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on Market Microstructure |
| By: | Lin, Zhongguo; Hamill, Philip A.; Li, Youwei; Sun, Zhuowei; Waterworth, James |
| Abstract: | The impact of trades on price dynamics in the European sovereign debt markets is of significant importance to policy makers and market participants. This paper uses high-frequency quote and transaction data from the MTS European sovereign bond inter-dealer platform to investigate price-order-flow dynamics from July 2005 until December 2011 for Germany, France, Portugal, Italy, Ireland, Spain and Greece. We find that order-flow had a larger impact on quote revision in a relatively low-intensity trading environment than in a relatively high-intensity trading environment implying that informed traders should only execute in low-intensity trading environments when they value immediacy over discretion. This analysis is consistent with the limited prior literature for European debt markets. Our analysis indicates that this relationship persists during turbulent market conditions. Also, we find that the impact of order-flow on subsequent trades was larger during periods of high-trading intensity implying that market participants use order splitting trading strategies. |
| Keywords: | Order-flow; Price impact; Trading intensity; Sovereign Bonds |
| JEL: | G01 G23 G24 |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:97768&r=all |
| By: | Fabrice Rousseau (Economics, National University of Ireland, Maynooth); Herve Boco (TBS Business School); Laurent Germain (TBS Business School) |
| Abstract: | In the following paper we analyze the strategic competition between fast and slow traders. A fast or High Frequency Trader (HFT) is defned as a trader that has the ability to react to information faster than other informed traders and as a consequence can trade more than other traders. This trader benefits from low latency compared to slower trader. In such a setting, we prove the existence and the unicity of an equilibrium with fast and slow traders. We and that the speed advantage of HFTs has a beneficial effect on market liquidity as well as price effciency. The positive effect on liquidity is present only if there are 2 or more HFTs. However, despite those effects slower traders are at a disadvantage as they are not able to trade on their private information as many times as their HFTs counterpart. Once they can, most of their private information has been incorporated into prices due to the lower latency of HFTs. This implies that slower traders are worse off when HFTs are present. The speed differential benefits HFTs as they earn higher expected profits than their slower counterparts and also benefits liquidity traders. We find the existence of an optimal level of speed for HFT. |
| Keywords: | High frequency trading, Insider, Volatility, Market effciency. |
| JEL: | D43 D82 G14 G24 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:may:mayecw:n296-20.pdf&r=all |
| By: | Ingomar Krohn; Vladyslav Sushko |
| Abstract: | We study the joint evolution of foreign exchange (FX) spot and swap market liquidity. Trading in FX swaps exceeds that of spot, yet this market segment has been largely ignored in prior research on liquidity in FX markets. We find strong co-movement in spot and swap market liquidity conditions and a strong link between FX funding and market liquidity, as gleaned from the pricing of both instruments. This link has strengthened over time with changes in dealer behaviour. Some of the largest dealers periodically pull back from pricing FX swaps and wider spreads attract smaller dealers. At the same time, liquidity in FX swaps remains impaired, which leads to adverse illiquidity spillovers to the spot market. Our findings suggest that funding liquidity has become a more important driver of spot market liquidity than it used to be. |
| Keywords: | foreign exchange, market and funding liquidity, microstructure, dealer activity, window dressing |
| JEL: | F31 G15 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:836&r=all |
| By: | David Rushing Dewhurst; Yi Li; Alexander Bogdan; Jasmine Geng |
| Abstract: | Securities markets are quintessential complex adaptive systems in which heterogeneous agents compete in an attempt to maximize returns. Species of trading agents are also subject to evolutionary pressure as entire classes of strategies become obsolete and new classes emerge. Using an agent-based model of interacting heterogeneous agents as a flexible environment that can endogenously model many diverse market conditions, we subject deep neural networks to evolutionary pressure to create dominant trading agents. After analyzing the performance of these agents and noting the emergence of anomalous superdiffusion through the evolutionary process, we construct a method to turn high-fitness agents into trading algorithms. We backtest these trading algorithms on real high-frequency foreign exchange data, demonstrating that elite trading algorithms are consistently profitable in a variety of market conditions---even though these algorithms had never before been exposed to real financial data. These results provide evidence to suggest that developing \textit{ab initio} trading strategies by repeated simulation and evolution in a mechanistic market model may be a practical alternative to explicitly training models with past observed market data. |
| Date: | 2019–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1912.09524&r=all |
| By: | Jean-Sébastien Fontaine; Adrian Walton |
| Abstract: | Dealers connect investors who want to buy or sell securities in financial markets. Over time, dealers and investors form trading networks to save time and resources. An emerging field of research investigates how networks form. Using detailed data on trades in Government of Canada bonds, we reconstruct dealer networks and document how they respond to the release of relevant economic information. On one hand, we find that networks handle larger volumes of transactions and become more complex. On the other hand, we document more frequent and more severe contagion of settlement fails across dealer networks following these information releases. Settlement fails are unexpected delays in a buyer receiving bonds from a seller, creating counterparty risk and potential disruption to trading. Our findings suggest a trade-off. Large, complex dealer networks effectively connect investors but are also associated with contagion and an increase in counterparty risk due to settlement fails. One way to simplify dealer networks is through a central counterparty (CCP). A CCP reduces settlement volume, making fails less likely. |
| Keywords: | Financial markets; Market structure and pricing; Payment clearing and settlement systems |
| JEL: | E4 G1 G21 L14 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:20-1&r=all |