Investment bankers and analysts are exploring applications of new techniques to understand
the price behavior in the stock market. A plethora of concepts from physics are used in the
field of finance—like earth quake prediction techniques to predict stock market price
fluctuations (Sorenette, 2004), quantum physics to understand stock price behavior and the
concept of Brownian motion in option pricing (Beinhocker, 2007). This study applies an
engineering concept, fuzzy logic, to understand the underpinning relationship between
national sentiments, investor sentiments and their impact on stock market activities. Though
share price is affected by a number of extended factors, it depends mainly on the demand for
and supply of the particular security. When the number of shares available in a given company
is limited, increase in demand for the company share will automatically increase the price of
the share and vice versa. In theory, only the performance of a company should impact upon
its share price and those reporting growing profit are likely to have higher demand (Irungu,
2013). However, the current state of the market and the economy as a whole has a bearing on
stock price fluctuations. For example, though the terrorist attacks in September 2001 had
nothing to do directly with many publicly traded companies, stock markets around the world
plummeted as investors sold shares in a fit of panic. Eventually, it is public mood that sparks
the movement in share prices in the short run (Narayanan, 2007). Hence, this research tests
the relationship between national sentiments and stock markets.
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