30 janeiro 2020
Propaganda horrorosa de software de imposto de renda
Nos EUA existem softwares para ajudar as pessoas a declararem imposto de renda. Ano novo, imposto a declarar em qualquer país. A Intuit fez um comercial que será vinculado no Super Bowl, um dos intervalos mais disputados da televisão. A letra (horrorosa, assim como o comercial) é a seguinte:
All People are Tax People REMIX
All people. All people. All people are tax people.
All people. All people. All people are tax people.
If you filing by yourself, let me see you clap it up.
Clap it up, clap it up.
If you need a little help go ahead and hit us up.
Hit us up. Hit us up.
You got a question to ask? A CPA can help you there,
help you there, help you there.
Got a W-2? Go on and wave it in the air.
Wave it in the air, wave it in the air.
Now take a picture, take a picture.
Easy uploads is a mobile feature.
English, Spanglish, Español.
We all speak refund, go and get yours.
Now get deductions, get deductions.
Make sure you’re not missing nothing.
You can file it, you can do it.
You can file it, you can do it.
We can help you getting through it.
Get it filed, nothing to it.
Do ya taxes, do ya taxes. Everybody, everybody, do ya taxes.
Got everything you need to reenact this. Do ya taxes, do ya taxes.
All people. All people. All people are tax people.
All people. All people. All people are tax people.
Eu já tinha escrito a postagem quando li no Going Concern que o custo para vincular o comercial é de 5,6 milhões de dólares. Ah, eles também acharam o comercial horroroso.
29 janeiro 2020
Previsão de lucro: é possível bater o random walk
Resumo:
As a crucial input to many valuation models, earnings forecasts are important to many practitioners and academics. Unfortunately, there is a large sample of firms that analysts do not cover, and analysts’ earnings forecasts are less accurate than a random walk at long horizons. Recent work by Hou, van Dijk, and Zhang (2012) and Li and Mohanram (2014) suggested the use of cross-sectional models to produce earnings forecasts. Several studies immediately used these models because of the obvious advantage that forecasts can be formed for a sample that is much greater than the sample of firms covered by analysts. Unfortunately, these models also produce earnings forecasts significantly worse than random walk forecasts. We present a simple and intuitive modification to these models – the use of quantile rather than OLS regressions in the prediction model – that produces earnings forecasts significantly better than a random walk. Subsequent analysis suggests that this simple modification produces earnings forecasts that lead to more accurate return forecasts, and better represents market expectations.
Easton, Peter D. and Kelly, Peter and Neuhierl, Andreas, Beating a Random Walk (August 7, 2018). Available at SSRN: https://ssrn.com/abstract=3040354 or http://dx.doi.org/10.2139/ssrn.3040354
As a crucial input to many valuation models, earnings forecasts are important to many practitioners and academics. Unfortunately, there is a large sample of firms that analysts do not cover, and analysts’ earnings forecasts are less accurate than a random walk at long horizons. Recent work by Hou, van Dijk, and Zhang (2012) and Li and Mohanram (2014) suggested the use of cross-sectional models to produce earnings forecasts. Several studies immediately used these models because of the obvious advantage that forecasts can be formed for a sample that is much greater than the sample of firms covered by analysts. Unfortunately, these models also produce earnings forecasts significantly worse than random walk forecasts. We present a simple and intuitive modification to these models – the use of quantile rather than OLS regressions in the prediction model – that produces earnings forecasts significantly better than a random walk. Subsequent analysis suggests that this simple modification produces earnings forecasts that lead to more accurate return forecasts, and better represents market expectations.
Easton, Peter D. and Kelly, Peter and Neuhierl, Andreas, Beating a Random Walk (August 7, 2018). Available at SSRN: https://ssrn.com/abstract=3040354 or http://dx.doi.org/10.2139/ssrn.3040354
Enquanto isto, na ciência...
A ciência não se cansa de surpreender. A seguir um conjunto de pesquisas interessantes
Pontes e Hoegg, em Journal of Experimental Psychology Applied, mostraram que as mulheres casadas (versus as solteiras) foram influenciadas no julgamento de homens quando o perfil era exibido em fundo vermelho (versus branco). A cor foi percebida como um sinal de ameaça. Clique aqui
Chang e Meyerhoefer usaram as eleições de Taiwan para mostrar que neste período as pessoas ficam mais doentes (+19%). Clique aqui
Adam, Aimee manipularam o tamanho dos cílios em fotografias de homens e mulheres e procuraram verificar o efeito na atratividade, idade percebida, saude percebida e feminilidade. Cílios mais longos tornam as mulheres mais atraentes (mas não os homens), assim como a percepção de saúde e feminilidade. Clique aqui
Folke e Rickne, no American Economic Journal: Applied Economics mostraram as promoções nos empregos aumentam a probabilidade de divórcio para as mulheres, mas não para os homens. Doi: 10.1257/app.20180435
No The Journal of Health Economics, Giulietti, Tonin e Vlassopoulos descobriram existir uma relação entre o comportamento do mercado acionário e os acidentes automobilísticos, especialmente com a baixa do mercado. Via aqui
IFRS para PME
O SME Implementation Group (SMEIG), do Iasb, divulgou um documento procurando saber sobre a adoção de normas internacionais de contabilidade para as empresas de menor porte. Neste documento, o SMEIG apresenta algumas considerações e faz algumas perguntas como: Na sua opinião, as IFRS para as Pequenas e Médias empresas devem estar alinhadas, na sua totalidade, com os padrões IFRS?
Os interessados deverão responder até 27 de julho de 2020 ao documento. Lembrando que as normas para as PME foram inicialmente emitidas em julho de 2009. Já ocorreram duas revisões, uma em 2012 e outra em 2014. Entretanto, um conjunto de normas foram aprovadas pelo Iasb recentemente (receita, instrumentos financeiros, seguros, leasing ...) e a questão básica é saber como isto será incorporado (se é que será incorporado).
Marcas de Luxo
9. Prada = $4,781 bilhões de dólares
8. Burberry = $5,205
7. Tiffany & Co. = $5,335
6. Dior = $6,045
5. Cartier = $8,192
4. Gucci = $15,949
3. Hermès = $17,92
2. Chanel = $22,134
1. Louis Vuitton = $32,223 bilhões
Via aqui
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