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Twitter. Simulation results show that our network-embedded prediction market can produce better predictions as a result of the … forecasting errors decrease with the cost of acquiring information in a network-embedded prediction market …
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and information exchange promote the forecast efficiency in prediction markets? Our study shows that a social network is … not a panacea in terms of improving forecast efficiency. The use of social networks could be detrimental to forecast … and increasing in the network density. The aforementioned results are robust to two commonly used mechanisms of prediction …
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Behavioral and experimental literature on financial instability focuses on either subjective price expectations (Learning-to-Forecast experiments) or individual trading (Learning-to-Optimize experiments). Bao et al. (2017) have shown that subjects have problems with both tasks. In this paper, I...
Persistent link: https://www.econbiz.de/10011956452
Behavioral and experimental literature on financial instability focuses on either subjective price expectations (Learning-to-Forecast experiments) or individual trading (Learning-to-Optimize experiments). Bao et al. (2018) have shown that subjects have problems with both tasks. In this paper, I...
Persistent link: https://www.econbiz.de/10012894616
This paper contributes to model the industry interconnecting structure in a network context. General predictive model … interdependency networks. Empirical results show a denser network with heterogeneous central industries in tail cases. Network … out-of-sample forecast of portfolio returns and network centrality-based trading strategies seem to outperform market …
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