nep-mst New Economics Papers
on Market Microstructure
Issue of 2016‒03‒29
five papers chosen by
Thanos Verousis


  1. Cross-response in correlated financial markets: individual stocks By Shanshan Wang; Rudi Sch\"afer; Thomas Guhr
  2. Real-time forecasting with a MIDAS VAR By Mikosch, Heiner; Neuwirth, Stefan
  3. Disentangled jump-robust realized covariances and correlations with non-synchronous prices By Vander Elst, Harry; Veredas, David
  4. Estimating the money market microstructure with negative and zero interest rates By Edoardo Rainone; Francesco Vacirca
  5. Overconfident Investors, Predictable Returns, and Excessive Trading By Kent Daniel; David Hirshleifer

  1. By: Shanshan Wang; Rudi Sch\"afer; Thomas Guhr
    Abstract: Previous studies of the stock price response to trades focused on the dynamics of single stocks, i.e. they addressed the self-response. We empirically investigate the price response of one stock to the trades of other stocks in a correlated market, i.e. the cross-responses. How large is the impact of one stock on others and vice versa? -- This impact of trades on the price change across stocks appears to be transient instead of permanent as we discuss from the viewpoint of market efficiency. Furthermore, we compare the self-responses on different scales and the self- and cross-responses on the same scale. We also find that the cross-correlation of the trade signs turns out to be a short-memory process.
    Date: 2016–03
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1603.01580&r=mst
  2. By: Mikosch, Heiner; Neuwirth, Stefan
    Abstract: This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon lag polynomial scheme which is designed to reduce the parameter space while keeping models fexible. We show how to recast the resulting non-linear MIDAS type mixed frequency VAR into a linear equation system that can be easily estimated. A pseudo out-of-sample forecasting exercise with US real-time data yields that the mixed frequency VAR substantially improves predictive accuracy upon a standard VAR for dierent VAR specications. Forecast errors for, e.g., GDP growth decrease by 30 to 60 percent for forecast horizons up to six months and by around 20 percent for a forecast horizon of one year.
    Keywords: Forecasting, mixed frequency data, MIDAS, VAR, real time
    JEL: C53 E27
    Date: 2015–04–13
    URL: http://d.repec.org/n?u=RePEc:bof:bofitp:urn:nbn:fi:bof-201504131156&r=mst
  3. By: Vander Elst, Harry; Veredas, David
    Abstract: We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyse – in a through Monte Carlo study – different combinations of quantile-and-median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes and in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that pre-averaged disentangled estimators provide a precise, computationally efficient and easy alternative to measure integrated covariances on basis of noisy and asynchronous prices. Moreover, the gain is not only statistical but also financial. A minimum variance portfolio application shows the superiority of the disentangled realized estimators in terms of numerous performance metrics.
    Keywords: Syncrhonization; Jumps; Noise; Realized measures
    Date: 2014–09–08
    URL: http://d.repec.org/n?u=RePEc:cte:wsrepe:ws142416&r=mst
  4. By: Edoardo Rainone (Bank of Italy); Francesco Vacirca (ECB and Bank of Italy)
    Abstract: Money market microstructure is fundamental to studying bank behaviour, to evaluating monetary policy and to assessing the financial stability of the system. Given the lack of granular data on interbank loans, Furfine (1999) proposed an algorithm to estimate the microstructure using data from the payment system. We propose an econometric methodology to assess and improve the quality of the money market microstructure estimated by the Furfine algorithm in the presence of zero and negative rates, exploiting information coming from market regularities. We first extend the standard Furfine algorithm to include negative rates and verify the presence of significant noise at a specific rate. Secondly, we propose an inferential procedure that enriches and corrects the standard algorithm based on the economic likelihood of loans. Market regularities observed in this decentralized market are used to increase the reliability of the estimated interbank network. Thirdly, the methodology is applied to TARGET2, the European wholesale payment system. The main impacts of recent monetary policy decisions on key interest rates are studied, comparing the standard algorithm with the new econometric procedure.
    Keywords: interbank markets, money, payment systems, trading networks, measurement error
    JEL: E52 E40 C21 G21 D40
    Date: 2016–02
    URL: http://d.repec.org/n?u=RePEc:bdi:wptemi:td_1059_16&r=mst
  5. By: Kent Daniel; David Hirshleifer
    Abstract: Individuals and asset managers trade aggressively, resulting in high volume in asset markets, even when such trading results in high risk and low net returns. Asset prices display patterns of predictability that are difficult to reconcile with rational expectations–based theories of price formation. This paper discusses how investor overconfidence can explain these and other stylized facts. We review the evidence from psychology and securities markets bearing upon overconfidence effects, and present a set of overconfidence based models that are consistent with this evidence.
    JEL: G02 G11 G12 G14 G2
    Date: 2016–01
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:21945&r=mst

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