16 julho 2019
Concentração e Mudança Tecnológica
O interessante na abordagem dos autores é que usam a estrutura de custo - em particular a participação dos novos custos fixos tecnológicos - para procurar entender a concentração no setor. A conclusão dos autores é que a concentração não apresentou mudança substancial - nem aumento, nem redução - durante o período analisado.
Mas será que isto é válido para a contabilidade? Sendo uma atividade de serviço, também não deveria existir um aumento na concentração. É importante notar que a questão da concentração é bastante complexa. Bonfigliogi, Crinò e Gancia mostraram que as transações de empresas multinacionais podem afetar este valor. Rossi-Hansberg e outros indicaram que a concentração nacional parece aumentar, enquanto a concentração local indica uma redução.
E a contabilidade? A questão da concentração é uma preocupação bastante presente entre as empresas de auditoria. Este assunto é bastante pesquisado na literatura, como em Dantas, Medeiros e Paulo, em 2011. Entretanto, no escritório de contabilidade não sabemos ao certo se a concentração está aumentando ou não. No caso da contabilidade, muitas vezes é uma atividade "terceirizada" e isto pode afetar a concentração. Dois outros fatores podem afetar esta concentração: a mudança tecnológica (vide Hsieh e Hansberg) afetando a estrutura de custo e a mudança de legislação, como a criação do MEI.
Recentemente, Souza, Silva, Silva e Souza (é isto mesmo) analisaram a concentração dos profissionais de contabilidade em termos geográficos. Sabemos que cidades com mais habitantes possuem mais profissionais, mas os autores mostraram que quando se analisa em termos proporcionais, a concentração é afetada por um fator: o desenvolvimento humano do local.
The Industrial Revolution in Services - Chang-Tai Hsieh, Esteban Rossi-Hansberg - NBER Working Paper No. 25968 - Issued in June 2019
Bonfiglioli, A, R Crinò and G Gancia (2019), "Concentration in international markets: Evidence from US imports," CEPR Discussion paper 13566.
Diverging Trends in National and Concentration - Esteban Rossi-Hansberg, Pierre-Daniel Sarte, Nicholas Trachter. NBER Working Paper No. 25066. Issued in September 2018
DANTAS, José Alves; DE MEDEIROS, Otávio Ribeiro; PAULO, Edilson. Relação entre concentração e rentabilidade no setor bancário brasileiro. Revista Contabilidade Finanças, v. 22, n. 55, p. 5-28, 2011.
15 julho 2019
Turing na nota de 50 libras
Alan Turing irá aparecer na nova nota de 50 libras do Bank of England. Turing foi responsável pela quebra do código dos nazistas durante a segunda guerra mundial. A nota deve entrar em circulação em 2021. Turing foi um matemático e considerado o pai da computação e da inteligência artificial. Durante a guerra, Turing ajudou a quebrar o código do Enigma, a máquina de código dos alemães. Mas em 1952 foi condenado por indecência, por ter um caso com um homem, sendo castrado quimicamente. Somente em 2013 recebeu o perdão real.
Quando pensou em lançar uma homenagem a um cientista, o Banco da Inglaterra recebeu 227 mil indicações. Entre os finalistas: Mary Anning, Paul Dirac, Rosalind Franklin, William Herschel e Caroline Herschel, Dorothy Hodgkin, Ada Lovelace e Charles Babbage, Stephen Hawking, James Clerk Maxwell, Srinivasa Ramanujan, Ernest Rutherford, Frederick Sanger e Alan Turing.
14 julho 2019
Falência do Lehman Brothers: o papel da E&Y
Resumo:
For many years prior to its demise, Lehman Brothers employed Ernst & Young (EY) as the firm’s independent auditors to review its financial statements and express an opinion as to whether they fairly represented the company’s financial position. EY was supposed to try to detect fraud, determine whether a matter should be publicly disclosed, and communicate certain issues to Lehman’s Board audit committee. After Lehman filed for bankruptcy, it was discovered that the firm had employed questionable accounting with regard to an unorthodox financing transaction, Repo 105, which it used to make its results appear better than they were. EY was aware of Lehman’s use of Repo 105, and its failure to disclose its use. EY also knew that Lehman included in its liquidity pool assets that were impaired. When questioned, EY insisted that it had done nothing wrong. However, Anton R. Valukas, the Lehman bankruptcy examiner, concluded that EY had not fulfilled its duties and that probable claims existed against EY for malpractice. In this case, participants will consider the role and effectiveness of independent auditors in ensuring complete and accurate financial statements and related public disclosure.
Fonte:
Wiggins, Rosalind Z.; Bennett, Rosalind L.; and Metrick, Andrew (2019) "The Lehman Brothers Bankruptcy D: The Role of Ernst & Young," Journal of Financial Crises: Vol. 1 : Iss. 1, 100-123.
For many years prior to its demise, Lehman Brothers employed Ernst & Young (EY) as the firm’s independent auditors to review its financial statements and express an opinion as to whether they fairly represented the company’s financial position. EY was supposed to try to detect fraud, determine whether a matter should be publicly disclosed, and communicate certain issues to Lehman’s Board audit committee. After Lehman filed for bankruptcy, it was discovered that the firm had employed questionable accounting with regard to an unorthodox financing transaction, Repo 105, which it used to make its results appear better than they were. EY was aware of Lehman’s use of Repo 105, and its failure to disclose its use. EY also knew that Lehman included in its liquidity pool assets that were impaired. When questioned, EY insisted that it had done nothing wrong. However, Anton R. Valukas, the Lehman bankruptcy examiner, concluded that EY had not fulfilled its duties and that probable claims existed against EY for malpractice. In this case, participants will consider the role and effectiveness of independent auditors in ensuring complete and accurate financial statements and related public disclosure.
Fonte:
Wiggins, Rosalind Z.; Bennett, Rosalind L.; and Metrick, Andrew (2019) "The Lehman Brothers Bankruptcy D: The Role of Ernst & Young," Journal of Financial Crises: Vol. 1 : Iss. 1, 100-123.
13 julho 2019
Teoria e Efeito causal
Em fevereiro, Stefan Szymanski publicou um texto no site Soccernomics chamado "Soccer Analytics: Science or Alchemy?". Ele trata de muitos temas: previsão no futebol, aumento no número de dados, modelos com muitas variáveis, teoria a partir dos dados, etc. Vários dos aspectos foram tratados no blog nos últimos anos.
No final ele apresenta quatro pontos:
(1) Theories are useful because they help us to identify causal effects. Big data approaches in soccer seem largely to avoid theorizing, which risks reducing the analysis simply to the search for correlations. I don’t think any science can prosper if straightjacketed in this way.
(2) In natural science causal effects are usually tested using controlled experiments. Social science relies on observational data, which makes the identification of causality much more difficult. There have been huge advances in our understanding of how to identify causality through statistical methods over the last three decades, but as yet I’ve seen little recognition of the issue in soccer analytics papers.
(3)There is a financial profit to be made in soccer analytics. Mostly this is not about beating the bookies but advising clubs on identification of strategies, playing talent and so on. This world closely resembles the world of alchemy- it is secretive and given to obscure utterings. Results are announced but not explained, success is claimed but not proven. This is perhaps inevitable as long as the potential for profit exists. There are also such non-scientific analyses of the stock market, together with promises of untold returns. The only cure for this a healthy skepticism.
(4) In the end, I believe, soccer analytics will be judged on its capacity to predict. I have outlined some of the challenges to developing predictions in relation to game results, but there are potentially other areas where soccer analytics can contribute, involving outcome related to specific on-field events.
No final ele apresenta quatro pontos:
(1) Theories are useful because they help us to identify causal effects. Big data approaches in soccer seem largely to avoid theorizing, which risks reducing the analysis simply to the search for correlations. I don’t think any science can prosper if straightjacketed in this way.
(2) In natural science causal effects are usually tested using controlled experiments. Social science relies on observational data, which makes the identification of causality much more difficult. There have been huge advances in our understanding of how to identify causality through statistical methods over the last three decades, but as yet I’ve seen little recognition of the issue in soccer analytics papers.
(3)There is a financial profit to be made in soccer analytics. Mostly this is not about beating the bookies but advising clubs on identification of strategies, playing talent and so on. This world closely resembles the world of alchemy- it is secretive and given to obscure utterings. Results are announced but not explained, success is claimed but not proven. This is perhaps inevitable as long as the potential for profit exists. There are also such non-scientific analyses of the stock market, together with promises of untold returns. The only cure for this a healthy skepticism.
(4) In the end, I believe, soccer analytics will be judged on its capacity to predict. I have outlined some of the challenges to developing predictions in relation to game results, but there are potentially other areas where soccer analytics can contribute, involving outcome related to specific on-field events.
Índice de Sharpe esconde riscos
O gráfico abaixo mostra no eixo X o índice de Sharpe para 3098 fundos de hedge de Janeiro de 2004 a 2007 e no eixo Y suas perdas medidas pelo desvio-padrão após a crise de 2008. Os fundos menos voláteis tiveram as maiores perdas. Quanto mais estável o retorno, maior a chance de perdas. Ou seja,o índice sharpe não consegue prever desempenho futuro e não prevê perdas durante crises. Ele não funciona out-of-sample (fora da amostra)
Fonte: aqui
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