Questions 51 to 55 are based on the following passage. Clear Macro CEO Mike Simcock, who has 25 years of professional asset management experience, says he started the company to help investment managers that were drowning in a deluge of data. There has been a massive explosion in data sources, many offering the prospect of more timely information and more impactful signals. But the big data revolution is actually compounding a problem that was already there, says Simcock. Advancements in technology are ytical processes accessible beyond the world of hedge funds (对冲基金) and CTAs( 交易顾问 ) ; things like back testing tools and ways of aggregating information and visualizing information in a really efficient way. Clear Macro is building a “ Wikipedia of investment strategies ” . It applies strategic, tactical and systematic asset allocation strategies, alongside a combination of select data sets providing real time macro insights, from text media and now-casting to cross border central bank liquidity statistics. Simcock suggests a less is more approach to data. “We are not scraping the internet for data. We are doing aggregation in the sense that we are sourcing what we call best quality data sets for the categories of information that we think decision makers care about holistically, as well as tools to back test and gain conviction over what works and what doesn’t. “He said big data sets within the hedge fund space tend to be really focused on tactical, higher frequency, shorter term decision , such as trying to gain an edge on payrolls or the next move in inflation, or company results. The industry is very quickly going to move much further toward data driven automated research and investible strategies. “Funds or products that are essentially driven more and more by rules, and can be delivered in different ways, whether it’s an ETF structure or simply connecting to interactive brokers.” Suddenly all sorts of owners of data are realizing the power of their data sets. “We are completely unaware of whether we use traditional data or new data. If we can demonstrate it adds some value then that can justify paying for it.” Data does not come cheap: all sorts of entities are offering to sell their data, from anywhere between £ 25K and £ 250K , and upward. “The value of data is in the eyes of the beholder,” said Simcock. “Typically I think the way that data sales work is that everything is up for negotiation,” he said. “Some of the things we are finding is a lot of the classic data sets are delivering better performance when you build them into strategies. The message I would give to someone asking how should I deal with this landscape—embrace technologies that can make your job easier and take your time.”