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on Market Microstructure |
| By: | Markus Bibinger; Nikolaus Hautsch; Alexander Ristig |
| Abstract: | We propose methods to infer jumps of a semi-martingale, which describes long-term price dynamics based on discrete, noisy, high-frequency observations. Different to the classical model of additive, centered market microstructure noise, we consider one-sided microstructure noise for order prices in a limit order book. We develop methods to estimate, locate and test for jumps using local order statistics. We provide a local test and show that we can consistently estimate price jumps. The main contribution is a global test for jumps. We establish the asymptotic properties and optimality of this test. We derive the asymptotic distribution of a maximum statistic under the null hypothesis of no jumps based on extreme value theory. We prove consistency under the alternative hypothesis. The rate of convergence for local alternatives is determined and shown to be much faster than optimal rates for the standard market microstructure noise model. This allows the identification of smaller jumps. In the process, we establish uniform consistency for spot volatility estimation under one-sided microstructure noise. A simulation study sheds light on the finite-sample implementation and properties of our new statistics and draws a comparison to a popular method for market microstructure noise. We showcase how our new approach helps to improve jump detection in an empirical analysis of intra-daily limit order book data. |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.00819&r=mst |
| By: | Galati, Luca; De Blasis, Riccardo |
| Abstract: | This paper examines the market impact of large blocks in decentralised crypto markets. We examine this issue using a natural experiment in Bitcoin provided by the Gemini exchange, which introduced a block trading facility but changed, in December 2019, the ability of market participants to trade a block and report it with a delay in smaller-sized trades. Consistent with theoretical predictions and earlier empirical findings, we largely confirm that the information content of large trades is significantly lower in the upstairs market than in the downstairs. In contrast with prior research in traditional markets, we find that delaying the reporting of a block traded away from the continuous book discourages informed trading and potentially decreases the informativeness of trading and, therefore, information efficiency. Further, we find that the newly implemented size requirement for upstairs trades increases the total market impact, thereby not working as the intended introduction of a block trading facility. |
| Keywords: | block trading, decentralised markets, information efficiency, informed trading, market microstructure, price impact |
| JEL: | C58 D47 D82 G14 G18 |
| Date: | 2024–03–25 |
| URL: | http://d.repec.org/n?u=RePEc:mol:ecsdps:esdp24094&r=mst |
| By: | Hafner, Christian (Université catholique de Louvain, LIDAM/ISBA, Belgium); Linton, Oliver (obl20@cam.ac.uk); Wang, Linqi |
| Abstract: | We develop a dynamic framework to detect the occurrence of permanent and transitory breaks in the illiquidity process. We propose various tests that can be applied separately to individual events and can be aggregated across different events over time for a given firm or across different firms. In an empirical study, we use this methodology to study the impact of stock splits on the illiquidity dynamics of the Dow Jones index constituents and the effects of reverse splits using stocks from the S&P 500, S&P 400 and S&P 600 indices. Our empirical results show that stock splits have a positive and significant effect on the permanent component of the illiquidity process while a majority of the stocks engaging in reverse splits experience an improvement in liquidity conditions. |
| Keywords: | Amihud illiquidity ; Difference in Difference ; Event Study ; Nonparametric Estimation ; Reverse Split ; Structural Change |
| JEL: | C12 C14 G14 G32 |
| Date: | 2024–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:aiz:louvad:2024007&r=mst |
| By: | Oluwafemi F Olaiyapo |
| Abstract: | The objective of this research is to examine how sentiment analysis can be employed to generate trading signals for the Foreign Exchange (Forex) market. The author assessed sentiment in social media posts and news articles pertaining to the United States Dollar (USD) using a combination of methods: lexicon-based analysis and the Naive Bayes machine learning algorithm. The findings indicate that sentiment analysis proves valuable in forecasting market movements and devising trading signals. Notably, its effectiveness is consistent across different market conditions. The author concludes that by analyzing sentiment expressed in news and social media, traders can glean insights into prevailing market sentiments towards the USD and other pertinent countries, thereby aiding trading decision-making. This study underscores the importance of weaving sentiment analysis into trading strategies as a pivotal tool for predicting market dynamics. |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.00785&r=mst |
| By: | Hafner, C. M.; Linton, O. B.; Wang, L. |
| Abstract: | We develop a dynamic framework to detect the occurrence of permanent and transitory breaks in the illiquidity process. We propose various tests that can be applied separately to individual events and can be aggregated across different events over time for a given firm or across different firms. In an empirical study, we use this methodology to study the impact of stock splits on the illiquidity dynamics of the Dow Jones index constituents and the effects of reverse splits using stocks from the S&P 500, S&P 400 and S&P 600 indices. Our empirical results show that stock splits have a positive and significant effect on the permanent component of the illiquidity process while a majority of the stocks engaging in reverse splits experience an improvement in liquidity conditions. |
| Keywords: | Amihud illiquidity, Difference in Difference, Event Study, Nonparametric Estimation, Reverse Split, Structural Change |
| JEL: | C12 C14 G14 G32 |
| Date: | 2024–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:2410&r=mst |