Peer-to-peer (P2P) lending began as a kind of sharing economy within the field of finance. Using internet platforms, P2P lending attempts to offer an alternative to traditional financial institutions like banks. However, the P2P sector plays only a minor role in the finance industry in Israel, compared to the traditional banking system that suffers from an oligopoly structure. We conducted two studies in order to investigate this gap, comparing the dual connection between lenders and the platforms. In the first study, we conducted a conjoint analysis to examine the attributes that have higher utility for the lenders, and impact their decision to invest through the P2P platforms. In the second study, we shift the research prism toward the platforms, and examine the factors they use to determine the lending interest rate for loans, other than the borrowers’ financial condition. We found that although lenders wish to decrease their risk and guarantee their investment, P2P companies encourage borrowers, thereby increasing the risk inherit in lending to strangers. This contradiction between the priorities of the lenders and the platforms, may explain why the general public considers P2P lending highly risk, and avoids this financial tool. Based on our results, we offer a number of suggestions to increase the attractiveness of the industry.
{"title":"Lack of Competition in the Financial Market in Israel: The Conflict between the Needs of P2P Lenders and the Platforms’ Intentions","authors":"Galit Klein, Ze'ev Shtudiner, M. Zwilling","doi":"10.2139/ssrn.3700107","DOIUrl":"https://doi.org/10.2139/ssrn.3700107","url":null,"abstract":"Peer-to-peer (P2P) lending began as a kind of sharing economy within the field of finance. Using internet platforms, P2P lending attempts to offer an alternative to traditional financial institutions like banks. However, the P2P sector plays only a minor role in the finance industry in Israel, compared to the traditional banking system that suffers from an oligopoly structure. We conducted two studies in order to investigate this gap, comparing the dual connection between lenders and the platforms. In the first study, we conducted a conjoint analysis to examine the attributes that have higher utility for the lenders, and impact their decision to invest through the P2P platforms. In the second study, we shift the research prism toward the platforms, and examine the factors they use to determine the lending interest rate for loans, other than the borrowers’ financial condition. We found that although lenders wish to decrease their risk and guarantee their investment, P2P companies encourage borrowers, thereby increasing the risk inherit in lending to strangers. This contradiction between the priorities of the lenders and the platforms, may explain why the general public considers P2P lending highly risk, and avoids this financial tool. Based on our results, we offer a number of suggestions to increase the attractiveness of the industry.","PeriodicalId":142352,"journal":{"name":"Columbia: Decision","volume":"37 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124842753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The banking sector around the world has undergone significant changes in its environment, resulting on its performance on significant impact. The bank plays an important role in the economy because of the function play by the bank as a financial intermediary linking both units of surplus and deficit unit. There are many factors that can affect the bank performance. Therefore, this study was conducted to examine the effect of specific bank and macro-economic factors affecting bank performance at Ally Financial Bank, United State In order to achieve the objective of this study, time series regression analysis of Ally Financial Bank in United States with the period from 2013 to 2017 is used.
{"title":"Evaluating Bank Performing Management on Banking Industry","authors":"Mahmud Mohd Samsudin","doi":"10.2139/ssrn.3301927","DOIUrl":"https://doi.org/10.2139/ssrn.3301927","url":null,"abstract":"The banking sector around the world has undergone significant changes in its environment, resulting on its performance on significant impact. The bank plays an important role in the economy because of the function play by the bank as a financial intermediary linking both units of surplus and deficit unit. There are many factors that can affect the bank performance. Therefore, this study was conducted to examine the effect of specific bank and macro-economic factors affecting bank performance at Ally Financial Bank, United State In order to achieve the objective of this study, time series regression analysis of Ally Financial Bank in United States with the period from 2013 to 2017 is used.","PeriodicalId":142352,"journal":{"name":"Columbia: Decision","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117340206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many financial markets operate as electronic limit order books under a price-time priority rule. In this setting, among all resting orders awaiting trade at a given price, earlier orders are prioritized for matching with contra-side liquidity takers. This creates a technological arms race among high-frequency traders and other automated market participants to establish early (and hence advantageous) positions in the resulting first-in-first-out (FIFO) queue. We develop a model for valuing orders based on their relative queue position that incorporates both eco- nomic (informational) and stochastic modeling (queueing) aspects. Our model identifies two important components of positional value: (i) a static component that relates to the trade-off at an instant of trade execution between earning a spread and incurring adverse selection costs, and incorporates the fact that adverse selection costs are increasing with queue position; (ii) a dynamic component, that captures the optionality associated with the future value that accrues by locking in a given queue position. Our model offers predictions of order value at different positions in the queue as a function of market primitives, and can be empirically calibrated. We validate our model by comparing it with estimates of queue value realized in backtesting simulations and find the predictions to be accurate. Moreover, for some large tick-size stocks, we find that queue value can be of the same order of magnitude as the bid-ask spread. This suggests that accurate valuation of queue position is a necessary and important ingredient in considering optimal execution or market-making strategies for such assets.
{"title":"A Model for Queue Position Valuation in a Limit Order Book","authors":"C. Moallemi, Kai Yuan","doi":"10.2139/SSRN.2996221","DOIUrl":"https://doi.org/10.2139/SSRN.2996221","url":null,"abstract":"Many financial markets operate as electronic limit order books under a price-time priority rule. In this setting, among all resting orders awaiting trade at a given price, earlier orders are prioritized for matching with contra-side liquidity takers. This creates a technological arms race among high-frequency traders and other automated market participants to establish early (and hence advantageous) positions in the resulting first-in-first-out (FIFO) queue. We develop a model for valuing orders based on their relative queue position that incorporates both eco- nomic (informational) and stochastic modeling (queueing) aspects. Our model identifies two important components of positional value: (i) a static component that relates to the trade-off at an instant of trade execution between earning a spread and incurring adverse selection costs, and incorporates the fact that adverse selection costs are increasing with queue position; (ii) a dynamic component, that captures the optionality associated with the future value that accrues by locking in a given queue position. Our model offers predictions of order value at different positions in the queue as a function of market primitives, and can be empirically calibrated. We validate our model by comparing it with estimates of queue value realized in backtesting simulations and find the predictions to be accurate. Moreover, for some large tick-size stocks, we find that queue value can be of the same order of magnitude as the bid-ask spread. This suggests that accurate valuation of queue position is a necessary and important ingredient in considering optimal execution or market-making strategies for such assets.","PeriodicalId":142352,"journal":{"name":"Columbia: Decision","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115904591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study a supply chain where a retailer buys from a supplier who cannot fully finance her production. Informational problems about the supplier’s demand prospects and production capabilities restrict her access to capital. By committing to a minimum purchase quantity, the retailer can mitigate these informational problems and expand the supplier’s feasible production set. We assume a newsvendor model of operations and analyze the strategic interaction of the two parties as a sequential game. Key parameters in our model are the supplier’s ex-ante credit limit; her informational transparency (which conditions the amount of additional capital released by the commitment); and the demand characteristics of the final market. We show that in equilibrium the supplier can benefit from a lower ex-ante credit limit or lower informational transparency. The retailer always benefits from an increase in these parameters. Moreover, the supplier’s ex-ante credit limit and informational transparency may be substitutes or complements with respect to her own profit, but are always substitutes with respect to the retailer’s profit. Our study provides a novel perspective on capital market frictions in supply chain contracting.
{"title":"Purchase Order Financing: Credit, Commitment, and Supply Chain Consequences","authors":"M. Reindorp, Fehmi Tanrısever, A. Lange","doi":"10.2139/ssrn.2616812","DOIUrl":"https://doi.org/10.2139/ssrn.2616812","url":null,"abstract":"We study a supply chain where a retailer buys from a supplier who cannot fully finance her production. Informational problems about the supplier’s demand prospects and production capabilities restrict her access to capital. By committing to a minimum purchase quantity, the retailer can mitigate these informational problems and expand the supplier’s feasible production set. We assume a newsvendor model of operations and analyze the strategic interaction of the two parties as a sequential game. Key parameters in our model are the supplier’s ex-ante credit limit; her informational transparency (which conditions the amount of additional capital released by the commitment); and the demand characteristics of the final market. We show that in equilibrium the supplier can benefit from a lower ex-ante credit limit or lower informational transparency. The retailer always benefits from an increase in these parameters. Moreover, the supplier’s ex-ante credit limit and informational transparency may be substitutes or complements with respect to her own profit, but are always substitutes with respect to the retailer’s profit. Our study provides a novel perspective on capital market frictions in supply chain contracting.","PeriodicalId":142352,"journal":{"name":"Columbia: Decision","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115906074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider a multiperiod single product pricing problem with an unknown demand curve. The seller's objective is to adjust prices in each period so as to maximize cumulative expected revenues over a given finite time horizon; in doing so, the seller needs to resolve the tension between learning the unknown demand curve and maximizing earned revenues. The main question that we investigate is the following: How large of a revenue loss is incurred if the seller uses a simple parametric model that differs significantly i.e., is misspecified relative to the underlying demand curve? We measure performance by analyzing the price trajectory induced by this misspecified model and quantifying the magnitude of revenue losses as a function of the time horizon relative to an oracle that knows the true underlying demand curve. The "price of misspecification" is expected to be significant if the parametric model is overly restrictive. Somewhat surprisingly, we show under reasonably general conditions that this need not be the case. This paper was accepted by Gerard Cachon, stochastic models and simulation.
{"title":"On the (Surprising) Sufficiency of Linear Models for Dynamic Pricing with Demand Learning","authors":"Omar Besbes, A. Zeevi","doi":"10.2139/ssrn.1983274","DOIUrl":"https://doi.org/10.2139/ssrn.1983274","url":null,"abstract":"We consider a multiperiod single product pricing problem with an unknown demand curve. The seller's objective is to adjust prices in each period so as to maximize cumulative expected revenues over a given finite time horizon; in doing so, the seller needs to resolve the tension between learning the unknown demand curve and maximizing earned revenues. The main question that we investigate is the following: How large of a revenue loss is incurred if the seller uses a simple parametric model that differs significantly i.e., is misspecified relative to the underlying demand curve? We measure performance by analyzing the price trajectory induced by this misspecified model and quantifying the magnitude of revenue losses as a function of the time horizon relative to an oracle that knows the true underlying demand curve. The \"price of misspecification\" is expected to be significant if the parametric model is overly restrictive. Somewhat surprisingly, we show under reasonably general conditions that this need not be the case. \u0000 \u0000This paper was accepted by Gerard Cachon, stochastic models and simulation.","PeriodicalId":142352,"journal":{"name":"Columbia: Decision","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131848679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We characterize the equilibrium behavior in a broad class of competition models in which the competing firms' market shares are given by an attraction model, and the aggregate sales in the industry depend on the aggregate attraction value according to a general function. Each firm's revenues and costs are proportional with its expected sales volume, with a cost rate that depends on the firm's chosen attraction value according to an arbitrary increasing function. Whereas most existing competition papers with attraction models can be viewed as special cases of this general model, we apply our general results to a new set of quality competition models. Here an industry has N suppliers of a given product, who compete for the business of one or more buyers. Each of the suppliers encounters an uncertain yield factor, with a given general yield distribution. The buyers face uncertain demands over the course of a given sales season. The suppliers compete by selecting key characteristics of their yield distributions, either their means, their standard deviations, or both. These choices have implications for their per-unit cost rates.
{"title":"Competition Under Generalized Attraction Models: Applications to Quality Competition Under Yield Uncertainty","authors":"A. Federgruen, N. Yang","doi":"10.1287/mnsc.1090.1073","DOIUrl":"https://doi.org/10.1287/mnsc.1090.1073","url":null,"abstract":"We characterize the equilibrium behavior in a broad class of competition models in which the competing firms' market shares are given by an attraction model, and the aggregate sales in the industry depend on the aggregate attraction value according to a general function. Each firm's revenues and costs are proportional with its expected sales volume, with a cost rate that depends on the firm's chosen attraction value according to an arbitrary increasing function. Whereas most existing competition papers with attraction models can be viewed as special cases of this general model, we apply our general results to a new set of quality competition models. Here an industry has N suppliers of a given product, who compete for the business of one or more buyers. Each of the suppliers encounters an uncertain yield factor, with a given general yield distribution. The buyers face uncertain demands over the course of a given sales season. The suppliers compete by selecting key characteristics of their yield distributions, either their means, their standard deviations, or both. These choices have implications for their per-unit cost rates.","PeriodicalId":142352,"journal":{"name":"Columbia: Decision","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132924490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider a trader who aims to liquidate a large position in the presence of an arbitrageur who hopes to profit from the trader's activity. The arbitrageur is uncertain about the trader's position and learns from observed price fluctuations. This is a dynamic game with asymmetric information. We present an algorithm for computing perfect Bayesian equilibrium behavior and conduct numerical experiments. Our results demonstrate that the trader's strategy differs significantly from one that would be optimal in the absence of the arbitrageur. In particular, the trader must balance the conflicting desires of minimizing price impact and minimizing information that is signaled through trading. Accounting for information signaling and the presence of strategic adversaries can greatly reduce execution costs.
{"title":"The Execution Game","authors":"C. Moallemi","doi":"10.2139/ssrn.1916298","DOIUrl":"https://doi.org/10.2139/ssrn.1916298","url":null,"abstract":"We consider a trader who aims to liquidate a large position in the presence of an arbitrageur who hopes to profit from the trader's activity. The arbitrageur is uncertain about the trader's position and learns from observed price fluctuations. This is a dynamic game with asymmetric information. We present an algorithm for computing perfect Bayesian equilibrium behavior and conduct numerical experiments. Our results demonstrate that the trader's strategy differs significantly from one that would be optimal in the absence of the arbitrageur. In particular, the trader must balance the conflicting desires of minimizing price impact and minimizing information that is signaled through trading. Accounting for information signaling and the presence of strategic adversaries can greatly reduce execution costs.","PeriodicalId":142352,"journal":{"name":"Columbia: Decision","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129204059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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