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on Market Microstructure |
| By: | Yutong Lu; Gesine Reinert; Mihai Cucuringu |
| Abstract: | The time proximity of high-frequency trades can contain a salient signal. In this paper, we propose a method to classify every trade, based on its proximity with other trades in the market within a short period of time, into five types. By means of a suitably defined normalized order imbalance associated to each type of trade, which we denote as conditional order imbalance (COI), we investigate the price impact of the decomposed trade flows. Our empirical findings indicate strong positive correlations between contemporaneous returns and COIs. In terms of predictability, we document that associations with future returns are positive for COIs of trades which are isolated from trades of stocks other than themselves, and negative otherwise. Furthermore, trading strategies which we develop using COIs achieve conspicuous returns and Sharpe ratios, in an extensive experimental setup on a universe of 457 stocks using daily data for a period of three years. |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2209.10334&r= |
| By: | Terrence Hendershott (University of California, Berkeley - Haas School of Business); Dan Li (Board of Governors of the Federal Reserve System); Dmitry Livdan (University of California, Berkeley); Norman Schürhoff (Swiss Finance Institute - HEC Lausanne); Kumar Venkataraman (Southern Methodist University (SMU) - Finance Department) |
| Abstract: | Using data on indicative quotes dealers provide to clients, we establish empirical relationships regarding quote competition in the corporate bond market. Market-wide higher quoting activity is associated with greater trading volume and lower trading costs. At the dealer level, quoting dealers attract order flow with more and better quotes attracting more volume. These effects are larger when uncertainty is higher in terms of lower credit ratings and higher volatility, including the onset of Covid-19. Quote competition for order flow is associated with improved execution as clients receive better prices when more dealers quote and when clients trade with better quoting dealers. Our results are consistent with quote competition playing an important role in corporate bond trading. |
| Keywords: | Pretrade transparency, quotes, corporate bonds, OTC markets, order flow competition |
| JEL: | G12 G14 G24 |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp2270&r= |
| By: | Aldo Barrios; Rob Franolic; Davide Giovanardi; Michael Melvin |
| Abstract: | FX trade settlement data from CLS provides the most comprehensive view of the opaque market of OTC currency trades. We use the flows of investment funds and non-financial corporates and develop trading signals where the former reflects speculative strategies, while the latter trade for liquidity needs. The implication is we trade in the direction of the funds flows and trade against large corporate flows, which should be followed by price reversals. Trading with informed flows yields positive risk-adjusted performance. Incorporating the liquidity trades signal improves risk-adjusted performance and greatly lowers the tail risk of the model. |
| Keywords: | foreign exchange, currency flows, informed trading, currency investing |
| JEL: | F31 G15 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9921&r= |
| By: | Rainer Haselmann; Christian Leuz; Sebastian Schreiber |
| Abstract: | This study analyzes information production and trading behavior of banks with lending relationships. We combine trade-by-trade supervisory data and credit-registry data to examine banks' proprietary trading in borrower stocks around a large number of corporate events. We find that relationship banks build up positive (negative) trading positions in the two weeks before events with positive (negative) news, even when these events are unscheduled, and unwind positions shortly after the event. This trading pattern is more pronounced in situations when banks are likely to possess private information about their borrowers, and cannot be explained by specialized expertise in certain industries or certain firms. The results suggest that banks' lending relationships inform their trading and underscore the potential for conflicts of interest in universal banking, which have been a prominent concern in the regulatory debate for a long time. Our analysis illustrates how combining large data sets can uncover unusual trading patterns and enhance the supervision of financial institutions. |
| JEL: | G01 G14 G15 G18 G21 G24 G28 G38 K22 |
| Date: | 2022–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30521&r= |