Static and Stochastic Financial Statement (SFS)

Components of a Financial Statement

A financial statement package usually comprises the following:

a valance sheet (BS)
a profit- und loss-Statement (P&L)
a statement of change in equity (being ignored here)
a cash flow statement (CFS)

The normal financial statement uses fixed values.

The financial statement is typically used to report on the performance and state of a company. Neglecting practical valuation and depreciation problems, the resulting financial statements’ contents can be described as fixed/static and past-oriented: the statement reflects and recapitulates the business in the reported past period. It is past business that will not change anymore. Accordingly, the results and figures reported are fixed.

Point-in-time vs. Period: The different perspectives of the financial statement

For the further discussion it is important to stress the differences in character of the components of a financial statement:

The balance sheet (BS) reports the state of the company at a given point in time (usually at quarter or business years’ ends).
The P&L reports on the business during a given reporting period. It is thus period related.
The cash-flow statement connects BS and P&L by reporting the causes of the changes in cash during the given reporting period.

Together the the three components (acutually only two: BS and P&L) define a stock-flow-problem. The BS at the beginning of the period defines a starting point to which the business activity (flow) is added in order to get the end of period BS.

Projecting the financial statement into the future if there is uncertainty

If we try to project the financial statement into the future we often apply the same concepts we used to describe the past: fixed values. It is obvious that this is only going to be adequate as long as we stay within our known and established business.

But how do we deal/cope with CHANGE/UNCERTAINTY?

It is obvious that you need to adapt and change your financial planning. But how?

Basically you have just two options:

Ingnore it: You leave the model as it is and just adjust values and estimates.
Guess it: You try to identify the new typical case and adjust our model accordingly.

But how do you guess the typical case, how do we adjust the values and estimates?

Based on our real world experience, it is rare that you can extend an existing model adequately to include and embrace the new uncertainty.

You have to make a special effort analysing the new situation.
We believe a Stochastic Financial Statement projection is one of the best ways of doing that.

Once the stochastic analysis is done, the key risk drivers are identified and the expectations are known. From that point onwards a static projection can take over for day-to-day operations and to track progress. Because of the stochastic analysis, adverse developments within the set of key drivers can and will be detected early and easily.

Static and stochastic analysis thus complement each other.
Static analysis is for the day-to-day operation, stochastic analysis moves the structure of the static projection from one steady-state to the next.

Stochastic analysis and Stochastic Financial Statements

According to Wikipedia the term “stochastic” originally meant “pertaining to conjecturing”. This describes well what we attempt to do here: we make conjectures, estimates and assumptions in order to get a better take on future outcomes.

To achieve our goal, we must have a tool that allows for the direct specification of uncertainty. We want to be able to input expected value distributions in time.

We use the term “Stochastic Financial Statement” to describe a Financial Statement that accommodates inputs directly in the form of correlated distributions.

Basically, it means that we do our analysis and the calculating with variables that can take on a wide range of values at a given point in time. We thus accept the fact that there is uncertainty and that, in reality, a variable thus can take on a wide range of values over time. Further we assume that not all values of the variables have the same likelihood. We therefore assign to each outcome a specific probability. By doing so, we define a distribution of values which we then use directly in our projections.

Example: Quantities sold are not fixed but can take on a range of value (here shown: 95% probability)

We know that this sounds terribly complicated. And it actually is, if you do not have the right tools to help you. But if you have them, the resulting analysis is extremely powerful and useful.

Please go to our tools intro section to see and learn how we implement a Stochastic Financial Statement.

Of course, Stochastic Financial Statements not only accept distributions as inputs but they also provide expected value ranges as output for all items on the balance sheet, the P&L and the underlying details. This information can then be used to identify potentially critical situations and to implement the necessary risk control measures. The analysis provides a sound basis for the adjusted static model and it moves management focus automatically towards the critical factors.

As we have mentioned above, stochastic and static financial analysis complement each other. We do both. We prefer to do complex static modelling in Quantrix.

Please do not hesitate to contact us, if you want to hear more about static modelling and Quantrix. Don’t worry, we know one thing or two about Excel and its issues as well!