22 junho 2016
21 junho 2016
Sabedoria do Twitter: previsão dos retornos via tweets
Resumo:
With the rise of social media, investors have a new tool to measure sentiment in real time. However, the nature of these sources of data raises serious questions about its quality. Since anyone on social media can participate in a conversation about markets -- whether they are informed or not -- it is possible that this data may have very little information about future asset prices. In this paper, we show that this is not the case by analyzing a recurring event that has a high impact on asset prices: Federal Open Market Committee (FOMC) meetings. We exploit a new dataset of tweets referencing the Federal Reserve and shows that the content of tweets can be used to predict future returns, even after controlling for common asset pricing factors. To gauge the economic magnitude of these predictions, the authors construct a simple hypothetical trading strategy based on this data. They find that a tweet-based asset-allocation strategy outperforms several benchmarks, including a strategy that buys and holds a market index as well as a comparable dynamic asset allocation strategy that does not use Twitter information.
With the rise of social media, investors have a new tool to measure sentiment in real time. However, the nature of these sources of data raises serious questions about its quality. Since anyone on social media can participate in a conversation about markets -- whether they are informed or not -- it is possible that this data may have very little information about future asset prices. In this paper, we show that this is not the case by analyzing a recurring event that has a high impact on asset prices: Federal Open Market Committee (FOMC) meetings. We exploit a new dataset of tweets referencing the Federal Reserve and shows that the content of tweets can be used to predict future returns, even after controlling for common asset pricing factors. To gauge the economic magnitude of these predictions, the authors construct a simple hypothetical trading strategy based on this data. They find that a tweet-based asset-allocation strategy outperforms several benchmarks, including a strategy that buys and holds a market index as well as a comparable dynamic asset allocation strategy that does not use Twitter information.
Links
Efeito Dunning-Kruger explica os votos para Trump
Fundo de Pensão de Kentucky: parece um país terceiro mundo, com dois governos reivindicando o poder
6 mil anos de vida urbana em 3 minutos num mapa
KPMG abandonou a FIFA por não acreditar que a entidade estivesse comprometida com a governança
Fundo de Pensão de Kentucky: parece um país terceiro mundo, com dois governos reivindicando o poder
6 mil anos de vida urbana em 3 minutos num mapa
KPMG abandonou a FIFA por não acreditar que a entidade estivesse comprometida com a governança
20 junho 2016
Custos e Segurança
A razão alegada: segurança. A informação do custo do B21 poderia fornecer informação sobre o projeto para o inimigo.
Fiquei pensando como isto seria possível na contabilidade pública. Exceto se existirem outras despesas secretas, não seria difícil descobrir este custo; mas temos um problema: o custo deve estar diluído ao longo dos anos.
Links
3 tendências que estão ocorrendo hoje e que afetarão a contabilidade
Buster Keaton e a arte do cinema
Inglês nativo e economista: vantagem na publicação
Comendo pizza com a mão, Gauss e Teorema Egregium
Cristiano Ronaldo e a criatividade da internet (foto)
Modelando e mensurando comportamento irracional no mercado
Resumo:
Following a Geometrical Brownian Motion extension into an Irrational fractional Brownian Motion model, we re-examine agent behaviour reacting to time dependent news on the log-returns thereby modifying a financial market evolution. We specifically discuss the role of financial news or economic information positive or negative feedback of such irrational (or contrarian) agents upon the price evolution. We observe a kink-like effect reminiscent of soliton behaviour, suggesting how analysts' forecasts errors induce stock prices to adjust accordingly, thereby proposing a measure of the irrational force in a market.
Following a Geometrical Brownian Motion extension into an Irrational fractional Brownian Motion model, we re-examine agent behaviour reacting to time dependent news on the log-returns thereby modifying a financial market evolution. We specifically discuss the role of financial news or economic information positive or negative feedback of such irrational (or contrarian) agents upon the price evolution. We observe a kink-like effect reminiscent of soliton behaviour, suggesting how analysts' forecasts errors induce stock prices to adjust accordingly, thereby proposing a measure of the irrational force in a market.
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