Processing of informative signals on financial markets
Project Description
Many decision-making models highlight the importance of informative signals as a relevant source of information
on financial markets. However, although this importance is undisputed as such, we know only little
about what kind of signals gain our attention, how we can increase salience of specific information sources,
how we perceive different types of signals and how they influence our decision behavior.
This is a follow-up project to the FFF-financed project Perception and Processing of informative signals on
financial markets. Within these projects we concentrate on experimental asset markets and focus on three
important aspects of signals. First, we look at existing trading screens and analyze what kind of information
gets the most attention by traders. In a second step, we will use the produced knowledge and analyze how
specific information sources that are objectively important can be visualized so that they become more
salient, hence get more attention and therefore lead to enhanced investor behavior. In a third step we
loosen the assumption that signals are provided for free. We analyze how costly information is spread (un-
)willingly over the market and how trader networks process and buy information.
Trading screens and interfaces of stock market traders display a wide range of data and are a main source
of information. Traders not only execute their trades via these interfaces, they also see a lot of condensed
and visualized information on them, like price charts, current prices, historical transaction data, fundamental
evaluations and many others. The existence and influence of different types of information has been
studied in the past, and it is undisputed that the level and the type of information a trader has available
influences his trading behavior. However, a clear analysis of what type of information provided really grabs
the attention of traders is still missing. We aim at filling this gap by conducting an eye-tracking study to
analyze which information sources are used when and to what degree. As a result, we aim to better understand
how information is perceived. We also want to deliver a strong methodological contribution to the
experimental asset market literature, which can use our findings to improve experimental trading interfaces.
on financial markets. However, although this importance is undisputed as such, we know only little
about what kind of signals gain our attention, how we can increase salience of specific information sources,
how we perceive different types of signals and how they influence our decision behavior.
This is a follow-up project to the FFF-financed project Perception and Processing of informative signals on
financial markets. Within these projects we concentrate on experimental asset markets and focus on three
important aspects of signals. First, we look at existing trading screens and analyze what kind of information
gets the most attention by traders. In a second step, we will use the produced knowledge and analyze how
specific information sources that are objectively important can be visualized so that they become more
salient, hence get more attention and therefore lead to enhanced investor behavior. In a third step we
loosen the assumption that signals are provided for free. We analyze how costly information is spread (un-
)willingly over the market and how trader networks process and buy information.
Trading screens and interfaces of stock market traders display a wide range of data and are a main source
of information. Traders not only execute their trades via these interfaces, they also see a lot of condensed
and visualized information on them, like price charts, current prices, historical transaction data, fundamental
evaluations and many others. The existence and influence of different types of information has been
studied in the past, and it is undisputed that the level and the type of information a trader has available
influences his trading behavior. However, a clear analysis of what type of information provided really grabs
the attention of traders is still missing. We aim at filling this gap by conducting an eye-tracking study to
analyze which information sources are used when and to what degree. As a result, we aim to better understand
how information is perceived. We also want to deliver a strong methodological contribution to the
experimental asset market literature, which can use our findings to improve experimental trading interfaces.
