nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒12‒10
four papers chosen by
Thanos Verousis

  1. Estimation of Ornstein-Uhlenbeck Process Using Ultra-High-Frequency Data with Application to Intraday Pairs Trading Strategy By Vladim\'ir Hol\'y; Petra Tomanov\'a
  2. Testing for Stationarity at High Frequency By Jiang, Bibo; Lu, Ye; Park, Joon Y.
  3. Twitter versus Traditional News Media: Evidence for the Sovereign Bond Markets By Costas Milas; Theodore Panagiotidis; Theologos Dergiades
  4. Understanding Regressions with Observations Collected at High Frequency over Long Span By Chang, Yoosoon; Lu, Ye; Park, Joon Y.

  1. By: Vladim\'ir Hol\'y; Petra Tomanov\'a
    Abstract: When stock prices are observed at high frequencies, more information can be utilized in estimation of parameters of the price process. However, high-frequency data are contaminated by the market microstructure noise which causes significant bias in parameter estimation when not taken into account. We propose an estimator of the Ornstein-Uhlenbeck process based on the maximum likelihood which is robust to the noise and utilizes irregularly spaced data. We also show that the Ornstein-Uhlenbeck process contaminated by the independent Gaussian white noise and observed at discrete equidistant times follows an ARMA(1,1) process. To illustrate benefits of the proposed noise-robust approach, we analyze an intraday pairs trading strategy based on the mean-variance optimization. In an empirical study of 7 Big Oil companies, we show that the use of the proposed estimator of the Ornstein-Uhlenbeck process leads to an increase in profitability of the pairs trading strategy.
    Date: 2018–11
  2. By: Jiang, Bibo; Lu, Ye; Park, Joon Y.
    Abstract: The high frequency behavior of the KPSS test, which is most commonly used to test for stationarity, is analyzed in a continuous time framework. Our asymptotics show that the test has no discriminatory power at high frequency: It either always rejects stationarity or has no nontrivial power at high frequency. The test becomes valid at high frequency only when the bandwidth of its longrun variance estimate is chosen suitably in our framework. We also analyze the residual-based KPSS test for cointegration.
    Keywords: KPSS test; testing for stationarity; testing for cointegration; continuous time process; high frequency observation
    Date: 2018–07
  3. By: Costas Milas (Management School, University of Liverpool, UK; Rimini Centre for Economic Analysis); Theodore Panagiotidis (Department of Economics, University of Macedonia, Greece; Rimini Centre for Economic Analysis); Theologos Dergiades (Department of International and European Studies, University of Macedonia, Greece; School of Science and Technology, International Hellenic University, Greece)
    Abstract: This paper compares news in Twitter with traditional news outlets and then emphasizes their differential impact on Eurozone's sovereign bond market for a homogeneous news topic. We find a two-way information flow between Twitter's “Grexit” tweets and the respective mentions in traditional news outlets. The influence of Twitter on the traditional news is consistently more prolonged, especially in high-activity periods. We also assess the differential impact of the two news sources on sovereign spreads over and above the impact of economic/financial fundamentals, namely measures of default risk, liquidity risk and global financial risk. Our focus is on the borrowing costs of Eurozone's periphery; for comparison reasons, we also consider France as a core Eurozone country. The effect of Twitter on the Greek sovereign spread is positive and of higher magnitude than that of traditional news outlets. Weak contagion effects are recorded primarily for the case of Portugal and Ireland.
    Keywords: Grexit, Twitter, Traditional news outlets, Sovereign spreads
    JEL: C10 G01 G12
    Date: 2018–12
  4. By: Chang, Yoosoon; Lu, Ye; Park, Joon Y.
    Abstract: In this paper, we analyze regressions with observations collected at small time interval over long period of time. For the formal asymptotic analysis, we assume that samples are obtained from continuous time stochastic processes, and let the sampling interval δ shrink down to zero and the sample span T increase up to infinity. In this setup, we show that the standard Wald statistic diverges to infinity and the regression becomes spurious as long as δ → 0 sufficiently fast relative to T → ∞. Such a phenomenon is indeed what is frequently observed in practice for the type of regressions considered in the paper. In contrast, our asymptotic theory predicts that the spuriousness disappears if we use the robust version of the Wald test with an appropriate longrun variance estimate. This is supported, strongly and unambiguously, by our empirical illustration.
    Keywords: high frequency regression; spurious regression; continuous time model; asymptotics; longrun variance estimation
    Date: 2018–07

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