With equal parts of reluctance and confusion people around the world are opening business pages, tuning into financial programs and checking in with friends and family to better understand how and why the devaluation of China’s currency has sent uncertainty through global markets and ultimately to personal financial savings.
Most investors are faced with a similar question: Who can I trust to offer a simple explanation about what’s happening and what I should do? Trust is indeed hard to find when reactions from financial experts range from hyperbolic to chillax.
Turning Point – IBM Defeats Kasparov
Long before China’s devaluation, inside certain investment circles the advice about where and when to invest has been – shall we say – less than personal. In April 2015 the Wall Street Journal published a piece entitled, ‘How Computers Trawl a Sea of Data for Stock Picks’. In it reporter Bradley Hope introduces readers to the notion of quantitative investing, ‘quants’ for short. The concept is explained in the extract, below…
“The approach….relies mainly on mathematical models. But its practitioners differ from traditional “quants,” who program their computers to bet on statistical relationships among securities prices and don’t bother much with real-world information.”
Said another way quantitative investing is leveraging the analysis of data to arrive at what are believed to be better than human conclusions about where investments should be made. The process is explained further, here…
“In determining how to trade the stock of, say, a major big-box retailer…scientists and mathematicians devise dozens of computer-trading models related to the stock. One model would automatically pore through analysts’ research for patterns in how they view the retailer—much as a human broker might. Another would look for clues in Twitter: It might identify one pattern—a growing number of customers tweeting complaints, say—and correlate that with another pattern, such as data showing fewer people visiting stores. Additional algorithms would do other tasks human investors traditionally perform: watching for the stock price to break through a 200-day average, say, or monitoring whether executives are buying or selling company shares.”
Similar to the insight in knowing the model of car your mechanic drives it’s always interesting to know how financial experts choose to invest their own money. But whether it’s the brain or the CPU making the decisions, speed in transactions is undeniably a critical component in ensuring buyers and sellers are able to capitalize on opportunities and respond with agility to market changes.
Earlier this month Seagate announced an expansion of its Nytro Flash Products, which are designed for such environments. Seagate’s Nytro portfolio is built for demanding enterprise applications, such as online transaction processing (OLTP), high frequency trading, high-performance computing (HPC), data warehousing, data mining and data analytics as well as workloads with mixed IO sizes and multiple applications running simultaneously.
Flash storage technology is increasingly sought within financial service and other markets where high performance can be achieved alongside increases in storage densities, reduced storage footprints and power use in data centers. To learn more about Seagate’s line of flash technology visit our website.
