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Actuarial Mathematics for Modelling · Key assurance and annuity contracts

Present Value Random Variables and Actuarial Notation Explained

Updated 11 October 2026 · Fact-checked

A present value random variable is the value today of a contract's payments, written as a function of the future lifetime T_x or the curtate lifetime K_x. For whole life assurance, Z = v^(K_x+1) and A_x = E[Z]. For annuities, Y is a sum of discount factors. Write the variable first, then take its mean and variance.

Understand Present Value Random Variables and Actuarial Notation

A life contract pays money at times that depend on when a person dies. You do not know that time today. So the present value of the payments is not a fixed number. It is a random variable.

Start with the life. T_x is the future lifetime of a person aged x. It is continuous. K_x = ⌊T_x⌋ is the curtate future lifetime, the whole number of years lived. If death happens in year k+1, then K_x = k. The probability is P(K_x = k) = k|q_x = kp_x × q_(x+k).

Now attach a payment. A whole life assurance paying 1 at the end of the year of death has present value Z = v^(K_x+1). If it pays at the moment of death, the variable is Z = v^(T_x), and the notation gets a bar: Ā_x. A term assurance pays only if death is within n years, so Z is zero otherwise. An endowment pays at death or at time n, whichever comes first. A pure endowment pays n years from now only if the life survives.

An annuity pays while the life survives. Its present value Y is the value of a certain annuity for a random term. For an annuity-due, Y = ä_(K_x+1) (a certain annuity-due for K_x+1 years). For a continuous annuity, Y = ā_(T_x). The symbols A_x, ä_x and a_x are the expected values of these variables, not the variables themselves. That is the key idea in this topic.

The exam asks you to do three things. Write the variable correctly, find its mean (the actuarial present value), and find its variance. Most marks are lost at the first step, so always define the variable before you calculate.

Key rules to remember

Whole life assurance, end of year of death
Z = v^(K_x+1); A_x = E[Z] = Σ v^(k+1) × k|q_x, summed over k = 0, 1, 2, ...
v = 1 ÷ (1 + i). The sum runs until the end of the mortality table.
Whole life assurance, payable at death
Z = v^(T_x); Ā_x = E[Z] = ∫ v^t × tp_x × μ_(x+t) dt, from 0 to ∞
The bar means payment at the moment of death. Continuous time uses the force of mortality μ.
Term assurance
Z = v^(K_x+1) if K_x < n, else 0; A¹_(x:n) = Σ v^(k+1) × k|q_x, summed over k = 0 to n−1
The superscript 1 over x marks the death benefit. The value is zero if the life survives n years.
Pure endowment
Z = v^n if T_x > n, else 0; A_(x:n)^1 = v^n × np_x
The superscript 1 over the term n marks the survival benefit. Z takes only two values.
Endowment assurance
Z = v^(min(K_x+1, n)); A_(x:n) = A¹_(x:n) + A_(x:n)^1
The endowment is a term assurance plus a pure endowment.
Second moment of an assurance
E[Z²] = ²A_x = A_x calculated at v² (force of interest 2δ)
Use the same method with v replaced by v². Do not square A_x to get this.
Variance of an assurance
Var(Z) = ²A_x − (A_x)²
For a benefit of S, the variance is S² × Var(Z).
Whole life annuity-due variable
Y = ä_(K_x+1) = (1 − v^(K_x+1)) ÷ d; d = i ÷ (1 + i) = 1 − v
Y is a linear function of Z.
Mean of annuity-due from assurance
ä_x = E[Y] = (1 − A_x) ÷ d
The continuous version is ā_x = (1 − Ā_x) ÷ δ.
Variance of annuity-due
Var(Y) = Var(Z) ÷ d² = (²A_x − (A_x)²) ÷ d²
Continuous: Var(Ȳ) = (²Ā_x − (Ā_x)²) ÷ δ².
Pure endowment variance
Var(Z) = v^(2n) × np_x × (1 − np_x)
Z is v^n with probability np_x, otherwise 0.
Annuity-immediate link
a_x = ä_x − 1
For a whole life annuity paid in arrears.

How to solve Present Value Random Variables and Actuarial Notation questions

Use the same routine for any question on present value random variables. Do the logic first and the arithmetic last.

  1. 1Identify the benefit: when it is paid (end of year of death, moment of death, on survival) and how much.
  2. 2Identify the life variable: use K_x for discrete payments and T_x for continuous payments.
  3. 3Write the present value variable as a function of K_x or T_x. For term and endowment contracts, define Z on each range of K_x. Include the zero case.
  4. 4Write the probabilities for each outcome, such as k|q_x = kp_x × q_(x+k), or np_x for survival to n.
  5. 5Find the mean: E[Z] = Σ (value × probability), or the equivalent integral. Add up each contract's part separately.
  6. 6For the variance, find E[Z²] by replacing v with v² in every term. Then use Var(Z) = E[Z²] − (E[Z])².
  7. 7For annuities, express Y using Z, for example Y = (1 − Z) ÷ d, and use the linear link to get mean and variance. Multiply by the benefit or payment size (S for the mean, S² for the variance).
  8. 8Check: the answer must be positive, the mean of an assurance must be less than 1 per unit benefit, and the variance must not be negative.

Quickest way: Link everything to Z

When to use it: Use this when the question gives you A_x, ²A_x or a table of assurance values and asks for annuity values or variances. It saves you from summing a long series.

  1. Convert i to d = i ÷ (1 + i), or find δ if payments are continuous.
  2. Get the annuity mean from ä_x = (1 − A_x) ÷ d.
  3. Get Var(Z) = ²A_x − (A_x)² from the given values.
  4. Get Var(Y) = Var(Z) ÷ d². Use δ² for continuous annuities.
  5. For an annuity-immediate, subtract 1 from ä_x and do not change the variance. Y changes by the constant 1, which does not affect variance.
  6. Scale: multiply the mean by the benefit S and the variance by S².

Common mistakes in Present Value Random Variables and Actuarial Notation

  • Using v^(K_x) instead of v^(K_x+1) for a whole life assurance paid at the end of the year of death.

    K_x counts completed years lived, and students forget that payment is made at the end of the year of death, which is one year later.

    Fix: Say it in words: if K_x = 0, death is in year 1 and payment is at time 1, so the factor is v¹. Always use K_x + 1 for end-of-year payment.

  • Writing E[Z²] as (A_x)², giving a variance of zero.

    Students confuse the square of the mean with the mean of the square.

    Fix: E[Z²] = ²A_x, which is A_x calculated with v². Never square the number A_x to get the second moment.

  • Forgetting the zero outcome in term assurance or pure endowment.

    Students write Z = v^(K_x+1) for all K_x and sum to infinity.

    Fix: Write Z piece by piece. A term assurance is v^(K_x+1) when K_x < n, and 0 otherwise. The sum only goes to n−1.

  • Using Var(Y) = Var(Z) instead of Var(Z) ÷ d².

    Students copy the variance of the assurance and forget that Y = (1 − Z) ÷ d is a scaled variable.

    Fix: If Y = (1 − Z) ÷ d, then Var(Y) = Var(Z) ÷ d². Constants like 1 drop out, and the divisor d is squared.

  • Mixing discrete and continuous notation, for example using δ with ä_x or d with ā_x.

    The bar and the symbol for the interest rate look like small details.

    Fix: Discrete annuity-due: divide by d. Continuous: divide by δ. Check that the bar on the assurance matches the bar on the annuity.

  • Treating a_x (immediate) as ä_x (due), or omitting the −1 in a_x = ä_x − 1.

    The two symbols differ only by a double dot.

    Fix: Annuity-due pays at time 0, so it is worth 1 more than the immediate annuity. Write down the first payment time before you pick the symbol.

Worked examples

Example 1

A life aged x buys a 2-year term assurance paying ₹1,00,000 at the end of the year of death. Assume i = 5% per year, q_x = 0.01 and q_(x+1) = 0.02. Find the expected present value of the benefit and the standard deviation of the present value, per ₹1 of sum assured and for ₹1,00,000.

Show the solution
  1. Define the variable per unit: Z = v^(K_x+1) if K_x = 0 or 1, and Z = 0 if K_x ≥ 2.
  2. v = 1 ÷ 1.05 = 0.952381, v² = 0.907029, v⁴ = 0.822702.
  3. Probabilities: P(K_x = 0) = q_x = 0.01. P(K_x = 1) = (1 − 0.01) × 0.02 = 0.0198.
  4. Mean: E[Z] = 0.01 × 0.952381 + 0.0198 × 0.907029 = 0.009524 + 0.017959 = 0.027483.
  5. For ₹1,00,000 the mean is 1,00,000 × 0.027483 = ₹2,748 (to the nearest rupee).
  6. Second moment: E[Z²] = 0.01 × v² + 0.0198 × v⁴ = 0.01 × 0.907029 + 0.0198 × 0.822702 = 0.009070 + 0.016290 = 0.025360.
  7. Variance per unit: 0.025360 − (0.027483)² = 0.025360 − 0.000755 = 0.024605 (to about six decimals, 0.02460).
  8. Standard deviation per unit: √0.02460 ≈ 0.1569. For ₹1,00,000: about ₹15,686.

Answer: Expected present value ≈ 0.02748 per ₹1, or about ₹2,748 for ₹1,00,000. The standard deviation is about 0.1569 per ₹1, or about ₹15,686 for ₹1,00,000.

Example 2

For a life aged x, A_x = 0.40 and ²A_x = 0.20 at i = 5% per year. Find ä_x, the variance of the present value of a whole life annuity-due of ₹1 per year, and the standard deviation.

Show the solution
  1. Define the annuity variable: Y = ä_(K_x+1) = (1 − Z) ÷ d, where Z = v^(K_x+1).
  2. d = i ÷ (1 + i) = 0.05 ÷ 1.05 = 1 ÷ 21, so 1 ÷ d = 21 and 1 ÷ d² = 441.
  3. Mean: ä_x = (1 − A_x) ÷ d = (1 − 0.40) × 21 = 0.6 × 21 = 12.6.
  4. Variance of Z: Var(Z) = ²A_x − (A_x)² = 0.20 − 0.16 = 0.04.
  5. Variance of Y: Var(Y) = Var(Z) ÷ d² = 0.04 × 441 = 17.64.
  6. Standard deviation: √17.64 = 4.2.

Answer: ä_x = 12.6. Var(Y) = 17.64. The standard deviation is 4.2 (per ₹1 of annual payment).

Exam tips

  • Write the random variable in the first line of every answer, for example Z = v^(K_x+1). Many written marks are for defining the variable correctly.
  • Read the payment timing in the question. 'End of the year of death' means K_x+1 and no bar. 'Immediately on death' means T_x and a bar.
  • In MCQs, check the mean and variance against simple limits. The mean of an assurance per unit benefit must lie between 0 and 1.
  • For second moments, change v to v² in the same formula or table calculation. In Paper B, change the discount rate in your R or Excel sheet, not the mortality.
  • Show the link formula (ä_x = (1 − A_x) ÷ d) as the working line. Then substitute numbers, so you can earn method marks even if the arithmetic slips.

Practice questions from Key assurance and annuity contracts

Present Value Random Variables and Actuarial Notation: frequently asked questions

What is the difference between A_x and the present value random variable Z?

Z is the random variable, for example v^(K_x+1). It takes different values for different lifetimes. A_x is its expected value, a single number. In the exam, say which one you mean.

How do I derive the expected present value of a whole life assurance?

Write Z = v^(K_x+1) and list the probabilities k|q_x = kp_x × q_(x+k). Then A_x = Σ v^(k+1) × k|q_x over all k. For a continuous benefit, use Ā_x = ∫ v^t × tp_x × μ_(x+t) dt from 0 to ∞.

What is the variance of the present value of a term assurance?

Var(Z) = ²A¹_(x:n) − (A¹_(x:n))². Here ²A¹_(x:n) is the term assurance value calculated with v² in place of v. Multiply by S² if the sum assured is S.

Why is the variance of an annuity divided by d²?

An annuity-due variable is Y = (1 − Z) ÷ d. The constant 1 does not change the variance, but the divisor d is squared. So Var(Y) = Var(Z) ÷ d². In continuous time, replace d with δ.

When do I use K_x and when do I use T_x?

Use K_x when payments are made on a yearly basis, such as end of the year of death or annual annuity payments. Use T_x when the benefit is paid at the exact moment of death or the annuity is paid continuously.