relevant to understanding Polymarket's cost structure.

  2. Daian, P., Goldfeder, S., Kell, T., Li, Y., Zhao, X., Bentov, I., ... & Juels, A. (2020). "Flash Boys 2.0: Frontrunning in Decentralized Exchanges, Miner Extractable Value, and Consensus Instability." IEEE Symposium on Security and Privacy.

    • Exposes hidden transaction costs in blockchain-based markets, including frontrunning and sandwich attacks. Important for understanding the full cost of trading on platforms like Polymarket.

Overround and Probability Extraction

  1. Shin, H. S. (1993). "Measuring the Incidence of Insider Trading in a Market for State-Contingent Claims." Economic Journal, 103(420), 1141-1153.

    • The Shin method for removing overround from betting/prediction market prices. Provides a more sophisticated alternative to proportional normalization, accounting for informed trading.

  2. Clarke, S. R., & Norman, J. M. (1995). "Home Ground Advantage of Individual Clubs in English Soccer." The Statistician, 44(4), 509-521.

    • While focused on sports, this paper discusses methods for extracting true probabilities from betting odds, including handling the overround.

Online Resources and Data

  1. Polymarket Documentation — https://docs.polymarket.com/

    • Official documentation for Polymarket's API and fee structure. Essential for traders building automated systems on the platform.

  2. Kalshi Documentation — https://kalshi.com/docs/

    • Kalshi's official API documentation and fee schedule.

  3. Metaculus — https://www.metaculus.com/

    • While not a trading market, Metaculus provides well-calibrated probability forecasts that can serve as a reference for evaluating prediction market prices and overround.

For readers new to market microstructure: 1. Start with Harris (2003) — Trading and Exchanges for the practitioner foundation 2. Read Glosten & Milgrom (1985) for the theoretical basis of spreads 3. Review Almgren & Chriss (2001) for execution strategy 4. Then explore the prediction market-specific papers

For readers with market microstructure background: 1. Start with the prediction market papers (Manski, Wolfers & Zitzewitz) 2. Review blockchain-specific costs (Capponi & Jia, Daian et al.) 3. Study the overround literature (Shin) for probability extraction techniques