nep-mst New Economics Papers
on Market Microstructure
Issue of 2019‒12‒02
four papers chosen by
Thanos Verousis

  1. The Role of Daytime Stock Auctions in Intraday Return Seasonality By Ekaterina Serikova
  2. Judgment Day: Algorithmic Trading Around The Swiss Franc Cap Removal By Francis Breedon; Louisa Chen; Angelo Ranaldo; Nicholas Vause
  3. OTC discount By de Roure, Calebe; Mönch, Emanuel; Pelizzon, Loriana; Schneider, Michael
  4. Disagreement and Liquidity By Kruger, Samuel

  1. By: Ekaterina Serikova
    Abstract: The paper provides a fresh look at the role of daytime auctions in intraday periodicity of stock returns. First, I show that daytime auctions, together with market opening and market closing intervals, drive the periodicity of stock returns. Second, by applying the model of infrequent rebalancing, I find that price impact is the highest during the fifteen-minute interval after daytime auctions. Combining this evidence with high realized returns, high volume changes and high return volatility, I conclude that after-auction periods take over a large share of infrequent rebalancing, being attractive for a concentration of liquidity traders. Small, low-fragmented stocks heavily traded on the home market show the strongest evidence for infrequent rebalancing after the daytime auctions. Finally, I show that post-auction returns predict returns before the US market opening and before the domestic market closing, which might be further evidence on clustered liquidity trading.
    Keywords: Market microstructure, market design, auctions, intraday periodicity
    Date: 2019–07
  2. By: Francis Breedon; Louisa Chen; Angelo Ranaldo; Nicholas Vause
    Abstract: A key issue raised by the growth of algorithmic trading (AT) is how it responds in extreme situations. Using data on foreign exchange (FX) with a precise identification of AT, we find that AT contributed to the deterioration of market quality following the removal of the cap on the Swiss franc on 15 January 2015. Algorithmic traders withdrew market liquidity and generated uninformative volatility, both outside and during periods of perceived central bank intervention. We find that agency algorithms run by banks—rather than proprietary algorithms run by high-frequency traders—were particularly detrimental for market quality.
    Keywords: Algorithmic trading, Swiss franc, market liquidity, price efficiency, central bank intervention.
    JEL: G14 G23
    Date: 2019–07
  3. By: de Roure, Calebe; Mönch, Emanuel; Pelizzon, Loriana; Schneider, Michael
    Abstract: We study price dispersion and venue choice in the interdealer market for German sovereign bonds, where an exchange and over-the-counter segments coexist. We show that 85% of OTC traded prices are favorable with respect to exchange quotes, indicating the prevalence of an OTC discount. This discount is sizeable and driven by both search and information frictions. More than 75% of volume is transacted via interdealer brokers in trades that are larger, have less price impact, and less discount than comparable bilateral OTC trades. Dealers trade on the exchange for immediacy, highlighting the complementary roles played by the different segments.
    Keywords: Market Microstructure,Hybrid Markets,Venue Choice,Interdealer Brokerage,Fixed-Income,OTC Markets,Intermediation Frictions,Search Frictions,Information Frictions
    JEL: D4 D47 G1 G14 G24
    Date: 2019
  4. By: Kruger, Samuel
    Abstract: Disagreement is an increasingly popular explanation for trade of informationally sensitive securities. Yet, there is limited research on the relation between disagreement and liquidity, particularly regarding how disagreement affects private information's impact on trading and liquidity. This paper proposes a model in which trading is entirely generated by disagreement stemming from overconfident interpretation of private signals. Contrary to traditional intuition, the model predicts that private information increases trading and enhances liquidity. A more general version of the model incorporates both disagreement and liquidity trading. The general model relates traditional intuition about private information destroying liquidity and trade to disagreement trading. The relation between private information and liquidity is not monotonic. Private information at first decreases liquidity but then enhances it, potentially explaining why private information seems to destroy liquidity in money markets but not in markets that are more informationally sensitive to start with.
    Date: 2018–12–19

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