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The purpose of this thesis

The purpose of this thesis 9600w
The purpose of this thesis is to provide an insight into quantitative risk management through the introduction of the two risk measures, Value at Risk and Expected Shortfall by estimating these with GARCH, Semi-GARCH, and Volatility Weighted Historical Simulation. The theoretical background gives a basic understanding of risk management and risk measures for financial institutions. The development of Basel Accords can be regarded as a standard for bank’s trading portfolios by determining capital requirements. To effectively manage the market risks, it is extremely important to estimate the risk measures. The most commonly reported risk measure is Value at Risk, which is defined as the maximum expected loss of a portfolio over a defined time horizon with a given confidence level. However, VaR fails to capture tail risk and is not a coherent measure of risk due to its non-sub-additive character. The Expected Shortfall, on the other hand, satisfies this property and thus is a coherent risk measure. It is now widely used in quantitative risk management. Besides, the ES provides an average of the losses that exceed the VaR, that means it indicates a better property than VaR with respect to tail risk. Moreover, this thesis compares the forecasting ability of different models in estimating VaR and ES, whereby modelling of GARCH, Semi-GARCH and VWHS are investigated. These models represent the most important tools in the quantitative risk management for financial institutions. With the advancement of quantitative risk models for the analysis of financial time series, the risk managers could get potential opportunities to understand and study the structure as well as the behaviour of financial markets. The progress of each model and the procedure to estimate risk measures were introduced and then applied in the empirical section. In terms of forecasting risk measures, an accurate model should be evaluated by Backtesting. This is a method of testing risk models by providing probabilities about the extent to which the calculated forecasts match the actual losses. The results of Backtesting therefore might indicate possible problems and support risk managers in making decision as well as planning strategies. In conclusion, after presenting the different ways modeling risks and empirical analysis using various financial datasets, it is important to highlight that the Semi-GARCH model generates the best predictive performance in comparison, with GARCH and VWHS models also performing well.
The purpose of this thesis is to provide an insight into
quantitative
risk
management
through the introduction of the two
risk
measures
, Value at
Risk
and
Expected
Shortfall by estimating these with
GARCH
,
Semi-GARCH
, and Volatility Weighted Historical Simulation.

The theoretical background gives a basic understanding of
risk
management
and
risk
measures
for
financial
institutions.
The
development of Basel Accords can
be regarded
as a standard for bank’s trading portfolios by determining capital requirements. To
effectively
manage the market
risks
, it is
extremely
important
to estimate the
risk
measures
. The most
commonly
reported
risk
measure
is Value at
Risk
, which
is defined
as the maximum
expected
loss of a portfolio over a defined time horizon with a
given
confidence level.
However
,
VaR
fails to capture tail
risk
and is not a coherent
measure
of
risk
due to its non-sub-additive character. The
Expected
Shortfall,
on the other hand
, satisfies this property and
thus
is a coherent
risk
measure
. It is
now
widely
used
in
quantitative
risk
management
.
Besides
, the ES provides an average of the losses that exceed the
VaR
, that means it indicates a better property than
VaR
with respect to tail
risk
.

Moreover
, this thesis compares the forecasting ability of
different
models
in estimating
VaR
and ES, whereby modelling of
GARCH
,
Semi-GARCH
and
VWHS
are investigated
. These
models
represent the most
important
tools in the
quantitative
risk
management
for
financial
institutions. With the advancement of
quantitative
risk
models
for the analysis of
financial
time series, the
risk
managers could
get
potential opportunities to understand and study the structure
as well
as the
behaviour
of
financial
markets. The progress of each
model
and the procedure to estimate
risk
measures
were introduced
and then applied in the empirical section.

In terms of forecasting
risk
measures
, an accurate
model
should
be evaluated
by
Backtesting
. This is a method of testing
risk
models
by providing probabilities about the extent to which the calculated forecasts match the actual losses. The results of
Backtesting
therefore
might indicate possible problems and support
risk
managers in making decision
as well
as planning strategies.

In conclusion
, after presenting the
different
ways modeling
risks
and empirical analysis using various
financial
datasets, it is
important
to highlight that the
Semi-GARCH
model
generates the best predictive performance
in comparison
, with
GARCH
and
VWHS
models
also
performing well.
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IELTS essay The purpose of this thesis

Essay
  American English
5 paragraphs
386 words
5.5
Overall Band Score
Coherence and Cohesion: 6.0
  • Structure your answers in logical paragraphs
  • ?
    One main idea per paragraph
  • Include an introduction and conclusion
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  • Use cohesive linking words accurately and appropriately
  • Vary your linking phrases using synonyms
Lexical Resource: 5.0
  • Try to vary your vocabulary using accurate synonyms
  • Use less common question specific words that accurately convey meaning
  • Check your work for spelling and word formation mistakes
Grammatical Range: 6.5
  • Use a variety of complex and simple sentences
  • Check your writing for errors
Task Achievement: 5.0
  • Answer all parts of the question
  • ?
    Present relevant ideas
  • Fully explain these ideas
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