01 março 2017
Efeito na Odebrecht
O infográfico abaixo mostra o efeito das denúncias nos contratos da empresa Odebrecht (Efeito Lava Jato ameaça contratos de quase US$16 bi da Odebrecht no exterior, Renée Pereira, Estado de S Paulo, 27 de fevereiro, B1):
Picaretagem no ensino de Finanças
O mundo das finanças acadêmicas (financial economics, economia financeira em português) é permeado de teorias malucas que não tem nenhuma conexão com a realidade. Inclusive os criadores dessas teorias ganharam prêmios "Nobel" e criaram uma legião de professores e alunos doutrinados por esses métodos. No artigo abaixo, o professor Pablo Fernández (mestre e doutor em Finanças em Harvard, ele diz que tbm foi doutrinado por lá) diz que a teoria de finanças ensinada nas universidades e escolas de negócio pelo mundo a fora não têm nenhuma conexão com o mundo real. As conlusões e previsões desses modelos não tem nenhuma validade. Por exemplo, o CAPM. É um dos artigos mais interessantes sobre economia financeira, pois mostra quão inútil são todos esses modelos.
Resumo:
This document tries to answer to a frequent question of students and clients: are Finance and Financial Economics the same thing? My answer is NO: I think that they are very different, although the terms are very often confused and many Finance professor positions in many Business Schools have been filled with Financial Economists.
Two ways, among others, to see the differences: a) attend a class on “Finance for managers” taught by a sensible Finance professor and attend another taught by a “Financial Economist”; b) read a book on “Finance for managers” and another on “Financial Economics”.
Financial Economics is a subject developed by economists whose main purpose is to elaborate “models” based on unrealistic assumptions. The conclusions and predictions of the “models” have very little to do with the real world: companies, financial markets, investors, managers… the most emblematic example is the CAPM.
The most used word in the Nobel Prize lectures of Fama, Shiller, Hansen and Sharpe was “model” (513 times).
This document contains facts and some opinions held by the author. I welcome comments (disagreements, errors, anecdotes…) that will help the readers and me to better differentiate between Finance and Financial Economics.
Resumo:
This document tries to answer to a frequent question of students and clients: are Finance and Financial Economics the same thing? My answer is NO: I think that they are very different, although the terms are very often confused and many Finance professor positions in many Business Schools have been filled with Financial Economists.
Two ways, among others, to see the differences: a) attend a class on “Finance for managers” taught by a sensible Finance professor and attend another taught by a “Financial Economist”; b) read a book on “Finance for managers” and another on “Financial Economics”.
Financial Economics is a subject developed by economists whose main purpose is to elaborate “models” based on unrealistic assumptions. The conclusions and predictions of the “models” have very little to do with the real world: companies, financial markets, investors, managers… the most emblematic example is the CAPM.
The most used word in the Nobel Prize lectures of Fama, Shiller, Hansen and Sharpe was “model” (513 times).
This document contains facts and some opinions held by the author. I welcome comments (disagreements, errors, anecdotes…) that will help the readers and me to better differentiate between Finance and Financial Economics.
Fernandez, Pablo, Finance and Financial Economics: A Debate About Common Sense and Illogical Models (February 25, 2017). Available at SSRN: https://ssrn.com/abstract=2906887
28 fevereiro 2017
Gates, Musk e Hawking estão errados
Para o autor do texto, as máquinas não vão eliminar tantos trabalhos como várias pessoas imaginam.
Quincy Larson quotes Bill Gates, Elon Musk and Stephen Hawking as he warns
There’s a rising chorus of concern about how quickly robots are taking away human jobs.
He also cites an Oxford U. study
In 2013, policy makers largely ignored two Oxford economists who suggested that 45% of all US jobs could be automated away within the next 20 years. But today that sounds all but inevitable.
Gates, Musk and Hawking are the smartest humans in the world and I have cited them early and often in my innovation blogs and books. But, no disrespect, but none of them is a full time market watcher. We should take much more detailed studies from Oxford, Gartner (my former employer), McKinsey and other market watchers a bit more seriously.
Unless their studies are flawed.
In researching my recent book, Silicon Collar I found many flaws. Here are a couple in the Oxford study from my book
Nobody appears to have mapped the Oxford report to actual employment trends in the job categories they analyzed. The professors had calculated a high 0.79 “susceptibility to computerisation factor” (with 1.0 being the highest) to heavy truck and tractor-trailer drivers. This, when the U.S. trucking industry says driver shortages could reach as high as 175,000 positions by 2024 (even if the industry adopts autonomous trucks, regulations will likely require a driver as a backup). The professors had assigned an even higher factor of 0.84 to cartographers and photogrammetrists (who deduce measurements from images), which the BLS projects as one of the fastest growing occupations over the next decade. They had assigned a yet higher 0.94 factor to accountants and auditors, whereas hiring at U.S. public accounting firms jumped to reach record levels in 2013–2014.
Similarly, few appear to have asked the Oxford professors whether it is all doom and gloom. What about new jobs from the automation and new digital businesses? J.P. Gownder, an analyst at the research firm Forrester, is one of the few to have analyzed the Oxford work, and he estimated that “new automation will cause a net loss of only 9.1 million U.S. jobs by 2025.” His numbers are well under the roughly 70 million jobs that Frey and Osbourne believe to be in danger of vaporization.
Many of the jobs the Oxford study analyzed require combinations of finger dexterity, crawling capability, visual acumen, social grace, or cognitive and many other human skills. Of course, you can point to individual technologies that can match humans on each skill but show me a systems integrator which has put such a “Frankensoft” machine together for each of the 800 occupations the Bureau of Labor Statistics tracks? And when they do, how long before it matures? (before you answer, check what version of OS you are on after decades of evolution of the PC) And what will it cost to be competitive with a human?
In 2014, Gartner predicted “one in three jobs will be converted to software, robots and smart machines by 2025…New digital businesses require less labor; machines will make sense of data faster than humans can. By 2018, digital business will require 50% fewer business process workers.”
The fact is that Gartner issues hundreds of similar predictions each year and rarely audits them for future accuracy. It usually assigns a probability to them, as an indicator of its confidence in such a prediction, and this statement did not indicate any such hedge.
[...]
You can go back every few decades all the way back to the Luddites and you find similar panic attacks. The Luddites, of course, had the ultimate panic attack. They were bands of English workers in the 1810s who destroyed newly introduced machinery, especially in cotton and woolen mills, fearing their jobs would be lost.
Studying the history of automation allows you to calmly assess what I call in this article “circuit breakers” that slow down societal adoption of automation
Agriculture has gradually been automated for centuries and we are still not done as we enter a phase of “precision agriculture” where GPS, drones and other technology allow for highly customized farm care. Ditto with manufacturing where we are moving to a new stage of robotics, wearables, 3D printing and other technology which is allowing cities like Greenville, SC to be reborn from a textile mill town to one which makes BMW SUVs for the world.
UPC scanners which started showing up in grocery stores in the 1970s have decades later not killed checkout clerk jobs. ATM machines and mobile banking have still not killed teller jobs (you may be shocked to hear we still have 90,000 bank branches with human employees in the US, and many times that around the world) Email and e-commerce may have reduced the demand for the delivery of letters, but they have not killed off the U.S. Postal Service. In fact, e-commerce has created an entirely new category of postal jobs related to delivering items ordered online. The robots at the mail marketing company Valpak and those at the distribution centers of Amazon and other companies help keep more than 600,000 postal employees busy.
[...]
Fonte: aqui
Quincy Larson quotes Bill Gates, Elon Musk and Stephen Hawking as he warns
There’s a rising chorus of concern about how quickly robots are taking away human jobs.
He also cites an Oxford U. study
In 2013, policy makers largely ignored two Oxford economists who suggested that 45% of all US jobs could be automated away within the next 20 years. But today that sounds all but inevitable.
Gates, Musk and Hawking are the smartest humans in the world and I have cited them early and often in my innovation blogs and books. But, no disrespect, but none of them is a full time market watcher. We should take much more detailed studies from Oxford, Gartner (my former employer), McKinsey and other market watchers a bit more seriously.
Unless their studies are flawed.
In researching my recent book, Silicon Collar I found many flaws. Here are a couple in the Oxford study from my book
Nobody appears to have mapped the Oxford report to actual employment trends in the job categories they analyzed. The professors had calculated a high 0.79 “susceptibility to computerisation factor” (with 1.0 being the highest) to heavy truck and tractor-trailer drivers. This, when the U.S. trucking industry says driver shortages could reach as high as 175,000 positions by 2024 (even if the industry adopts autonomous trucks, regulations will likely require a driver as a backup). The professors had assigned an even higher factor of 0.84 to cartographers and photogrammetrists (who deduce measurements from images), which the BLS projects as one of the fastest growing occupations over the next decade. They had assigned a yet higher 0.94 factor to accountants and auditors, whereas hiring at U.S. public accounting firms jumped to reach record levels in 2013–2014.
Similarly, few appear to have asked the Oxford professors whether it is all doom and gloom. What about new jobs from the automation and new digital businesses? J.P. Gownder, an analyst at the research firm Forrester, is one of the few to have analyzed the Oxford work, and he estimated that “new automation will cause a net loss of only 9.1 million U.S. jobs by 2025.” His numbers are well under the roughly 70 million jobs that Frey and Osbourne believe to be in danger of vaporization.
Many of the jobs the Oxford study analyzed require combinations of finger dexterity, crawling capability, visual acumen, social grace, or cognitive and many other human skills. Of course, you can point to individual technologies that can match humans on each skill but show me a systems integrator which has put such a “Frankensoft” machine together for each of the 800 occupations the Bureau of Labor Statistics tracks? And when they do, how long before it matures? (before you answer, check what version of OS you are on after decades of evolution of the PC) And what will it cost to be competitive with a human?
In 2014, Gartner predicted “one in three jobs will be converted to software, robots and smart machines by 2025…New digital businesses require less labor; machines will make sense of data faster than humans can. By 2018, digital business will require 50% fewer business process workers.”
The fact is that Gartner issues hundreds of similar predictions each year and rarely audits them for future accuracy. It usually assigns a probability to them, as an indicator of its confidence in such a prediction, and this statement did not indicate any such hedge.
[...]
You can go back every few decades all the way back to the Luddites and you find similar panic attacks. The Luddites, of course, had the ultimate panic attack. They were bands of English workers in the 1810s who destroyed newly introduced machinery, especially in cotton and woolen mills, fearing their jobs would be lost.
Studying the history of automation allows you to calmly assess what I call in this article “circuit breakers” that slow down societal adoption of automation
Agriculture has gradually been automated for centuries and we are still not done as we enter a phase of “precision agriculture” where GPS, drones and other technology allow for highly customized farm care. Ditto with manufacturing where we are moving to a new stage of robotics, wearables, 3D printing and other technology which is allowing cities like Greenville, SC to be reborn from a textile mill town to one which makes BMW SUVs for the world.
UPC scanners which started showing up in grocery stores in the 1970s have decades later not killed checkout clerk jobs. ATM machines and mobile banking have still not killed teller jobs (you may be shocked to hear we still have 90,000 bank branches with human employees in the US, and many times that around the world) Email and e-commerce may have reduced the demand for the delivery of letters, but they have not killed off the U.S. Postal Service. In fact, e-commerce has created an entirely new category of postal jobs related to delivering items ordered online. The robots at the mail marketing company Valpak and those at the distribution centers of Amazon and other companies help keep more than 600,000 postal employees busy.
[...]
Fonte: aqui
Fnac: operações descontinuadas
A Fnac publicou o seu relatório anual nesta terça-feira e informou que deixará o Brasil. A subsidiária brasileira foi classificada como operação descontinuada:
A companhia apresentou a linha final do balanço zerada em 2016, ante um lucro consolidado de 48 milhões de euros (R$ 157,2 milhões) em 2015, com os resultados daquele ano já ajustados para a reclassificação do Brasil como operação descontinuada. O lucro das operações continuadas da Fnac Darty somou 22 milhões de euros em 2016, enquanto as operações descontinuadas registraram prejuízo idêntico, de 22 milhões de euros, levando ao resultado final nulo no ano passado. Desconsideradas despesas com a aquisição da Darty, a companhia calcula que o lucro das suas operações continuadas seria de 74 milhões de euros, alta de 37% na comparação anual.
As receitas da empresa somaram 5,37 bilhões de euros em 2016, uma alta de 43,6% em relação a 2015, também considerada a base ajustada. Em base pró-forma, que considera o efeito da consolidação da Darty a partir de janeiro de 2015, as receitas cresceram 1,9%, segundo a companhia.
"La filiale brésilienne a été classée en activités non poursuivies (IFRS 5), le Groupe ayant entamé un processus actif de recherche de partenaire pouvant mener à un désengagement de ce pays."
Saiu no Valor:
A companhia apresentou a linha final do balanço zerada em 2016, ante um lucro consolidado de 48 milhões de euros (R$ 157,2 milhões) em 2015, com os resultados daquele ano já ajustados para a reclassificação do Brasil como operação descontinuada. O lucro das operações continuadas da Fnac Darty somou 22 milhões de euros em 2016, enquanto as operações descontinuadas registraram prejuízo idêntico, de 22 milhões de euros, levando ao resultado final nulo no ano passado. Desconsideradas despesas com a aquisição da Darty, a companhia calcula que o lucro das suas operações continuadas seria de 74 milhões de euros, alta de 37% na comparação anual.
As receitas da empresa somaram 5,37 bilhões de euros em 2016, uma alta de 43,6% em relação a 2015, também considerada a base ajustada. Em base pró-forma, que considera o efeito da consolidação da Darty a partir de janeiro de 2015, as receitas cresceram 1,9%, segundo a companhia.
Regulamentação na Telefonia
Estudamos como fatores políticos moldam a concorrência no setor de telecomunicações móveis. Mostramos que a forma como um governo concebe as regras do jogo tem um impacto sobre a concentração, a concorrência e os preços. A regulamentação favorável à concorrência reduz os preços, mas não prejudica a qualidade dos serviços ou dos investimentos. Governos mais democráticos tendem a projetar regras mais competitivas, enquanto que países com empresas com ligações políticas são capazes de distorcer as regras em seu favor, restringindo a concorrência. A intervenção governamental tem grandes efeitos redistributivos: os consumidores norte-americanos ganhariam US $ 65 bilhões por ano se os preços dos serviços móveis dos EUA estivessem em linha com os alemães e US $ 44 bilhões se estivessem em linha com os dinamarqueses.
Political Determinants of Competition in the Mobile Telecommunication Industry - Mara Faccio, Luigi Zingales
Political Determinants of Competition in the Mobile Telecommunication Industry - Mara Faccio, Luigi Zingales
Superávit do setor público
O setor público apresentou no mês de janeiro de 2017 um superávit de 37 bilhões de reais. Trata-se do melhor resultado desde 2002. Em janeiro do ano passado o governo tinha obtido um superávit de 28 bilhões. O resultado foi possível graças ao superávit do governo central.
O resultado positivo já era esperado, mas o valor foi acima do previsto. Em dezembro, o déficit tinha ficado em 71 bilhões, enquanto novembro foi de 39 bilhões. Além disto, o ano de 2018 é um ano eleitoral, quando existe um relaxamento nas despesas.
O resultado positivo já era esperado, mas o valor foi acima do previsto. Em dezembro, o déficit tinha ficado em 71 bilhões, enquanto novembro foi de 39 bilhões. Além disto, o ano de 2018 é um ano eleitoral, quando existe um relaxamento nas despesas.
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