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نتیجه جستجو - Financial markets

تعداد مقالات یافته شده: 40
ردیف عنوان نوع
1 Valuing Supply Chain Performance Within and Across Manufacturing Industries: A DEA-based Approach
ارزش گذاری عملکرد زنجیره تأمین در داخل و سراسر صنایع تولیدی: رویکردی مبتنی بر DEA-2021
Journal Pre-proof Managers often use financial metrics based on internal accounting data to gauge firm performance. In this paper, we analyze firm value and related levers of operational supply chain (SC) performance from a financial market perspective. This allows us to study the contributions of profitability (earns) and asset utilization (turns) as the two major drivers of firm value. For this purpose, we apply data envelopment analysis to a large-scale longitudinal dataset of listed US companies (2007–2015) that covers 13 manufacturing industries. In so doing, we shed light on the implications of the 2008/2009 financial crisis for operational SC performance. Our findings can be summarized as follows: First, earns and turns are negatively correlated from an internal accounting-based viewpoint that distinguishes ‘high earns/low turns’ from ‘low earns/high turns’ industries. Second, manufacturing com-∗Phone +49-7131-645636-826, fax +49-7131-645636-27Email addresses: gerd.hahn@ggs.de (G.J. Hahn),marcus.brandenburg@hs-flensburg.de (M. Brandenburg), jochen.becker@iname.com(J. Becker)Preprint submitted to International Journal of Production Economics April 16, 2021panies mostly tend to be less efficient in translating earns as opposed to turns into firm value. Finally, we observe declining efficacy of approaches to value- based supply chain management in manufacturing industries since 2007 (the last year before the financial crisis). General firm value appreciation in the stock markets overcompensated for this decline until 2015.
Keywords: DEA | Supply Chain Management | Performance Measurement | Financial Markets
مقاله انگلیسی
2 The global financial crisis, the EMU sovereign debt crisis and international financial regulation: lessons from a systematic literature review
بحران مالی جهانی ، بحران بدهی دولتی EMU و مقررات مالی بین المللی: درسهایی از مرور ادبیات سیستماتیک-2020
To ensure the safety and soundness of the global financial system as well as individual financial institutions and to reduce systemic risk, numerous policy measures and regulatory reforms have been brought forward as a reaction to the Global Financial Crisis and the European Sovereign Debt Crisis. Simultaneously, numerous academic works have critically reviewed these developments. Therefore, based on a dataset of 455 papers, this article intends to structure the multitude of publications and provide a comprehensive overview of post-crisis regulatory research publications. Studies can be roughly divided into three overarching clusters: publications identifying causes of the crisis, articles focusing on policy and reform reactions, and literature investigating whether these reforms fit their purpose. A holistic and systematic review allows us to extract relevant recommendations and areas of action to prevent such a crisis in the future.
Keywords: EMU | Sovereign debt crisis | Global financial crisis | Financial regulation | Banking sector | Insurance industry | Financial markets | Policy reform
مقاله انگلیسی
3 Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets
رویای یادگیری ماشین: پسوندهای Lipschitz برای یادگیری تقویتی در بازارهای مالی-2020
We consider a quasi-metric topological structure for the construction of a new reinforcement learning model in the framework of financial markets. It is based on a Lipschitz type extension of reward func- tions defined in metric spaces. Specifically, the McShane and Whitney extensions are considered for a reward function which is defined by the total evaluation of the benefits produced by the investment decision at a given time. We define the metric as a linear combination of a Euclidean distance and an angular metric component. All information about the evolution of the system from the beginning of the time interval is used to support the extension of the reward function, but in addition this data set is enriched by adding some artificially produced states. Thus, the main novelty of our method is the way we produce more states—which we call “dreams”—to enrich learning. Using some known states of the dynamical system that represents the evolution of the financial market, we use our technique to sim- ulate new states by interpolating real states and introducing some random variables. These new states are used to feed a learning algorithm designed to improve the investment strategy by following a typical reinforcement learning scheme.
Keywords: Pseudo-metric | Reinforcement learning | Lipschitz extension | Mathematical economics | Financial market | Model
مقاله انگلیسی
4 Enforceability and the effectiveness of laws and regulations
قابلیت اجرا و اثربخشی قوانین و مقررات-2020
A major threat to the development of financial markets in emerging markets is “tunneling.” In China, this took on the form of controlling shareholders diverting assets from listed firms or coercing firms to serve as guarantors on questionable loans. A new set of rules enacted in 2005 prohibited asset diversion for “non-operational” purposes. Firms complying with these rules have experienced a reduction in related party transactions, an increase in investment, and better performance. In contrast, another set of contemporary rules, which aimed to standardize the practice of firms providing loan guarantees, has had very little impact. We attribute the contrasting design, implementation, and effectiveness of these two sets of rules to the difference in enforcement costs of the two types of tunneling activities. Relative to loan guarantees, it is much easier for a third party to determine (ex ante) whether a particular form of diversion destroys firm value, and to verify (ex post) that the losses to the firm resulted from the diversion. Our results highlight the importance of enforceability—laws and regulations that can be enforced at lower costs are more likely to succeed, especially in countries with underdeveloped formal institutions.
Keywords: Enforceability | Controlling shareholder | Tunneling | Loan guarantee | Asset diversion
مقاله انگلیسی
5 اهمیت تاثیرات تقویم در بازار برق
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 28
چگونگی هماهنگی عرضه و تقاضا تبدیل به یک سوال طولانی مدت در بازار برق شده است، و ناهنجاری های مرتبط با اشکالات تقویم عوامل بحرانی برای تخصیص منابع هستند. این مقاله یک روش ارزیابی اهمیت تمام تاثیرات ممکن در فرکانس های زمانی متفاوت معرفی می‌کند. ما روش تست خودمان را در بزرگ ترین پلت فرم معاملات برق در ایالات متحده پیاده سازی می‌کنیم. با استفاده از اطاعات معاملات روزانه فرکانس بالا، تاثیرات تقویم در فرکانس های زمانی متفاوت (روز-از-هفته، ساعت-از-روز، ماه-از-سال، روز-از-ماه و فصل) را ارزیابی می‌کنیم. نتایج ما وجود تاثیرات تقویم در هر بعد از فرکانس زمانی، و مخصوصا آن تاثیرات تقویم با اهمیت آماری را تایید می کند. علاوه بر آن، این مطالعه وجوه اشتراک بین بازارهای برق و بازار های پولی که امکان درخواست مدیریت بازار های پولی به بازار های برق را کشف می‌کند. در کنار آن، تاثیرات شناسایی شده تقویم الگو های دوره ای تعادل بازار و تسهیل پیاده سازی راه حل های فنی صحیح در بازار های برق را شرح می‌دهد.
کلید واژه ها: تاثیرات تقویم | بازار برق PJM | قیمت برق | نوسان قیمت
مقاله ترجمه شده
6 Anticipating bank distress in the Eurozone: An Extreme Gradient Boosting approach
پیش بینی بحران مالی بانک ها در منطقه یورو: یک رویکرد تقویت گرادیان شدید-2019
The banking sector plays a special role in the economy and has critical functions which are essential for economic stability. Hence, systemic banking crises disrupt financial markets and hinder global economic growth. In this study, Extreme Gradient Boosting, a state of the art machine learning method, is applied to identify a set of key leading indicators that may help predict and prevent bank failure in the Eurozone banking sector. The crosssectional data used in this study consists of 25 annual financial ratio series for commercial banks in the Eurozone. The sample includes Eurozone listed failed and non-failed banks for the period 2006–2016. A number of early warning systems and leading indicator models have been developed to prevent bank failure. Yet the breadth and depth of the recent financial crisis indicates that these methods must improve if they are to serve as a useful tool for regulators and managers of financial institutions. Our goal is to build a classification model to determine which variables should be monitored to anticipate bank financial distress. A set of key variables are identified to anticipate bank defaults. Identifying leading indicators of bank failure is necessary so that regulators and financial institutions management can take preventive and corrective measures before it is too late.
Keywords: Bank failure prediction | Bank failure prevention | Bank financial distress | Machine learning | Extreme Gradient Boosting |XGBoost
مقاله انگلیسی
7 An agent-based system with temporal data mining for monitoring financial stability on insurance markets
سیستم مبتنی بر نمایندگی با داده کاوی زمانی برای نظارت بر ثبات مالی در بازارهای بیمه-2019
We describe an expert system to monitor the stability of insurance markets. It consists of two compo- nents: an agent-based simulation component and a temporal data mining component. Like other financial markets, insurance markets experience destabilizing cycles and suffer episodic crises. The expert system assists market regulators by monitoring the financial position of individual insurers and of the overall market, and by forecasting cycles and impending insolvencies. The agent-based simulation component runs a forward simulation allowing for interaction among insurers in a competitive market, and between insurers and customers. The temporal data mining component extracts useful information for market reg- ulators from the simulations. A prototype of the system is applied to the automobile insurance market. We show how the system may be used to forecast cycles, investigate stability, and analyze insurers’ herd- ing behavior on the market. A practical policy conclusion is that regulators should monitor individual in- surers’ pricing pattern because aggressive price undercutting creates a “winner’s curse”, with subsequent losses and market instability.
Keywords: Agents | Motif | Anomaly | Cycle | Crisis | Automobile insurance
مقاله انگلیسی
8 Growing up without finance
رشد بدون مالی-2019
Early life exposure to local financial institutions increases household financial inclusion and leads to long-term improvements in consumer credit outcomes. We identify the effect of local financial markets using Congressional legislation that led to unintended differences in financial market development across Native American reservations. Individuals from finan- cially underdeveloped reservations enter consumer credit markets later, and upon reaching adulthood, have ten point lower credit scores and four percentage point more delinquent accounts. These effects are long-lived and depreciate slowly after individuals move to more developed areas. Formative exposures to local banking improve consumer credit behavior by increasing financial literacy and financial trust.
Keywords: Household finance | Native American reservations | Formative exposures | Financial development | Local banking
مقاله انگلیسی
9 Predicting failure in the U:S: banking sector: An extreme gradient boosting approach
پیش بینی شکست در بخش بانکی ایالات متحده: رویکرد افزایش شدید شیب-2019
Banks play a central role in developed economies. Consequently, systemic banking crises destabilize financial markets and hamper global economic growth. In this study, extreme gradient boosting was used to predict bank failure in the U.S. banking sector. Key variables were identified to anticipate and prevent bank defaults. The data, which spanned the period 2001 to 2015, consisted of annual series of 30 financial ratios for 156 U.S. national commercial banks. Identifying leading indicators of bank failure is vital to help regulators and bank managers act swiftly before distressed financial institutions reach the point of no return. The findings indicate that lower values for retained earnings to average equity, pretax return on assets, and total risk-based capital ratio are associated with a higher risk of bank failure. In addition, an exceedingly high yield on earning assets increases the chance of bank financial distress.
Keywords: Bank failure prediction | Bank failure prevention | Bank financial distress | Machine learning | Extreme gradient boosting | XGBoost
مقاله انگلیسی
10 An agent-based system with temporal data mining for monitoring financial stability on insurance markets
سیستم مبتنی بر نمایندگی با داده کاوی زمانی برای نظارت بر ثبات مالی در بازارهای بیمه-2019
We describe an expert system to monitor the stability of insurance markets. It consists of two compo- nents: an agent-based simulation component and a temporal data mining component. Like other financial markets, insurance markets experience destabilizing cycles and suffer episodic crises. The expert system assists market regulators by monitoring the financial position of individual insurers and of the overall market, and by forecasting cycles and impending insolvencies. The agent-based simulation component runs a forward simulation allowing for interaction among insurers in a competitive market, and between insurers and customers. The temporal data mining component extracts useful information for market reg- ulators from the simulations. A prototype of the system is applied to the automobile insurance market. We show how the system may be used to forecast cycles, investigate stability, and analyze insurers’ herd- ing behavior on the market. A practical policy conclusion is that regulators should monitor individual in- surers’ pricing pattern because aggressive price undercutting creates a “winner’s curse”, with subsequent losses and market instability.
Keywords: Agents | Motif | Anomaly | Cycle | Crisis | Automobile insurance
مقاله انگلیسی
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