Basel II : operational risk measurement in the portuguese Banking sector and an evaluation of the quantitive impacts

The present work is aimed at understanding the general notion and origin of the New Basel Accord, which intends to attain international bank stability, emphasizing the convergence between regulatory capital and economic capital, applying its risk sensitive methodologies. This work focuses on one of the principal novelties of Basel II – operational risk and its respective methodologies for calculating minimum capital requirements. The New Capital Accord encourages financial institutions to gradually evolve from basic to sophisticated methodologies. Institutions using more sophisticated methods will be rewarded by deductions on the capital allocated for the calculation of the capital ratio. The methodologies associated to operational risk will be applied to a group of national banking institutions. These methodologies are referred to in Pillar I of the New Capital Accord: (i) basic indicator approach, (ii) the standardized approach and (iii) the alternative standardized approach. The purpose of this practical application is to evaluate and quantify the impact due to the introduction of Basel II.info:eu-repo/semantics/publishedVersio

Fund family tournament and performance consequences: evidence from the UK fund industry

By applying tournament analysis to the UK Unit Trusts data, the results support significant risk shifting in the family tournament; i.e. interim winning managers tend to increase their level of risk exposure more than losing managers. It also shows that the risk-adjusted returns of the winners outperform those of the losers following the risk taking, which implies that risk altering can be regarded as an indication of managers’ superior ability. However, the tournament behaviour can still be a costly strategy for investors, since winners can be seen to beat losers in the observed returns due to the deterioration in the performance of their major portfolio holdings

The Network of Counterparty Risk: Analysing Correlations in OTC Derivatives

Counterparty risk denotes the risk that a party defaults in a bilateral contract. This risk not only depends on the two parties involved, but also on the risk from various other contracts each of these parties holds. In rather informal markets, such as the OTC (over-the-counter) derivative market, institutions only report their aggregated quarterly risk exposure, but no details about their counterparties. Hence, little is known about the diversification of counterparty risk. In this paper, we reconstruct the weighted and time-dependent network of counterparty risk in the OTC derivatives market of the United States between 1998 and 2012. To proxy unknown bilateral exposures, we first study the co-occurrence patterns of institutions based on their quarterly activity and ranking in the official report. The network obtained this way is further analysed by a weighted k-core decomposition, to reveal a core-periphery structure. This allows us to compare the activity-based ranking with a topology-based ranking, to identify the most important institutions and their mutual dependencies. We also analyse correlations in these activities, to show strong similarities in the behavior of the core institutions. Our analysis clearly demonstrates the clustering of counterparty risk in a small set of about a dozen US banks. This not only increases the default risk of the central institutions, but also the default risk of peripheral institutions which have contracts with the central ones. Hence, all institutions indirectly have to bear (part of) the counterparty risk of all others, which needs to be better reflected in the price of OTC derivatives.Comment: 36 pages, 18 figures, 2 table

Benchmark-adjusted performance of US equity mutual funds and the issue of prospectus benchmarks

This study examines the impact of mismatch between prospectus benchmark and fund objectives on benchmark-adjusted fund performance and ranking in a sample of 1281 US equity mutual funds. All funds in our sample report S&P500 index as a prospectus benchmark, yet 2/3 of those are placed in the Morningstar category with risk and objectives different to those of the S&P500 index. We identify more appropriate ‘category benchmarks’ for those mismatched funds and obtain their benchmark-adjusted alphas using recent Angelidis et al. (J Bank Finance 37(5):1759–1776, 2013) methodology. We find that S&P500-adjusted alphas are higher than ‘category benchmark’-adjusted alphas in 61.2% of the cases. In terms of fund quartile rankings, 30% of winner funds lose that status when the prospectus benchmark is substituted with the one better matching their objectives. In the remaining performance quartiles, there is no clear advantage of using S&P 500 as a benchmark. Hence, the prospectus benchmark can mislead investors about fund’s relative performance and ranking, so any reference to performance in a fund’s prospectus should be treated with caution

Measuring the Behavioural Component of the S&P 500 and its Relationship to Financial Stress and Aggregated Earnings Surprises

Scholars in management and economics have shown increasing interest in isolating the behavioural dimension of market evolution. Indeed, by improving forecast accuracy and precision, this exercise would certainly help firms to anticipate economic fluctuations, thus leading to more profitable business and investment strategies. Yet, how to extract the behavioural component from real market data remains an open question. By using monthly data on the returns of the constituents of the S&P 500 index, we propose a Bayesian methodology to measure the extent to which market data conform to what is predicted by prospect theory (the behavioural perspective), relative to the (standard) subjective expected utility theory baseline.We document a significant behavioural component that reaches its peaks during recession periods and is correlated to measures of financial volatility, market sentiment and financial stress with expected sign. Moreover, the behavioural component decreases around macroeconomic corporate earnings news, while it reacts positively to the number of surprising announcements

Mengukur Kinerja Bank Syariah Dengan RGEC(Risk Profile, Good Corporate Governance, Earnings, Capital)(Studi Kasus PT. Bank BNI Syariah Tahun 2014-2017)

This study aims to measure the performance of Islamic banks with the RGEC method (Risk Profile, Corporate Governance, Income, Capital) on health in the case of Bank “X” Syariah in Indonesia from 2014 to 2017. This study uses the RGEC method which aims to start from Capital, Assets, Management Methods, Revenues, Liquidity, and Sensitivity to market risk (CAMELS) methods for analyzing and measuring the health of banks by using the composite ranking calculations on financial statements. This type of research is descriptive, the sampling techniques is study kasus. The population used by banking companies is secondary data taken in annual financial reports issued by Bank “X” Syariah Indonesia for the period 2014-2017. The study assessed four factors, namely Risk Profile through NPL and FDR ratios, Good Corporate Governance, Earnings through ROA, ROE, and NIM ratios, and Capital through CAR ratio

Enterprise Risk Management In The Oil And Gas Industry: An Analysis Of Selected Fortune 500 Oil And Gas Companies Reaction In 2009 And 2010

In 2009, four of the top ten Fortune 500 companies were classified within the oil and gas industry. Organizations of this size typically have an advanced Enterprise Risk Management system in place to mitigate risk and to achieve their corporations\u27 objectives. The companies and the article utilize the Enterprise Risk Management Integrated Framework developed by the Committee of Sponsoring Organizations (COSO) as a guide to organize their risk management and reporting. The authors used the framework to analyze reporting years 2009 and 2010 for Fortune 500 oil and gas companies. After gathering and examining information from 2009 and 2010 annual reports, 10-K filings, and proxy statements, the article examines how the selected companies are implementing requirements identified in the previously mentioned publications. Each section examines the companies Enterprise Risk Management system, risk appetite, and any other notable information regarding risk management. One observation was the existence or non-existence of a Chief Risk Officer or other Senior Level Manager in charge of risk management. Other observations included identified risks, such as changes in economic, regulatory, and political environments in the different countries where the corporations do business. Still others identify risks, such as increases in certain costs that exceed natural inflation, volatility and instability of market conditions. Fortune 500 oil and gas companies included in this analysis are ExxonMobil, Chevron, ConocoPhillips, Baker Hughes, Valero Energy, and Frontier Oil Corporation. An analysis revealed a sophisticated understanding and reporting of many types of risks, including those associated with increasing production capacity. Specific risks identified by companies included start-up timing, operational outages, weather events, regulatory changes, geo-political and cyber security risks, among others. Mitigation efforts included portfolio management and financial strength. There is evidence that companies in later reports (2013) are more comprehensive in their risk management and reports as evidenced by their 10-K and Proxy Statements (Marathon Oil Corporation, 2013)