| dc.description.abstract | The purpose of this thesis is to investigate the relationship between multiple possible leading
indicators and the stock market (S&P500 index). A leading indicator can be defined as a piece
of data that corresponds to the future movements in a variable of interest. Thus, considering
the information they contain, one may be able to anticipate the movement of the stock market.
The indicators to examine are representations of market sentiment, reflecting the risk tolerance
of investors in the financial markets. They have been determined based on existing literature,
in addition to reflections of the authors of this thesis. For example, the Put/Call ratio (Pan and
Poteshman, 2003) and the Gold/Platinum ratio (Huang and Kilic, 2019) has been shown to
have predictive abilities towards the stock market. Previous research has mainly focused on
the potential leading indicators individually. To explore their abilities combined is therefore
of interest.
The results appear to favorize the inclusion of multiple indicators in this analysis. However, it
shows conflicting evidence for the predictive abilities of the indicators toward the stock index.
Parts of the analysis appear to show predictive capabilities, while others are less conclusive,
which complicates the utilization of the results. The patterns seem to change as different
periods are examined, but when changes in the economic environment are considered many
of these observations seem reasonable.
A vector autoregressive model (VAR-model) is facilitating the use of both the present and past
notations of the indicators in a system. Multiple models were created, one where the whole
sample period was included, in addition to several subsets to display the potential changes that
occur. The model including the whole sample period (2005-2020) is reporting an adjusted R2
of 12,0%, where the subsets range from 18,1% to 28,4%, suggesting that the importance of
the indicators varies through time, as different pattern emerges.
The results from the VAR-model are evaluated using granger causality test and impulse
response analysis. The indicators appear to be granger causal throughout the analysis, with
only one exemption in one of the subsets. In the impulsive response functions, a theoretical
shock is performed on the indicators. It illustrates that whenever there is an increase in
indicators like the Put/Call ratio, the U.S. Dollar index (the relative strength of the dollar) and
the credit spread (Baa-Aaa), the stock index appears to consistently react negatively to this.
The Gold/Platinum and the Volume Weighted Moving Average looks to result in rather
inconsistent reactions. The decomposition of the variance shows that most of the variance
comes from the shocks in the stock index itself, which is the recurring observation throughout
the subsets. This is to be expected in the beginning of the simulated period. Later, more of the
variance is explained by the other indicators. Nonetheless, the increase should have been larger
to claim it supports the hypothesis of the predictive abilities. | en_US |
