wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We propose in this paper closed-form approximations for the bid and ask quotes a market maker should set for optimally managing the risk of his/her multi-asset market making book. Our work is an extension of the paper "Optimal market making" by Gu\'eant. We also consider generalizations with asymmetric arrival rate intensities. Moreover, we consider the case where the reference price is modeled with a drift and adverse selection .
Revised:  We propose in this paper closed-form approximations for the bid and ask quotes a market maker should set for optimally managing the risk of his/her multi-asset extensions of the Avellaneda-Stoikov model. These approximations or proxies can be used (i) as heuristic evaluation functions, (ii) as initial value functions in reinforcement learning algorithms, and/or (iii) directly to design quoting strategies through a greedy approach. Regarding the latter, our results lead to new and easily interpretable closed-form approximations for the optimal quotes, both in the finite-horizon case and in the asymptotic (ergodic) regime. Furthermore, we propose a perturbative approach to improve our closed-form approximations through Monte-Carlo simulations .
Edit intent: meaning-changed
Original:  We  show that existing convergence results for quantile estimators may be directly converted to convergence results for production sets  .
Revised:  We characterize the identified set for production sets, and provide conditions that ensure point identification. We present a general computationally-feasible framework for sharp counterfactual bounds, such as bounds on quantities at a counterfactual price. We show that existing convergence results for quantile estimators may be directly converted to convergence results for production sets .
Edit intent: meaning-changed
Original:  We extend classical duality results for price-taking firms to a setup with rich heterogeneity, and with limited variation in prices. We characterize the identified set for production sets, and provide conditions that ensure point identification. We present a general computationally-feasible framework for sharp counterfactual bounds, such as bounds on quantities at a counterfactual price. We show that existing convergence results for quantile estimators may be directly converted to convergence results for production sets , which facilitates statistical inference .
Revised:  We extend classical duality results for price-taking firms to a setup with rich heterogeneity, and with limited variation in possibly latent prices. Finally, we show that convergence results for quantile estimators may be directly converted to convergence results for production sets , which facilitates statistical inference .
Edit intent: clarity
Original:  A stable central limit theorem is attained with estimable asymptotic covariance matrix .
Revised:  A stable central limit theorem is attained with estimable asymptotic covariance matrices. This paper form a basis for infill asymptotic results of, for example, the realized Laplace transform, the realized principal component analysis, the continuous-time linear regression, and the generalized method of integrated moments, hence helps to extend the application scopes to more frequently sampled noisy data .
Edit intent: meaning-changed
Original:  In fact, as demonstrated in (Feinstein and Rudloff ( 2018 )), scalar risk measures with the same scalarization weight at all times would not be time consistent in general.
Revised:  In fact, as demonstrated in (Feinstein and Rudloff ( 2020 )), scalar risk measures with the same scalarization weight at all times would not be time consistent in general.
Edit intent: meaning-changed
Original:  In this way we develop a direct notion of a "moving scalarization" for scalar time consistency that corroborates recent research on scalarizations of dynamic multi-objective problems (Karnam, Ma, and Zhang (2017), Kovacova and Rudloff ( 2018 )).
Revised:  In this way we develop a direct notion of a "moving scalarization" for scalar time consistency that corroborates recent research on scalarizations of dynamic multi-objective problems (Karnam, Ma, and Zhang (2017), Kovacova and Rudloff ( 2020 )).
Edit intent: meaning-changed
Original:  We show that ignoring measurement error in the RP approach may lead to overrejection of the UMT. To solve this problem, this paper proposes a new statistical RP framework for consumption panel data sets that allows for testing the UMT in the presence of measurement error.
Revised:  We show that ignoring measurement error in the RP approach may lead to overrejection of the UMT. To solve this problem, we propose a new statistical RP framework for consumption panel data sets that allows for testing the UMT in the presence of measurement error.
Edit intent: clarity
Original:  We develop two applications that provide new evidence about the UMT. First, we find support in a survey dataset for the dynamic and time-consistent UMT in single-individual households, in the presence of nonclassical measurement error in consumption.
Revised:  We develop two applications that provide new evidence about the UMT. First, we find support in a survey data set for the dynamic and time-consistent UMT in single-individual households, in the presence of nonclassical measurement error in consumption.
Edit intent: clarity
Original:  In real-time , they know the price associated with their trades on the dealer-to-dealer (D2D) and dealer-to-client (D2C) markets, they know the result of the requests for quotes (RFQ) they answered, and they have access to composite prices (e.g., Bloomberg CBBT).
Revised:  In real time , they know the price associated with their trades on the dealer-to-dealer (D2D) and dealer-to-client (D2C) markets, they know the result of the requests for quotes (RFQ) they answered, and they have access to composite prices (e.g., Bloomberg CBBT).
Edit intent: fluency
Original: A fundamental question in biology is URLanisms integrate sensory and social evidence to make decisions . However, few models describe how both these streams of information can be combined to optimize choices .
Revised: To make decisions we are guided by the evidence we collect, as well as the opinions of friends and neighbors. How do we integrate our private beliefs with information we obtain from our social network? To understand the strategies humans use to do so it is useful to compare them to observers that optimally integrate all evidence .
Edit intent: clarity
Original:  Here we develop a normative model for collective decision making in a network of agents performing a two-alternative forced choice task. We assume that rational (Bayesian) agents in this network make private measurements , and observe the decisions of their neighbors until they accumulate sufficient evidence to make an irreversible choice .
Revised:  Here we derive network models of rational (Bayes optimal) agents who accumulate private measurements and observe decisions of their neighbors until they accumulate sufficient evidence to make an irreversible choice .
Edit intent: clarity
Original:  We assume that rational (Bayesian) agents in this network make private measurements , and observe the decisions of their neighbors until they accumulate sufficient evidence to make an irreversible choice . As each agent communicates its decision to those observing it, the flow of social information is described by a directed graph. The decision-making process in this setting is intuitive, but can be complex. We describe when and how the absence of a decision of a neighboring agent communicates social information, and how an agent must marginalize over all unobserved decisions.
Revised:  We assume that rational (Bayesian) agents in this network make private measurements , and observe the decisions of their neighbors until they accumulate sufficient evidence to make an irreversible choice between two options. The resulting information exchange dynamics has interesting properties: When one option is preferred, the absence of a decision can be increasingly informative over time. In recurrent networks an absence of a decision of a neighboring agent communicates social information, and how an agent must marginalize over all unobserved decisions.
Edit intent: meaning-changed
Original:  We describe when and how the absence of a decision of a neighboring agent communicates social information, and how an agent must marginalize over all unobserved decisions. We also show how decision thresholds and network connectivity affect group evidence accumulation, and describe the dynamics of decision making in social cliques. Our model provides a bridge between the abstractions used in the economics literature and the evidence accumulator models used widely in neuroscience and psychology.
Revised:  We describe when and how the absence of a decision can lead to a sequence of belief updates akin to those in the literature on common knowledge. Information obtained from observing repeated non-decisions is independent of realization, unless the private information of agents is redundant. On the other hand, in larger networks a single decision can trigger a cascade of agreements and disagreements that depend on the private information agents have gathered. Our approach provides a bridge between the abstractions used in the economics literature and the evidence accumulator models used widely in neuroscience and psychology.
Edit intent: meaning-changed
Original:  We analyse the mean-field game (MFG) limit of the stochastic game and show that the Nash equilibria is given by the solution to a non-standard vector-valued forward-backward stochastic differential equation.
Revised:  We analyse the mean-field game (MFG) limit of the stochastic game and show that the Nash equilibrium is given by the solution to a non-standard vector-valued forward-backward stochastic differential equation.
Edit intent: clarity
Original:  A constant is suggested subsequently that characterizes how easily a vesicle can absorb amphiphiles into its periphery . Furthermore, the vesicle-growth is proven to be a Poisson process and the average half-life is obtained for this process by comparing the distribution function with experimental results .
Revised:  A constant is suggested subsequently that characterizes how easily a vesicle can absorb amphiphiles into its periphery .
Edit intent: coherence
Original:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures  then place groups within a taxonomy, providing a  "social assay" of group-level knowledge.
Revised:  By looking for heuristics that depend upon rank information , we can back-infer the types of knowledge individuals possess . Summary measures then place groups within a taxonomy, providing a "social assay" of group-level knowledge.
Edit intent: clarity
Original:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures  then place groups within a taxonomy, providing a  "social assay" of group-level knowledge.
Revised:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of information individuals possess about the macro-level properties of their group . Summary measures then place groups within a taxonomy, providing a "social assay" of group-level knowledge.
Edit intent: meaning-changed
Original:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures  then place groups within a taxonomy, providing a  "social assay" of group-level knowledge.
Revised:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures of these heuristics then place groups within a taxonomy, providing a "social assay" of group-level knowledge.
Edit intent: clarity
Original:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures  then place groups within a taxonomy, providing a  "social assay" of group-level knowledge.
Revised:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures then place groups within a taxonomy, providing a biologically-relevant "social assay" of group-level knowledge.
Edit intent: meaning-changed
Original:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures  then place groups within a taxonomy, providing a  "social assay" of group-level knowledge. This assay allows the identification of consensus strategies at the group level.
Revised:  By looking for heuristics that depend upon knowledge of group-level facts , we can back-infer the types of knowledge individuals possess . Summary measures then place groups within a taxonomy, providing a "social assay" to quantify the amount of social information and to identify consensus strategies at the group level.
Edit intent: clarity
Original:  The majority of animal groups in our dataset (112 groups, 65\%) follow a downward heuristic  , spreading aggression relatively equally across lower-ranked opponents . An additional 50 groups (29\%) use strategies that are indicative of more detailed rank knowledge.
Revised:  The majority of animal groups in our dataset (112 groups, 65\%) follow a downward heuristic , spreading aggression relatively equally across lower-ranked opponents but 50 groups (29\%) use strategies that are indicative of more detailed rank knowledge.
Edit intent: clarity
Original:  An additional 50 groups (29\%) use strategies that are indicative of more detailed rank knowledge. Different groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression  should not be considered a fixed characteristic of a species .
Revised:  An additional 50 groups (29\%) use strategies that are indicative of more detailed rank information. Strategies are not phylogenetically constrained and groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression should not be considered a fixed characteristic of a species .
Edit intent: meaning-changed
Original:  Different groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression  should not be considered a fixed characteristic of a species .
Revised:  Different groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic of a species .
Edit intent: meaning-changed
Original:  We present a new method for detecting social information in dominance hierarchies, that infers individual-level rules for aggression based on how aggression decisions are influenced by differences in social rank. We apply this method to 172 social groups across 85 species in 22 orders.
Revised:  We present a new method that can serve as a social assay to quantify how patterns of aggression depend upon information about the ranks of individuals within social dominance hierarchies. Applied to existing data on aggression in 172 social groups across 85 species in 22 orders.
Edit intent: clarity
Original:  We apply this method to 172 social groups across 85 species in 22 orders. By looking for heuristics that depend upon rank information, we can back-infer the types of information individuals possess about the macro-level properties of their group. Summary measures of these heuristics then place groups within a taxonomy, providing a biologically-relevant "social assay" to quantify the amount of social information and to identify consensus strategies at the group level .
Revised:  We apply this method to 172 social groups across 85 species in 23 orders, it reveals three main patterns of rank-dependent social dominance: the downward heuristic (aggress uniformly against lower-ranked opponents), close competitors (aggress against opponents ranked slightly below self), and bullying (aggress against opponents ranked much lower than self) .
Edit intent: meaning-changed
Original:  follow a downward heuristic to structure their fights, spreading aggression relatively equally across lower-ranked opponents but 50 groups (29\%) use strategies that are indicative of more detailed rank information . Strategies are not phylogenetically constrained and  groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic .
Revised:  follow a downward heuristic , but a significant minority (38 groups, 22\%) show more complex social dominance patterns (close competitors or bullying) consistent with higher levels of social information use. These patterns are not phylogenetically constrained and groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic .
Edit intent: meaning-changed
Original:  use strategies that are indicative of more detailed rank information . Strategies are not phylogenetically constrained and  groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic .
Revised:  use strategies that are indicative of more detailed rank information . Strategies are not phylogenetically constrained and different groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic .
Edit intent: fluency
Original:  use strategies that are indicative of more detailed rank information . Strategies are not phylogenetically constrained and  groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic .
Revised:  use strategies that are indicative of more detailed rank information . Strategies are not phylogenetically constrained and groups within the same species can use different patterns, suggesting that heuristics use may depend on context and the structuring of aggression by social information should not be considered a fixed characteristic .
Edit intent: clarity
Original:  use strategies that are indicative of more detailed rank information . Strategies are not phylogenetically constrained and  groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic . Instead, individuals may be able to plastically respond to local conditions by increasing or decreasing the complexity of their strategies .
Revised:  use strategies that are indicative of more detailed rank information . Strategies are not phylogenetically constrained and groups within the same species can use different strategies, indicating that the choice of heuristics may be contextual and that the structuring of aggression by social information should not be considered a fixed characteristic of a species .
Edit intent: clarity
Original: We propose a simple cross-sectional research design to identify causal effects that is robust to unobservable heterogeneity . When many observational units are adjacent , it may be sufficient to regress the "spatial first differences" (SFD) of the outcome on the treatment and omit all covariates.
Revised: We propose a simple cross-sectional research design to identify causal effects in the presence of unobservable heterogeneity without instruments. When units are dense in physical space , it may be sufficient to regress the "spatial first differences" (SFD) of the outcome on the treatment and omit all covariates.
Edit intent: clarity
Original:  This approach is conceptually similar to first differencing approaches in time-series or panel models, except the index for time is replaced with an index for locations in space. The SFD approach identifies plausibly causal effects so long as local changes in the treatment and unobservable confounders are not systematically correlated between immediately adjacent neighbors. We illustrate how this approach can mitigate omitted variables bias through simulation and by estimating returns to schooling along 10th Avenue in New York and I-90 in Chicago. We then more fully explore the benefits of this approach by estimating effects of climate and soil on maize yields across US counties. In each case, we demonstrate the performance of the research design by withholding important covariates during estimation. SFD has multiple appealing features, such as internal robustness checks that exploit rotation of the coordinate system or double-differencing across space, it is immediately applicable to spatially-gridded data sets, and it can be easily implemented in statical packages by replacing a single index in pre-existing time-series functions .
Revised:  The identifying assumptions of SFD are similar in mathematical structure and plausibility to other quasi-experimental designs. We use SFD to obtain new estimates for the effects of time-invariant geographic factors, soil and climate, on long-run agricultural productivities --- relationships crucial for economic decisions, such as land management and climate policy, but notoriously confounded by unobservables .
Edit intent: clarity
Original: A fundamental problem in linear programming, machine learning, and computational geometry is the%DIFDELCMD < {\it %%%  Convex Hull Membership (CHM)  : Given a point p and a subset S of n points in R^m, is p \in conv(S)?
Revised: %DIFDELCMD < {\it %%% Convex Hull Membership (CHM) : Given a point p and a subset S of n points in R^m, is p \in conv(S)?
Edit intent: coherence
Original: A fundamental problem in linear programming, machine learning, and computational geometry is the%DIFDELCMD < {\it %%%  Convex Hull Membership (CHM)  : Given a point p and a subset S of n points in R^m, is p \in conv(S)?
Revised: A fundamental problem in linear programming, machine learning, and computational geometry is the%DIFDELCMD < {\it %%% The it Convex Hull Membership (CHM) : Given a point p and a subset S of n points in R^m, is p \in conv(S)?
Edit intent: meaning-changed
Original: A fundamental problem in linear programming, machine learning, and computational geometry is the%DIFDELCMD < {\it %%%  Convex Hull Membership (CHM)  : Given a point p and a subset S of n points in R^m, is p \in conv(S)?
Revised: A fundamental problem in linear programming, machine learning, and computational geometry is the%DIFDELCMD < {\it %%% Convex Hull Membership (CHM) problem is : Given a point p and a subset S of n points in R^m, is p \in conv(S)?
Edit intent: clarity