visualizing pattern from cross risk factors scenario information

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Visualizing pattern from cross risk factors scenario information

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Visualizing pattern from

cross risk factors scenario information

About me…

Sai-Ming(Simon) LawMajored in Math at KSU, Georgia2nd Year, Master’s in Applied StatisticsPassed: Exam P and FMInterned w/ Pacific Life Insurance Co.

(Summer 2012)

Goals: Visually present cross risk factors scenario information

2D & 3D plots Automate the input /output process

Overlay scenario graphs with associated severity of outcomes Outline pattern, “hot spots” in the scenarios where severity

tends to be high or low (EC)

About the project I worked on…

About this talk…

How to use R from within Excel

How to automate the input/output process

How to use R from within Excel

How to use R from within Excel

Install RExcel• http://

homepage.univie.ac.at/erich.neuwirth/php/rcomwiki/doku.php?id=wiki:how_to_install

Enable Macro and Developer Ribbon

Go to C:\Program Files (x86)\RExcel\xls

Run the Macro, RExcelAddinAutoInstall

Check References, RExcelVBAlib, in a Macro Window

How to use R from within Excel

About macros in Excel• a series of commands and functions that are stored in a Microsoft

Visual Basic module • can be run whenever you need to perform the task.

Video Demostration • http://rcom.univie.ac.at/RExcelDemo/

How to automate the input/output process

Goals: Visually present cross risk factor scenario information

2D & 3D plots Automate the input /output process

Overlay scenario graphs with associated severity of outcomes Outline pattern, “hot spots” in the scenarios where severity

tends to be high or low (EC)

How to automate the input/output process

Tasks:1. Read in Scenario Information ( a big data set)

Excel Visual Basic Application Error Checking

2. Manipulate the data R

3. Apply bucketing algorithm

4. Summarize data

5. Create Plot

6. Transport plots R Excel

PL: SWAP 10Y x EQUITY S&P x CREDIT

Scenario frequency findings

Correlation

Edges

Clusters

Outcome severity findings Dark (losses)

vs. light (gains)

Credit & interest rates have highest impact

PL’s “perfect storm” scenario

PL: SWAP 10Y x EQUITY S&P x CREDIT

PL: SWAP 10Y x EQUITY S&P x CREDIT Frequency vs. Severity

“Blind spots” Frequency clusters are trivial spots in severity

IIP: SWAP 10Y x SWAP 1Y x CREDIT Frequency vs. Severity

Credit dominates SWAP rates have high correlation

Special Thanks…

Dr. Feldman

Benson Chen

Q & A …