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Èý¸öÉó¸åÒâ¼û£¬Á½¸ö±È½ÏÕýÃæ£¬×îºóÒ»¸öÓеã³Ô²»×¼¡£±à¼¸øÁËmajor revision¡£ reviewer 1: ...Overall, this is a very interesting and well executed paper. I have some questions and some suggestions for improvement, where the latter ones refer mainly to structure, motivation and readability. As the model is novel and, in my view, adds something important to the literature, the paper could make a valuable contribution to XXXX after a careful revision.... reviewer 1ÁÐÁËÆß°ËÌõÒâ¼û£¬µ«¶¼²»Ì«Äѻش𡣠reviewer 2: ...To the best of my knowledge, the authors are right that they are the first to carefully analyze a tractable equilibrium model with both belief heterogeneity and prospect-theory preferences. Theorems 1 and 2 are interesting, and so is the empirical exercise in section 4. As explained by the authors, prediction markets constitute a growing toolbox for aggregating probability forecasts. The theoretical literature discussed by the authors has aimed to improve on this toolbox, in part by better understanding the actual behavior of market participants. The present article is a very good contribution to this theoretical literature.... reviewer 2ÁÐÁË18ÌõÐÞ¸ÄÒâ¼û£¬µ«´ó²¿·Ö¶¼ÊÇÖ¸³öһЩtypoÍâ¼ÓһЩÓïÑÔÐðÊöÉϵĽ¨Ò飬×ÜÌåÒ²»¹ºÃ¡£ reviewer 3: This paper is interesting and engaging to read. ...The model and market equilibrium appear to be sound and are well-explained. Modelling prospect theory is not my area of expertise but the authors do a good job at explaining this to the non-expert. The paper is technical in nature and appears to be well-executed. I do have a number of substance concerns that that authors might consider. Each of these is discussed further below. The most concerning is whether the FLB or rFLB bias is actually the appropriate lens to empirically test a binary (win/lose or home/away) outcome. In my mind, this is not what the FLB or rFLB is about. ... ÎҸоõreviewer 3¹À¼Æ¶ÔÕâ¸ötopic²»ÊÇÌ«Á˽⣬Ëû¶ÔÎÒÃǵÄÄ£Ð͵ÄÊÊÓÃÐÔºÍһЩ»ù´¡¼ÙÉèÌá³öÁËÒÉÎÊ£¬µ«Êµ¼ÊÉÏÕâЩ¼ÙÉèÔÚÁìÓòÄÚËãÊDZȽϳ£¼ûµÄ×ö·¨¡£Ç°Á½Î»Éó¸åÈËÃ÷ÏÔ¶ÔÕâ¸ötopic±È½ÏÁ˽⣬Òò´Ë¶ÔÕâЩ¼ÙÉèûÓÐÌá³öÖÊÒÉ¡£ÕâÖÖÇé¿öÏÂÈç¹ûÎÒÒýһЩÁìÓòÄÚµÄÏà¹ØÎÄÏ×À´Ö¤Ã÷¼ÙÉèµÄºÏÀíÐÔ£¬ÊÇ·ñÓлú»áŤתreviewer 3µÄÓ¡Ïó£¿ |
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