We investigate several statistical properties of the order book of three liquid stocks of the Paris Bourse. The results are to a large degree independent of the stock studied. The most interesting features concern (i) the statistics of incoming limit order prices, which follows a power-law around the current price with a diverging mean; and (ii) the humped shape of the average order book, which can be quantitatively reproduced using a `zero intelligence' numerical model, and qualitatively predicted using a simple approximation.

Statistical properties of stock order books: empirical results and models

Review of factors affecting consumer acceptance of cultured meat

High-Frequency Trading and Price Discovery

We develop a prioritization framework for foodborne risks that considers public health impact as well as three other factors (market impact, consumer risk acceptance and perception, and social sensitivity). Canadian case studies are presented for six pathogen-food combinations: Campylobacter spp. in chicken; Salmonella spp. in chicken and spinach; Escherichia coli O157 in spinach and beef; and Listeria monocytogenes in ready-to-eat meats. Public health impact is measured by disability-adjusted life years and the cost of illness. Market impact is quantified by the economic importance of the domestic market. Likert-type scales are used to capture consumer perception and acceptance of risk and social sensitivity to impacts on vulnerable consumer groups and industries. Risk ranking is facilitated through the development of a knowledge database presented in the format of info cards and the use of multicriteria decision analysis (MCDA) to aggregate the four factors. Three scenarios representing different stakeholders illustrate the use of MCDA to arrive at rankings of pathogen-food combinations that reflect different criteria weights. The framework provides a flexible instrument to support policymakers in complex risk prioritization decision making when different stakeholder groups are involved and when multiple pathogen-food combinations are compared.

/pdf/a-multifactorial-risk-prioritization-framework-for-foodborne-1gcym68mer.pdf

A Multifactorial Risk Prioritization Framework for Foodborne Pathogens

Examining those risk and benefit perceptions utilised in the formation of attitudes and opinions about emerging technologies such as nanotechnology can be useful for both industry and policy makers involved in their development, implementation and regulation. A broad range of different socio-psychological and affective factors may influence consumer responses to different applications of nanotechnology, including ethical concerns. A useful approach to identifying relevant consumer concerns and innovation priorities is to develop predictive constructs which can be used to differentiate applications of nanotechnology in a way which is meaningful to consumers. This requires elicitation of attitudinal constructs from consumers, rather than measuring attitudes assumed to be important by the researcher. Psychological factors influencing societal responses to 15 applications of nanotechnology drawn from different application areas (e.g. medicine, agriculture and environment, food, military, sports, and cosmetics) were identified using repertory grid method in conjunction with generalised Procrustes analysis. The results suggested that people differentiate nanotechnology applications based on the extent to which they perceive them to be beneficial, useful, necessary and important. The benefits may be offset by perceived risks focusing on fear and ethical concerns. Compared to an earlier expert study on societal acceptance of nanotechnology, consumers emphasised ethical issues compared to experts but had less concern regarding potential physical contact with the product and time to market introduction. Consumers envisaged fewer issues with several applications compared to experts, in particular food applications.

/pdf/ethics-risk-and-benefits-associated-with-different-5goqn76ia2.pdf

Ethics, Risk and Benefits Associated with Different Applications of Nanotechnology: a Comparison of Expert and Consumer Perceptions of Drivers of Societal Acceptance

Since they were authorized by the U.S. Security and Exchange Commission in 1998, electronic exchanges have boomed, and by 2010 high frequency trading accounted for over 70% of equity trades in the US. Such markets are thought to increase liquidity because of the presence of market makers, who are willing to trade as counterparties at any time, in exchange for a fee, the bid-ask spread. In this paper, we propose an equilibrium model showing how such market makers provide liquidity. The model relies on a codebook for client trades, the implied alpha. After solving the individual clients optimization problems and identifying their implied alphas, we frame the market maker stochastic optimization problem as a stochastic control problem with an infinite dimensional control variable. Assuming either identical time horizons for all the clients, or a stochastic partial differential equation model for their beliefs, we solve the market maker problem and derive tractable formulas for the optimal strategy and the resulting limit-order book dynamics.

High Frequency Market Making

Handbook of Price Impact Modeling

High Frequency Trading (HFT) represents an ever growing proportion of all financial transactions as most markets have now switched to electronic order book systems. The main goal of the paper is to propose continuous time equations which generalize the self-financing relationships of frictionless markets to electronic markets with limit order books. We use NASDAQ ITCH data to identify significant empirical features such as price impact and recovery, rough paths of inventories and vanishing bid-ask spreads. Starting from these features, we identify microscopic identities holding on the trade clock, and through a diffusion limit argument, derive continuous time equations which provide a macroscopic description of properties of the order book.These equations naturally differentiate between trading via limit and market orders. We give several applications (including hedging European options with limit orders, market maker optimal spread choice, and toxicity indexes) to illustrate their impact and how they can be used to the benefit of Low Frequency Traders (LFTs).

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2365122_code619297.pdf?abstractid=2365122&mirid=1&type=2

The Self-Financing Equation in High Frequency Markets

Since they were authorized by the U.S. Security and Exchange Commission in 1998, electronic exchanges have boomed, and by 2010 high frequency trading accounted for over 70% of equity trades in the US. Such markets are thought to increase liquidity because of the presence of market makers, who are willing to trade as counterparties at any time, in exchange for a fee, the bid-ask spread. In this paper, we propose an equilibrium model showing how such market makers provide liquidity. The model relies on a codebook for client trades, the implied alpha. After solving the individual clients optimization problems and identifying their implied alphas, we frame the market maker stochastic optimization problem as a stochastic control problem with an innite dimensional control variable. Assuming either identical time horizons for all the clients, or a stochastic partial dierential equation model for their beliefs, we solve the market maker problem and derive tractable formulas for the optimal strategy and the resulting limit-order book dynamics.

High frequency market making

We study how short-term informational advantages can be monetized in a high-frequency setting, when large inventories are explicitly penalized. We find that if most of the additional information is...

Information and Inventories in High-Frequency Trading

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