با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
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1 |
Effects of IFRS-13 on the relevance of fair value adjusted by credit risk: Evidence from Europe
تاثیرات IFRS-13 روی مناسب بودن ارزش کالای تنظیم شده توسط خطر اعتباری: شواهدی از اروپا-2018 Accounting harmonization in Europe by International Financial Reporting Standard adoption is a recurrent object of study in the accounting literature. In this paper the consequences of the adoption of Standard-13 are analyzed. In particular, this research analyzes the effects on the implied volatility option (risk) for non-financial companies of three variables: financial leverage, own probability default (Debt Value Adjusted) and financial institutions credit risk (Credit Value Adjusted), before and after the adoption of the accounting standard on fair value. The empirical study focuses on member companies of the European Monetary Union zone to avoid other risk factors different to market risk (such as exchange rate or different risk free rate) and at the same time, easily identify the market portfolio (EUROSTOXX-50). To overcome the problems of endogeneity in the panel data, we use the technique System Generalized Method of Moments with instrumental variables to estimate the parameters. The results show that the leverage effect on excess risk does not change after adopting the Standard, however, its own and the financial institutions default probabilities become statistically significant. Furthermore, this novel methodology allows estimate industry asset betas and, in all cases the asset betas were lower than equity betas and, found an average debt beta of 0.4 for the sample period.
keywords: Credit Value Adjust|Debt Value Adjust|Fair value|Industry beta|Volatility |
مقاله انگلیسی |
2 |
بررسی کارایی شرکت های مالی در مالزی با استفاده از مدل تحلیل پوششی داده ها
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 11 - تعداد صفحات فایل doc فارسی: 13 نسبت مالی و ریسک، شاخص های مالی مهمی برای ارزیابی عملکرد مالی یا کارایی شرکت ها هستند. بنابراین، برای ارزیابی کارایی شرکتها با مدل تحلیل پوششی دادهها (DEA) باید نسبت مالی و عامل ریسک بررسی شوند. در مدل DEA، کارایی شرکت به صورت نسبت خروجیهای وزندار به مجموع ورودیهای وزن دارد اندازهگیری میشود. هدف این مقاله ارائه یک مدل DEA با ترکیب نسبت مالی و عامل ریسک در ارزیابی و مقایسه کارایی شرکتهای مالی در مالزی است. در این مطالعه، شرکت های مالی پذیرفته شده در بورس مالزی از سال 2004 تا 2015 مورد بررسی قرار گرفته است. نتایج این مطالعه نشان میدهد که شرکتهای AFFIN، ALLIANZ، APEX، BURSA، HLCAP، HLFG، INSAS، LPI، MNRB، OSK، PBBANK، RCECAP و TA جز شرکت های کارآمد رتبه بندی شده اند. این نشان می دهد که این شرکت های کارآمد از منابع یا ورودی های خود به طور بهینه برای تولید حداکثر خروجی استفاده کرده اند. این مطالعه حائز اهمیت است زیرا به شناسایی شرکت های مالی کارآمد و همچنین تعیین وزن ورودی و خروجی بهینه در به حداکثر رساندن کارایی شرکت های مالی در مالزی کمک می کند. |
مقاله ترجمه شده |
3 |
Big Data techniques to measure credit banking risk in home equity loans
تکنیک های داده های بزرگ برای اندازه گیری ریسک اعتباری بانکی در وام های سرمایه گذاری خانگی-2018 Nowadays, the volume of databases that financial companies manage is so great that it has become necessary to
address this problem, and the solution to this can be found in Big Data techniques applied to massive financial
datasets for segmenting risk groups. In this paper, the presence of large datasets is approached through the
development of some Monte Carlo experiments using known techniques and algorithms. In addition, a linear
mixed model (LMM) has been implemented as a new incremental contribution to calculate the credit risk of
financial companies. These computational experiments are developed with several combinations of dataset sizes
and forms to cover a wide variety of cases. Results reveal that large datasets need Big Data techniques and
algorithms that yield faster and unbiased estimators. Big Data can help to extract the value of data and thus
better decisions can be made without the runtime component. Through these techniques, there would be less risk
for financial companies when predicting which clients will be successful in their payments. Consequently, more
people could have access to credit loans.
Keywords: Credit scoring ، Big Data ، Monte Carlo ، Data mining |
مقاله انگلیسی |
4 |
Which financial stocks did short sellers target in the subprime crisis?
Which financial stocks did short sellers target in the subprime crisis?-2015 Tracing the SEC ban on the short selling of financial stocks in September 2008, this paper investigates
whether such selling activity before the 2008 short ban reflected financial companies’ risk exposure in
the subprime crisis. Evidence suggests that short sellers sold short stocks that had the greatest asset
and insolvency risk exposures, and that the short selling of financial firms’ stocks was not significantly
greater than that of non-financial firms after we match them on firm size and insolvency risk. When
the short ban was in effect, the market quality of financial stocks without subprime assets exposure
had deteriorated to a larger degree than that of financial companies with subprime assets exposure.
The findings imply that such a regulation may mute the market disciplining effects of investors and
may also be seen as a counterweight to any perceived macro or systemic risk reduction benefits resulting
from such a ban
Keywords:
Short selling
Subprime assets
Financial crisis
Short-sale ban
CDS spread |
مقاله انگلیسی |