nep-mst New Economics Papers
on Market Microstructure
Issue of 2020‒07‒27
four papers chosen by
Thanos Verousis

  1. The Evolution of Price Discovery in an Electronic Market By Alain P. Chaboud; Erik Hjalmarsson; Filip Zikes
  2. The Price of BitCoin: GARCH Evidence from High Frequency Data By d’Artis Kancs; Pavel Ciaian; Miroslava Rajcaniova
  3. Inside the Mind of a Stock Market Crash By Stefano Giglio; Matteo Maggiori; Johannes Stroebel; Stephen Utkus
  4. Randomized Double Auctions: Gains from Trade, Trader Roles, and Price Discovery By Katerina Sherstyuk; Krit Phankitnirundorn; Michael J. Roberts

  1. By: Alain P. Chaboud; Erik Hjalmarsson; Filip Zikes
    Abstract: We study the evolution of the price discovery process in the euro-dollar and dollar-yen currency pairs over a ten-year period on the EBS platform, a global trading venue used by both manual and automated traders. We find that the importance of market orders decreases sharply over that period, owing mainly to a decline in the information share from manual trading, while the information share of market orders from algorithmic and high-frequency traders remains fairly constant. At the same time, there is a substantial, but gradual, increase in the information share of limit orders. Price discovery also becomes faster, suggesting improvements in market efficiency. The results are consistent with theoretical predictions that in more efficient markets, informed traders tend to use more limit orders.
    Keywords: High-frequency trading; Limit orders; Price discovery
    JEL: G14 G15 F31
    Date: 2020–06–24
  2. By: d’Artis Kancs (European Commission - JRC); Pavel Ciaian (European Commission - JRC); Miroslava Rajcaniova (SAU, Department of Economic Policy)
    Abstract: This is the first paper that estimates the price determinants of BitCoin in a Generalised Autoregressive Conditional Heteroscedasticity framework using high frequency data. Derived from a theoretical model, we estimate BitCoin transaction demand and speculative demand equations in a GARCH framework using hourly data for the period 2013-2018. In line with the theoretical model, our empirical results confirm that both the BitCoin transaction demand and speculative demand have a statistically significant impact on the BitCoin price formation. The BitCoin price responds negatively to the BitCoin velocity, whereas positive shocks to the BitCoin stock, interest rate and the size of the BitCoin economy exercise an upward pressure on the BitCoin price.
    Keywords: Virtual currencies; BitCoin returns; volatility; price formation; GARCH; Digital Economy
    JEL: E31 E42 G12
    Date: 2019–02
  3. By: Stefano Giglio; Matteo Maggiori; Johannes Stroebel; Stephen Utkus
    Abstract: We analyze how investor expectations about economic growth and stock returns changed during the February-March 2020 stock market crash induced by the COVID-19 pandemic, as well as during the subsequent partial stock market recovery. We surveyed retail investors who are clients of Vanguard at three points in time: (i) on February 11-12, around the all-time stock market high, (ii) on March 11-12, after the stock market had collapsed by over 20%, and (iii) on April 16-17, after the market had rallied 25% from its lowest point. Following the crash, the average investor turned more pessimistic about the short-run performance of both the stock market and the real economy. Investors also perceived higher probabilities of both further extreme stock market declines and large declines in short-run real economic activity. In contrast, investor expectations about long-run (10-year) economic and stock market outcomes remained largely unchanged, and, if anything, improved. Disagreement among investors about economic and stock market outcomes also increased substantially following the stock market crash, with the disagreement persisting through the partial market recovery. Those respondents who were the most optimistic in February saw the largest decline in expectations, and sold the most equity. Those respondents who were the most pessimistic in February largely left their portfolios unchanged during and after the crash.
    Keywords: surveys, expectations, sentiment, behavioural finance, trading, rare disasters
    JEL: G11 G12 R30
    Date: 2020
  4. By: Katerina Sherstyuk (University of Hawaii at Manoa, Department of Economics); Krit Phankitnirundorn (University of Hawaii at Manoa, Department of Economics); Michael J. Roberts (University of Hawaii at Manoa, Department of Economics)
    Abstract: Experimental double-auction commodity markets are known to exhibit robust convergence to competitive equilibria under stable or cyclical supply and demand conditions, but little is known about their performance in truly random environments. We provide a comprehensive study of double auctions in a stochastic setting where the equilibrium prices, trading volumes and gains from trade are highly variable across periods, and with commodity traders who may buy or sell their goods depending on market conditions and their individual outcomes. We find that performance in this stochastic environment is sensitive to underlying market conditions. Efficiency is higher and convergence to the competitive equilibrium stronger when the potential gains from trade are high and when the equilibrium spans a wide range of quantities, implying a large number of marginal trades. Speculative re-trading is prevalent, especially for individual traders who have little to gain under equilibrium pricing, leading to some redistribution of gains from high to low expected earners. Those with the largest expected gains typically earn far less than predicted, while those with little or no predicted earnings gain modestly from speculation. Excessive trading volumes are associated with negative efficiencies in markets with low gains from trade, but not in the high-gains markets, where zero-sum trading and re-trading appear not to obstruct and possibly enforce efficiency and near-equilibrium pricing. Buyers earn more relative to their competitive equilibrium benchmark than sellers do. Introducing trader specialization leads to fewer trading errors and higher market efficiency, but it does not eliminate zero-sum trading and re trading.
    Keywords: economic experiments; double auction markets; gains from trade; speculation
    JEL: C92 D02 D41
    Date: 2020–07

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