nep-mst New Economics Papers
on Market Microstructure
Issue of 2019‒09‒16
three papers chosen by
Thanos Verousis

  1. Bayesian Inference on Volatility in the Presence of Infinite Jump Activity and Microstructure Noise By Qi Wang; Jos\'e E. Figueroa-L\'opez; Todd Kuffner
  2. Does sentiment harm market efficiency? An empirical analysis using a betting exchange setting By Oliver Merz; Raphael Flepp; Egon Franck
  3. Heterogeneous wealth distribution, round-trip trading and the emergence of volatility clustering in Speculation Game By Kei Katahira; Yu Chen

  1. By: Qi Wang; Jos\'e E. Figueroa-L\'opez; Todd Kuffner
    Abstract: Volatility estimation based on high-frequency data is key to accurately measure and control the risk of financial assets. A L\'{e}vy process with infinite jump activity and microstructure noise is considered one of the simplest, yet accurate enough, models for financial data at high-frequency. Utilizing this model, we propose a "purposely misspecified" posterior of the volatility obtained by ignoring the jump-component of the process. The misspecified posterior is further corrected by a simple estimate of the location shift and re-scaling of the log likelihood. Our main result establishes a Bernstein-von Mises (BvM) theorem, which states that the proposed adjusted posterior is asymptotically Gaussian, centered at a consistent estimator, and with variance equal to the inverse of the Fisher information. In the absence of microstructure noise, our approach can be extended to inferences of the integrated variance of a general It\^o semimartingale. Simulations are provided to demonstrate the accuracy of the resulting credible intervals, and the frequentist properties of the approximate Bayesian inference based on the adjusted posterior.
    Date: 2019–09
  2. By: Oliver Merz (Department of Business Administration, University of Zurich); Raphael Flepp (Department of Business Administration, University of Zurich); Egon Franck (Department of Business Administration, University of Zurich)
    Abstract: This paper investigates whether the sentimental preferences of investors influence market efficiency. We use a betting exchange market environment to analyze the influence of sentimental bettors on market efficiency in 2,333 soccer matches played between 2006-2014 during the last three hours of the pre-play period. Contrary to bookmaker markets, there is no intermediary in a betting exchange and, thus, the market prices solely reflect the beliefs of person to person betting. We use three different proxy variables to measure the bettor sentiment and find that price changes are more likely to be inefficient for betting events that are more prone to sentiment. Based on that finding, we propose a trading strategy that generates positive returns before considering the transaction costs and commission fees. Although the returns turn negative after considering the transaction costs and commission fees, the proposed trading strategy still outperforms a random betting strategy.
    Keywords: Sentiment bias, Market efficiency, Forecasting, Betting markets, Soccer
    JEL: D40 L83
    Date: 2019–08
  3. By: Kei Katahira; Yu Chen
    Abstract: This study is a detailed analysis of Speculation Game, a minimal agent-based model of financial markets, in which the round-trip trading and the dynamic wealth evolution with variable trading volumes are implemented. Instead of herding behavior, we find that the emergence of volatility clustering can be induced by the heterogeneous wealth distribution among traders. In particular, the spontaneous redistribution of market wealth through repetitions of round-trip trades can widen the wealth disparity and establish the Pareto distribution of the capital size. In the meantime, large fluctuations in price return are brought on by the intermittent placements of the relatively big orders from rich traders. Empirical data are used to support the scenario derived from the model.
    Date: 2019–09

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