To Pay or Be Paid? The Impact of Taker Fees and Order Flow Inducements on Trading Costs in U.S. Options Markets

2011 ◽  
Author(s):  
Robert H. Battalio ◽  
Andriy Shkilko ◽  
Robert A. Van Ness
Keyword(s):  
Order Flow ◽  
Trading Costs ◽  
Options Markets ◽  
The Impact

To Pay or Be Paid? The Impact of Taker Fees and Order Flow Inducements on Trading Costs in U.S. Options Markets

2016 ◽  
Vol 51 (5) ◽  
pp. 1637-1662 ◽  
Author(s):  
Robert Battalio ◽  
Andriy Shkilko ◽  
Robert Van Ness
Keyword(s):  
Order Flow ◽  
Trading Costs ◽  
Options Markets ◽  
Prior Literature ◽  
Liquidity Cost ◽  
Liquidity Costs ◽  
The Impact

Consistent with prior literature, we find that average relative effective spreads are higher for venues that pay for order flow (PFOF) than for venues utilizing the maker-taker (MT) model. This relation becomes more nuanced when liquidity fees are incorporated into liquidity cost measures. For the majority of options, PFOF venues offer lower average liquidity costs net of taker fees. Net liquidity costs for the high-priced options, however, are lower for MT venues. Overall, our results suggest that the inclusion of fees and rebates can rationalize the routing of most, but not all, marketable orders to PFOF venues.

The Impact of Regulation Fair Disclosure: Trading Costs and Information Asymmetry

CFA Digest ◽  
2004 ◽  
Vol 34 (4) ◽  
pp. 9-10 ◽  
Author(s):  
William A. Trent
Keyword(s):  
Information Asymmetry ◽  
Trading Costs ◽  
Regulation Fair Disclosure ◽  
Fair Disclosure ◽  
The Impact

The impact of order flow on event study returns: New evidence from zero-leverage firms

2021 ◽  
Vol 80 ◽  
pp. 627-634
Author(s):  
Sijia Zhang ◽  
Andros Gregoriou
Keyword(s):  
Event Study ◽  
Order Flow ◽  
The Impact ◽  
New Evidence

BV-VPIN: Measuring the Impact of Order Flow Toxicity and Liquidity on International Equities Markets

2016 ◽  
Author(s):  
Rand Kwong Yew Low ◽  
Te Li ◽  
Terry Marsh
Keyword(s):  
Order Flow ◽  
International Equities ◽  
The Impact

Unfiltered Market Access and Liquidity: Evidence from the SEC Rule 15c3-5

2020 ◽  
Author(s):  
Bidisha Chakrabarty ◽  
Pankaj K. Jain ◽  
Andriy Shkilko ◽  
Konstantin Sokolov
Keyword(s):  
Adverse Selection ◽  
Market Access ◽  
Securities And Exchange Commission ◽  
Order Flow ◽  
Trading Costs ◽  
Liquidity Provision ◽  
New Information ◽  
The U.S

In November 2011, the U.S. Securities and Exchange Commission implemented the final provision of Rule 15c3-5 curbing unfiltered market access. The provision mandated that brokers verify their clients’ order flow for compliance with credit and capital thresholds before routing to market centers. We find that the new checks introduce latency to order flow and force some latency-sensitive strategies out of the market. As a result, liquidity providers are better able to revise their quotes in response to new information, adverse selection declines, and liquidity improves. Consistent with the notion that the market for liquidity provision is competitive, our results show that the benefit of lower adverse selection is transferred entirely to liquidity demanders in the form of lower trading costs. This paper was accepted by Karl Diether, finance.

scholarly journals A Comparative Study on the Routing Problem of Electric and Fuel Vehicles Considering Carbon Trading

2019 ◽  
Vol 16 (17) ◽  
pp. 3120 ◽  
Author(s):  
Wenzhu Liao ◽  
Lin Liu ◽  
Jiazhuo Fu
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicles ◽  
Carbon Emissions ◽  
Great Influence ◽  
Carbon Price ◽  
Initial Population ◽  
Carbon Trading ◽  
Trading Costs ◽  
Battery Capacity ◽  
The Impact

In order to explore the impact of using electric vehicles on the cost and environment of logistics enterprises, this paper studies the optimization of vehicle routing problems with the consideration of carbon trading policies. Both the electric vehicle routing model and the traditional fuel vehicle routing model are constructed aiming at minimizing the total costs, which includes the fixed costs of vehicles, depreciation costs, penalty costs for violating customer time window, energy costs and carbon trading costs. Then a hybrid genetic algorithm (HGA) is proposed to address these two models, the advantages of greedy algorithm and random full permutation are combined to set the initial population, at the same time, the crossover operation is improved to retain the excellent gene fragments effectively and the hill climbing algorithm is embedded to enhance the local search ability of HGA. Furthermore, a case data is used with HGA to carry out computational experiments in these two models and the results indicate that first using electric vehicles for distribution can indeed reduce the carbon emissions, but results in a low customer satisfaction compared with using fuel vehicles. Besides, the battery capacity and charge rate have a great influence on total costs of using electric vehicles. Second, carbon price plays an important role in the transformation of logistics companies. As the carbon price changes, the total costs, carbon trading costs, and carbon emissions of using electric vehicles and fuel vehicles are affected accordingly, yet the trends are different. The changes of carbon quota have nothing to do with the distribution scheme and companies’ transformation but influence the total costs of using electric and fuel vehicles for distribution, and the trends are the same. These reasonable proposals can support the government on carbon trading policy, and also the logistics companies on dealing the relationship between economic and social benefits.

Linear models for the impact of order flow on prices. I. History dependent impact models

2018 ◽  
Vol 18 (6) ◽  
pp. 903-915 ◽  
Author(s):  
Damian Eduardo Taranto ◽  
Giacomo Bormetti ◽  
Jean-Philippe Bouchaud ◽  
Fabrizio Lillo ◽  
Bence Tóth
Keyword(s):  
Linear Models ◽  
Order Flow ◽  
The Impact ◽  
Impact Models

Analysis of Carbon Emissions Trading Costs Influencing Factors in Power Industry

2014 ◽  
Vol 651-653 ◽  
pp. 1410-1414
Author(s):  
Wen Yan Liu ◽  
Xiao Bao Yu ◽  
Pu Yu He ◽  
Yan Li Huang ◽  
Bing Bing Zhou ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Emissions Trading ◽  
Structural Model ◽  
Trading Costs ◽  
Carbon Emissions Trading ◽  
Transport Chain ◽  
The Cost ◽  
Accuracy Of Prediction ◽  
The Impact

The uncertain factors that impact of carbon emissions trading costs are so many, the impact of various factors interact to form a complex system. To improve the accuracy of prediction, it is necessary to deepen the study of these influencing factors. Through investigation identified 21 main factors that affecting the cost of carbon emissions trading, processing and analysis explained by structural model was constructed of carbon emissions trading cost factors and the impact of transport chain hierarchy, based on this model to find the factors that most affect carbon emissions trading costs.

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