MNB One Credit-Card Portfolio

2017 ◽  
pp. 1-8
Author(s):  
Samuel E. Bodily ◽  
Jason Hull ◽  
William Scherer
Keyword(s):  
Markov Process ◽  
Credit Card ◽  
Future Earnings ◽  
Over Time

A credit-card company must value portfolios of customers based on their future earnings. The payment characteristics of customers serve to classify them into states. This case can be the basis for discussing state dynamics over time in a Markov process.

Usefulness of Accounting Estimates

2016 ◽  
Vol 32 (1) ◽  
pp. 123-135 ◽  
Author(s):  
Li Li Eng ◽  
Thanyaluk Vichitsarawong
Keyword(s):  
Cash Flow ◽  
Exploratory Study ◽  
Abnormal Returns ◽  
Cash Flows ◽  
Recent Period ◽  
Future Earnings ◽  
China And India ◽  
Accounting Estimates ◽  
Out Of Sample ◽  
Over Time

This is an exploratory study to examine the quality or usefulness of accounting estimates of companies in China and India over time. Specifically, we examine how well the accounting estimates are able to predict future earnings and cash flows during the period 2003-2013. The results for India indicate that the out-of-sample earnings and cash flow predictions derived are more accurate and more efficient in the more recent period (2010-2013) than the earlier period (2003-2006). In contrast, the out-of-sample earnings and cash flow predictions for China are generally more biased, less accurate, and less efficient. The results indicate abnormal returns earned on hedge portfolios formed on earnings (cash flow) predictions for India in the recent period. In contrast, none of the portfolios for China earn positive returns. The results suggest that the accounting estimates in India in recent years have become better predictors of future earnings and cash flow than accounting estimates in the earlier period. However, the accounting estimates in China are not relevant for predicting earnings and cash flows over the years in the sample period.

The Predictability of Future Aggregate Earnings Growth and the Relation between Aggregate Analyst Recommendation Changes and Future Returns

2020 ◽  
pp. 0000-0000
Author(s):  
Bruce K. Billings ◽  
Sami Keskek ◽  
Spencer R. Pierce
Keyword(s):  
Risk Premia ◽  
Expected Returns ◽  
Positive Relation ◽  
Negative Relation ◽  
Earnings Growth ◽  
Future Earnings ◽  
Industry Level ◽  
Aggregate Information ◽  
Expected Earnings ◽  
Over Time

We extend prior research examining the relation between aggregate recommendation changes and future returns by documenting that this relation varies over time as a function of the predictability of future earnings growth. When industry-level earnings growth is more predictable, we find that recommendation changes relate negatively to future returns. Our evidence suggests that this negative relation results from analysts revising recommendations upward for higher expected earnings growth but failing to adjust downward for a related decrease in investor risk aversion and demand for risk premia leading to lower expected returns. In contrast, when industry-level earnings growth is less predictable, we find that recommendation changes relate positively to future returns. However, this positive relation results from analysts and investors similarly underestimating earnings growth persistence. Overall, the evidence fails to support the claim that analysts' recommendation changes incorporate aggregate information in a manner that adds value to investors by predicting future returns.

Dynamic Data Mining

2011 ◽  
pp. 722-728 ◽  
Author(s):  
Richard Weber
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Credit Card ◽  
Knowledge Discovery In Databases ◽  
Stream Data ◽  
Dynamic Data ◽  
Change Over Time ◽  
Professional Activities ◽  
Feature Values ◽  
Over Time

Since the First KDD Workshop back in 1989 when “Knowledge Mining” was recognized as one of the top 5 topics in future database research (Piatetsky-Shapiro 1991), many scientists as well as users in industry and public organizations have considered data mining as highly relevant for their respective professional activities. We have witnessed the development of advanced data mining techniques as well as the successful implementation of knowledge discovery systems in many companies and organizations worldwide. Most of these implementations are static in the sense that they do not contemplate explicitly a changing environment. However, since most analyzed phenomena change over time, the respective systems should be adapted to the new environment in order to provide useful and reliable analyses. If we consider for example a system for credit card fraud detection, we may want to segment our customers, process stream data generated by their transactions, and finally classify them according to their fraud probability where fraud pattern change over time. If our segmentation should group together homogeneous customers using not only their current feature values but also their trajectories, things get even more difficult since we have to cluster vectors of functions instead of vectors of real values. An example for such a trajectory could be the development of our customers’ number of transactions over the past six months or so if such a development tells us more about their behavior than just a single value; e.g., the most recent number of transactions. It is in this kind of applications is where dynamic data mining comes into play! Since data mining is just one step of the iterative KDD (Knowledge Discovery in Databases) process (Han & Kamber, 2001), dynamic elements should be considered also during the other steps. The entire process consists basically of activities that are performed before doing data mining (such as: selection, pre-processing, transformation of data (Famili et al., 1997)), the actual data mining part, and subsequent steps (such as: interpretation, evaluation of results). In subsequent sections we will present the background regarding dynamic data mining by studying existing methodological approaches as well as already performed applications and even patents and tools. Then we will provide the main focus of this chapter by presenting dynamic approaches for each step of the KDD process. Some methodological aspects regarding dynamic data mining will be presented in more detail. After envisioning future trends regarding dynamic data mining we will conclude this chapter.

Potential Jurisprudential Adaptation for the Tripartite Credit Card Transaction from an Islamic Perspective

2014 ◽  
Vol 28 (4) ◽  
pp. 317-365
Author(s):  
Mohammed Jassem Mohammed ◽  
Rahmah Ismail ◽  
Ruzian Markom
Keyword(s):  
Credit Card ◽  
Credit Cards ◽  
Great Effort ◽  
Financial Instruments ◽  
Financial Contracts ◽  
The West ◽  
Islamic Perspective ◽  
Financial Contract ◽  
Over Time

The credit card represents one of the most important financial instruments at present. The credit card concept originated and was developed in the West under the rules of conventional law. Over time the credit card has invaded the Islamic markets. A credit card transaction does not fall under any of the known financial contract categories in Islamic principles. Therefore, determining the Islamic rulings and finding a jurisprudential adaptation for such credit card transactions is essential for clarifying relevant jurisprudential rulings, as one cannot specify whether a specific transaction is permitted or prohibited without a jurisprudential adaptation on the matter. Islamic researchers have taken great effort to clarify the jurisprudential adaptation of a credit card transaction. This article will examine the potential legitimate nature of the credit card transaction in order to determine Islamic rulings. The concept ‘credit card’ originated in the West and developed under the rules of conventional law. Although credit cards have since invaded the Islamic markets, their transactions do not fall under any of the known categories for Islamic financial contracts; therefore, one must determine the Islamic rulings that relate to such transactions. Islamic scholars have exerted much effort to find a jurisprudential adaptation for the credit card transaction, which is essential in order to clarify jurisprudential rulings on transactions and to specify whether a transaction is permitted or prohibited. This article examines the potential legitimate nature of the credit card transaction in order to determine the Islamic rulings.

Credit card possesion and use: Changes over time

1989 ◽  
Vol 41 (2) ◽  
pp. 127-142 ◽  
Author(s):  
James T. Lindley ◽  
Patricia Rudolph ◽  
Edward B. Selby
Keyword(s):  
Credit Card ◽  
Changes Over Time ◽  
Over Time

How Will State-Run Auto-IRAs Affect Workers?

2018 ◽  
Keyword(s):  
Survey Data ◽  
Credit Card ◽  
Retirement Savings ◽  
Retirement Plans ◽  
National Scale ◽  
Individual Retirement Accounts ◽  
Financial Difficulties ◽  
Retirement Accounts ◽  
Opt Out ◽  
Over Time

In order to encourage savings among workers without access to employer-sponsored retirement plans, several states have proposed defaulting workers into state-run individual retirement accounts known as Auto-IRAs. Plans such as OregonSaves automatically enroll workers and, by default, increase their contributions over time. Given low opt-out rates, these policies have the potential to increase retirement savings for workers without access to employer-sponsored plans. Using survey data, we find that over 24 million workers could automatically be enrolled in an Auto-IRA, if enacted on a national scale. Nonetheless, these policies have the potential to adversely affect individuals with debt and current financial difficulties who do not actively opt-out. One-third of potentially affected workers hold credit card debt with an average balance exceeding $5,000. Furthermore, approximately 15% of potentially affected workers have difficulty meeting basic needs.

scholarly journals Regulating Consumer Financial Products: Evidence from Credit Cards *

2014 ◽  
Vol 130 (1) ◽  
pp. 111-164 ◽  
Author(s):  
Sumit Agarwal ◽  
Souphala Chomsisengphet ◽  
Neale Mahoney ◽  
Johannes Stroebel
Keyword(s):  
Credit Card ◽  
Financial Regulation ◽  
Consumer Credit ◽  
Credit Cards ◽  
Set Covering ◽  
Difference In Differences ◽  
Data Set ◽  
Financial Products ◽  
Regulatory Limits ◽  
Over Time

Abstract We analyze the effectiveness of consumer financial regulation by considering the 2009 Credit Card Accountability Responsibility and Disclosure (CARD) Act. We use a panel data set covering 160 million credit card accounts and a difference-in-differences research design that compares changes in outcomes over time for consumer credit cards, which were subject to the regulations, to changes for small business credit cards, which the law did not cover. We estimate that regulatory limits on credit card fees reduced overall borrowing costs by an annualized 1.6% of average daily balances, with a decline of more than 5.3% for consumers with FICO scores below 660. We find no evidence of an offsetting increase in interest charges or a reduction in the volume of credit. Taken together, we estimate that the CARD Act saved consumers $11.9 billion a year. We also analyze a nudge that disclosed the interest savings from paying off balances in 36 months rather than making minimum payments. We detect a small increase in the share of accounts making the 36-month payment value but no evidence of a change in overall payments.

Accounting Choice and the Fair Value Option

2011 ◽  
Vol 25 (3) ◽  
pp. 487-510 ◽  
Author(s):  
Katherine Guthrie ◽  
James H. Irving ◽  
Jan Sokolowsky
Keyword(s):  
Commercial Banks ◽  
Fair Value ◽  
Data Availability ◽  
Complete Picture ◽  
Financial Instruments ◽  
Accounting Choice ◽  
Early Adopters ◽  
Future Earnings ◽  
Over Time

SYNOPSIS Under the fair value option, SFAS No. 159, firms have full discretion over electing to report specified financial instruments at fair value on a contract-by-contract basis. Building on Henry's (2009) study of early adopting banks, this paper examines to what extent firms' election of instruments benefited their current or future earnings. Our sample comprises the constituents of the S&P 1500 Index for the first quarters of fiscal years 2007 and 2008. Expanding the sample across industries and over time allows us to obtain a more complete picture of the adoption of the fair value option. We identify 72 adopters, two-thirds of which are not commercial banks. We do not find evidence of systematic opportunistic election of the fair value option. In only a handful of cases—concentrated among early adopters with an earnings shortfall—did firms experience a significant improvement in current or future earnings that casts doubt on whether their adoption was keeping with the intent and spirit of the standard. Data Availability: The list of adopters used in this paper is available from the authors upon request.

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