|
Showing 1 - 6 of
6 matches in All Departments
Statistical techniques can be used to address new situations. This
is important in a rapidly evolving risk management and financial
world. Analysts with a strong statistical background understand
that a large data set can represent a treasure trove of information
to be mined and can yield a strong competitive advantage. This book
provides budding actuaries and financial analysts with a foundation
in multiple regression and time series. Readers will learn about
these statistical techniques using data on the demand for
insurance, lottery sales, foreign exchange rates, and other
applications. Although no specific knowledge of risk management or
finance is presumed, the approach introduces applications in which
statistical techniques can be used to analyze real data of
interest. In addition to the fundamentals, this book describes
several advanced statistical topics that are particularly relevant
to actuarial and financial practice, including the analysis of
longitudinal, two-part (frequency/severity), and fat-tailed data.
Datasets with detailed descriptions, sample statistical software
scripts in "R" and "SAS," and tips on writing a statistical report,
including sample projects, can be found on the book s Web site:
http: //research.bus.wisc.edu/RegActuaries.
This focuses on models and data that arise from repeated
observations of a cross-section of individuals, households or
companies. These models have found important applications within
business, economics, education, political science and other social
science disciplines. The author introduces the foundations of
longitudinal and panel data analysis at a level suitable for
quantitatively oriented graduate social science students as well as
individual researchers. He emphasizes mathematical and statistical
fundamentals but also describes substantive applications from
across the social sciences, showing the breadth and scope that
these models enjoy. The applications are enhanced by real-world
data sets and software programs in SAS and Stata.
Predictive modeling uses data to forecast future events. It
exploits relationships between explanatory variables and the
predicted variables from past occurrences to predict future
outcomes. Forecasting financial events is a core skill that
actuaries routinely apply in insurance and other risk-management
applications. Predictive Modeling Applications in Actuarial Science
emphasizes life-long learning by developing tools in an insurance
context, providing the relevant actuarial applications, and
introducing advanced statistical techniques that can be used to
gain a competitive advantage in situations with complex data.
Volume 2 examines applications of predictive modeling. Where Volume
1 developed the foundations of predictive modeling, Volume 2
explores practical uses for techniques, focusing on property and
casualty insurance. Readers are exposed to a variety of techniques
in concrete, real-life contexts that demonstrate their value and
the overall value of predictive modeling, for seasoned practicing
analysts as well as those just starting out.
Predictive modeling involves the use of data to forecast future
events. It relies on capturing relationships between explanatory
variables and the predicted variables from past occurrences and
exploiting this to predict future outcomes. Forecasting future
financial events is a core actuarial skill actuaries routinely
apply predictive-modeling techniques in insurance and other
risk-management applications. This book is for actuaries and other
financial analysts who are developing their expertise in statistics
and wish to become familiar with concrete examples of predictive
modeling. The book also addresses the needs of more seasoned
practicing analysts who would like an overview of advanced
statistical topics that are particularly relevant in actuarial
practice. Predictive Modeling Applications in Actuarial Science
emphasizes life-long learning by developing tools in an insurance
context, providing the relevant actuarial applications, and
introducing advanced statistical techniques that can be used by
analysts to gain a competitive advantage in situations with complex
data."
Statistical techniques can be used to address new situations. This
is important in a rapidly evolving risk management and financial
world. Analysts with a strong statistical background understand
that a large data set can represent a treasure trove of information
to be mined and can yield a strong competitive advantage. This book
provides budding actuaries and financial analysts with a foundation
in multiple regression and time series. Readers will learn about
these statistical techniques using data on the demand for
insurance, lottery sales, foreign exchange rates, and other
applications. Although no specific knowledge of risk management or
finance is presumed, the approach introduces applications in which
statistical techniques can be used to analyze real data of
interest. In addition to the fundamentals, this book describes
several advanced statistical topics that are particularly relevant
to actuarial and financial practice, including the analysis of
longitudinal, two-part (frequency/severity), and fat-tailed data.
Datasets with detailed descriptions, sample statistical software
scripts in "R" and "SAS," and tips on writing a statistical report,
including sample projects, can be found on the book s Web site:
http: //research.bus.wisc.edu/RegActuaries.
This focuses on models and data that arise from repeated
observations of a cross-section of individuals, households or
companies. These models have found important applications within
business, economics, education, political science and other social
science disciplines. The author introduces the foundations of
longitudinal and panel data analysis at a level suitable for
quantitatively oriented graduate social science students as well as
individual researchers. He emphasizes mathematical and statistical
fundamentals but also describes substantive applications from
across the social sciences, showing the breadth and scope that
these models enjoy. The applications are enhanced by real-world
data sets and software programs in SAS and Stata.
|
You may like...
Merry Christmas
Mariah Carey, Walter Afanasieff, …
CD
R122
R112
Discovery Miles 1 120
|