DISSERTATIONS

 

Students

MSc Dissertation Title

Project Description

2004 Dissertations

Isla Cunningham

 

Jianchun Wu

“Modelling a With-Profits Annuity”

The with-profits annuitants (WPAs) of Equitable Life receive annuity payments (P) made up of a guaranteed annuity amount (GA) and a non-guaranteed annuity amount (NGA) so P=GA+NGA. The WPAs have suffered a reduction in the annuity paid (P) to them of some 30% of P, by reducing the NGA by more than 30%. The level of guaranteed annuity (GA) goes down every year in a prescribed way, according to the so-called ‘anticipated bonus rate’ (ABR). The project will involve modeling the WPA fund by each year’s annuity payment being treated as the maturity proceeds of a pure with-profits endowment with a single premium of SP(i) {where i runs from 1 to the expectation of life} and where the total of SP(i) equals the purchase price of the annuity. Each SP(i) will be invested in fixed-interest stock maturing exactly when the corresponding pure endowment matures and matching exactly the amount of guaranteed annuity (GA) and the balance of SP(i) will be invested in equities and property. Given the way equities and property have moved over the last seven or so years the proceeds of the (already matured) pure endowments will be worked out as well as the likely proceeds of the yet-to-mature pure endowments.

References

Trapped Annuitants web-site -   see   http://www.cookham.com/community/equitable/elta.htm

Barclay’s Gilt/Equity study - from Faculty Library

Commercial Property Index see - http://www.ipdindex.co.uk/results/indices/uk_annual/index_uk_annual.asp

Letter sent to Norwich Union, Standard Life and Prudential asking them what they would now be paying on their WPA, corresponding to Equitable’s WPA.

Renren Zhong

 

Hui Yu

“A Guaranteed Annuity Option either as an Exchange Option (so called Type 1 GAR) or as a Quanto Option (so called Type 2 GAR)”

The topic required the capabilities of a compiled language like C++  to run tests for a guaranteed annuity rate option (GAR) on a with-profits policy looking at the situation (a) where the full accumulated fund is applied at the guaranteed annuity rate (GAR) - a so called 'Hyman-annuity-guarantee'  or Type 2 GAR (b) where the full accumulated fund is applied at the current annuity rate (CAR not GAR) but with a minimum 'floor annuity' payable (where the ‘floor annuity' is only the guaranteed (contractual) fund (i.e. ignoring terminal bonus) applied at the guaranteed annuity rate- GAR - a  so called 'Equitable-Life-annuity-guarantee' or Type 1 GAR.

References

Waters and Wilkie GAO paper to the Faculty of Actuaries

Yang PhD Thesis

Huijuan Liu

 

Fenghui Tan

 

Indu Shah

“The Realistic Balance Sheet for a With-Profits fund”

The 'realistic balance sheet' (RBS) (based on asset shares) more or less replaces the 'statutory balance sheet' based only on guaranteed benefits. The need is to have enough assets in the with-profits fund to meet the requirements of the RBS taking into account the firm’s Principles and Practice of Financial Management (PPFM). In addition there needs to be enough assets either within the with-profits fund or elsewhere within the life office to meet the Risk Capital Margin (RCM) which is designed to cover market, credit and persistency risks. The RCM, inter alia, allows for instantaneous fall in asset values, a deterioration in credit ratings for the assets and for persistency rates to be 50% of those assumed when valuing the liabilities for the purposes of the RBS. The project could involve setting up a model of a with-profits fund, setting out an assumed PPFM and calculating the RBS consistent with the PPFM covering asset shares and enhancements for guarantees, options and smoothing and then calculating the RCM.   

References

David Hare's  Working Party Paper (63 pages) ,

Needleman and Dullaway Paper (47 pages),

Head of FSA John Tiner's letter of March 2003 (23 pages) etc.

FSA CP 97

FSA CP143

FSA PS and CP136

FSA CP 195

2005 Dissertations

Adrian Parris

 

Mei Feng

“Actuarial Add-in for Microsoft Excel”

Build an Actuarial add-in (in the computer language Visual Basic for Applications (VBA) or in C++) to Microsoft EXCEL which has a range of actuarial functions in it, possibly on a variety of mortality tables.

Preparatory work

(1)     Determine the actuarial functions you want to program,

(2)     Knowledge of Microsoft EXCEL on PC Caledonia (see Help Centre Document 159),

(3)     Flow diagram for the logic of doing these calculations,

(4)     Knowledge of Visual Basic for Applications (VBA)

(5)     Knowledge of C++

 

References

1)       Manuals from PC Caledonia on EXCEL and Visual Basic for Applications (VBA)

2)       EXCEL Visual Basic for Applications (VBA) Programming for Dummies

3)       C++ Guide to the language and how to write programs in it (to be handed out)

4)       EXCEL add-in development in C/C++  by Steve Dalton (obtainable from Amazon U.K. )

Kim Teh

 

Jingjing Li

“Unit-Linked Policies with a Maturity Value Guarantee”

Pricing and hedging strategies for unit-linked or with-profits maturity guarantees are relevant to life offices. The book by M J Brennan and E S Schwartz gives a program in FORTRAN program in the back of the book. The project would be to understand the program, compile and run it and then possibly convert it into a language like Visual Basic or C++.

Preparatory work

(1) Knowledge of Microsoft EXCEL on PC Caledonia (see Help Centre Document 159)

(2) Study Freddie Delbaen’s paper (see below)

(3) Study Phelim Boyle’s paper (see below)

(4) Study John Hull’s book for Call and Put Options (see below)

 

References

(1) Hull J. C. (2003), Options Futures and Other Derivatives, Prentice Hall

(2) Delbaen F (1990), Equity-linked Policies, Bulletin Association Royal Actuaires Belges, 35-52

(3) Boyle, P.P. and Schwartz, E.S.(1977), Equilibrium Prices of Guarantees Under Equity-Linked Contracts, The Journal of Risk and Insurance, XLIV, 4, 639-660

(4) Brennan M J and Schwartz  E S (1979), Pricing and Investment Strategies for Guaranteed Equity-Linked Life Insurance, S. S. Huebner Foundation for Insurance Education, University of Pennsylvania.

Sozos Christodoulou

 

Chao Yang

“Correlation between Internal Working Capital and Maturity Pay-outs in a With-profits Fund”

The correlation between with-profit payouts and having Working Capital (Working Capital =’realistic assets’ of the with-profits fund less the ‘realistic liabilities’=monies in the with-profits fund which does not enter any shareholder value i.e. monies in excess of asset shares, guarantees and options in the with-profits fund (or monies in the non-profit fund in excess of non-profit reserves and which has nothing to do with shareholders).

 

For with-profits, look at of the Principles and Practices of Financial Management (PPFM), of different life offices.

 

When offices publish their 'realistic balance sheet' at end-2004 giving their Working Capital ('Working Capital for the With-Profits Fund' in line 61 of the new Form 19 of the Statutory Returns to the FSA), analysis of how much of this Working Capital belongs to shareholders and how much to existing and potential policyholders.  Offices realistic balance sheets published by March 2005 showing the Working Capital in the with-profits fund.

Preparatory work

(1)     Determine if you can get access to copies of the monthly magazine Money Management (for example does the HW Library have a copy?)

(2)     Study  the FSA publication PS 04/16 particularly the individual items in the realistic balance sheet.

 

References

Money Management (a monthly magazine)–Actual Results of with-profits endowment and pension policies. Obtain actual results from Aviva, Norwich Union, Prudential, Legal and General, Standard Life, Scottish Widows and Equitable Life.

FSA Policy Statement 04/16 see section 7.4 and Form 19, the Realistic Balance Sheet.

Realistic Balance Sheet (see FSA Handbook) in particular Form 19.

Obtain Form 19 from Aviva, Prudential, Legal and General, Norwich Union, Standard Life, Scottish Widows and Equitable Life.

Obtain PPFM from Aviva, Norwich Union, Prudential, Legal and General, Standard Life, Scottish Widows and Equitable Life.

2006 Dissertations

Rasmi Gopinath

 

Quing Li

“The Demutualisation of Standard Life”

The Standard Life is a major UK mutual insurance company (i.e. owned by its policyholders) but it is about to demutualise and become owned by shareholders. It will in future have a U.K. stock-market value and quotation which can be compared with Prudential, Aviva and Legal & General. The Project will involve studying Standard Life's demutualisation ‘pack’, determination of the nature of, and amount of future cash flow, which will give profits to shareholders and therefore give Standard Life its market value. The Project will involve the study of embedded values (i.e. the valuation of shareholder profits from existing business) and how goodwill derives from the flow of profits arising from future new business.

Candidates will learn:-

(1)     About shareholder value for a proprietary life company,

(2)     Where the flow of profits to shareholders come from,

(3)     Analysis of the Realistic Balance Sheet for a with-profits fund, the Estate and its future.

 

References (copies of these can be downloaded from the Internet http://ukgroup.standardlife.com/sgm/content/index.html

(1)     Document ‘pack’ sent to all Standard Life with-profit policyholders,

(2)     Full Report on demutualisation by the Independent Actuary,

(3)     Full Report on demutualisation from the Actuarial Function Holder and With-Profits Actuary.

Computing  

Own laptop preferable, EXCEL spreadsheets.

Ankush Sehgal

 

Shruti Vyas

“Projecting Mortality using the Lee-Carter method”

Firstly, we look at the Heligman-Pollard method. Using Heligman and Pollard we see that eliminating all infant deaths and the accident humps only causes a very small increase in the expectation of life at birth. The projection of the parameter G (senescent mortality - assuming H and K are constants which is not far from the truth) is the critical factor.

Secondly, we apply the Singular Value Decomposition (SVD) of a matrix to the 15 ELTM's and 15 ELTF's (the 30 graduated data sets and, where the data is available, the raw un-graduated data) to determine the best fitting k(t) and a(x)'s and b(x)'s to fit the ELT data -the Lee/Carter method where m(x,t)=exp{a(x)+k(t)*b(x)} as opposed to the Gompertz method where μ(x,t)=exp(a(t)+b*x). Then applying some suitable method to project k(t) into the future, determine the 'funnel of doubt'.

 

References (Copies of these will be given out to the candidates)

1) LEE R. D. and CARTER R. C. (1992), Modelling and Forecasting U.S. Mortality, Journal of the American Statistical Association, 87, 659-671

2) LEE R. D. (2000), The Lee-Carter Method for Forecasting Mortality with various Extensions and Applications, North American Actuarial Journal, 4, 80-93

2) GOOD I J (1969), Some Applications of the Singular Value Decomposition of a Matrix,  Technometrics, 11, 4.

Computing

Own laptop preferable, EXCEL add-in to do the SVD can be downloaded from internet, maybe some VBA.

 2007 Dissertations

Botao Liu

 

Joel Samson

 

Bo Xin

"Solvency II, European Embedded Values, Individual Capital Assessment and Individual Capital Guidance".

There is much more awareness now, than in the past, of the risks being run by life offices e.g. longevity risks, the risks of guarantees and options ‘biting’ (i.e. being ‘in the money’). Because the market is what is called ‘incomplete’, the only way the determine the extent and nature of these risks is by stochastic modelling of the funds which carry these risks and this makes shareholders’ embedded value (after allowing for money to be put aside to meet any policyholder options and guarantees) and holding money back from going to shareholders (to allow for the possibility that the guarantees and options given to policyholders will bite) that much more important. Students on this project will look at one of the following three areas in relation to life office solvency:

a) the Solvency II Project of the European Union which aims towards a more ‘risk-based’ solvency model. Students on this project will learn about the Solvency II Project what ‘solvency’ means in the context of an insurance company.

b) the European Embedded Value Project of the forum for Chief Financial Officers of European insurance companies. Students on this project will learn about the European Embedded Value Project and how the profitability of the insurance  company is measured by the change over a year in the shareholders’ European Embedded Value. Clearly understanding the ‘dynamics’ of the European Embedded Value is critical and how it relates to Financial Reporting Standard 27 (FRS27) and the International Financial Reporting Standards (IFRS 4) for life offices are is important.

c) Individual Capital Assessments (ICAs) and the Regulator’s Individual Capital Guidance (ICG) to Life Offices. The Project will involve the ICA, that is the company’s assessment on the amount of capital it needs. The ICG is a minimum amount of capital the Financial Services Authority determines and the FSA may/will intervene if the company is unable to find this capital. Pillar 2 requires both these assessments to be made. Students on this project will learn about ICAs and ICGs and Pillar II and the requirements of a life office to cover all its liabilities, given that the market is incomplete.

 

References:

a) See Solvency II on the EU's website, and search Google for "Solvency II",

b) see CFO Forum - EEV Principles and http://www.cfoforum.nl/eev_principles.pdf and the links from these.

Also search on Google for “European Embedded Value”

2008 Dissertations

Nivedita Shetty

 

Radhika Sen

 

Emmanuel  Arthur

 

Michael Brennan

Radhika Sen's MSc Dissertation won the 2009 SCOR Prize

"Influence of Year of Birth on Mortality Projections"

An Extension of the Lee-Carter Model to Project Mortality by Incorporating the Cohort Effect

Students will examine the so-called “cohort-effect” on mortality i.e. the influence of year of birth on the rate of mortality. Thus students will look at an extension of the Lee-Carter model to bring in the “cohort effect".The extended model is Ln {m(x,t)}= a(x)+b(x)*k(t)+λ(x-t)  which, subject to certain constraints, can be fitted to past data.

 The time series resulting for k(t) and λ(x-t)  and can be used to project mortality into the future. We shall examine projections of mortality up to the calendar year 2016 using the Office for National Statistics data for the England and Wales population (both the Deaths at each age and the Exposed to risk for each age) from 1991-2006 at 90 ages, so 4140=90*46 data points

 

References

  1. LEE R. D. and CARTER R. C. (1992), Modelling and Forecasting U.S. Mortality, Journal of the American Statistical Association, 87, 659-671
  2. LEE R. D. (2000), The Lee-Carter Method for Forecasting Mortality with various Extensions and Applications, North American Actuarial Journal, 4, 80-93.
  3. RICHARDS S. J, KIRBY J. G. and CURRIE I. D. (2006), The Importance of Year of Birth in Two Dimensional Mortality, British Actuarial Journal, 12, 5-62.
  4. BROUHNS N., DENUIT M. and VERMUNT J.K. (2002), A Poisson log-bilinear regression approach to the construction of projected mortality tables, Insurance Mathematics and Economics, 31, 373-393.
  5. CMI PROJECTIONS – see CMI pages of Faculty and Institute of Actuaries website.

Farzana Gilani

 

"Equitable Life"

The UK insurance company, Equitable Life is the oldest life insurance company in the world, founded in 1762.

It closed to new business on 8 December 2000, a few months after losing a  legal case in the House of Lords regarding the application of its guaranteed annuity rate option (its so-called ‘GAR’ option).

 The Parliamentary Ombudsman has been investigating Equitable Life for a number of years and the Parliamentary Ombudsman’s Report is due out in early July 2008.

Students will study the background to the Equitable Life case so as to be prepared for the Ombudsman’s Report in July.

 

Students will study:-

         (1)      The forthcoming (July 2008) Report by the Parliamentary Ombudsman on Equitable Life,

         (2)      The solvency of Insurance Companies,

         (3)      The reasonable expectations of policyholders (PRE),

         (4)      Different types of financial guarantee in a with-profits fund e.g. guaranteed investment returns (GIRs) or guaranteed annuity rates (GARs) both a 'Hyman-annuity-guarantee' (a Type 1 GAR) or an 'Equitable-Life-annuity-guarantee' (a Type 2 GAR),

         (5)      The risks the which the different types of annuity-guarantee are exposed,

         (6)      The difference between the ‘average’ cost and the ‘upper tail’ of the distribution of the likely cost of an (unhedged or unhedgeable) annuity-guarantee,

         (7)      An appropriate charge to the policyholders for the different annuity-guarantees, 

         (8)      The structure of a with-profits fund, and

        (9)      The need for an Estate (spare money built up by taking a small charge from premiums) when there are un-hedgeable guarantees inside the with-profits fund, so that all policyholders are treated fairly when (a) annuity-guarantees, contained in those policies with such guarantees, 'bite' or when maturity guarantees ‘bite’ and (b) when maturity payouts (actual results) are smoothed, without adversely affecting the reasonable expectations of those policyholders whose policies do not contain such guarantees.

Liang Wen (Edinburgh University)

Modelling Derivatives (Options) in C++ using EXCEL as the front end  by implementing  the 'xlw' wrapper.

 

The computer language C++ is the most common in investment banks for modelling derivatives and is a requirement for ‘Quants’ (i.e. quantitative analysts in investment banks).

A free compiler for C++ can be downloaded from the internet at http://www.bloodshed.net/dev/devcpp.html . Alternatively Edinburgh University have the C++ language on their Network..

Students learning C++, can model the programs in Drs. Atchison and King’s Heriot-Watt C++ Course (which is on the internet at  http://www.ma.hw.ac.uk/ams/msc_finmath/cppnotes.pdf  )  

If you know a computer language, you may wish to move straight to the Clewlow and Strickland book (see Amazon.co.uk: Implementing Derivative Models: Amazon.co.uk:: Les Clewlow,Chris Strickland) and implement all techniques in it.

If you know C++ you can move straight away to Mark Joshi’s book, “C++ Design Patterns and Derivative Pricing” (see

http://www.amazon.co.uk/s/ref=nb_ss_w_h_/026-2860419-6447618?url=search-alias%3Daps&field-keywords=mark+joshi&Go.x=10&Go.y=8

and implement all techniques in it.

You should built the front end in EXCEL with the calculations (e.g. Monte Carlo simulations) being done in C++ using the 'xlw' wrapper.

 Once these techniques have been mastered you can move onto some of the books by Duffy, London. 

 Solving the pricing problem for Options can involve exact solutions, partial differential equations, trees or Monte Carlo simulation as different models permit different approaches. Optimization for speed is often important.

Books

Mark Joshi’s book is “C++ Design Patterns and Derivative Pricing” (CUP) as well as his book “The Concepts and Practice of Mathematical Finance” ( see

http://www.amazon.co.uk/s/ref=nb_ss_w_h_/026-2860419-6447618?url=search-alias%3Daps&field-keywords=mark+joshi&Go.x=10&Go.y=8

I have run all the programs in Mark Joshi’s book “C++ Design Patterns and Derivative Pricing” on the compiler at http://www.bloodshed.net/dev/devcpp.html which may be a good place for MSc Operations Research students (taking the Finance Option) to start. There are many books devoted to C++ and derivatives.

 

 

2009  Dissertations

Lin Huang

Timothy Lee

Pengzhu Xu

Josephine Tamakloe

Xiao Sun

“The use of VBA to perform actuarial calculations”

The computer language Visual Basic for Applications (VBA) enables Microsoft EXCEL to be programmed to carry out all sorts of actuarial calculations – whether on annuities (with any mortality table, improvement factor, interest rate, single life, joint life etc.), assurances, profit testing of non-profit or unit-linked policies, graduation (of raw mortality data), Wilkie Equations, Markov Claims, multiple state models, epidemic models (e.g. the SIR - susceptible/infected/recovered - model) Bonus-Malus system  etc.

 

Students will develop many actuarial functions and a friendly user interface in VBA  thereby developing a library of actuarial functions which can be used by future actuarial students.

 

Preparatory work

(1)     Determine the actuarial functions you want to program,

(2)     Knowledge of Microsoft EXCEL on PC Caledonia (see Heriot-Watt Help Centre, Document 159),

(3)     Knowledge of Visual Basic for Applications (VBA)

 

References

(1)       Manuals from PC Caledonia on EXCEL and Visual Basic for Applications (VBA)

(2)       The book ‘EXCEL VBA Programming for Dummies’.

 

 

2010 Dissertations

Thanasit Chawalittara

 

Napoleon Papastergiou

 

(Edinburgh University)

“Modelling Credit Risk with Copulas”

‘Credit risk’ is all to do with borrowing and not being able to repay the principal borrowed (or the interest thereon) in full. Credit derivatives are designed to mitigate ‘credit risk’ and come in different shapes and sizes.

CDS=credit default swap   CDO=collaterised debt obligation

Students will:-

(1) cover the size of CDS and CDO market and the credit market in general,

(2) read the CreditMetrics document from J.P. Morgan and know about Credit Migration thresholds (AAA to AA etc.).

(3) know structure of CDOs,

(4) program, in the computer language VBA for example, the density and cdf functions of different copulas (e.g. the Maximum, Minimum, Independent, Gaussian, Student, Clayton, Frank, Gumbel copulas),

(5) program the sampling from Gaussian, Student, Clayton, Frank, Gumbel copulas no matter what the dimension (Marshall-Olkin),

(6) set each copula to have the same Kendall tau (a measure of correlation), yet seen the difference the choice of copula makes,

(7) calculate the (marginal) the time to default of one loan (using exponential distribution - constant hazard rate) and then the correlated times to default of portfolio of bonds according to the copula and its tau,

(8) calculate the probability of default of the different tranches of a CDO according to their (i)  attachment points (ii) copula and (iii) tau,

(9) recognise the failure of American International Group (AIG), one of the largest insurance companies in the world, to use quantitative risk management in so far as assessing the risks of writing CDSs on the super-senior tranche of a CDO on sub-prime morgtages (AIG thought there was no risk to them of writing this business!! But the US Government had to bail out AIG to tune of about 145 billion dollars as AIG was "too big to fail" etc...)

(10) price a CDS on a single loan,

(11) price a CDS on the first to default of a portfolio of loans,

(12) price a CDS on a tranche of a CDO.

For Books see list below in 2011 Dissertations

Deepshilka Roy

Ian MacLugash

Ling Tong

Andrew Hislop

Jy-Hwa Chang

Richard Walsh 

 

(Heriot-Watt University)

“Valuation of Guarantees, Hedging of Guarantees, Incompleteness of Markets, Quantile Reserves”.

Topics covered will be:-

(1)   Maturity Guarantees with single premium,

(2)   Maturity Guarantees with monthly premium,

(3)   Annuity guarantees applying only to the guaranteed contractual maturity fund (i.e. without terminal bonus),

(4)   Annuity guarantees applying to the whole maturity fund (i.e. including terminal bonus),

(5)   Incomplete markets,

(6)   Quantile reserves.

Two and three sources of risk will be considered as well as the theoretical hedge and the difficulties of realising this in practice in a life office.

Rohan Gosalia

Arumungam M. Gowri

Huadong Liu

Andreas Luca

Anna Tiganitaki

Tarig Ali-Grigir

Chen Yi

 

 

(Heriot-Watt University)

“Practical Application of Non-Life Mathematical Theory using R/Excel/VBA”.

Topics covered will be:-

(1)   Several ‘Run-off Triangle’ methods including Chain Ladder, Average Cost per Claim and Bornhuetter-Ferguson,

(2)   Ruin theory including the Lindberg Bound,

(3)   No-claims discount in car insurance.

(4)   Where possible the random arrival time of claims and the random size of claims will be simulated.

Books

(1)   Hossak I.B., Pollard J.H. and Zehnwirth B.(1983), Introductory statistics with applications in general insurance,Cambridge University Press.

(2)   Boland B.  (2007), Statistical and Probabalistic Methods in Actuarial Science,Chapman Hall.

(3)   Dickson D. C. M. (2005), Insurance Risk and Ruin, Cambridge University Press.

(4)   Tse Y-K, (2008) Non-life Actuarial Models, Cambridge University Press.

(5)   Hogg R.V. ad Klugman S. A. (1984), Loss Distributions, John Wiley.

(6)   Klugman, S. A., Panjer, H. H. and Willmot, G. E. (1998), Loss Models, From Data to Decisions, John Wiley.

(7)   Waters H.R. (1987), An Introduction to Credibility Theory, Special Note of Institute and Faculty of Actuaries.

(8)   Bowers N. L. et al. (1984), Risk Theory, Part of Society of Actuaries textbook on Actuarial Mathematics.

(9)   R Packages CRAN - Contributed Packages

(10)The relevant R-packages seem to me to be ChainLadder, actuar, survival and lossDev.

Also students may wish to use EXCEL as the front-end and R as the calculation engine, see RExcel under  http://sunsite.univie.ac.at/rcom/.

 

 

2011 Dissertations

Yang Liu

 

Prashant Choudhary

 

 (Edinburgh University)

“Protection of Credit Risk using CDOs, CDSs and First to Default credit derivatives”.

‘Credit risk’ is all to do with borrowing and not being able to repay the principal borrowed (or the interest thereon) in full. Credit derivatives are designed to mitigate ‘credit risk’ and come in different shapes and sizes.

Books

  1. McNeil A. J, Frey R. and Embrechts P., (2005), Quantitative Risk Management, Princeton University Press.
  2. Löffler G. and Posch P. N., (2007), Credit Risk modeling using EXCEL and VBA, John Wiley.
  3. Schonbucher P.  J. (2003),   Credit Derivatives Pricing Models: Models, Pricing and Implementation , John Wiley
  4. Cherubini U. et. al., (2004), Copula Methods in Finance, John Wiley
  5. D. O’Kane, (2008), Modelling Single-Name and Multi-Name Credit Derivatives, John Wiley.
  6. Lewis M. (1990) Liar’s Poker: Rising through the Wreckage on Wall Street, New York, Penguin.
  7. Tett G. (2009) Fool’s Gold: How Unrestrained Greed Corrupted a Dream, Shattered Global Markets and Unleashed a Catastrophe, London: Little, Brown.

Papers

·        Li, D. X. (2001), On Default Correlations: A Copula Function Approach, Journal of Fixed Income, 9, 43-54. see

            http://papers.ssrn.com/sol3/Delivery.cfm/Delivery.cfm/991018203.pdf?abstractid=187289&mirid=1

·        CreditMetrics document  http://www.ma.hw.ac.uk/~mcneil/F79CR/CMTD1.pdf

·        Dorey M. and Joubert P. (2005), Modelling Copulas : An Overview, The Staple Inn Actuarial Society.

2012 Dissertations
Xin Wang

Shengzhi Wang

Na Zhang

(Edinburgh University)

"Counterparty Credit Risk (CCR)"

Counterparty Credit Risk’ (CCR) is the risk of the other party to a transaction (whether Government or a company) not being able to meet its obligation to pay interest or to repay the capital on money it has borrowed or both.

Students covered:- 

(1)   the size of credit market, defining 'Counterparty Credit Risk' (CCR), quantifying CCR, pricing CCR (including the incorporation of ‘wrong-way’ risk) and hedging CCR,

(2)  credit ratings, AAA, AA etc.

(3)   time to default of one loan (using the exponential distribution and  depending on the hazard rate) and multiple loans,

(4)   use of EXCEL spreadsheets to determine the price of financial instruments like Interest Rate Swaps (IRS) and Credit Default Swaps (CDS),

(5)   programming in the computer language VBA (which comes with EXCEL), 

(6)  how to mitigate CCR through use of the ISDA Master Agreement, netting, collateral, hedging, creating a central clearing house (exchange) etc.

(7)   how to make the calculation of CVA (‘credit valuation adjustment’) using EXCEL and VBA,

(8)   determination if a ‘trade’ is profitable i.e. if the ‘spread’ exceeds the ‘CVA’,

(9) recognition of the failure of American International Group (AIG), one of the largest insurance companies in the world, to use quantitative risk management. [AIG insured, against default, certain parts of loans backed by sub-prime mortgages. AIG thought there was no risk to them of writing this business! But the US Government had to bail out AIG to tune of about 145 billion dollars as AIG was "too big to fail" etc....],

(10)     the future of CCR.

  

Books

  1. Gregory J. (2010), Counterparty Credit Risk, the new challenge for global financial markets, John Wiley.
  2. Löffler G. and Posch P. N., (2007), Credit Risk modeling using EXCEL and VBA, John Wiley
  3. For interest rate swaps, currency swaps and options on swaps (swaptions) see Hull J. C. (2003) Options, Futures and Other Derivatives, (latest edition)

 

 

Andreas Anthis

Keith Smith

Jianling Ai

Quin Liu

Zhanru Zing

Asaad Mohamed Ibrahim
"Non-Life Credibility Theory"

The idea of credibility theory is to up-date the premium charged according to the experience of the insured group and the size of the experience.

 

A proportion (credibility factor, Z<=1) is applied the actual experience, D, of the insured group and the premium for the risk according to the insurance company's rating manual, M. Thus, the actual premium charged by the insurance company is Z.D +(1-Z).M.

 There are different approaches to the calculation of Z (the credibility factor):-

  1. Bayesian credibility

  2. Full credibility,

  3. Partial credibility,

  4. Buhlmann credibility

  5. Bühlmann-Staub credibility,

Students undertaking the above project will acquire a good knowledge of the different aspects of credibility and work though various examples in EXCEL.

Books

  1. Tse Yiu-Kuen, "Nonlife Actuarial Models" Chapters 6,7,8,9  

  2. Waters H. R. Lecture notes and reference material on Credibility Theory (Heriot-Watt University)

 

2013 Dissertations

Adalsteinn Arnarson



Ken Newlamds
'Counterparty Credit Risk'




'Credit Risk, Standard and Poors and LIBOR'
Credit Risk (CCR) became a very serious issue in the credit crunch of 2008-09 because if anyone had said, in 2006, that a huge bank like Lehman Brothers, full of 'quants' (experts in quantitative finance), would fail, they would have laughed at you. However, Lehman Brothers went bankrupt!

In the UK, Northern Rock, Royal Bank of Scotland (RBS) and Bank of Scotland (BoS) had to be bailed out by the UK Government and UK taxpayer, costing them a very large sum of money.

In the USA, Fannie Mae and Freddie Mac were given best quality credit ratings - AAA - by the rating agents (like Standard and Poors) - but still failed and (as well as American International Group (AIG) and others) had to be bailed out by the US Government and the US taxpayer, costing them a very large sum of money.

Rating agencies (like Standard and Poors) gave AAA ratings (i.e. the best rating) to bonds that should never have had such favourable credit ratings. So credit risk and credit rating became a major issue.

The American Government are now (2013) suing Standard and Poors for giving misleading advice over the creditworthiness (credit rating) of certain bonds.

Furthermore, it has been discovered that banks were manipulating the LIBOR rate (which is an interest rate on which many financial transactions depend). This resulted in mayor fines for banks (e.g. £270 million for Barclays Bank, £1,000 million for Union Bank of Switzerland).This culminated in the Wheatley Review (http://cdn.hm-treasury.gov.uk/wheatley_review_libor_finalreport_280912.pdf )

Now all banks and other financial institutions are much more cautious and make an adjustment (CVA, ‘credit valuation adjustment’) for their own assessment of the creditworthiness of their counterparties and the determine whether a ‘trade’ is likely to be profitable, taking account of the possibility that the counterparty might fail.

It would be useful for students to develop some familiarity (prior to the MSc beginning) of the undernoted book by John Gregory and his spreadsheets, see his website www.oftraining.com

Students



will cover the size of credit market, defining CR, quantifying CR, pricing CR (including the incorporation of ‘wrong-way’ risk) and hedging CR,
will learn about LIBOR and the manipulation of LIBOR,
will know about ‘rating agencies) like Standard and Poors, credit ratings, AAA, AA etc.of bonds according to their creditworthiness,
will learn about the US Government suing Standard and Poors for giving far too high a credit rating (for bonds) that turned out to be unhustified,
will calculate the time to default of one loan (using the exponential distribution and depending on the hazard rate which measures the risk of default) and multiple loans,
will use EXCEL spreadsheets to determine the price of financial instruments like Interest Rate Swaps (IRS) and Credit Default Swaps (CDS),
will program, in the computer language VBA (which comes with EXCEL), 
will learn how to mitigate Counterparty Credir Risk (CCR) through use of the ISDA Master Agreement, netting, collateral, hedging, creating an exchange etc.
will learn how to make the calculation of CVA (‘credit valuation adjustment’) using EXCEL and VBA,
will determine if a ‘trade’ is profitable i.e. if the ‘spread’ exceeds the ‘CVA’,
will recognise the failure of American International Group (AIG), one of the largest insurance companies in the world, to use quantitative risk management. [AIG insured, against default, certain parts of loans backed by sub-prime mortgages. AIG thought there was no risk to them of writing this business! But the US Government had to bail out AIG to tune of about 145 billion dollars as AIG was "too big to fail" etc....],
the future of CCR.

References

http://en.wikipedia.org/wiki/Libor_scandal and the pages that it recommends e.g. http://www.accountingdegree.net/numbers/libor.php
Regarding the US Government suing Standard and Poors
See http://www.bbc.co.uk/news/business-21334502 and
http://www.policymic.com/articles/25364/s-p-lawsuit-the-questions-that-should-ve-been-asked and
Gregory J. (2012), Counterparty Credit Risk, the new challenge for global financial markets (second edition), John Wiley.
Löffler G. and Posch P. N., (2007), Credit Risk modeling using EXCEL and VBA, John Wiley.