How to manage Interest Rate Risk in the Banking Book considering the monetary...Ziad Fares
The past few years have seen central banks use unconventional tools to stimulate an economy that has kept on struggling since the 2008 crisis. In order to avoid deflation and other economic turmoil, the FED launched a massive bond-buying program called the Quantitative Easing (QE). After the American “experiment”, the ECB launched a similar program early march 2015 as an emergency stimulus to a weakened economy. Such unconventional monetary policy has an impact on interest rates, and therefore, requires a closer monitoring of the Interest Rate Risk in the Banking Book (IRRBB). In such a context, this white paper focuses on understanding how current market conditions (low interest rates) can affect banks’ revenues and profitability while discussing and analyzing the impacts of any changes of the term structure of yield curves on the Net Interest Income. Additionally, as regulators are taking a closer look on how to capture (and cover) the IRRBB, this white paper provides a methodology for measuring the IRRBB and analyzes, via simulations on a real portfolio, the impacts of interest rate moves on the Economic Value of Equity and the Earnings at Risk.
Dr Haluk F Gursel, A Monetary Base Analysis and Control ModelHaluk Ferden Gursel
This report is one of the first studies discussing monetary base analysis and control model, a concept even today is alive and more developed by, for example, by IMF to use its analysis. The study presents monetary base approach to control of money flows and the links between monetary base, money supply and monetary income. Further, the monetary policy problems of the developing countries are reviewed.
The research devotes a section to a developing country data application and analysis.
In developing countries, there are similar tendencies for many variables, although each country has different characteristics, economic and social structures. It follows that remedies can be broadly similar although applications will differ from country to
country. The outlined policies do not address themselves to the solution of all problems; however, the necessity for designing different policies fitting the special conditions of each country and the need for other policies complementary to monetary policies is apparent. Thus, the solutions suggested in conclusion should be considered as guidelines.
A Quantitative Analysis of Indian Banks’ Performance and Efficiency-A Panel R...Saurabh Trivedi
In this report, an attempt has been made to analyze the effects of various internal factors and the effect of ownership structure on the profitability and the efficiency of a bank. The methodology used for the analysis is that of Panel Regression which becomes relevant when there are data for a period of time for each of the units being considered and thus, becomes readily applicable to the present case because for the banks that have been considered in this paper, the data on the relevant variables are available for several years
How to manage Interest Rate Risk in the Banking Book considering the monetary...Ziad Fares
The past few years have seen central banks use unconventional tools to stimulate an economy that has kept on struggling since the 2008 crisis. In order to avoid deflation and other economic turmoil, the FED launched a massive bond-buying program called the Quantitative Easing (QE). After the American “experiment”, the ECB launched a similar program early march 2015 as an emergency stimulus to a weakened economy. Such unconventional monetary policy has an impact on interest rates, and therefore, requires a closer monitoring of the Interest Rate Risk in the Banking Book (IRRBB). In such a context, this white paper focuses on understanding how current market conditions (low interest rates) can affect banks’ revenues and profitability while discussing and analyzing the impacts of any changes of the term structure of yield curves on the Net Interest Income. Additionally, as regulators are taking a closer look on how to capture (and cover) the IRRBB, this white paper provides a methodology for measuring the IRRBB and analyzes, via simulations on a real portfolio, the impacts of interest rate moves on the Economic Value of Equity and the Earnings at Risk.
Dr Haluk F Gursel, A Monetary Base Analysis and Control ModelHaluk Ferden Gursel
This report is one of the first studies discussing monetary base analysis and control model, a concept even today is alive and more developed by, for example, by IMF to use its analysis. The study presents monetary base approach to control of money flows and the links between monetary base, money supply and monetary income. Further, the monetary policy problems of the developing countries are reviewed.
The research devotes a section to a developing country data application and analysis.
In developing countries, there are similar tendencies for many variables, although each country has different characteristics, economic and social structures. It follows that remedies can be broadly similar although applications will differ from country to
country. The outlined policies do not address themselves to the solution of all problems; however, the necessity for designing different policies fitting the special conditions of each country and the need for other policies complementary to monetary policies is apparent. Thus, the solutions suggested in conclusion should be considered as guidelines.
A Quantitative Analysis of Indian Banks’ Performance and Efficiency-A Panel R...Saurabh Trivedi
In this report, an attempt has been made to analyze the effects of various internal factors and the effect of ownership structure on the profitability and the efficiency of a bank. The methodology used for the analysis is that of Panel Regression which becomes relevant when there are data for a period of time for each of the units being considered and thus, becomes readily applicable to the present case because for the banks that have been considered in this paper, the data on the relevant variables are available for several years
This paper presents two models of key determinants in the evolution of the shadow banking system. First of all, a shadow banking measure is built from a European perspective. Secondly, information on several variables is retrieved basing their selection in previous literature. Thirdly, those variables are grouped in: 1) the base model: real GDP, Institutional investors’ assets, term-spread, banks’ net interest margin and liquidity; and 2) the extended model: the former five plus an indicator of systemic stress, an index of banking concentration and inflation. Finally, regression analysis on those models is conducted for different countries’ samples. Both OLS and panel data analysis is undergone. Results suggest important and consistent geographical differences in relations between shadow banking and key determinant variables’ effects. Thus, this essay provides financial authorities with a valuable benchmark to which they should pay attention before designing optimal policies seeking to reduce the financial risk that shadow banking entails.
Rwa density what lies behind this underrated financial ratioLéonard Brie
The objective of this article is to provide a new angle to the study of RWA density. The worth of this ratio, created and largely used by financial analysts, has long been underestimated by banks. Yet as analyses show, this tool may enable a more subtle approach to risk appraisal within a financial institution.
The first part of this article will cover the origins of the ratio and the history of its use in financial analysis. The second part will showcase its characteristics and behavioural traits (including during stress periods), exemplified through a number of theoretical tests. It will be followed by a cross-analysis of the ratio with other indicators that will help underline the informative and predictive value of RWA density.
Finally, the last two parts of the article will put the theoretical value of RWA density to the test, by conducting a practical analysis of its behaviour in Europe over the 2012-2014 period.
The conclusion will appraise the usage and evolution needed to improve and refine the ratio, in order to monitor scarce resources.
This paper presents two models of key determinants in the evolution of the shadow banking system. First of all, a shadow banking measure is built from a European perspective. Secondly, information on several variables is retrieved basing their selection in previous literature. Thirdly, those variables are grouped in: 1) the base model: real GDP, Institutional investors’ assets, term-spread, banks’ net interest margin and liquidity; and 2) the extended model: the former five plus an indicator of systemic stress, an index of banking concentration and inflation. Finally, regression analysis on those models is conducted for different countries’ samples. Both OLS and panel data analysis is undergone. Results suggest important and consistent geographical differences in relations between shadow banking and key determinant variables’ effects. Thus, this essay provides financial authorities with a valuable benchmark to which they should pay attention before designing optimal policies seeking to reduce the financial risk that shadow banking entails.
Rwa density what lies behind this underrated financial ratioLéonard Brie
The objective of this article is to provide a new angle to the study of RWA density. The worth of this ratio, created and largely used by financial analysts, has long been underestimated by banks. Yet as analyses show, this tool may enable a more subtle approach to risk appraisal within a financial institution.
The first part of this article will cover the origins of the ratio and the history of its use in financial analysis. The second part will showcase its characteristics and behavioural traits (including during stress periods), exemplified through a number of theoretical tests. It will be followed by a cross-analysis of the ratio with other indicators that will help underline the informative and predictive value of RWA density.
Finally, the last two parts of the article will put the theoretical value of RWA density to the test, by conducting a practical analysis of its behaviour in Europe over the 2012-2014 period.
The conclusion will appraise the usage and evolution needed to improve and refine the ratio, in order to monitor scarce resources.
Estimation of Net Interest Margin Determinants of the Deposit Banks in Turkey...inventionjournals
Banks, which are the irreplaceable intermediaries of the financial system, are financial institutions that significantly contributeto economic development. The basiccriterion that indicates the efficiency of the intermediation activities of banks is the net interest margins. These costs are assumed to be high for developing countries such as Turkey. The degree to which banks are willing to redeem the funds they collect as credit to the system is directly related to how low their intermediation costs will be. In this paper, it is aimed to estimate the net interest margin determinants of deposit banks in Turkey. Three different panel data models are used for this purpose. These are the Fixed and Random Static models and the GMM (Generalized Moment Models) Dynamic model
DETERMINANTS OF BANK-SPECIFIC AND MACROECONOMIC FACTORS THAT ARE AFFECTING T...Uni-assignment
DETERMINANTS OF BANK-SPECIFIC AND MACROECONOMIC FACTORS THAT ARE AFFECTING THE PROFITABILITY OF COMMERCIAL BANKS A STUDY ON THE BRIC FROM THE EMERGING MARKET
Lesson 6 Discussion Forum Discussion assignments will beDioneWang844
Lesson 6 Discussion Forum :
Discussion assignments will be graded based upon the criteria and rubric specified in the Syllabus.
550 Words
For this Discussion Question, complete the following.
1. Review the two articles about bank failures and bank diversification that are found below this. Economic history assures us that the health of the banking industry is directly related to the health of the economy. Moreover, recessions, when combined with banking crisis, will result in longer and deeper recessions versus recessions that do occur with a healthy banking industry.
2. Locate two JOURNAL articles which discuss this topic further. You need to focus on the Abstract, Introduction, Results, and Conclusion. For our purposes, you are not expected to fully understand the Data and Methodology.
3. Summarize these journal articles. Please use your own words. No copy-and-paste. Cite your sources.
Please post (in APA format) your article citation.
Reply to Post 1: 160 words and Reference
Discussion on Bank’s failures and its diversification
Over the last two decades, business cycle volatility has decreased in the US. For example, some analysts claimed that companies handle inventory better today than ever, or that advances in financial systems have helped smooth industry volatility. Some emphasized stronger economic policy. Banking changes were also drastic in this same era, contributing to the restructuring and convergence of massive, global banking institutions in a better-organized structure. The article (Strahan, 2006) points out that some regulatory reform driven by individual countries rendered it possible for banks to preserve their resources and income by gradually diversifying from local downturns. Both low state volatility rates and a decline in partnerships between the local market and the central banking sector is a net influence on the diversification in banks. Considering the less fragile state economies following these intergovernmental financial reforms, there are some signs that financial convergence – while certainly not the only piece of the puzzle – has been less unpredictable.
Another article (Walter, 2005) argues that a long-standing reason for bank collapses during the crisis is a contagion, which contributes to systemic bank failures and the collapse of one bank initially. This indicates why several losses in the crisis period were unintentional, which ensured that the banks remained stable and endured without contagion-induced falls. The response to the contagion was the central government’s deposit policy, bringing an end to defaults. Nevertheless, since the sequence of errors began in the early 1920s, well before contagion was evident, the underlying trigger must be contagion.
Now it seems like the bank sector has undergone a shake-out that was worsened during the crisis by the deteriorating economic conditions. Although the reality that incidents occurred almost syno ...
In the backdrop of the buzz that Interest Rate Risk in the Banking Book (IRRBB) has generated in the banking industry, Aptivaa is pleased to launch a series of articles providing our perspective on various issues highlighted by our esteemed clients during interactions in the recent months. This post gives an overview of the revised guidelines on IRRBB which has been issued by the Basel Committee, the approaches and the associated challenges in the implementation of IRRBB framework for all internationally active banks.We look forward to your valuable feedback on the current article or the challenges faced by you in IRRBB implementation.
Ch cie gra - stress-test-diffusion-model-and-scoring-performanceC Louiza
The 2008 crisis has demonstrated the importance of conducting stress tests to prevent banking failure. This exercise has also a significant impact on banks’ capital, organization and image.
This paper aims to provide a methodology that diffuses the stress applied on a credit portfolio while taking into account risk and performance for each rating category.
The content is structured in three parts:
The importance of stress testing and the impacts on reputation
Methodology for a dynamic stress diffusion model
Study on a real SME portfolio showing that the model designed in this paper captures relationship between Gini index and the stress diffusion
Dynamic Stress Test Diffusion Model Considering The Credit Score PerformanceGRATeam
After the crisis of 2008, and the important losses and shortfall in capital that it revealed, regulators conducted massive stress testing exercises in order to test the resilience of financial institutions in times of stress conditions. In this context, and considering the impact of these exercises on the banks’ capital, organization and image, this white paper proposes a methodology that diffuses dynamically the stress on the credit rating scale while considering the performance of the credit score. Consequently, the aim is to more accurately reflect the impact of the stress on the portfolio by taking into account the purity of the score and its ability to precisely rank the individuals of the portfolio.
CASE Networks Studies & Analyses No. 480
The European Central Bank (ECB) recently became engaged in macro-prudential policies and the micro-prudential
supervision of the largest Euro area banks. These new tasks should help complete financial integration, and make the Euro area more resilient to financial instability risks. However, the multiplicity of mandates and instruments involves a risk of their inconsistency which could compromise the ECB’s core price-stability mandate as well as its independence. The experience of central banks during the recent global financial crisis confirms that such risks are not purely hypothetical.
Authored by: Marek Dąbrowski
Published: 02-02-2016
201310 Risk Aggregation and Reporting. More than Just a Data IssueFrancisco Calzado
Many banks feel overwhelmed by the sheer volume of regulation that is coming their way. It is not surprising, therefore, that when the Basel Committee on Banking Supervision (BCBS) consultative paper, “Principles for effective risk data aggregation and risk reporting” was published in June 2012 it raised a number of concerns
Similar to The Interest Rate Risk on the Banking Book (20)
Counterparty Credit RISK | Evolution of standardised approachGRATeam
In this Article, we have made a focus on the new standard methodology (SA-CCR) for computing the EAD related to Counterparty Credit Risk portfolios. The implementation of a SA-CCR approach will become increasingly important for the Banks given the publication of the finalised Basel III reforms; in which it will require from financial institutions to compute an output floor to compare their level of RWAs between Internal and Standard approaches.
Stochastic modelling of the loss given default (LGD) for non-defaulted assetsGRATeam
In the Basel framework of credit risk estimation, banks seek to develop precise and stable internal models to limit their capital charge. Following the recent changes in terms of regulatory requirements (Basel regulation, definition of the Downturn…), it is prudent to think about innovative methods to estimate the credit risk parameters with the constrains of models’ stability, robustness, and economic cycles sensitivity.
This paper introduces a different recovery forecasting methodology for LGD (loss given default) parameter. The goal is to model the recovery dynamic by assuming that each maturity in default has a specific behavior and that the recovery rate depends on default generation change. The model focuses on the recovery rate time series where the time period is the default generation. Thus, the estimation of upcoming recoveries uses vertical diffusions, where the triangle’s columns are completed one by one through stochastic processes. This model is suggested to replace classical horizontal forecasting with Chain-Ladder methods.
First, a definition of the LGD parameter and the regulatory modelling requirements are provided, as well as a presentation of the data set used and the construction of the recovery triangle. Second, the stochastic forecasting is introduced with details of how to calibrate the model. Third, three classical methods of recovery forecasting based on Chain-Ladder are presented for comparison and to contest and the stochastic methodology. Finally, a regulatory calibration of the LGD for non-defaulted assets is proposed to include Downturn effects and margins of prudence.
Back-testing of Expected Shortfall : Main challenges and methodologies GRATeam
In a context of an ever-changing regulatory environment over the last years, Banks have
witnessed the draft and publication of several regulatory guidelines and requirements in order
to frame and structure their internal Risk Management.
Among these guidelines, one has been specifically designed for the risk measurement of market
activities. In January 2016, the Basel Committee on Banking Supervision (BCBS) published
the Fundamental Review of the Trading Book (FRTB). Amid the multiple evolutions discussed
in this paper, the BCBS presents the technical context in which the potential loss estimation has
changed from a Value-at-Risk (VaR) computation to an Expected Shortfall (ES) evaluation.
The many advantages of an ES measure are not to be demonstrated, however this measure is
also known for its major drawback: its difficulty to be back-tested. Therefore, after recalling
the context around the VaR and ES models, this white paper will review ES back-testing
findings and insights along many methodologies; these have either been drawn from the latest
publications or have been developed by the Global Research & Analytics (GRA) team of
Chappuis Halder & Co.
As a conclusion, it has been observed that the existing methods rely on strong assumptions and
that they may lead to inconsistent results. The developed methodologies proposed in this paper
also show that even though the ES97.5% metric is close to a VaR99,9% metric, it is not as easily
back-tested as a VaR metric; this is mostly due to the non-elicitability of the ES measure.
Regulatory capital requirements pose a major challenge for financial institutions today.
As the Asian financial crisis of 1997 and rapid development of credit risk management revealed many shortcomings and loop holes in measuring capital charges under Basel I, Basel II was issued in 2004 with the sole intent of improving international convergence of capital measurement and capital standards.
This paper introduces Basel II, the construction of risk weight functions and their limits in two sections:
In the first, basic fundamentals are presented to better understand these prerequisites: the likelihood of losses, expected and unexpected loss, Value at Risk, and regulatory capital. Then we discuss the founding principles of the regulatory formula for risk weight functions and how it works.
The latter section is dedicated to studying the different parameters of risk weight functions, in order to discuss their limits, modifications and impacts on the regulatory capital charge coefficient.
GRA Pricer - 2013 - Valuation & Pricing SolutionsGRATeam
Philosophy
CH&Co Global Research & Analytics (GRA) is a team of passionate people. One unifying criteria in the GRA remains the dominant quantitative topics, including the risk modelling part.
As such, each member works regularly on topics likely to be of interest to the financial community. The results of this work are always freely downloadable and fully shared with anyone interested. Because we consider “risk modelling” as a hobby, we try to share ideas or researches that we found useful within our day to day practice
Introduction
The following document is in response to repeated requests from various players in the market and asking for quick access to a conventional financial pricing library. Formerly available on the internet, it is now more difficult to find on the web.
Our approach is to bring up to date all the work done by Espen Gaarder HAUG and to complete it with a summary document to assist the reader. This document is based on his great work. Moreover, we would like to thank him for his significant contribution in options pricing field and to share it with the financial community.
In an initiative to promote knowledge and expertise sharing, Chappuis Halder & Co decided to put this Options Pricer on free access. It contains a charts generator and the detail sheets of each type of options.
Warning of no property
This document and all its contents, including texts, formulas, charts and any other material, are not the property of CH&Co
CVA Capital Charge under Basel III standardized approachGRATeam
Since the 2007 – 2009, Counterparty Credit Risk (CCR) has become one of the biggest issues and challenges for financial institutions.
As the crisis revealed shortcomings and loopholes in managing CCR, and more specifically CVA risk, new regulations have been issued in the sole intent of capturing this risk and building an extra cushion of capital to absorb losses and consequently to strengthen the resilience of the banking industry.
Basel III framework proposes two ways for measuring CVA Risk: a standardized approach and an advanced approach.
In this paper, the standardized approach will be analyzed and studied. At first, an analysis will be provided to better understand why CCR became so important, what are its characteristics, etc... Then a discussion around the CVA definition from the regulator’s perspective will be presented. Finally, a paragraph will be dedicated to better understand what the standardized formula refers to, what is being computed, and for what purpose.
Our decision to focus on the treatment of counterparty risk in Basel III - standard method only - can be explained by three major observations:
1) A lot of literature already exists, and a certain number of very good specialists refer to the subject. We do not pretend to add other new elements, in all cases not herein;
2) Few banks actually are able to assess their counter party risk under some advanced and internal methodologies. The application of the standard method is highly widespread among financial institutions subject to Basel III;
3) Few people, when they need to assess their risk using the standard approach, really take the time to analyze choices and specific assumptions according to this method.
Our main objective here is to help financial institutions better understand how their regulatory capital levels evolve under this approach and the impact on their day to day business.
Collateral Optimization – Liquidity & Funding Value Adjustments, Best PracticesGRATeam
The purpose of this paper is to understand how the current financial landscape shaped by the crises and new regulations impacts Investment Banking’s business model. We will focus on quantitative implications, i.e. valuation, modeling and pricing issues, as well as qualitative implications, i.e. best practices to manage quantitative aspects and handle these functions to the current Investment Banking organization.
We considered two pillars to shape our vision of collateral optimization:
1. Collateral as a refinancing instrument. Collateral is shifting from a mere hedging instrument for counterparty risk to a strategic refinancing instrument.
2. Improve asymmetric collateral quality and profitability. Recent requirements on collateralization highly impact collateral management through the increase in haircuts and funding of good-quality collateral. As a result, more and more banks are considering their net collateral balance as a KPI, i.e. monitoring their net collateral balance position and identifying the need in cash funding or transforming.
Value-at-Risk (VaR) has been adopted as the cornerstone and commonlanguage of risk management by virtually all major financial institutions and regulators. However, this risk measure has failed to warn the market participants during the financial crisis. In this paper, we show this failure may come from the methodology that we use to calculate VaR and not necessarily for VaR measure itself. we compare two different methods for VaR calculation, 1)by assuming the normal distribution of portfolio return, 2)
by using a bootstrap method in a nonparametric framework. The Empirical exercise is implemented on CAC 40 index, and the results show us that the first method will underestimate the market risk - the failure of VaR measure occurs. Yet, the second method overcomes the shortcomings of the first method and provides results that pass the tests of VaR evaluation.
Optimization of Post-Scoring Classification and Impact on Regulatory Capital ...GRATeam
The 2008 crisis was the main cause of tough market regulation and banks’ consolidation basement. These new constraints have caused a major increase in banks’ capital. As a result, banks need to optimize their return on equity, which has suffered a big drop (due both to a drop in profitability as well as an increase in capital).
Moreover, as this crisis showed loopholes in risk measurement and management, regulators’ tolerance becomes more and more stringent. Consequently, banks are facing challenges while dealing with Low Default Portfolios (LDP) and discerning the way to meet regulatory requirements in terms of credit risk management under the Advanced Approach (IRBA) of Basel rules.
The purpose of this paper is to focus on post-scoring classification for LDPs with the aim to study the possibility of building a rating scale for these portfolios, that meets regulatory requirements as well as to identify the opportunities to optimize RWA. This will be accomplished by studying the relationship between the number of classes within a rating scale and the impact on RWA. The analysis will follow different steps.
Risk management in exotic derivatives tradingGRATeam
Banks’ product offering has become more and more sophisticated with the emergence of financial products tailored to the specific needs of a more complex pool of investors. This particularity has made them very popular among investors. By contrast to liquid, easily understandable “vanilla products” with a simple payoff, “exotic” or structured products have a complex risk profile and expected payoff. As a result, risk management for these structured products has proven to be costly, complex and not always perfect, namely due to their inherent dynamic characteristics inherited from their optionality features. In particular, banks’ traders and investors in financial products with a digital optionality have experienced severe losses, either from pure downward pressure on asset prices or from difficulties to manage the inherent market risks properly. This white paper presents a particular occurrence of this issue on the interest rate market, extends it to commodities, and details some risk management techniques that could have been used in order to avoid losses.
RWA Density | What Lies Behind This Underrated Financial RatioGRATeam
The objective of this article is to provide a new angle to the study of RWA density. The worth of this ratio, created and largely used by financial analysts, has long been underestimated by banks. Yet as analyses show, this tool may enable a more subtle approach to risk appraisal within a financial institution.
The first part of this article will cover the origins of the ratio and the history of its use in financial analysis. The second part will showcase its characteristics and behavioural traits (including during stressperiods), exemplified through a number of theoretical tests. It will be followed by a cross-analysis of the ratio with other indicators that will help underline the informative and predictive value of RWA density.
Finally, the last two parts of the article will putthe theoretical value of RWA density to the test, by conducting a practical analysis of its behaviour in Europe over the 2012-2014 period.
The conclusion will appraise the usage and evolution needed to improve and refine the ratio, in order to monitor scarce resources.
Cat bonds & Artificial Neural Networks | An example of reinsurance products’ ...GRATeam
Over the last fifty years, numbers and costs of natural disasters have not ceased to multiply. Given this phenomenon, insurers and reinsurers struggle to cover the associated losses. Consequently, they turned to financial markets in order to obtain new hedging capabilities, by using various types of products, suchas excess of loss contracts (named XL) and cat bonds.
This paper presents a mathematic model allowing to predict the number and the cost of incoming catastrophes. Data used include wind catastrophes affecting the southeast area of the United States and whose damages are worth more than a billion dollars. This model helps to price insurance risk transfer products, such as XL contracts or cat bonds. First a regression relying on neural network methodology is implemented in order to predict the global annual cost of future catastrophes. Then, based on the same methodology, a classification is done in order to allocate these costs to the various catastrophes.
Our models are used to price several contracts included in the reinsurance program of “Heritage Insurance,” so our results help estimate the share of premiums received by the reinsurer. Two calculations methods are applied: the exposure curve and the “burning cost” method.
Ours models are also validated on cat bond products, but this time using a financial method. This method allows to estimate the share of the Expected Excess Return (EER) depending of the Probability of First Loss (PFL) and the Conditional Expected Loss (CEL).
SMA | Comments on BCBS (June 2016) consultation (Standardized Measurement App...GRATeam
CH&Co provides a response to the Basel Committee on Banking Supervision’s consultative document based on the public data communicated by the Bank for International Settlements.
Our comments represent an open response including different lines of thought. However, the proposals should not be considered as final solutions but as a strong willingness on the part of CH&Co to open the debate about the Standardised Measurement Approach and to challenge the topics that seem relevant to us. We aim at identifying potential limits and weaknesses, providing alternatives and possible area for improvements. The proposals presented in this document are complementary, as they provide different visions and area for improvements within the SMA methodology.
Our comments relate to 3 areas:
SMA method inputs : specific analysis of the internal losses data
SMA method components : specific analysis of the LC
Capital calculation methodology : specific analysis of the SMA formula
Modelling: What’s next for Financial Services in Europe?GRATeam
This paper outlines a practical roadmap to realising cost savings, delivering a material reduction in the volume and complexity of models by outlining five key principles of model optimisation: develop a comprehensive review of models, harmonise methodologies, re-design model validation/monitoring process, re-think its modelling team’s organisation & governance and build new expertise and recruit talent.
Only one year after its creation, the GRA team has been completely transformed. Surpassing all of the original ambitions, the team now stretches over three zones (Europe, Asia and the US) and continues to grow.
Our philosophy is distinctly influenced by the gratification of working together on subject matter which daily fascinates and inspires us. It also conveys the richness of our exchanges, as we collaborate with several practitioners and enthusiasts.
This document has no other purpose than to bring some responsive elements to the questions we face constantly, reminding us also to practice patience and humility - for many answers are possible, and the path of discovery stretches out long before us...”
2. Elemental Economics - Mineral demand.pdfNeal Brewster
After this second you should be able to: Explain the main determinants of demand for any mineral product, and their relative importance; recognise and explain how demand for any product is likely to change with economic activity; recognise and explain the roles of technology and relative prices in influencing demand; be able to explain the differences between the rates of growth of demand for different products.
how to sell pi coins in South Korea profitably.DOT TECH
Yes. You can sell your pi network coins in South Korea or any other country, by finding a verified pi merchant
What is a verified pi merchant?
Since pi network is not launched yet on any exchange, the only way you can sell pi coins is by selling to a verified pi merchant, and this is because pi network is not launched yet on any exchange and no pre-sale or ico offerings Is done on pi.
Since there is no pre-sale, the only way exchanges can get pi is by buying from miners. So a pi merchant facilitates these transactions by acting as a bridge for both transactions.
How can i find a pi vendor/merchant?
Well for those who haven't traded with a pi merchant or who don't already have one. I will leave the telegram id of my personal pi merchant who i trade pi with.
Tele gram: @Pi_vendor_247
#pi #sell #nigeria #pinetwork #picoins #sellpi #Nigerian #tradepi #pinetworkcoins #sellmypi
What website can I sell pi coins securely.DOT TECH
Currently there are no website or exchange that allow buying or selling of pi coins..
But you can still easily sell pi coins, by reselling it to exchanges/crypto whales interested in holding thousands of pi coins before the mainnet launch.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and resell to these crypto whales and holders of pi..
This is because pi network is not doing any pre-sale. The only way exchanges can get pi is by buying from miners and pi merchants stands in between the miners and the exchanges.
How can I sell my pi coins?
Selling pi coins is really easy, but first you need to migrate to mainnet wallet before you can do that. I will leave the telegram contact of my personal pi merchant to trade with.
Tele-gram.
@Pi_vendor_247
Yes of course, you can easily start mining pi network coin today and sell to legit pi vendors in the United States.
Here the telegram contact of my personal vendor.
@Pi_vendor_247
#pi network #pi coins #legit #passive income
#US
What price will pi network be listed on exchangesDOT TECH
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the telegram contact of my personal pi vendor to trade with.
@Pi_vendor_247
1. Elemental Economics - Introduction to mining.pdfNeal Brewster
After this first you should: Understand the nature of mining; have an awareness of the industry’s boundaries, corporate structure and size; appreciation the complex motivations and objectives of the industries’ various participants; know how mineral reserves are defined and estimated, and how they evolve over time.