
on Market Microstructure 
By:  Victor Olkhov 
Abstract:  This paper considers price volatility as the reason for description of the seconddegree economic variables, trades and expectations aggregated during certain time interval {\Delta}. We call it  the secondorder economic theory. The nth degree products of costs and volumes of trades, performed by economic agents during interval {\Delta} determine price nth 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 nth statistical moments of price but that is almost impossible. We define squares of agent's trades and macro expectations those approve the seconddegree trades aggregated during interval {\Delta}. We believe that agents perform trades under action of multiple expectations. We derive equations on the seconddegree 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 seconddegree trades and expectations. In the linear approximation we derive mean square price and volatility disturbances as functions of the first and seconddegree trades disturbances. In simple approximation numerous expectations and their perturbations can cause small harmonic oscillations of the seconddegree 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 microstructural 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. Pertrader 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 firmspecific news in an emerging market. Using intraday prices of all stocks traded on the Borsa Istanbul, Turkey over the period 20052013, 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, Firmspecific 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 