Monday 27 June 2016

Financial Risk Measurement

                             Financial Risk Measurement
                                                for 
                             Financial Risk Management

The current system is still largely a restrictive approach to measuring market risk
Historical simulation or RiskMetrics. On the contrary, it is proposed
Take advantage of recent developments in financial economics and statistics that flexible ways
They are likely to generate more accurate assessment of risk, both treatment portfoliolevel
Analysis and asset levels. Surface analysis is particularly difficult asset
Due to the demands of real-world risk management in financial institutions
- In particular, the dimensions of the high risk monitoring in real time -
Imposes strict limits on model complexity.



Therefore, we emphasize the powerful and parsimonious
The model was easily guess. In addition, we stress the need
And market risk and to deepen economic ties between
Fundamentals, mainly the capital, focusing on the links between the goods return volatilities
volatilities growth and economic development. Every time, we try not only to deepen
Our scientific understanding of market risk, but also put fertilizer through education
Header and communities, promoting a better measure of market risk

Technology based on the best of both.

 Introduction

Financial risk management is a huge field with diverse and changing components, such as
The best of both historical and current development as evidenced by Diebold
Practice. One such ingredient - perhaps the main ingredient
Specific measurement of financial assets in return volatilities, risk measurement
Now connect the volatilities. Basically, volatilities and return assets
They are variable in time, with a continuous animated. All assets, the asset class is true,
Many surfaced during the crisis period of time and countries, so vividly
Events, most recently as 2007-2008 financial crisis and its long-term
The sequelae. Financial Econometrics field devoted considerable attention
The volatility for different measuring and modeling tools and
prediction. In this chapter, it is advisable to offer new practical applications down
Economic statistics to measure parsimonious and exposed to market risk management,
The model was easily guess. Our ultimate goal is to encourage dialogue
Between academic and practitioner communities, develop best market practices
Risk measurement and management technologies by drawing upon the best of both.

Six Emergent Themes 

 Six main themes emerged, and highlight them here. We tried some of them directly
We treat others indirectly touching these parts, clearly focused on
Bob around, and in different places from different angles.
The first issue relates to the aggregation level. We both portfolio level (overall consideration,
"Top-down") and the assets (disaggregated, "down") modeling, emphasis on
Discrimination related to the measurement and risk management.
Risk measurement and risk management Generally, only one model portfolio level
This requires an active surface model.
The second issue is the question of observation data frequency. We consider
Both low-frequency and high-frequency data, and the associated parametric
Than nonparametric volatility measure. We treat all cases but emphasized
Nonparametric methods used measure of volatility used with high attention
Count frequency data, is deliberately followed by parametric modeling.
The third problem is a question of modeling and monitoring variables in conditional tense
Not only on the density and conditional volatilities. It is argued that a complete subject
Point density necessary for a comprehensive risk assessment, and BestPractice
Movement and indeed is - - the direction it should move risk management.
Construction, discusses methods for the collection, evaluation and full conditional densities are believed to
Forecasts.
The fourth issue related to the dimensionality reduction of multivariate "big data"
Environment, a major problem in the asset-level analysis. We devote considerable attention
Higher Dimensional Modeling Facility management framework that
The estrangement of practical relevance matrix. Methods of contraction factor structure
(And interface) feature.
The fifth issue is the question of links between market risk and economic fundamentals.
A recent work has begun to explore the links between asset market volatility
And macroeconomic fundamentals. These links are focusing the discussion on the
Return, real growth and real development of relations between volatilities of shares in volatilities.
The sixth issue, supported unconditional subject to the risk
We are dedicated to measuring the next paragraph long, so it is important
Discussion of the subject. In this chapter the argument for most that is,
Financial risk management, subject outlook is clearly more
Relevant to the daily market risk monitoring.