Big data: Costly, but is it useful?Although big data is usually directly associated with machine learning, there is still a debate whether new data sources, such as web crawling through news or social media, credit card data, geolocation data, and so on, is helpful in the investment process. Some specific examples of trading strategies based on such data include using Twitter sentiment to make bets on the equity market as a whole or individual stocks in particular or using geolocation data to estimate retail activity relevant to individual stocks (e.g., footfall at retail stores).
The Barclays report states that 54% of surveyed investment managers use alternative data, such as web crawling social media data, satellite data, or credit card data. This finding suggests it is less prevalent than tick data (100% usage) or fundamental data (62% usage), such as balance sheet or income statement data, but more prevalent than economic data (38% usage), such as employment or inflation figures, or sell-side data (31% usage), such as analyst reports or broker recommendations.
Despite the widespread use of alternative data, 80% of surveyed investment managers in the Barclays report said that their biggest challenge was in assessing the usefulness of the data.
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The Barclays report states that 54% of surveyed investment managers use alternative data, such as web crawling social media data, satellite data, or credit card data. This finding suggests it is less prevalent than tick data (100% usage) or fundamental data (62% usage), such as balance sheet or income statement data, but more prevalent than economic data (38% usage), such as employment or inflation figures, or sell-side data (31% usage), such as analyst reports or broker recommendations.
Despite the widespread use of alternative data, 80% of surveyed investment managers in the Barclays report said that their biggest challenge was in assessing the usefulness of the data.
More >>>
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