Investigating Long-Term Behavior of Milan Stock Exchange (Italy)

Investigating Long-Term Behavior of Milan Stock Exchange (Italy)

DOI: 10.4018/978-1-5225-9269-3.ch017

Abstract

The main purpose of this chapter is to highlight the long-term behavior of Milan Stock Exchange (Italy) based on the FTSE MIB major stock market index. The empirical analysis covers a long period of time from January 1999 to December 2013 and describes the daily stock price movements in order to identify both financial expansion and contraction cycles. However, Milan Stock Exchange is a developed stock market that exhibits a more stable behavior than emerging stock markets, even stylized facts are much lower in this case. The econometric analysis provides an exhaustive perspective, because selected stock market behavior has changed completely due to the negative influence of the global financial crisis.
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Applied Methodology

Birau (2014a) argued that the results of the empirical analysis enable access to subsequent advance stock market performance based on the case of Milan Stock Exchange (Italy). This study empirically established the relationship between the long-term behavior of Milan stock exchange and the recent financial crisis.

The global financial crisis that erupted in mid-2007 in U.S.A. triggered severe consequences on various stock markets all over across the world. Dramatically, such an extreme event is relatively rare and highly unpredictable, while being almost impossible to predict because does not follow a historical pattern. Therefore, beyond the arguments that support the validity of normal distribution assumption, dramatic financial events followed by significant stock market disturbances or crashes occurred quite frequently in recent past.

Birau, R. (2014d) suggested that the influence of economic, monetary, financial and technical factors holds a massive weight in terms of investment phenomenon dimensions considering that the significant benefits of internalization derived from international linkages and global economic interdependencies. In this regard, the impact of technical factors is determined by the widespread use of high-performance computers, high-frequency trading, increasingly sophisticated software and communications systems, in addition with the increasing volume of financial transactions, especially speculative trades.

Moreover, stock crashes followed by severe financial crisis occurred quite frequently in the last century, sometimes reaching global dimensions, such as: the Great Depression between the years 1929-1933, Latin American financial debt crisis of the 1980s, Black Monday (Black Monday) in 1987, the Asian financial crisis of 1997 – 1998, Russian financial crisis or Ruble crisis in 1998, DOTCOM bubble during 2000 and 2002 and the Subprime crisis that erupted in August 2007 in U.S.A.

Financial time series, such as daily stock market returns are characterized by high-frequency and excessive volatility, respectively the stylized facts called “volatility clustering”. The continuously-compounded daily returns are calculated using the log-difference of stock markets selected indices, as follows:

978-1-5225-9269-3.ch017.m01
where p is the daily closing price.

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