Results Of The Use Of Predictive Analytics In Life And Health Insurance


wealthymattersPredictive analytics involves the analysis of large data sets ie big data ,to make inferences by identifying meaningful relationships between different variables and using these relationships to forecast what might happen in the future with an acceptable level of reliability.Predictive Analytics includes what-if scenarios and risk assessments.

Now, insurance is an industry where intelligent use of data can provide huge competitive advantages.So over the last dozen years, insurance companies world-wide have tried to be early adopters in using the emerging science of predictive analytics in life and health insurance to get ahead of their competitors.They have attempted to use predictive analytics to segment and underwrite their risks in a more accurate, reliable and cost-effective way. Read more of this post

Tobias Preiss And Google Trends


wealthymattersGoogle Trends, a tool that looks at patterns of searches on the internet, is a potential money-spinner for investors as it provides hints of impending stock movements according to a study  led by Tobias Preis at the Warwick Business School in England .The researchers analysed data from Google Trends from 2004 to 2011.They looked at the volume of searches for 98 terms, such as “metals”, “stock”, “finance”, “forex”, “house”, “unemployment” and “health” as well as non-specific or neutral words, such as “ring”, “train”, kitchen” and “fun”.They then constructed a virtual portfolio of investment in the Dow Jones Industrial Average (DJIA), with a strategy based on search volumes that occurred on Sundays.If the search volume that day was high compared with a week earlier, the DJIA investment was systematically sold at the closing price the following day, and then repurchased at the end of the first day of trading in the week after.Conversely, if the search volume on Sunday was low compared with the previous week, the researchers “bought” the following day.Using the keyword “debt” – the term that saw the most fluctuation during the study period – the strategy netted a whopping cyber-profit of 326 per cent over seven years.By comparison, a strategy of buy-and-hold – purchasing in 2004 and selling in 2011 – would have yielded only 16 per cent profit, equal to the rise in the DJIA during this time.A third strategy, of buying or selling on the basis of movements in the Dow itself, would have netted a gain of 33 per cent.The results suggest that, following this logic, during the period 2004 to 2011, Google Trends search query volumes for certain terms could have been used in the construction of profitable trading strategies. Read more of this post

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