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on Market Microstructure |
| By: | Victor Olkhov |
| Abstract: | This paper considers price volatility as the reason for description of the second-degree economic variables, trades and expectations aggregated during certain time interval {\Delta}. We call it - the second-order economic theory. The n-th degree products of costs and volumes of trades, performed by economic agents during interval {\Delta} determine price n-th statistical moments. First two price statistical moments define volatility. To model volatility one needs description of the squares of trades aggregated during interval {\Delta}. To describe price probability one needs all n-th statistical moments of price but that is almost impossible. We define squares of agent's trades and macro expectations those approve the second-degree trades aggregated during interval {\Delta}. We believe that agents perform trades under action of multiple expectations. We derive equations on the second-degree trades and expectations in economic space. As economic space we regard numerical continuous risk grades. Numerical risk grades are discussed at least for 80 years. We propose that econometrics permit accomplish risk assessment for almost all economic agents. Agents risk ratings distribute agents by economic space and define densities of macro second-degree trades and expectations. In the linear approximation we derive mean square price and volatility disturbances as functions of the first and second-degree trades disturbances. In simple approximation numerous expectations and their perturbations can cause small harmonic oscillations of the second-degree trades disturbances and induce harmonic oscillations of price and volatility perturbations. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.14278&r=all |
| By: | Xuan Tao; Andrew Day; Lan Ling; Samuel Drapeau |
| Abstract: | Spoofing is an illegal act of artificially modifying the supply to drive temporarily prices in a given direction for profit. In practice, detection of such an act is challenging due to the complexity of modern electronic platforms and the high frequency at which orders are channeled. We present a micro-structural study of spoofing in a simple static setting. A multilevel imbalance which influences the resulting price movement is introduced upon which we describe the optimization strategy of a potential spoofer. We provide conditions under which a market is more likely to admit spoofing behavior as a function of the characteristics of the market. We describe the optimal spoofing strategy after optimization which allows us to quantify the resulting impact on the imbalance after spoofing. Based on these results we calibrate the model to real Level 2 datasets from TMX, and provide some monitoring procedures based on the Wasserstein distance to detect spoofing strategies in real time. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.14818&r=all |
| By: | Eyster, Erik; Rabin, Matthew; Vayanos, Dimitri |
| Abstract: | We model a financial market where some traders of a risky asset do not fully appreciate what prices convey about others' private information. Markets comprising solely such “cursed” traders generate more trade than those comprising solely rationals. Because rationals arbitrage away distortions caused by cursed traders, mixed markets can generate even more trade. Per-trader volume in cursed markets increases with market size; volume may instead disappear when traders infer others' information from prices, even when they dismiss it as noisier than their own. Making private information public raises rational and “dismissive” volume, but reduces cursed volume given moderate noninformational trading motives. |
| JEL: | G0 G00 |
| Date: | 2019–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:87477&r=all |
| By: | SHABIR A.A. SALEEM; PETER N. SMITH; ABDULLAH YALAMAN |
| Abstract: | We investigate whether the daily betas of individual stocks vary with the release of firm-specific news in an emerging market. Using intraday prices of all stocks traded on the Borsa Istanbul, Turkey over the period 2005-2013, we find evidence that average market betas increase significantly from two weeks before the earning announcement day, and then revert to their average levels two weeks after the announcement. The increase in betas is greater for larger, positive surprise earnings announcements than for smaller, negative news. The results are consistent with features of the learning model of Patton and Verardo (2012) but not with a number of their empirical results. |
| Keywords: | Realized Beta, Firm-specific News, Earnings Announcements, Emerging Market |
| JEL: | C22 G10 G11 G33 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:yor:yorken:20/09&r=all |