wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We prove several versions of such a result for general distortion risk measures of V@R-type, explicitly construct suitable allocations of the group portfolio, and finally demonstrate how these findings can be extended beyond distortion risk measures  .
Revised:  We prove several versions of such a result for general distortion risk measures of V@R-type, explicitly construct suitable allocations of the group portfolio, and finally demonstrate how these findings can be extended beyond distortion risk measures . We also discuss why consolidation requirements cannot completely eliminate this problem. Capital regulation should thus be based on coherent or convex risk measures like average value at risk or expectiles .
Edit intent: meaning-changed
Original: In this paper, we investigate conditions to represent derivative price under XVA explicitly. As long as we consider different borrowing/lending rates, XVA problem becomes a non-linear equa- tion and this makes finding explicit solution of XVA difficult.
Revised: In this paper, we investigate conditions to convert nonlinear equations of XVA to linear equations. As we consider different borrowing/lending rates, XVA problem becomes a non-linear equa- tion and this makes finding explicit solution of XVA difficult.
Edit intent: clarity
Original: In this paper, we investigate conditionsto convert nonlinear equations of XVA to linear equations. As we consider different borrowing/lendingrates, pricing derivatives encounters a non-linear equation and this makes finding an analytic solution for the price with the XVA difficult. Thus, in general, we have to resort to expensive numerical computation. In most previous works, the attempts to find an analytic solution were conducted on a restrictive assumption that the borrowing / lending rates are same.
Revised: We discuss a binary nature of funding impacts. Under some conditions, funding is either cost or benefit, i.e., one of the lending / lending rates are same.
Edit intent: meaning-changed
Original:  In most previous works, the attempts to find an analytic solution were conducted on a restrictive assumption that the borrowing / lending rates are same. We find conditions to relax the assumption. Moreover, the conditions are mild in the sense that it is often satisfied in practice .
Revised:  In most previous works, the attempts to find an analytic solution were conducted on a restrictive assumption that the borrowing / borrowing rates does not play any role in pricing derivatives. When we price derivatives, considering different lending/borrowing rates leads to semi-linear BSDEs and PDEs, so we need to solve the equations numerically. However, once we can guarantee that only one of the rates affects pricing, we can recover linear equations and derive analytic formulae. Moreover, as a byproduct, our results explain how debt value adjustment (DVA) and funding benefits are different. It is often believed that DVA and funding benefits are overlapped but it will be shown that the two components are affected by different mathematical structures of derivative transactions. We will see later that FBA occurs where the payoff is non-increasing, but this relationship becomes weaken as the funding choices of underlying assets are transferred to repo markets .
Edit intent: meaning-changed
Original:  The aim of the document is to gather in one place the relevant material that can help the researcher in the field to have a bigger picture, the quantitative researcher to play with this alternative modeling of the financial time series , and the decision maker to leverage the insightsobtained from these methods.
Revised:  The aim of this review is to gather in one place the relevant material that can help the researcher in the field to have a bigger picture, the quantitative researcher to play with this alternative modeling of the financial time series , and the decision maker to leverage the insightsobtained from these methods.
Edit intent: clarity
Original:  The aim of the document is to gather in one place the relevant material that can help the researcher in the field to have a bigger picture, the quantitative researcher to play with this alternative modeling of the financial time series , and the decision maker to leverage the insightsobtained from these methods.
Revised:  The aim of the document is to gather in one place the relevant material from different fields, e.g. machine learning, information geometry, econophysics, statistical physics, econometrics, behavioral finance. We hope it will help researchers to use more effectively this alternative modeling of the financial time series , and the decision maker to leverage the insightsobtained from these methods.
Edit intent: meaning-changed
Original:  The aim of the document is to gather in one place the relevant material that can help the researcher in the field to have a bigger picture, the quantitative researcher to play with this alternative modeling of the financial time series , and the decision maker to leverage the insightsobtained from these methods. We hope that this document will form a basis for implementation of an open toolbox of standard tools to study correlations, hierarchies, networks and clustering in financial markets.
Revised:  The aim of the document is to gather in one place the relevant material that can help the researcher in the field to have a bigger picture, the quantitative researcher to play with this alternative modeling of the financial time series . Decision makers and quantitative researchers may also be able to leverage its insights. Finally, we also hope that this document will form a basis for implementation of an open toolbox of standard tools to study correlations, hierarchies, networks and clustering in financial markets.
Edit intent: clarity
Original:  We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cots is a faction of NMF's.
Revised:  We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cost is a fraction of NMF's.
Edit intent: fluency
Original:  Such a programme require monitoring of end-use appliances energy consumption in real-time . The worldwide recent adoption of smart-meter in smart-grid, has led to the rise of Non-Intrusive Load Monitoring (NILM); which enables estimation of appliance-specific power consumption from building's aggregate power consumption reading. NILM provides households with cost-effective real-time monitoring of end-use appliances to help them understand their consumption pattern and become part and parcel of energy conservation strategy .
Revised:  Such a programme require monitoring of end-use appliances energy consumption in real-time .
Edit intent: coherence
Original:  We investigate the dynamics of the quantum correlations generated through two hydrogen bonds between a prototypical enzyme and a substrate , and discuss the possibility of utilizing these correlationsas a resource in the catalytic power of the enzyme .
Revised:  We investigate the dynamics of the quantum correlations generated through two hydrogen bonds between a substrate and a prototypical enzyme that first catalyzes the tautomerization of the substrate to move on to a subsequent catalysis , and discuss the possibility of utilizing these correlationsas a resource in the catalytic power of the enzyme .
Edit intent: meaning-changed
Original:  If the enzyme suddenly returns to its initial state after the binding stage, the substrate ends in a quantum superposition state. Environmental effects can then naturally drive the reaction in the forward direction from the substrate to the product without needing the additional catalytic stage that is usually assumed to follow the binding stage .
Revised:  If the enzyme suddenly returns to its initial state after the binding stage, the substrate ends in a new transition state corresponding to a quantum superposition. Open quantum system dynamics can then naturally drive the reaction in the forward direction from the substrate to the product without needing the additional catalytic stage that is usually assumed to follow the binding stage .
Edit intent: clarity
Original:  Our construction), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }\newline  is inspired by a new interpretation of the quasiconvex duality and naturally leads to the introduction of the general class of Value\&Risk measures .
Revised:  We introduce a general class of Value\&Risk (V\&R) measures as a function of (p,X,\mathbb{P), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }\newline is inspired by a new interpretation of the quasiconvex duality and naturally leads to the introduction of the general class of Value\&Risk measures .
Edit intent: meaning-changed
Original:  Our construction), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }\newline  is inspired by a new interpretation of the quasiconvex duality and naturally leads to the introduction of the general class of Value\&Risk measures .
Revised:  Our construction), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }\newline Our approach is inspired by a new interpretation of the quasiconvex duality and naturally leads to the introduction of the general class of Value\&Risk measures .
Edit intent: clarity
Original:  Our construction), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }\newline  is inspired by a new interpretation of the quasiconvex duality and naturally leads to the introduction of the general class of Value\&Risk measures .
Revised:  Our construction), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }\newline is inspired by a new interpretation of the quasiconvex duality in a Knightian setting, where a family of probability measures replaces the single reference probability and is then applied to value financial positions. Diametrically, our construction of V\&R measures is based on the selection of a basket of claims to test the reliability of models .
Edit intent: meaning-changed
Original:  We introduce a general class of Value\&Risk (V\&R) measures as a function of (p,X,\mathbb{P), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }%DIFDELCMD < \newline %%% Our approach is inspired by a new interpretation of the quasiconvex duality in a Knightian setting, where a family of probability measures replaces the single reference probability and is then applied to value financial positions.
Revised:  ), where p is the observed initial value of X or is assigned by \pi _{P}(X) under the probability P. }%DIFDELCMD < \newline %%% Our approach is inspired by a new interpretation of the quasiconvex duality in a Knightian setting, where a family of probability measures replaces the single reference probability and is then applied to value financial positions.
Edit intent: clarity
Original:  Diametrically, our construction of V\&R measures is based on the selection of a basket of claims to test the reliability of models  .
Revised:  Diametrically, our construction of V\&R measures is based on the selection of a basket of claims to test the reliability of models . We compare a random payoff X with a given class of derivatives written on X , and use these derivatives to \textquotedblleft test\textquotedblright\ the pricing measures. We further introduce and study a general class of Value\&Risk measures \% R(p,X,\mathbb{P .
Edit intent: meaning-changed
Original:  We provide a simple linear formula characterizing agents' actions in terms of paths in the network and use this formula to determine when society learns correctly in the long-run. Because early agents are disproportionately influential, standard network structures can lead to herding on incorrect beliefs .
Revised:  We provide a simple linear formula characterizing agents' actions in terms of paths in the network and use this formula to determine when society eventually learns correctly. Disproportionately influential early agents can cause herding on incorrect beliefs .
Edit intent: clarity
Original:  Because early agents are disproportionately influential, standard network structures can lead to herding on incorrect beliefs . The probability of mislearning increases when link densities are higher and when networks are more integrated. When actions can only communicate limited information, segregated networks often lead to persistent disagreement between groups.
Revised:  Because early agents are disproportionately influential, standard network structures can lead to herding on incorrect beliefs and we compute comparative statics of the probability of herding with respect to network parameters. When networks are segregated, divergent early signals can lead to persistent disagreement between groups.
Edit intent: meaning-changed
Original:  We provide a simple linear formula characterizing agents' actions in terms of network paths and use this formula to determine when society eventually learns correctly . Disproportionately influential early agents can cause herding on incorrect beliefs and we compute comparative statics of the probability of  herding with respect to network parameters.
Revised:  We provide a simple linear formula expressing agents' actions in terms of network paths and use this formula to determine when society eventually learns correctly . Disproportionately influential early agents can cause herding on incorrect beliefs and we compute comparative statics of the probability of herding with respect to network parameters.
Edit intent: clarity
Original:  We provide a simple linear formula characterizing agents' actions in terms of network paths and use this formula to determine when society eventually learns correctly . Disproportionately influential early agents can cause herding on incorrect beliefs and we compute comparative statics of the probability of  herding with respect to network parameters.
Revised:  We provide a simple linear formula characterizing agents' actions in terms of network paths and use this formula to completely characterize the set of networks allowing eventual correct learning . Disproportionately influential early agents can cause herding on incorrect beliefs and we compute comparative statics of the probability of herding with respect to network parameters.
Edit intent: meaning-changed
Original:  We provide a simple linear formula characterizing agents' actions in terms of network paths and use this formula to determine when society eventually learns correctly . Disproportionately influential early agents can cause herding on incorrect beliefs and we compute comparative statics of the probability of  herding with respect to network parameters.
Revised:  We provide a simple linear formula characterizing agents' actions in terms of network paths and use this formula to determine when society eventually learns correctly . Disproportionately influential early agents can cause herding on incorrect beliefs ; we compute comparative statics of the probability of herding with respect to network parameters.
Edit intent: coherence
Original:  We provide a simple linear formula characterizing agents' actions in terms of network paths and use this formula to determine when society eventually learns correctly . Disproportionately influential early agents can cause herding on incorrect beliefs and we compute comparative statics of the probability of  herding with respect to network parameters.
Revised:  We provide a simple linear formula characterizing agents' actions in terms of network paths and use this formula to determine when society eventually learns correctly . Disproportionately influential early agents can cause herding on incorrect beliefs and we compute comparative statics of the probability of incorrect herding with respect to network parameters.
Edit intent: fluency
Original:  Agents wrongly believe their predecessors act solely on private information , so they neglect redundancies among observed actions .
Revised:  Agents apply a heuristic rule to aggregate predecessors' actions. They weigh these actions according the strengths of their social connections to different predecessors. We show this rule arises endogenously when agents wrongly believe others act solely on private information , so they neglect redundancies among observed actions .
Edit intent: meaning-changed
Original:  The estimated twist-bend coupling coefficient from oxDNA simulations is G=30 (1) nm, in agreement with the value obtained from a recent analysis of magnetic tweezers data (G=40(10) nm) \pm1 \approx 80~nm, which is different from the intrinsic torsional stiffness C \approx 110~nm.
Revised:  The estimated twist-bend coupling coefficient from oxDNA simulations is G=30 \pm1 \approx 80~nm, which is different from the intrinsic torsional stiffness C \approx 110~nm.
Edit intent: coherence
Original:  The estimated twist-bend coupling coefficient from oxDNA simulations is G=30 (1) nm, in agreement with the value obtained from a recent analysis of magnetic tweezers data (G=40(10) nm) \pm1 \approx 80~nm, which is different from the intrinsic torsional stiffness C \approx 110~nm.
Revised:  The estimated twist-bend coupling coefficient from oxDNA simulations is G=30 (1) nm, in agreement with the value obtained from a recent analysis of magnetic tweezers data (G=40(10) nm) \pm1~nm. The groove asymmetry induces a novel twist length scale and an associated renormalized twist stiffness \kappa_{\rm t \approx 80~nm, which is different from the intrinsic torsional stiffness C \approx 110~nm.
Edit intent: meaning-changed
Original:  In this paper, we propose a novel measure for aggregate market risk based on news network and news tones, namely media connection index (MCI) . We show that the change of MCI predicts a negative return with a higher in-sample and out-of-sample performance than average correlation index in Pollet and Wilson (2010).
Revised:  In this paper, we propose a novel measure for aggregate market risk based on news network and news tones, namely media connection index (MCI) , using news tones of media news that mentions more than one stocks to proxy effects that induced by additional attention, i.e. sentiment spillover, sentiment co-movement and connected news coverage. In general, we show our predictors are powerful and outperform other predictors, such as sentiment indices and economic predictors, in terms of both in-sample and out-of-sample performance than average correlation index in Pollet and Wilson (2010).
Edit intent: meaning-changed
Original:  We show that the change of MCI predicts a negative return with a higher in-sample and out-of-sample performance than average correlation index in Pollet and Wilson (2010). In addition, our findings are also statistically as well as economically significant even though we control for different economic predictorsused in Goyal and Welch (2008). We also find this measure is capable of predicting cross-sectional stock returns sorted by B/M, size, momentum, industry, investment and profitability. Further analysis shows that the predictability of our measure mainly comes from the negative tones which is consistent with Tetlock (2007) .
Revised:  We show that the change of MCI predicts a negative return with a higher in-sample and out-of-sample predictability. In-depth analysis show that the predictability of our measure mainly comes from the negative tones which is consistent with Tetlock (2007) .
Edit intent: clarity
Original: Investor attention has long been noticed as an important driving force of stock returns. A large number of papers have been focusing on providing direct or indirect proxies for overall investor attention . However, we believe that additional attention is a more crucial driver than overall attention in affecting stock returns . In this paper, we propose a new class of predictors, media connection indices (MCI), using news tones of media news that mentions more than one stocks to proxy effects that induced by additional attention , i.e. sentiment spillover, sentiment co-movement and connected news coverage.
Revised: We examine the effect of investor attention spillover on stock return predictability. Using a novel measure, the News Network Triggered Attention index (NNTA), we find that NNTA negatively predicts market returns with a monthly in(out)-of-sample R-square of 5.97\% (5.80\%). In the cross-section, a long-short portfolio based on news co-occurrence generates a significant monthly alpha of 68 basis points. The results are robust to the inclusion of alternative attention proxies, sentiment co-movement and connected news coverage.
Edit intent: meaning-changed
Original:  In this paper, we propose a new class of predictors, media connection indices (MCI), using news tones of media news that mentions more than one stocks to proxy effects that induced by additional attention , i.e. sentiment spillover, sentiment co-movement and connected news coverage. In general, we show our predictors are powerful and outperform other predictors, such as sentiment indices and economic predictors, in terms of both in-sample and out-of-sample predictability. In-depth analysis show that the predictability of MCI mainly comes from negative news tones which is consistent with \mbox{%DIFAUXCMD Tetlock2008 .
Revised:  In this paper, we propose a new class of predictors, media connection indices (MCI), using news tones of media news that mentions more than one stocks to proxy effects that induced by additional attention , i.e. sentiment spillover, sentiment measures, other news- and information-based predictors, across recession and expansion periods. We further validate the attention spillover effect by showing that news co-mentioning leads to greater increases in Google and Bloomberg search volumes than unconditional news coverage. Our findings suggest that attention spillover in a news-based network can lead to significant stock market overvaluations, and especially when arbitrage is limited .
Edit intent: meaning-changed
Original: A recent formulation of random-phase-approximation polymer theory for disordered protein phase separation is applied to investigate how the tendency for multiple chains of a protein to phase separate, as characterized by the critical temperature T^*_{\rm cr}, is related to the protein's single-chain average radius of gyration \langle R _g \rangle.
Revised: Liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is a major undergirding factor in the regulated formation of URLanelles in the cell. The phase behavior of an IDP is sensitive to its amino acid sequence. Here we apply a recent random-phase-approximation polymer theory for disordered protein phase separation is applied to investigate how the tendency for multiple chains of a protein to phase separate, as characterized by the critical temperature T^*_{\rm cr}, is related to the protein's single-chain average radius of gyration \langle R _g \rangle.
Edit intent: meaning-changed
Original: A recent formulation of random-phase-approximation polymer theory for disordered protein phase separation is applied to investigate how the tendency for multiple chains of a protein to phase separate, as characterized by the critical temperature T^*_{\rm cr}, is related to the protein's single-chain average radius of gyration \langle R _g \rangle.
Revised: A recent formulation of random-phase-approximation polymer theory to investigate how the tendency for multiple chains of a protein to phase separate, as characterized by the critical temperature T^*_{\rm cr}, is related to the protein's single-chain average radius of gyration \langle R _g \rangle.
Edit intent: clarity