| Account | Cash | CCY |
|---|---|---|
| {{ row.name }} | {{ row.amount }} | {{ row.ccy.name }} |
| Initial cash |
|
{{ defaultCCY.name }} |
| Counterparty | Expected payment risk | Expected delay (days) | Annual growth rate |
|---|---|---|---|
| {{ row.name }} | {{ percent(row.paymentRisk) }} | {{ row.expectedDelayInDays }} | {{ row.growthRate | percent2 }} |
To investigate scenarios for credit risk and counterparty risk. One can set the following risk factors for each counterparty:
Estimated growth rates can be applied to individual counterparties ...
Each currency has a configurable interest rate which is used for discounting future cashflows in that currency. Rates can be found on central bank web sites ...
Modelling systematic risks impact the wider economy, financial crisis and pandemics are largely binary events with uncertain impact ...
| Counterparty | Date | Amount | CCY | Starts (years) | Ends (years) |
|---|---|---|---|---|---|
| {{ row.counterparty.name }} | {{ row.date | date }} |
|
{{ row.ccy.name }} |
| Counterparty | Date | Amount | CCY | Starts (years) | Ends (years) |
|---|---|---|---|---|---|
| {{ row.counterparty.name }} | {{ row.date | date }} |
|
{{ row.ccy.name }} |
| Account | Market value | CCY | Expected growth | Expected years before sale | Expected sales cost (%) |
|---|---|---|---|---|---|
| {{ row.name }} | {{ row.marketValue }} | {{ row.ccy.name }} | {{ row.expectedCapitalGain | percennt2 }} | {{ row.expectedYearsBeforeSale }} | {{ row.expectedLossRateOnSale | percent2 }} |
| Total | {{ defaultCCY.name }} |
| CCY | FX | Base interest rate (i) | Discount (v) | Date | Default |
|---|---|---|---|---|---|
| {{ row.name }} | {{ 1/(1+row.baseInterestRate) | percent2 }} | {{ row.date | date }} |
These interest rates are used to find the Net Present Value (NPV) of all cashflows:
{{ defaultCCY.name }}
| Type | PV |
|---|---|
| Fixed assets | |
| Cash | |
| NPV(cashflows) | |
| Total | |
| Counterparty | Day | Date | Days | Amount | CCY | Sum (Σ) | WC(Σ+Cash) | ΔAmount | ΔDate |
|---|---|---|---|---|---|---|---|---|---|
| {{ row.counterparty.name }} | {{ dayOfWeek(row.date) }} | {{ row.date | date }} | {{ row.days }} | {{ row.ccy.name }} | {{ row.deltaPayment | percent }} | {{ row.deltaDays }} |
A small or medium size business would be interested in forecasts to help manage their working capital. In particular, if the sum of cashflows ever go negative then the company becomes insolvent regardless of how much revenue the future might bring.
The forecast will find dates when the working capitcal goes negative and adapting the risk parameters for individual counterparties can identify scenarios which could produce insolvency.
Solutions including asking customers to pay earlier, suppliers to accept later payment, short term bridging loads. ...
Dividends are cashflows like any other and can be forecasted using the same algorithms. An investor might model future dividends.
Forecasting dividends for a stock portfolio involve taking all the dividends paid this year for your stock portfolio and use these as the Annual Cashflow Pattern. ...
Cashflows are typically not paid on weekends or bank holidays. There are often exchange specific rules for divideneds. Some applications may expect certain cashflows to always fall on the first tuesday or third thursday of each month. Exchanges have their own open days which change from year to year.
Currently this App just shift forecast dates so they do not fall on a Saturday or Sunday. Note Weekends are not always Saturday and Sunday ...
One can forecast dividends for individual stocks, for a portfolio or for an index. For index forecasting one would like to calculate dividend point using formula for the index and the value of each dividend. ...
One way to value a firm is to sum up it's future cashflows. The sum of (discounted) future cashflows gives a single number saying what they are worth today, their present value. For example, if our cashflows are dividends then in theory by the Dividend Discount Model a firm is equal to the present value of the future dividends.
One could apply this for an individual firm. To value an index fund or ETF one migh summing up all the dividends in the index.
Many firms pay regular dividends in patterns of one, two or four per annum that can be forecast using the method given here. Of course not all firms pay dividends, market value and often does not reflect validations ...
As individuals we have finanical assets and liabilities with regular revenues and costs, that can be forecast using the same algorithm. We can model our future costs and income from work and rental.
This might tell you how rich are you when you die or help estimate when you might be able to retire. It might also be useful to know when you have enough for a mortgage deposit or other large outgoing..
Items to add include: