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Visualizing pattern from cross risk factors scenario information

Visualizing pattern from cross risk factors scenario information . About me…. Sai -Ming(Simon) Law Majored in Math at KSU, Georgia 2 nd Year, Master’s in Applied Statistics Passed: Exam P and FM Interned w/ Pacific Life Insurance Co. (Summer 2012 ).

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Visualizing pattern from cross risk factors scenario information

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  1. Visualizing pattern from cross risk factors scenario information

  2. About me… • Sai-Ming(Simon) Law • Majored in Math at KSU, Georgia • 2nd Year, Master’s in Applied Statistics • Passed: Exam P and FM • Interned w/ Pacific Life Insurance Co. (Summer 2012)

  3. About the project I worked on… 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)

  4. About this talk… • How to use R from within Excel • How to automate the input/output process

  5. How to use R from within Excel

  6. 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

  7. 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/

  8. 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)

  9. How to automate the input/output process Tasks: • Read in Scenario Information ( a big data set) • Excel Visual Basic Application • Error Checking • Manipulate the data • R • Apply bucketing algorithm • Summarize data • Create Plot • Transport plots • R  Excel

  10. PL: SWAP 10Y x EQUITY S&P x CREDIT • Scenario frequency findings • Correlation • Edges • Clusters

  11. PL: SWAP 10Y x EQUITY S&P x CREDIT • Outcome severity findings • Dark (losses) vs. light (gains) • Credit & interest rates have highest impact • PL’s “perfect storm” scenario

  12. PL: SWAP 10Y x EQUITY S&P x CREDIT Frequency vs. Severity • “Blind spots” • Frequency clusters are trivial spots in severity

  13. IIP: SWAP 10Y x SWAP 1Yx CREDIT Frequency vs. Severity • SWAP rates have high correlation • Credit dominates

  14. Special Thanks… • Dr. Feldman • Benson Chen

  15. Q & A …

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