Understanding 'Loss Capacity' & 'Major Loss' functionality

'Loss Capacity' simulation vs. 'Major Loss' functionality – differences between the two modes

When seeking to model a 'market crash', within Voyant, one has the choice of doing so either (1) in 'simulation mode' only, or (2) within the client's financial plan itself (i.e. within the Base Plan and/or 'what if' scenarios). The difference, of course, is that any inputs made, or outputs generated while in 'simulation mode' will not persist the moment one leaves 'simulation mode'. One has the option, by contrast, of building-in a 'market crash' as an effectively permanent part of the client’s Base Plan, and/or 'what if' scenario. Both options are outlined, below:

 

1. Simulation Mode – an explanation of the outputs

One can initiate the 'Loss Capacity' simulation, by hitting the 'Loss Capacity' option, below the chart, in the Let's See screen, as illustrated below:

Loss-Capacity_Simulation.jpg

To reiterate, the 'Loss Capacity' function is for simulation-purposes only – when one leaves the 'Loss Capacity' simulation, the effects do not persist within the client plan. When the 'Loss Capacity' simulation is run (by hitting the 'Calculate Need' button), the software will provide 2 results, as follows:

  1. Need from Start
  2. Need after Major Loss

 

Need from Start – what does this result mean?

This is the average annual return which, if achieved in every year of the plan, excepting the already-specified 'major loss' year(s), will suffice to ensure that there is no shortfall in any single year of the plan.

 

Need after Major Loss – what does this result mean?

This is the average annual return which, if achieved in every year after the 'major loss', will suffice to ensure that there is no shortfall in any single year of the plan. Note that – in contrast to the 'Need from Start' result – this result takes as a given one’s starting assumptions about investment returns, prior to the incidence of the 'major loss'.

 

2. Using the Major Loss event

As opposed to operating in 'simulation mode', the software allows one to build-in a 'market crash' as a (semi) permanent feature of a client's financial plan (be it in the Base Plan, or in a 'what if' scenario), using the special 'Major Loss' event, located in the Time screen:

Major-Loss_Event.jpg

Note that one can add as many of these events to the Timeline as desired. Once an event has been added to the Timeline, one will want to hit the 'Edit Settings' button, to determine the duration, and magnitude of the 'loss', or deviation from the mean.

 

The Settings (inputs)

Whether using the 'Loss Capacity' simulation, or adding a 'Major Loss' event, one will need to specify the duration, and the magnitude of the proposed market deviation. In both cases, one is invited to enter details of a deviation lasting anywhere from 1 to 5 years, as well as the magnitude of the proposed deviation – please note the 2 columns:

  1. Fixed Growth
  2. Allocation Percentile

 

Edit_Settings.jpg

 

Fixed Growth – what does this refer to?

Thinking about a 'market crash' in terms of finite, 'fixed growth' percentage values requires that one disregards, or sets aside, questions about the specific, underlying combination of investment holdings within one's investment, and/or pension accounts. Consequently, a 'fixed growth' market crash is one that will be applied equally to an account invested entirely in, e.g., fixed interest holdings, as to an account invested entirely in emerging markets equities. The use of 'fixed growth' rates, therefore, requires one to set aside (for the moment) the reality that investment returns are, inherently, probabilistic in nature, i.e, risk-based.

 

Allocation Percentile – what does this refer to?

Investment returns are 'probabilistic' in nature (i.e. unpredictable, except in terms of statistical probability), but some outcomes, of course, are more probable than others. Consequently, for any given asset class (or combination of asset classes), there is a 'probability distribution' (based on past performance), which shows the likelihood of achieving any particular return (in any single year). The distribution also sets bounds on the range of (assumed) possible returns, relative to the assumed long-term mean. Typically, it is assumed that investment returns are 'normally distribute' and are, therefore, assumed to conform to a symmetrical 'bell curve' type distribution. The allocation percentile, therefore, refers to a position 'under the curve', along the continuum of (assumed) possible outcomes, between the 0th percentile (worst possible return), approximately 3 standard deviations below the long-term mean return, and the 100th percentile (best possible return), approximately 3 standard deviations above the long-term mean return. The assumed long-term mean return sits (by definition), of course, on the 50th percentile, straight down the middle of the bell curve.

For users who choose to derive investment returns (for investment/pension accounts) based on an underlying asset allocation, the practical upshot is that one will need to specify a 'market crash' in terms not of the investment outcome itself, but in probabilistic (i.e. percentile-based) terms. For users unfamiliar with these concepts, it may be useful to refer an actual 'bell curve' distribution, such as the one shown in the accompanying 'primer' to using Voyant's market-based functionality, linked-to here >>>

 

Related articles

Major Loss, or Loss Capacity - What does 'allocation percentile' mean, and how does it correlate to market loss or gain?

Growth is Fixed - what does it mean?