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on Market Microstructure |
| By: | Tristan Roger (DRM-Finance - DRM - Dauphine Recherches en Management - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique); Wael Bousselmi (CREST - Centre de Recherche en Economie et Statistique [Bruz] - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz]); Patrick Roger (LARGE - Laboratoire de recherche en gestion et économie - UNISTRA - Université de Strasbourg - L'europe en mutation : histoire, droit, économie et identités culturelles - UNISTRA - Université de Strasbourg - CNRS - Centre National de la Recherche Scientifique); Marc Willinger (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - INRA - Institut National de la Recherche Agronomique - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier) |
| Abstract: | Conventional finance models indicate that the magnitude of stock prices should not influence portfolio choices or future returns. This view is contradicted, however, by empirical evidence. In this paper, we report the results of an experiment showing that trading prices, in experimental markets, are processed differently by participants, depending on their magnitude. Our experiment has two consecutive treatments. One where the fundamental value is a small number (the small price market) and a second one where the fundamental value is a large number (the large price market). Small price markets exhibit greater mispricing than large price markets. We obtain this result both between-participants and within-participants. Our findings show that price magnitude influences the way people perceive the distribution of future returns. This result is at odds with standard finance theory but is consistent with: (1) a number of observations in the empirical finance and accounting literature; and (2) evidence in neuropsychology on the use of different mental scales for small and large numbers. |
| Keywords: | number perception,mental scales,behavioral bias,experimental markets,stock price magnitude |
| Date: | 2018–12–14 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpceem:hal-01954921&r=all |
| By: | Vladislav Gennadievich Malyshkin |
| Abstract: | A new approach to obtaining market--directional information, based on a non--stationary solution to the dynamic equation "future price tends to the value that maximizes the number of shares traded per unit time" [1] is presented. In our previous work[2], we established that it is the share execution flow ($I=dV/dt$) and not the share trading volume ($V$) that is the driving force of the market, and that asset prices are much more sensitive to the execution flow $I$ (the dynamic impact) than to the traded volume $V$ (the regular impact). In this paper, an important advancement is achieved: we define the "scalp--price" ${\cal P}$ as the sum of only those price moves that are relevant to market dynamics; the criterion of relevance is a high $I$. Thus, only "follow the market" (and not "little bounce") events are included in ${\cal P}$. Changes in the scalp--price defined this way indicate a market trend change --- not a bear market rally or a bull market sell--off. The software calculating the scalp--price given market observations triples (time, execution price, shares traded) is available from the authors. |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1903.11530&r=all |
| By: | Notheisen, Benedikt; Marino, Vincenzo; Englert, Daniel; Weinhardt, Christof |
| Abstract: | The trust-free nature of blockchain-based systems challenges the role of traditional platform providers and enables the creation of new, intermediary-free markets. Despite the growing number of such markets, the impact of the blockchain's configuration on market outcomes remains unclear. In this study, we utilize order-level data from realworld financial markets to explore the impact of the blockchain parameters block size and block creation time on the quality of decentralized markets. More specifically, we find that increasing the blocks' capacity improves market activity, while higher block frequencies impose a trade-off between higher turnovers and lower trade sizes. In addition, we identify the block creation time and block size as core drivers of daily and intraday liquidity, respectively. In consequence, improving liquidity goes hand in hand with a higher activity. However, the reciprocal relationship between blockchain parameters and the increasing price impact of a block also indicate that faster and bigger blocks are no silver bullet to scale decentralized markets and may facilitate volatility. In total, we contribute an initial, technology-agnostic assessment of the quality of decentralized markets that aims to guide interdisciplinary researchers and innovative practitioners. |
| Keywords: | Decentralized markets,Blockchain,Market quality,Market design,Market engineering,FinTech |
| JEL: | G14 L86 N2 O16 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:kitwps:129&r=all |
| By: | Galanis, S.; Kotronis, S. |
| Abstract: | The ability of markets to aggregate information through prices is examined in a dynamic environment with unawareness. We find that if all traders are able to minimally update their awareness when they observe a price that is counterfactual to their private information, they will eventually reach an agreement, thus generalising the result of Geanakoplos and Polemarchakis [1982]. Moreover, if the traded security is separable, then agreement is on the correct price and there is information aggregation, thus gen- eralizing the result of Ostrovsky [2012] for non-strategic traders. We find that a trader increases her awareness if and only if she is able to become aware of something that other traders are already aware of and, under a mild condition, never becomes aware of anything more. In other words, agreement is more the result of understanding each other, rather than being unboundedly sophisticated. |
| Keywords: | Agreement; InformationAggregation; Unawareness; FinancialMarkets; InformationMarkets; PredictionMarkets |
| Date: | 2019–02–11 |
| URL: | http://d.repec.org/n?u=RePEc:cty:dpaper:19/03&r=all |