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Exam P Probability (Course1)
The examination for this material consists of 3 hours of multiple-choice questions and is identical to CAS Exam 1.

LEARNING OUTCOMES
Candidates should be able to use and apply the following concepts in a risk management context:
General Probability
Set functions including set notation and basic elements of probability
Mutually exclusive events
Addition and multiplication rules
Independence of events
Combinatorial probability
Conditional probability – Non Bayes Theorem
Bayes Theorem / Law of total probability
Univariate probability distributions (including binomial, negative binomial, geometric, hypergeometric, Poisson, uniform, exponential, chi-square, beta, Pareto, lognormal, gamma, Weibull, and normal).
Probability functions and probability density functions
Cumulative distribution functions
Conditional probability
Mode, median, percentiles, and moments
Variance and measures of dispersion
Moment generating functions
Transformations
Multivariate probability distributions (including the bivariate normal)
Joint probability functions and joint probability density functions
Joint cumulative distribution functions
Central Limit Theorem
Conditional and marginal probability distributions
Moments for joint, conditional, and marginal probability distributions
Joint moment generating functions
Variance and measures of dispersion for conditional and marginal probability distributions
Covariance and correlation coefficients
Transformations and order statistics
Probabilities and moments for linear combinations of independent random variables
 
Suggested Texts
There is no single required text for this exam. The texts listed below may be considered as representative of the many texts available to cover material on which the candidate may be examined.
 
Not all the topics may be covered adequately by just one text. You may wish to use more than one of the following or other texts of your choosing in your preparation. Earlier or later editions may also be adequate for review.
 
参考書目
# A First Course in Probability (Seventh Edition), 2005, by Ross, S.M., Chapters 1–8.
Fundamentals of Probability (Third Edition), 2005, by Ghahramani, S., Chapters 1–11.
John E. Freund’s Mathematical Statistics with Applications (Seventh Edition), 2004, by Miller, I., Miller, M., Chapters 1-8.
Mathematical Statistics with Applications (Sixth Edition), 2002, by Wackerly, D., Mendenhall III, W. Scheaffer, R., Chapters 1-7.
Probability for Risk Management, 1999, by Hassett, M. and Stewart, D., Chapters 1–11.
Probability: The Science of Uncertainty with Applications to Investments, Insurance and Engineering 2001, by Bean, M.A., Chapters 1–9.
 Exam FM Financial Mathematics(Course2)
The examination for this material consists of two hours of multiple-choice questions and is identical to CAS Exam 2.

LEARNING OUTCOMES
  1. Candidates will know definitions of key terms of financial mathematics: inflation; rates of interest [simple, compound (interest and discount), real, nominal, effective, dollar-weighted, time-weighted, spot, forward], term structure of interest rates; force of interest (constant and varying); equivalent measures of interest; yield rate; principal; equation of value; present value; future value; current value; net present value; accumulation function; discount function; annuity certain (immediate and due); perpetuity (immediate and due); stocks (common and preferred); bonds (including zero-coupon bonds); other financial instruments such as mutual funds, and guaranteed investment contracts.
Specifically, candidates are expected to demonstrate the ability to:
    1. Choose the term, given a definition
    2. Define a given term
    3. Determine an equation of value, given a valuation problem involving one or more sets of cash flows at specified times
  1. Candidates will understand key procedures of the financial mathematics: determining equivalent measures of interest; discounting; accumulating; determining yield rates; estimating the rate of return on a fund; amortization
Specifically, candidates are expected to demonstrate the ability to:
a.      Calculate the equivalent annual effective rate of interest, given a nominal annual rate and a frequency of interest conversion, discrete or continuous, other than annual.
    1. Calculate the equivalent effective rate of interest per payment period given a payment period different from the interest conversion period.
    2. Estimate the interest return on a fund
    3. Calculate the appropriate equivalent single value (present value, net present value, future (accumulated) value or combination), given a set of cash flows (level or varying), an appropriate term structure of interest rates, the method of crediting interest (e.g., portfolio or investment year) as necessary, an appropriate set of inflation rates as necessary, and accounting for reinvestment interest rates as necessary; for example:
      1. Calculate the loan amount or outstanding loan balance, given a set of loan payments (level or varying) and the desired yield rate (level or varying)
      2. Calculate the price of a bond (callable or non-callable), given the bond coupons, the redemption value, the term of the bond (constant or varying), the coupon interest rate, and the desired yield rate (level or varying)
      3. Calculate the value of a stock, given the pattern of dividends and the desired yield rate (level or varying)
      4. Calculate the net present value, given a set of investment contributions and investment returns
e.    Calculate a unique yield rate, when it exists, given a set of investment cash flows
    1. Calculate the amount(s) of investment contributions, given there is more than one contribution, and given a set of yield rates, the amount(s) and timing of investment return(s), and the desired timing of the investment contributions
    2. Calculate the amount(s) of investment returns, given there is more than one return, and given a set of yield rates, the amount(s) and timing of investment contribution(s) and the desired timing of the investment returns; for example:
                     i.        Calculate loan payments, given the loan amount(s), the term of the loan, and the desired yield rate (level or varying)
      1. Calculate the principal and interest portions of a loan payment, given the loan amount, the set of loan payments (level or varying), and a set of interest rates (level or varying)
      2. Calculate bond coupons or redemption values, given the bond price, the term of the bond, and the desired yield rate (level or varying)
h.   Calculate the term of an investment, given a set of cash flows (level or varying), and a set of interest rates (level or varying); for example
                     i.        Calculate the length of time required to accumulate a given amount, given the yield rate and an initial amount
      1. Calculate the length of time to repay a given loan amount, given the loan payments and the loan interest rate(s)
      2. Calculate the time to maturity of a bond, given the price of the bond, the coupon payments, redemption value, and yield rate
  1. Candidates will know definitions of key terms of modern financial analysis at an introductory and intuitive level, and be able to complete basic calculations involving such terms: yield curves, spot rates, forward rates, duration, convexity, immunization, and short sales.

    Specifically, candidates are expected to demonstrate the ability to:
    1. Choose the term, given a definition
    2. Write the definition, given a term
    3. Perform calculations such as:
                     i.        yield rate on a short sale
      1. measuring interest rate risk using duration and convexity
      2. basic immunization calculations
Note that probability-based calculations for applications of financial mathematics are in Exam M.
Suggested Texts
The Candidate may use either of the options shown below. Knowledge and understanding of financial mathematics concepts are significantly enhanced through working out problems based on those concepts. Thus in preparing for the Financial Mathematics examination, whichever of the source of textbooks students choose to use, students are encouraged to work out the textbook exercises related to the listed readings.
参考書目
OPTION A
  • Theory of Interest (Second Edition), 1991, by Kellison, S.G., Chapters 1-2, Chapter 3 (exclude 3.6 and 3.10), Chapter 4, Section 4.1 and the rest of page 95 , Examples 4.1 and 4.2, Sections 4.4–4.8, Chapter 5, Sections 5.1–5.7, Chapter 6, Sections 6.1–6.4 and 6.6, Chapter 7, Sections 7.1–7.7 and 7.10, Chapter 8, Sections 8.7 and 8.8 (exclude Options, Futures, Forwards and Swaps), Chapter 9, Sections 9.4, 9.6, 9.8–9.10, Appendix VIII.
OPTION B
  • Mathematics of Investment and Credit (Third Edition), 2004, by Broverman, S.A., Chapter 1 through section 1.6, Chapter 2 through section 2.4 (excluding 2.4.2 and 2.4.3), Chapter 3 through section 3.3 (excluding pages 188–189), Chapter 4 through section 4.3.1, Chapter 5 through section 5.3 (excluding 5.1.3, 5.1.4 and 5.3.2), Chapter 6 through section 6.3 (excluding 6.2), Chapter 7 through section 7.2, Chapter 8, sections 8.2.1, 8.2.2, 8.2.4, 8.3.1–8.3.3.
Exam M Actuarial Models (Course3)
The examination for this material consists of four hours of multiple-choice questions.
LEARNING OUTCOMES
A.      Survival and severity models.
1.   Define survival-time random variables
a.    for one life, both in the single- and multiple-decrement models;
b.    for two lives, where the lives are independent or dependent (including the common shock model);
1.   Assuming a uniform distribution of deaths, define the continuous survival-time random variable that arises from the discrete survival-time random variable.
2.   Define severity random variables
a.    with or without a deductible;
b.    with or without a limit;
c.    with or without coinsurance.
1.   For any survival-time or severity random variable defined above, with single or mixed distributions, calculate
a.    expected values;
b.    variances;
c.    probabilities;
d.   percentiles.
1.   Define non-homogeneous and homogeneous discrete-time Markov Chain models and calculate the probabilities of
a.    being in a particular state;
b.    transitioning between particular states.
B.   Frequency models.
1.   Define and calculate expected values, variances and probabilities for frequency random variables
a.    under the Poisson distribution;
b.    under the Binomial distribution;
c.    under the Negative Binomial distribution;
d.   under the Geometric distribution;
e.    under any mixture of the above. |
1.   Define and calculate expected values, variances and probabilities for Poisson processes,
a.    using increments in the homogeneous case;
b.    using interevent times in the homogeneous case;
c.    using increments in the non-homogeneous case;
d.   resulting from special types of events in the Poisson process;
e.    resulting from sums of independent Poisson processes.
C.   Compound (aggregate) models.
1.   Define compound random variables, combining severity distributions with frequency distributions and Poisson processes.
2.   Calculate, for the compound random variables defined above,
a.    expected values, including recursion for aggregate deductibles (stop-loss insurance);
b.    variances;
c.    probabilities.
D.   Life contingencies
1.   Define present-value-of-benefit random variables for life insurances defined on survival-time random variables
a.    for one life, both in the single- and multiple-decrement models;
b.    for two lives, where the lives are independent or dependent (including the common shock model).
1.   Define present-value-of-benefit random variables for annuities defined on survival-time random variables
a.    for one life, in the single-and multiple-decrement models;
b.    for two lives, where the lives are independent or dependent (including the common shock model).
1.   Calculate the expected values, variances and probabilities for present-value-of-benefit random variables for the life insurances and annuities described above.
2.   Define and calculate the expected values, variances and probabilities for the present-value-of-lossat-issue random variables, as a function of the considerations (premiums), for the life insurances and annuities described above.
3.   Calculate considerations (premiums) for life insurances and annuities,
a.    using the Equivalence Principle;
b.    using percentiles.
1.   Define and calculate the expected values, variances and probabilities for the present-value-of-futureloss random variables for life insurances and annuities.
2.   Calculate liabilities, analyzing the present-value-of-future-loss random variables for life insurances and annuities,
a.    using the prospective method;
b.    using the retrospective method;
c.    using special formulas.
1.   Using recursion, calculate expected values (reserves) and variances of present-value-of-future-loss random variables for general fully-discrete life insurances written on a single life.
2.   For the life insurances and annuities described above, calculate
a.    gross considerations (expense-loaded premiums);
b.    expense-loaded liabilities (reserves);
c.    asset shares.
1.   Extending present-value-of-benefit, present-value-of-loss-at-issue, present-value-of-future-loss random variables and liabilities to discrete-time Markov Chain models, calculate
a.    actuarial present values of cash flows at transitions between states;
b.    actuarial present values of cash flows while in a state;
c.    considerations (premiums) using the Equivalence Principle;
d.   liabilities (reserves) using the prospective method.
 
Note: Concepts, principles and techniques needed for Exam M are covered in the references listed below. Candidates and professional educators may use other references, but candidates should be very familiar with the notation and terminology used in the listed references.
参考書目
  • Actuarial Mathematics (Second Edition), 1997, by Bowers, N.L., Gerber, H.U., Hickman, J.C., Jones, D.A. and Nesbitt, C.J., Chapter 3 , Sections 3.1–3.3, 3.5, 3.6 (excluding constant force and hyperbolic assumptions), 3.7 and 3.8, Chapter 4, Sections 4.1–-4.4, Chapter 5, Sections 5.1–5.4, Chapter 6, Sections 6.1(excluding utility-theory approach), 6.2–6.4, Chapter 7, Sections 7.1(excluding utility-theory approach), 7.2–7.6, Chapter 8, Sections 8.1–8.2, 8.3 (only the recursion in Equation 8.3.9 and its equivalent variants), 8.4 (only Equation 8.4.6 for UDD and its equivalent variants), Chapter 9, Sections 9.1–9.5, 9.6.1, 9.7, Chapter 10, Sections 10.1–10.3, 10.5–10.5.1, 10.5.4, 10.6, Chapter 11, Sections 11.1–11.3 and Chapter 15, Sections 15.1–15.2.1, 15.4, 15.6–15.6.1.
  • Introduction to Probability Models (Eighth Edition), 2003, by Ross, S.M., Chapter 5, Sections 5.3.1, 5.3.2 (through Definition 5.1), 5.3.3, 5.3.4 (through Example 5.14 but excluding Example 5.13), Proposition 5.3 and the preceding paragraph, Example 5.18, 5.4.1(up to example 5.23), 5.4.2 (excluding Example 5.25), 5.4.3, and Exercise 40.
  • Loss Models: From Data to Decisions, (Second Edition) 2004, by Klugman, S.A., Panjer, H.H., and Willmot, G.E., Chapter 2 (background only), Chapter 3 (background only), Chapter 4, Sections 4.1–4.4 (excluding data-dependent distributions), 4.6.1–4.6.5, 4.6.7 through Theorem 4.51 (excluding zero-modified distributions, in particular Example 4.46, Theorem 4.49 and subsequent examples that depend on these distributions), 4.6.9–4.6.11, Chapter 5, Sections 5.1–5.6, Chapter 6, Sections 6.1–6.3, 6.7 (excluding discretization), Chapter 8, Section 8.1.1. [Candidates will not be responsible for zero-modified distributions including instances where they are used in examples.]

Exam C Construction and Evaluation of Actuarial Models(course 4)
The examination for this material consists of four hours of multiple-choice questions and is identical to CAS Exam 4.
LEARNING OUTCOMES
A.      Construction of Empirical Models
o    Estimate failure time and loss distributions using
§ Kaplan-Meier estimator, including approximations for large data sets
§ Nelson-Aalen estimator
§ Kernel density estimators
o    Estimate the variance of estimators and confidence intervals for failure time and loss distributions.
o    Estimate failure time and loss distributions with the Cox proportional hazards model and other basic models with covariates.
o    Apply the following concepts in estimating failure time and loss distribution
§ Unbiasedness
§ Consistency
§ Mean squared error
B.   Construction and Selection of Parametric Models
o    Estimate the parameters of failure time and loss distributions using
§ Maximum likelihood
§ Method of moments
§ Percentile matching
§ Bayesian procedures
o    Estimate the parameters of failure time and loss distributions with censored and/or truncated data using maximum likelihood.
o    Estimate the variance of estimators and the confidence intervals for the parameters and functions of parameters of failure time and loss distributions.
o    Apply the following concepts in estimating failure time and loss distributions
§ Unbiasedness
§ Asymptotic unbiasedness
§ Consistency
§ Mean squared error
§ Uniform minimum variance
o    Determine the acceptability of a fitted model using
§ Graphical procedures
§ Kolmogorov-Smirnov test
§ Anderson-Darling test
§ Chi-square goodness-of-fit test
§ Likelihood ratio test
C.   Credibility
o    Apply limited fluctuation (classical) credibility including criteria for both full and partial credibility.
o    Perform Bayesian analysis using both discrete and continuous models.
o    Apply Bühlmann and Bühlmann-Straub models and understand the relationship of these to the Bayesian model.
o    Apply conjugate priors in Bayesian analysis and in particular the Poisson-gamma model.
o    Apply empirical Bayesian methods in the nonparametric and semiparametric cases.
D.   Interpolation and Smoothing
o    Demonstrate an understanding of the purpose of smoothing data.
o    Apply polynomial splines, and cubic splines in particular to actuarial data.
E.   Simulation
o    Simulate both discrete and continuous random variables using the inversion method.
o    Estimate the number of simulations needed to obtain an estimate with a given error and a given degree of confidence.
o    Use simulation to determine the p-value for a hypothesis test.
o    Use the bootstrap method to estimate the mean squared error of an estimator.
o    Apply simulation methods within the context of actuarial models.
参考書目
  • Loss Models: From Data to Decisions, (Second Edition), 2004, by Klugman, S.A., Panjer, H.H. and Willmot, G.E., Chapter 1, Section 1.1 only, Chapters 9–11, Chapter 12 (excluding 12.5.4, 12.5.5 and 12.6), Chapter 13, Chapter 15 and Chapter 17.
Reading Options for Credibility
The candidate may use any of the alternatives shown below.
Option A
• Loss Models: From Data to Decisions, (Second Edition), 2004, by Klugman, S.A., Panjer, H.H., and Willmot, G.E., Chapter 16, Sections 16.3, 16.4 (excluding16.4.7), 16.5 (excluding 16.5.3, 16.1 (background only), 16.2 (background only).
Option B
  • Foundations of Casualty Actuarial Science (Fourth Edition), 2001, Casualty Actuarial Society, Chapter 8, “Credibility”, by Mahler, H.C., and Dean C.G., Section 1 (background only) Sections 2–5 (Available as SN C-21-01).
  • Topics in Credibility Theory (Study Note C-24-05) by Dean, C.G.
Option C
  • Introduction to Credibility Theory (Third Edition), 1999, Herzog, T.N., Chapter 1-3 (background only), 4–8, and 9 (background only).

Course 6 (Finance and Investments)
The examination for this course consists of five hours of multiple-choice and written-answer questions.  A read-through time will be given prior to the start of the exam, 15 minutes in the morning session and 10 minutes in the afternoon session.

This course extends the candidate’s knowledge of basic actuarial principles in the fields of investments and asset management.  Candidates completing this course will have developed some expertise in the areas of capital markets, investment vehicles, applications of derivatives, principles of portfolio management and asset-liability management.
LEARNING OBJECTIVES
The candidate is expected to be able to perform the following actions:
  1. Identify and evaluate the risk and return characteristics of various types of investments.
    • Explain the risks to which an investor may be exposed.
    • Evaluate the relationship between risk and return in the investment markets.
    • Explain the general design features and risk characteristics of fixed income and equity investments.
    • Evaluate the risk and return characteristics of government and corporate debt securities.
    • Evaluate the risk and return characteristics of real estate securities.
    • Evaluate the risk and return characteristics of Guaranteed Investment Contracts (GICs).
  2. Identify how markets operate and explain the fundamental principles of modern portfolio theory.
    • Explain how individual securities are valued and traded.
    • Evaluate the risk/return trade-off from an investor’s perspective.
    • Explain the term structure of interest rates including the yield curve and pricing of fixed income securities and spot and forward rates of interest.
    • Explain the Capital Asset Pricing model (CAPM) and its application to portfolio management.
    • Discuss the properties of the Markowitz Portfolio Selection model.
    • Evaluate the three versions of the efficient market hypothesis and explain their application to portfolio management.
    • Discuss the impact of investment diversification upon portfolio management.
    • Explain arbitrage pricing theory and its application to portfolio management.
    • Discuss the impact of behavioral finance on asset prices and financial markets.
  3. Determine how options are priced in financial markets.
    • Evaluate the features and risk/return characteristics of financial derivatives including put and call options, swaps, forwards, interest rate caps, floors and compound options.
    • Evaluate the factors that affect the value of an option.
    • Identify the principles and applications of no arbitrage pricing models.
    • Apply binomial option pricing techniques.
    • Determine how options are priced using the Black-Scholes model.
  4. Determine the value of cash flow streams with embedded options.
    • Calculate option-adjusted spreads including the impact of prepay on Mortgage-Backed Securities.
    • Apply option-adjusted pricing techniques to Mortgage-Backed Securities and other financial instruments.
    • Determine the cost and price-yield relationship of an embedded option in a series of cash flows.
  5. Apply the concepts of interest rate risk management and effective duration.
    • Explain the concepts of immunization including modern refinements and practical limitations.
    • Calculate an effective duration measure using option-adjusted spread analysis.
  6. Explain how principles of asset liability management (ALM) impact portfolio construction and management for institutional investors.
    • Evaluate the impact of liquidity requirements, valuation concerns, cash flow variability, regulatory constraints and investment management mandates in developing investment policies and strategies for insurance and other financial companies and pension plans.
    • Apply ALM principles to the establishment of investment policy and strategy including asset allocation.
    • Determine the impact of interest rate risk analysis on portfolio construction.
    • Apply matched funding and dedicated portfolio management strategies to control interest rate risk.
 
  1. Identify and apply portfolio management techniques to the ongoing investment management of financial institution and pension fund assets.
    • Explain principles of risk-based capital management and their impact upon portfolio management.
    • Apply principles of active and passive investment management techniques to equity and fixed income portfolios.
    • Evaluate key considerations in developing investment policies and strategies for financial institutions and pension plans.
    • Identify key considerations in managing surplus pension funds.
    • Identify and apply the obligations of a fiduciary in managing investment portfolios.
    • Describe liquidity requirements of an investor and their impact upon portfolio management.
Concepts, principles and techniques needed for Course 6 are covered in the references listed below. Candidates and professional educators may use other references, but candidates should be very familiar with the notation and terminology used in the listed references.
参考書目
  • Bond Portfolio Management, (Second Edition), 2001, by Fabozzi, F.J., editor, Chapters 2, 15–16.
  • Investments, (Sixth Edition), 2005, by Bodie, Z., Kane, A., and Marcus, A., Chapters 1 (background only), 2–5, 6 (excluding appendix), 7, 8 (excluding appendix), 9–12 and 25.
  • Financial Economics, 1998, by Panjer, H.H., editor, Chapters 2 (sections 1–6 only), 3, 5–6.
  • # Handbook of Fixed Income Securities, (Seventh Edition), 2005, by Fabozzi, F.J., Chapters, 1, 2, 7, 9, 10, 13, 16, 22, 23, 24 (pages 541–561 only), 27, 28 (pages 629 & 642–645 only), 29 (pages 647–666 only), 37, 39 (pages 902–911 only), 47, 48, 56 and 59.
  • Managing Investment Portfolios, (Second Edition), 1990, by Maginn, J.L., and Tuttle, D.L., Chapters 7 (exclude pp. 36–69), 8. (Out of Print. Available as SN 6-36-04)
  • Valuation of Interest-Sensitive Financial Instruments, (Second or Third Printing),1996, by Babbel, D. and Merrill, C., Chapters 1 (background only), 2–3, 5 and 8.

COURSE 7: APPLIED ACTUARIAL MODELING PRE-TEST


The pre-test covers the following topics described in the SOA Basic Education Catalog:
  • The Context of Modeling
  • Model Design Selection and Setup
  • Input Data Selection and Analysis
  • Analysis of Results
  • Communicating the Modeling Process
The following list contains all of the pre-reading for the Course 7 pre-test.  It consists of SOA study notes and an Internet download.  Candidates may want to bring the pre-reading material for the pre-test to their Course 7 seminar. Candidates should verify immediately that they have copies of the listed items. Candidates ordering study note "Revisions" will receive only the study note items marked with an asterisk (*). All questions concerning these pre-readings should be directed to the Society of Actuaries Publication Orders Department at (847) 706-3525.
Study Notes
7P-01-06*
Introductory Study Note
7P-10-04
Sample Pre-Test
7P-21-00
Long-Range Forecasting - From Crystal Ball to Computer (excluding pages 373-386)
7P-22-00
Pitfalls in Human Research - Ten Pivotal Points
7P-23-00
The Modeling Process
7P-25-00
Model Uncertainty, Data Mining and Statistical Inference (Excludes discussion)
7P-26-00
Applied Futurism - An Introduction for Actuaries
7P-29-00
The Strategic Uses of Value at Risk: Long-Term Capital Management for Property/Casualty Insurers
7P-31-00
A Mechanic’s Perspective to Model Building
7P-33-05
ASB Actuarial Standard of Practice No. 23 - Data Quality – Rev. Dec. 2004
7P-35-00
Designing Effective Graphs
7P-36-00
Report Writing: Communicating Analysis and Results
7P-37-00
Report Writing Aids and Author’s Checklist of Editorial Guidelines
7P-39-03
ASB Actuarial Standard of Practice No. 41 - Actuarial Communications (March 2002)
7P-41-02
ASB Actuarial Standard of Practice No. 38 – Using Models Outside the Actuary’s Area of Expertise
7P-42-04
CIA Consolidated Standards of Practice – Final – General Standards, May 2002, Revised Sept. 2003.  (Sections 1530, 1560, 1610, 1810, 1820, 1830, & 1840 only)
7P-43-04
Life Insurance Forecasting and Liability Models:  An Examination of the Trade-offs Involved with Certain Modeling Decisions (pages 1-23 only)
7P-44-04
Data Quality: Theory and Practice
7P-45-04
Understanding Actuarial Management: The Actuarial Control Cycle (Ch. 1, 8, 17 & 18 only)
"Modeling Policyholder Outcomes under a Disability Income-Type Long-Term Care Insurance Policy," 2003 by Jones, B.L.
PLEASE NOTE: 
7P-21-00
·         Chapter 14 - The entire chapter has been provided in the SN, but only pages 367-372 are required reading.
·         The exhibits missing from this SN were not printed due to copyright concerns.  Any reference to those exhibits may be ignored.
·         References to the Glossary, Appendix F or Exhibit 5-2 may be ignored.
7P-25-00
·         The discussion on pages 444-464 has been provided in this SN, but is not required reading.
Questions for the Course 7 Pre-test are set assuming that the candidate will have access to the current approved SOA calculator.  Candidates may use the battery- or solar-powered Texas Instruments BA-35 model calculator (the official SOA/CAS calculator), the BA II Plus*, the BA II Plus Professional*, or the Texas Instruments models TI-30X or TI-30Xa (the official CAS calculator) or TI-30X II* (IIS solar or IIB battery). Candidates using any of these calculators need not have calculators with the CAS or SOA logo, but may continue to use any previous calculator model bearing the SOA logo.  Candidates may use more than one of the approved calculators during the pre-test.  Candidates using a calculator other than the approved models will have their pre-test disqualified. Calculators are no longer available for sale through the SOA office.
*The memory of TI-30X II (IIS solar or IIB battery), the BA II Plus and BA II Plus Professional will need to be cleared by the examination supervisor upon the candidates’ entrance to the exam room.
 
 
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