nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒02‒26
six papers chosen by
Thanos Verousis

  1. The Power of Trading Polarity: Evidence from China Stock Market Crash By Shan Lu; Jichang Zhao; Huiwen Wang
  2. Dynamical regularities of US equities opening and closing auctions By Damien Challet; Nikita Gourianov
  3. Judgement Day: algorithmic trading around the Swiss franc cap removal By Breedon, Francis; Chen, Louisa; Ranaldo, Angelo; Vause, Nicholas
  4. Estimating unknown arbitrage costs: evidence from a three-regime threshold vector error correction model By Kristyna Ters; Jörg Urban
  5. Discriminatory pricing of over-the-counter derivatives By Harald Hau; Peter Hoffmann; Sam Langfield; Yannick Timmer
  6. Show us your shorts! By Kahraman, Bige; Pachare, Salil

  1. By: Shan Lu; Jichang Zhao; Huiwen Wang
    Abstract: The imbalance of buying and selling functions profoundly in the formation of market trends, however, a fine-granularity investigation of the imbalance is still missing. This paper investigates a unique transaction dataset that enables us to inspect the imbalance of buying and selling on the man-times level at high frequency, what we call 'trading polarity', for a large cross-section of stocks from Shenzhen Stock Exchange. The trading polarity measures the market sentiment toward stocks from a view of very essence of trading desire. When using the polarity to examine market crash, we find that trading polarity successfully reflects the changing of market-level behavior in terms of its flipping times, depth, and length. We further investigate the relationship between polarity and return. At market-level, trading polarity is negatively correlated with returns, while at stock-level, this correlation changes according to market conditions, which becomes a good signal of market psychology transition. Also, the significant correlation disclosed by the market polarity and market emotion implies that our presented polarity, which essentially calculated in the context of high-frequency trading data, can real-timely reflect the sentiment of the market. The trading polarity indeed provides a new way to understand and foresee the market behavior.
    Date: 2018–02
  2. By: Damien Challet; Nikita Gourianov
    Abstract: We first investigate static properties of opening and closing auctions such as typical auction volume relative to daily volume and order value distributions. We then show that the indicative match price is strongly mean-reverting because the imbalance is, which we link to strategic behavior. Finally, we investigate how the final auction price reacts to order placement, especially conditional on imbalance improving or worsening events and find a large difference between the opening and closing auctions, emphasizing the role of liquidity and simultaneous trading in the pre-open or open-market order book.
    Date: 2018–02
  3. By: Breedon, Francis (School of Economics and Finance, Queen Mary University of London); Chen, Louisa (School of Business, Management and Economics, University of Sussex); Ranaldo, Angelo (Swiss Institute of Banking and Finance, University of St. Gallen); Vause, Nicholas (Bank of England)
    Abstract: A key issue raised by the rapid growth of computerised algorithmic trading is how it responds in extreme situations. Using data on foreign exchange orders and transactions that includes identification of algorithmic trading, we find that this type of trading contributed to the deterioration of market quality following the removal of the cap on the Swiss franc on 15 January 2015, which was an event that came as a complete surprise to market participants. In particular, we find that algorithmic traders withdrew liquidity and generated uninformative volatility in Swiss franc currency pairs, while human traders did the opposite. However, we find no evidence that algorithmic trading propagated these adverse effects on market quality to other currency pairs.
    Keywords: Swiss franc; algorithmic trading; liquidity; volatility; price discovery; arbitrage opportunities
    JEL: G14 G23
    Date: 2018–02–16
  4. By: Kristyna Ters; Jörg Urban
    Abstract: We present a methodology for estimating a 3-regime threshold vector error correction model (TVECM) with an unknown cointegrating vector based on a new dynamic grid evaluation. This model is particularly suited to estimating deviations from parity conditions such as unknown arbitrage costs in markets with a persistent non-zero basis between two similar financial market instruments traded in the spot and the derivative markets. Our proposed 3-regime TVECM can estimate the area where arbitrageurs have no incentives for trading. Only when the basis exceeds a critical threshold, where the potential gain from the basis trade exceeds the overall transaction costs, do we expect arbitrageurs to step in and carry out the respective trade. This leads to non-linear adjustment dynamics and regimes with different characteristics. The overall transaction costs for the basis trades can be inferred from the estimated no-arbitrage regime. Our methodology allows us to quantify overall transaction costs for an arbitrage trade in markets where trading costs are opaque or unknown, as in credit risk or index arbitrage trading. The key contributions of this paper are the further development of the 2-threshold VECM, together with the numerical evaluation of the model through numerous simulations to prove its robustness. We present two short applications of the model in arbitrage trades in the palladium market and index trading for the S&P 500.
    Keywords: transaction cost, arbitrage, basis, threshold, regime switch, intraday, nonlinear, non-stationary, error correction
    JEL: G12 G14 G15
    Date: 2018–01
  5. By: Harald Hau; Peter Hoffmann; Sam Langfield; Yannick Timmer
    Abstract: New regulatory data reveal extensive discriminatory pricing in the foreign exchange derivatives market, in which dealer-banks and their non-financial clients trade over-the-counter. After controlling for contract characteristics, dealer fixed effects, and market conditions, we find that the client at the 75th percentile of the spread distribution pays an average of 30 pips over the market mid-price, compared to competitive spreads of less than 2.5 pips paid by the bottom 25% of clients. Higher spreads are paid by less sophisticated clients. However, trades on multi-dealer request-for-quote platforms exhibit competitive spreads regardless of client sophistication, thereby eliminating discriminatory pricing. JEL Classification: G14, G18, D4
    Keywords: dealer spreads, information rents, RFQ platforms, corporate hedging
    Date: 2017–12
  6. By: Kahraman, Bige; Pachare, Salil
    Abstract: How does greater public disclosure of arbitrage activity and informed trading affect informational efficiency? To answer this, we exploit rule amendments in U.S. securities markets, which increased the frequency of public disclosure of short positions. Higher public disclosure can potentially improve or deteriorate informational efficiency. We find that with more frequent disclosure, short-sellers' information is incorporated into prices faster, improving informational efficiency. In support of the mechanism driving this result, we document significant market reactions to short interest announcements, suggesting investor learning, and furthermore, we find increases in short-selling activity and reductions in short-sellers' holding periods with the rule amendments.
    Keywords: ShortInterest;PublicDisclosure;InformationalEfficiency
    Date: 2018–01

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