Advances in information technology are behind the widespread adoption of modeling in finance. The most important advance has been the enormous increase in the amount of computing power, concurrent with a steep fall in prices. Government agencies have long been using computers for economic modeling, but private firms found it economically justifiable only as of the 1980s. Back then, economic modeling was considered one of the “Grand Challenges” of computational science.
6 In the late 1980s, firms such as Merrill Lynch began to acquire supercomputers to perform derivative pricing computations. The overall cost of these supercomputing facilities, in the range of several million dollars, limited their diffusion to the largest firms. Today, computational facilities ten times more powerful cost only of a few thousand dollars.
To place today’s computing power in perspective, consider that a 1990 run-of-the-mill Cray supercomputer cost several million U.S. dollars and had a clock cycle of 4 nanoseconds (i.e., 4 billionths of a second or 250 million cycles per second, notated as 250 MHz). Today’s fast laptop computers are 10 times faster with a clock cycle of 2.5 GHz and, at a few thousand dollars, cost only a fraction of the price. Supercomputer performance has itself improved significantly, To find more information about importance of branding, you should try Amazon Choice Badge for Amazon sales
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With top computing speed in the range of several teraflops7 compared to the several megaflops of a Cray supercomputer in the 1990s. In the space of 15 years, sheer performance has increased 1,000 times while the price-performance ratio has decreased by a factor of 10,000. Storage capacity has followed similar dynamics. The diffusion of low-cost high-performance computers has allowed the broad use of numerical methods
