Are Asian exchanges outliers? A market quality criterion

  • 713 Views
  • 272 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

This paper provides a practical, empirical and theoretical framework that allows investment managers to evaluate stock exchanges’ market quality when choosing among different plausible international trading venues. To compare trading exchanges, it extends the hypothesis of market microstructure invariance to trading across exchanges. A measure ω, the ratio of the market-wide volatility to microstructure invariance, is introduced. The paper computes ω for the exchanges around the world. Its value for the NSE (India) is 24.5%, the Korea Exchange (Korea) is 7.9%, the Shanghai Exchange (China) is 3.5%, and the Shenzhen Exchange (China) is 4.4%, which is significantly different from that of major exchanges in the USA (NYSE – 0.8%, NASDAQ – 1.3%) and Europe (LSE (UK) – 0.4). This country risk dimension clearly identifies which equity exchanges cannot hold their own direct correlational hedges and therefore mandatorily require derivative positions, and has significant implications for the decision making of global long-short equity asset allocators in the Asian listed equity markets.

view full abstract hide full abstract
    • Figure 1. Trends in in 2004–2018
    • Figure 2. Platform growth: Number of companies listed on the exchanges from 2004 to 2018
    • Table 1. Quartile statistics for the turnover-per-trade (2018)*
    • Table 2. 2018 values for (sqrt (trades per day)) upon (turnover per trade)
    • Table 3. Trends in from 2004 to 2018 in emerging Asian stock exchanges (in percent)
    • Table 4. Derivative business (2018)
    • Table 5. Number of shares of representative stocks on the NYSE and NSE large cap index traded in a representative trade
    • Table A1. Data sample for the year 2018
    • Table A2. Daily turnover-per-trade with 2004 as the base year (normalized to 1)
    • Conceptualization
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Data curation
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Formal Analysis
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Investigation
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Methodology
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Resources
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Software
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Validation
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Visualization
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Writing – original draft
      Ranjan R. Chakravarty, Sudhanshu Pani
    • Writing – review & editing
      Ranjan R. Chakravarty, Sudhanshu Pani