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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:camjip:2423 |
| By: | Hoffmann, Peter; Jank, Stephan |
| Abstract: | This paper uses regulatory data to assess the value of retail order flow in the German equity market. To this end, we examine the performance of specialized retail market makers (RMMs) that internalize a large share of retail activity via affiliated trading venues. We show that retail market making is extremely profitable, with an average (gross) Sharpe ratio of 17.85, which is more than twice as large as that earned by proprietary trading firms (PTFs) active in public limit order markets. A simple calculation suggest that RMMs would be willing to give up around 60% of their revenues, or 1.76 bps of their trading volume, for access to retail order flow. The profitability of retail market making is rooted in reduced exposure to adverse selection and inventory risk. |
| Keywords: | Equity markets, retail trading, market making, internalization, payment for order flow |
| JEL: | G10 G12 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:bubdps:301865 |
| By: | Toru Yano |
| Abstract: | Volatility means the degree of variation of a stock price which is important in finance. Realized Volatility (RV) is an estimator of the volatility calculated using high-frequency observed prices. RV has lately attracted considerable attention of econometrics and mathematical finance. However, it is known that high-frequency data includes observation errors called market microstructure noise (MN). Nagakura and Watanabe[2015] proposed a state space model that resolves RV into true volatility and influence of MN. In this paper, we assume a dependent MN that autocorrelates and correlates with return as reported by Hansen and Lunde[2006] and extends the results of Nagakura and Watanabe[2015] and compare models by simulation and actual data. |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2408.17187 |