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LOMA 371- ISTAR > Chapter 4 > Flashcards

Chapter 4 Flashcards

1
Q

What is a financial model?

A

generally a computer-based mathematical model that approximates the operation of real-world financial processes.

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2
Q

insurers can use financial models to do what?

A

produce estimates of future cash inflows, cash outflows, and net cash flows.
- can also be used to estimate future valyes for assets, reserves, capital and expenses.

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3
Q

Financial models consist of what 3 primary compoenents?

A

1) inputs (user-defined assumptiosn for independent variables)
2) processes (complex math formulas and variables to stimulate real-world processes)
3) outputs (values of the models dependent variables)

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4
Q

Inputs in models take the form of variables. Define these.

A

items of data whose numerical value varies over time.

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5
Q

Independent variables represent the measure of real wold financial values. Define independent variables.

A

variable that influences the behavior of another variable,

- Labeled X

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6
Q

What is a random number generator?

A

a routine that automatically provides software with a pattern of individual values that we would expect to get by sampling from a given probability distribution.

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7
Q

What is a random sample?

A

a statistical sample in which each possible value is equally likely to be selected.

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8
Q

What is a randome scenario generator?

A

uses defined parameters (value ranges and time periods) to create sets of scenatios that meet the defined parameters.

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9
Q

the processes in most financial models are simulation processes. What is simulation modeling?

A

the use of a real-world process model and extrapolation to emulate the behaviour of the process over time.

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10
Q

In context of statistics, what is extrapolation?

A

the process of estimating values outside of a known range on the basis of other values derived from direct observation.

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11
Q

In the context of financial modeling, what is a scenario?

A

a set of values that describes actuarial and economic conditions.

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12
Q

What is a dependent variable?

A

a variable that reacts to outside influences.

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13
Q

what are data outputs?

A

can be single values or a listing of all the possible values in a data set (depending on the particular modeling technique used)
- labeled y

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14
Q

Insurers typically derive inputs for financial models from what two sources?

A

1) experience data (real-world observations)

2) estimates of possible future conditions.

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15
Q

what is an experience study?

A

study of data representing company or industry-wide historical experience with a specified modeling variable.

  • used by insueres for behavior trends of variables
  • limitation: future prediuctions depends on historical trends.
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16
Q

Insurance industry experience studies address what 4 topics?

A

1) observed expenses for specified products or distrubtion channels.
2) observed trends in mortality in specified groups
3) observed trends in the persistency of particular products
4) observed trends in policyholder behavior in such areas as the exercise of contractual rights and secondary beenfit and guarantee options.

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17
Q

What is trend analysis?

A

a form of technical analysis that progects the fuyure movement of specified variables based on historical patterns.

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18
Q

How do insureres model the future behavior of market interest rates?

A

they are volatile and may fall outside the range of observed values, insurers rely on random scenari generation techniques.

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19
Q

what do you call the outcomes generated by analyzing estimate future values?

A

possible outcomes- they represent the range of outcomes that can happen.
possible outcomes include: probable outcomes, preferred, or desired, outcomes.

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20
Q

What are probable outcomes

A

represent what is likely to happen, based on constat trends, such as the estimates produced by modeling experience data.

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21
Q

what do you call preferred, or desired, outcomes?

A

represent outcomes that a company would like to happen and are based on planned strategies and actions.

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22
Q

what are future studies?

A

they identify possible developments that could disrupt trends- thereby changing the extrapolation of the values from the past- and then produce an array of possibilities for future values based on these developments.

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23
Q

insurers use future studies in enterprise risk management (ERM) to identify potential future, low-probabiity, high-impact events known as wild cards. what are wild cards?

A

they may consitute turning points in the evolution of a trend of system.
they are often foreshadowed by weak signals which incomplete and fragmented data that hint at relevant future events.

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24
Q

Accuracy is an attribute typically sed to measure data quality. define this.

A

the degree to which data correctly describes the real-world phenomena they are deisgned to measure.

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25
Q

Revelance is an attribute typically sed to measure data quality. define this.

A

the degree to which information meets the needs of users.

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26
Q

timeliness is an attribute typically sed to measure data quality. define this.

A

the delay betwen the reference date for the data and the date the nalaysis is published.

27
Q

interpretability is an attribute typically sed to measure data quality. define this.

A

the ease with which data can be correctly interpreted.

28
Q

accessibility is an attribute typically sed to measure data quality. define this.

A

the ease with which needed data can be obtained.

29
Q

coherence is an attribute typically sed to measure data quality. define this.

A

the degree to which data can successfully be integrated with other statisticall information, both over time and in broad analytic framework.

30
Q

insueres can use what two moderling approaches to help them explore possibilities and decreibe potential future outcomes?

A

1) deterministic modeling

2) stochastic modeling.

31
Q

what is optimizatiion modeling

A

n decision markers who use modeling based on determinign the best outcome rather than an array of possible outcomes.

32
Q

Define deterministic modeling.

A

simulates the real-world interactions of a stated set of input variables and produces a single set of output variables.

  • independent variable derived from analysis of historical experience data.
  • output is not associate with a probability distribution
33
Q

what type of scenerios (3) are typically used, when you develop scenarios?

A

pessimistic scenario
optimistic scenario
best estimate scenario.

34
Q

why is deterministic modelling valuable to insures?

A

relately easy to use, relatively modest demand for system recourses and data, and its speed in prodcing decision-support information.
- support some of the applications US reguolatos require for monitoring insures.

35
Q

What are some down falls to deterministic modelling?

A

results are highly dependent on the quality of the values assigned to input variables. To counter thing- insurers take great care in developing value estimates of the variables they model.

36
Q

define stochatic modeling

AKA probablistic modeling

A

form of modeling in which an automatic process randomly assigns valyes to specified input data in order to create a large number of scenarios. Conducts numberous process iterations as needed and produces output data that can be described in the form of a probability distribution.

37
Q

What is a probably distribution?

A

listing or other depiction of all the values in a data set and the probability of observing each of those values.
* to support probabilistic results, it must begin with a data set of potential future outcomes for all critical variables.

38
Q

When is stochatic modeling used in financial process?

A

most often used to stimulate real wrold financial conditions

39
Q

What are some majoe benefits of stochastic modeling?

A

provides a high colume of decision-support information and the results are accompanied by assessments of probability and risk.

40
Q

what is a potential risk for stochatic modeling?

A

a poorly constructed model can produce greatly distorted outcomes and lead to a false confidence in the results.

41
Q

What is optimization modeling?

A

a form of modeling that focuses on finding and optimum solution to several simultaneous equations.
- Optimum solution generated by optimization modeling are single values.

42
Q

Insurers can use optimization modeling to determine what two objectives?

A

1) the maxiumum possible profit for a chosen level of risk

2) minimum possible risk level for a chosen level of profitability.

43
Q

Optimization modeling techniques include what 5 types of programming?

A
  • linear
  • quadratic
  • dynamic
  • multidimensional
44
Q

Optimization models, also produce single-valye estimates. What do you call an estimate that is assigned a single value?

A

post estimate.

45
Q

Alternative to assigning single values to estimates, you can acknowledge the unvertainty of forecasted values by specifying a range of values for a models outcome. What do you call an estimate that provides a range of possible outcome values?

A

range estimate.

46
Q

How can decision makers refine their range estimates?

A

by assiging specified probabiliities to various estimates.

each probability = likleylihood that a particular outcome will occur.

47
Q

What is a normal curve?

A

data plotted on a graph and forms a normal dsitribution known as a bell-shaped curve.

  • symmetrical curve.
  • mid point = mean,
  • mean = median
  • median = mode.

Data:

  1. 27% of data within one standard deviation
  2. 45% of data within 2 standard deviations
  3. 73% of data within 3 standard deviations.
48
Q

True or False

Sometimes the results of stochastic modeling follows a normal probability distribution.

A

true

49
Q

Define standard deviation

A

measure of the dispersion of values in a data set around the mean of the data set.

50
Q

Real-world observations are rarely distributed normally, and thus probability distributions produced by stochatic modeling are often asymmetrical. Describe this curve.

A

The number of values on one side of the mean is > than the number of values on the other side of the mean.

51
Q

What tools do analysts use to desctibe the asymmetrical probability distributions

A

kurtosis: statistical parameter describing shape, peaks, tails
skweness: statistical parameter that describes the lack of symmetry in distribution patterns.
median
mode
mean

52
Q

What is a +ve and -ve skewed pattern?

A

+Ve: the peak of the distribution is shifted to the Lt of the mean value.
-ve: the peak is shifted to the Rt of the mean.

53
Q

When is a distribution pattern tail considered “fat”

A

when the prbability of values occuring in the tail and the risk associated with tail values (tail risk) are higher than predicted by the normal distribition.

54
Q

How do insurers typically meausure the severity of the tail risk?

A

they calculate a statistic known as the conditional tail expectation.
This si the average of all the values within a specified range of the probability distribution.
* they will also often compare the CTE for a specific range with some measure of profitability such as IRR or ROA.

55
Q

What is scenario testing (for financial modeling)

A

involves entering different sets of data into a model and then determining how changes in the input data affect the models output.

56
Q

An impotant application of scenario testing is dynamic financial analysis. What is this?

A

its the use of simulation modeling and multiple scenario testing to project into a future period an insurer’s assets, libailities and owner’s equity as of a given valuation date and to compare the values of those variables at various times after the valuation date.
* produces deicsion-support information, used in narrowly focused or broad-rainging risk analysis

57
Q

At a strategic level, DFA often takes the form of dynamic solvency testing. What is this?

A

DST: is an application of DFA that involves projecting into a future periodan insuere’s capital as of a given valuation date and comparing the projected amounts of capital at various times, after the valuation date.

58
Q

define Capital adequacy.

A

refers to the minimum amount of capital that an insurer must hold to meet a specified standard for capital

59
Q

Scenario testing can also be used to determine the adequacy of the assets and liabilities backing an insurance company’s reserves. What is asset adequacy analysis

A

a braod actuarial practice undertaken to ensure that the assets backing reserves meet established stadnards.

60
Q

How do insurers typically measure the adequacy of assets and liabilities for a particular product?

A

through cash-flow testing CFT. its the use of stimulation modeling to project into a future period the cash flows associated with an insurance company’s assets and liabilities as a of a given valuation date and to compare the timing and amounts of assets and liability cash flows at various times after the valuation date.

61
Q

liability cash-flow modeling is commonly used to evaluate liabilities associated with what?

A

deferred annuities.

62
Q

Insurers use senstitivity analysis to assess the level of the change in input needed to create a change in the outputs. they also use it to identify the sensitivity of the company’s assets and liabilitiers to chanegs in the market interest rates. What is sensitivity analysis?

A

a method of measuing the responsiveness of the outputs produced by a mathematical model to changes in the values of the model’s input variables.

  • required multiple scenario and mutiple processing rungs.
  • its measures how much change in the independent variable is necessary to create a change in the dependent variable.
  • useful in identifying a range of values for independent variables over which the changes in dependent variables are acceptable.
63
Q

What is interest-sensitive cash-flow testing?

A

analysis of th eeffects of various interest-rate scenarios on cash flows.
* can be used to support various actuarial opinions and memoranda that regulators require.

LOMA 371- ISTAR (15 decks)

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