New Economics Papers
on Market Microstructure
Issue of 2013‒08‒10
three papers chosen by
Thanos Verousis

  1. Unveiling correlations between financial variables and topological metrics of trading networks: Evidence from a stock and its warrant By Ming-Xia Li; Zhi-Qiang Jiang; Wen-Jie Xie; Xiong Xiong; Wei Zhang; Wei-Xing Zhou
  2. The Liquidity Coverage Ratio: the need for further complementary ratios? By Ojo, Marianne
  3. Financial AnalystsÕ Forecast Accuracy: Do valuation methods matter? By Elisa Cavezzali; Ugo Rigoni

  1. By: Ming-Xia Li (ECUST); Zhi-Qiang Jiang (ECUST); Wen-Jie Xie (ECUST); Xiong Xiong (TJU); Wei Zhang (TJU); Wei-Xing Zhou (ECUST)
    Abstract: Traders adopt different trading strategies to maximize their returns in financial markets. These trading strategies not only results in specific topological structures in trading networks, which connect the traders with the pairwise buy-sell relationships, but also have potential impacts on market dynamics. Here, we present a detailed analysis on how the market behaviors are correlated with the structures of traders in trading networks based on audit trail data for the Baosteel stock and its warrant at the transaction level from 22 August 2005 to 23 August 2006. In our investigation, we divide each trade day into 48 time windows with a length of five minutes, construct a trading network within each window, and obtain a time series of over 1,100 trading networks. We find that there are strongly simultaneous correlations between the topological metrics (including network centralization, assortative index, and average path length) of trading networks that characterize the patterns of order execution and the financial variables (including return, volatility, intertrade duration, and trading volume) for the stock and its warrant. Our analysis may shed new lights on how the microscopic interactions between elements within complex system affect the system's performance.
    Date: 2013–08
  2. By: Ojo, Marianne
    Abstract: This paper considers components of the Liquidity Coverage Ratio – as well as certain prevailing gaps which may necessitate the introduction of a complementary liquidity ratio. The definitions and objectives accorded to the Liquidity Coverage Ratio (LCR) and Net Stable Funding Ratio (NSFR) highlight the focus which is accorded to time horizons for funding bank operations. A ratio which would focus on the rate of liquidity transformations and which could also serve as a complementary metric given certain gaps which currently prevail with the Liquidity Coverage Ratio, as well as existing gaps with other complementary liquidity monitoring tools, is proposed.
    Keywords: Liquidity Coverage Ratio (LCR); Net Stable Funding Ratio (NSFR); High Quality Liquid Assets (HQLA); liquidity monitoring tools; objectivity; comparability; transparency; disclosure
    JEL: E0 E02 G2 G3 K2
    Date: 2013–08–04
  3. By: Elisa Cavezzali (Università Ca' Foscari Venice); Ugo Rigoni (Università Ca' Foscari Venice)
    Abstract: This study investigates how different ways to evaluate a company influence the accuracy of the target price. We know that finance theory and professional practice propose alternative approaches to the evaluation of a company. The literature on the relationship between the valuation methods used and target price accuracy is still scant, and the results are inconclusive and contradictory. Coding the valuation methods of 1,650 reports, we find that the accuracy of target prices decreases when the target price is based just on a main method. Furthermore, we show that methods based on company fundamentals and those based on market multiples lead to similar levels of accuracy. Among different classes of methods, there are no superior methods. Therefore, we argue that in order to improve forecast accuracy, analysts need to assess company value by choosing and applying a set of different methods, combining them and getting the average value, but regardless of the specific technique chosen.
    Keywords: forecast accuracy, sell-side analysts, equity valuation, valuation methods
    JEL: M40 M41
    Date: 2013–08

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