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on Market Microstructure |
| By: | Zhao, X.; Hong, S. Y.; Linton, O. B. |
| Abstract: | We study the different origins of two closely related extreme financial risk factors: volatility bursts and price jumps. We propose a new method to separate these quantities from ultra-high-frequency data via a novel endogenous thresholding approach in the presence of market microstructure noise and staleness. Our daily jump statistic proxies volatility bursts when intraday jumps are accurately controlled by our local jump test (which proves to be highly powerful with extremely low misclassification rates due to its timely detections). We find that news is more related to volatility bursts; while high-frequency trading variables, especially volume and bid/ask spread, are prominent signals for price jumps. |
| Keywords: | Price Jumps, Volatility Bursts, Market Microstructure Noise, Endogenous Sampling, High-Frequency Trading, News Sentiment |
| JEL: | G12 G14 C14 |
| Date: | 2024–09–06 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2449 |
| By: | Nicola Borri (LUISS University); Yukun Liu (University of Rochester); Aleh Tsyvinski (Yale University); Xi Wu (University of California - Berkeley) |
| Abstract: | The European Union Emission Trading System is a prominent market-based mechanism to reduce emissions. While the theory is well- understood, we are the first to study the whole cap-and-trade mechanism as a financial market. Analyzing the universe of transactions in 2005-2020 (more than one million records of granular transaction data), we show that this market features significant inefficiencies undermining its goals. First, about 40% of firms never trade in a given ear. Second, many firms only trade during surrendering months, when compliance is immediate and prices are predictably high. Third, a number of operators engage in speculative trading, exploiting private information. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2403 |
| By: | Gonzalo Bohorquez; John Cartlidge |
| Abstract: | We propose that a tree-like hierarchical structure represents a simple and effective way to model the emergent behaviour of financial markets, especially markets where there exists a pronounced intersection between social media influences and investor behaviour. To explore this hypothesis, we introduce an agent-based model of financial markets, where trading agents are embedded in a hierarchical network of communities, and communities influence the strategies and opinions of traders. Empirical analysis of the model shows that its behaviour conforms to several stylized facts observed in real financial markets; and the model is able to realistically simulate the effects that social media-driven phenomena, such as echo chambers and pump-and-dump schemes, have on financial markets. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2409.00742 |