Coggit Tool Information: Risky Growth Plan

This is a tool that calculates the historical performance of a risky growth plan and displays a wide range of calculated performance factors for ready comparison with other structured product plans. In more detail, the plan is tested at historical points, going back over a hundred years, and at each point the various performance factors are calculated. These performance factors are then averaged over all the historical tests to provide the displayed historical performance results. A description of each of the results shown is given below after the details on the input data required. In addition, for further comparison, the tool calculates the historical results of a stock market investment over the same period as the plan.

Note: If there is no risk element to the plan, please use the Protected Growth Plan tool instead. If the plan can mature early as a result of a kick-out, please use either the Protected, or Risky, Kick-Out Plan tool. If the plan generates income, please use one of the Protected, or Risky, Income Plan tools.

The information required for the historical performance calculations can be considered in six parts, matching the layout of the tool.

The first part is the standard plan data, which is described in the following list:

The start date of the plan.
Either the end date of the plan or its term in years, with the other one being calculated.
The base return, which is the base return on investment that will be received at maturity, and is typically 100%. Any additional positive return (growth) is added to this base return and any calculated negative return (risk) reduces it. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The second part of the information required for the historical performance calculations is the start price (initial index level) data, which is either basic or advanced. In the basic case, it is only necessary to input a single date, on which the closing value of the market (or markets) is obtained. In the advanced case, observation over a pricing range or series of pricing points is needed in order to calculate the start price. In more detail, in the advanced case, the following information is required:

The price type, which is the average, highest or lowest price of the observed price (market) values.
The observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly or yearly, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all these types, the closing value of the market (or markets) is obtained for each observation. In the highest or lowest pricing cases, the observation frequency can also be continuous. In the continuous observation case, the highest or lowest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
The price start date, which is either inputted or calculated. If inputted, the tool calculates the number of pricing observations from the start and end dates and the observation frequency.
The price end date.
The number of observations, which is either inputted or calculated. If inputted, the tool calculates the price start date from the number of observations, the price end date and the observation frequency. Note: In the continuous observation case, the number of observation days is used instead of the number of observations.

The third part of the information required for the historical performance calculations is the end price (final index level) data, which is either basic or advanced. In the basic case, it is only necessary to input a single date, on which the closing value of the market (or markets) is obtained. In the advanced case, observation over a pricing range or series of pricing points is needed in order to calculate the end price. In more detail, in the advanced case, the following information is required:

The price type, which is the average, highest or lowest price of the observed price (market) values.
The observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly or yearly, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all these types, the closing value of the market (or markets) is obtained for each observation. In the highest or lowest pricing cases, the observation frequency can also be continuous. In the continuous observation case, the highest or lowest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
The price start date, which is either inputted or calculated. If inputted, the tool calculates the number of pricing observations from the start and end dates and the observation frequency.
The price end date.
The number of observations, which is either inputted or calculated. If inputted, the tool calculates the price start date from the number of observations, the price end date and the observation frequency. Note: In the continuous observation case, the number of observation days is used instead of the number of observations.

Note: If the plan has more than one price source (see below), the start and end prices are calculated for the underlying market for each price source, and the relative market performance is determined by comparing the end price to the start price for each market, and finding the average, best or worst of these comparisons. This should be taken into account when the relative market performance is mentioned below.

The fourth part of the information required for the historical performance calculations is the positive return data, which is used to determine the additional return (growth) that will be received at maturity (additional to the base return described above).

There are four basic types of positive return data. The first type is a call return, which requires the following information:

The call strike. If the relative market performance, comparing the calculated end price to the calculated start price, is better than the call strike, then an additional return will be received at maturity, e.g. if the call strike is 100%, then any increase in price will lead to an extra return. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The call gearing. If the call strike is exceeded, the gearing provides the multiplying factor on the performance gain to determine how much additional return is received, e.g. if the call strike is 100% and the gearing is 200% then any price increase is multiplied by 2 when calculating the return. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The second positive return type is a capped call return, which requires the following information:

The capped call strike. If the relative market performance, comparing the calculated end price to the calculated start price, is better than the call strike, then an additional return will be received at maturity, e.g. if the call strike is 100%, then any increase in price will lead to an extra return. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The capped call gearing. If the capped call strike is exceeded, the gearing provides the multiplying factor on the performance gain to determine how much additional return is received, e.g. if the call strike is 100% and the gearing is 150% then any price increase is multiplied by 1.5 when calculating the return. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
Either the cap strike or the return cap, with the other one being calculated:
- The cap strike, which specifies a maximum strike level on the relative market performance in the return calculation, with any further price increase being ignored, e.g. if the call strike is 100% and the cap strike is 150% but the calculated end price is 75% higher than the calculated start price, only the first 50% of the performance gain is relevant. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
- The return cap, which specifies the maximum additional return that will be received at maturity, e.g. if the return cap is 50%, this is the maximum even if the calculated return from the call strike and gearing would exceed this. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The third positive return type is a digital return, which requires the following information:

The digital strike. If the relative market performance, comparing the calculated end price to the calculated start price, is better than the digital strike, then an additional fixed return will be received at maturity, e.g. if the digital strike is 100%, then any increase in price will lead to the same fixed return. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The digital return, which specifies the additional fixed return that will be received if the digital strike is exceeded, e.g. if the digital return is 42% and the digital strike is 100%, then any increase in price will lead to a 42% return. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The fourth positive return type is a Twin-Win return, which requires the following information:

The upside return type, which is used to determine the additional return (growth) that will be received at maturity if there is a positive market performance and any upside knock-out barrier has not been breached. The possible upside return types are call return, capped call return or digital return.
The upside return information, which is dependent on the upside return type. Since the possible upside return types are the same as the positive return types described above, the information required for each type is not repeated here.
The downside return type, which is used to determine the additional return (growth) that will be received at maturity if there is a negative market performance and any downside knock-out barrier has not been breached. The possible downside return types are put return, floored put return or digital return.
The downside return information, which is dependent on the downside return type. Since the possible downside return types are the same as the negative return types described below, the information required for each type is not repeated here. However, there is a key difference: since, in the Twin-Win situation, a downside return is positive, the put gearing, return floor and digital return values are also positive rather than negative.
The knock-out barrier data, if there is a knock-out barrier for the upside and/or downside. In practice, the downside knock-out barrier tends to be the same as the soft protection barrier for the negative return part of a Twin-Win plan, since the negative return tends to become applicable at the same point as the downside positive return is knocked out, but it is specified separately for increased flexibility. In more detail, the upside/downside knock-out barrier(s) require the following information, with the barrier observation data applying to both upside and downside:
- The optional upside knock-out barrier level, which is the relative performance level that when breached during the barrier observation period, knocks out the upside participation in the Twin-Win positive return. For this level, the relative performance is determined by comparing the barrier observation price to the plan start price, e.g. if the upside barrier level is 150% then the upside return will be knocked out if the observed price is more than 50% higher than the start price. This level is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
- The optional downside knock-out barrier level, which is the relative performance level that when breached during the barrier observation period, knocks out the downside participation in the Twin-Win positive return. For this level, the relative performance is determined by comparing the barrier observation price to the plan start price, e.g. if the downside barrier level is 50% then the downside return will be knocked out if the observed price is more than 50% lower than the start price. This level is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
- The barrier observation type, which is the lowest, average or highest of the observed market values. It is also possible to specify highest/lowest, which finds the highest observed market value for the upside and the lowest observed market value for the downside.
- The barrier observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly or yearly, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all these types, the closing value of the market (or markets) is obtained for each observation. In the lowest or highest observation type cases, the observation frequency can also be continuous. In the continuous observation case, the lowest or highest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
- The barrier observation start date, which is either inputted or calculated. If inputted, the tool calculates the number of observations from the observation start and end dates and the observation frequency.
- The barrier observation end date.
- The number of observations, which is either inputted or calculated. If inputted, the tool calculates the observation start date from the number of observations, the observation end date and the observation frequency. Note: In the continuous observation case, the number of observation days is used instead of the number of observations.

In addition to, or in place of, the above positive return types, a plan may have a periodic growth builder. This is a mechanism that on a periodic basis calculates a locked-in return (positive or negative) depending on market performance, with the total of the individual returns being received at maturity, after optionally applying any growth minimum or maximum. This mechanism can be used to model basic growth building, where a locked-in return is added to the total growth every time a periodic condition is met, with the market performance for the condition check typically being determined by comparing the period end price with the initial start price of the plan. The functionality can also be used to model more complex cliquet style products, where the start price used for calculating performance is re-calculated for each return period, an amount can be gained or deducted each period, and the final return is determined by summing up the gains and losses over the periods with the application of a minimum and/or maximum to the total. If a periodic growth builder is part of the plan, select it and enter the required information, which can be considered in four parts, matching the layout of the tool.

The first part is the growth builder base data, which is described in the following list:

The number of return periods, which specifies the number of periods when a locked-in return is calculated. Summing up the calculated return for each period gives the overall growth builder return (after any overall minimum or maximum is applied).
The return period frequency, which consists of two parts: a frequency number and a frequency type. The type is monthly or yearly, with the frequency number indicating the type spacing, e.g. 6 monthly specifies a frequency of every 6 months (i.e. semi-annual). Combined with the number of return periods, this gives the total time over which the growth builder return is calculated.

The second part of the information required for the periodic growth builder is the return data, which is used to calculate the locked-in return for each period. The return data itself consists of three sections.

The first section is the positive return data, which is used to determine if there is any positive return for a period, and, if so, how much. Since the possible positive return types are the same as described above for calculating any top-level additional return that will be received at maturity, they are not repeated here, but it is important to keep in mind when reading the descriptions that the calculated return here is per period and locked-in.

The second section for the periodic growth builder return data is the optional negative return data, which is used to determine if there is any negative return for a period, and, if so, how much. Since the possible negative return types are the same as described below for calculating any top-level reduction in the return that will be received at maturity, they are not repeated here, but it is important to keep in mind when reading the descriptions that the calculated return reduction here is per period and locked-in.

The third section for the periodic growth builder return data is the optional overall minimum and maximum growth boundaries, which act as a floor and cap respectively on the overall growth returned by the periodic growth builder. In more detail:

The overall minimum growth should be entered if it is necessary to specify a minimum return for the growth builder, which is typically used to ensure that the growth builder always returns a positive return on investment irrespective of market performance. This return is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The overall maximum growth should be entered if it is necessary to specify a maximum return for the growth builder that differs from the maximum return that can be calculated by summing up the maximum return possible for each return period, so could be used, for example, if the individual period returns are themselves not capped. This return is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The third part of the information required for the periodic growth builder is the end price data, which is used to calculate the end price for each return period. The end price calculation requires the following information:

The period end price type, which is the average, highest or lowest price of the observed price (market) values.
The period end price observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly or yearly, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all these types, the closing value of the market (or markets) is obtained for each observation. In the highest or lowest pricing cases, the observation frequency can also be continuous. In the continuous observation case, the highest or lowest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
The number of observations for determining the observation end price, or the number of observation days if the observation frequency type is continuous. This is the same for every return period.
The first period end price observation end date, which, in combination with the number of observations and the observation frequency, is used by the tool to calculate the first period end price observation start date and range. The first period end price observation end date is also used, together with the number of return periods and the return period frequency, to calculate all the other period end price observation end dates. Note: If the required observation day of the year or month is not a week day for the first period observation end date, enter it as the required date anyway, to prevent all the other dates being calculated from the wrong date, e.g. if the observation end date should be on September 18th of each year starting from 2011, enter the first date as September 18th (Sunday) and not the 19th (Monday). The tool will handle any dates that don't fall on a week day by shifting them automatically to the next business day, e.g. September 19th 2011 for the first one.
The last period end price observation end date, which is calculated from the first period observation end date but, unlike the other period observation end dates, is also editable.

The fourth part of the information required for the periodic growth builder is the start price data, which is used to calculate and reset the start price for each return period, and is thus only required if market performance needs to be measured over the span of a period and not from the start of the plan to the period end. As an extra point, since it is assumed that the first return period always uses the initial start price of the plan, any start price calculation and resetting only begins at the start of the second return period. The start price calculation requires the following information:

The period start price type, which is the average, highest or lowest price of the observed price (market) values.
The period start price observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly or yearly, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all these types, the closing value of the market (or markets) is obtained for each observation. In the highest or lowest pricing cases, the observation frequency can also be continuous. In the continuous observation case, the highest or lowest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
The number of observations for determining the observation start price, or the number of observation days if the observation frequency type is continuous. This is the same for every return period.
The second period start price observation start date, which, in combination with the number of observations and the observation frequency, is used by the tool to calculate the second period start price observation end date and range. The second period start price observation start date is also used, together with the number of return periods and the return period frequency, to calculate all the other period start price observation start dates. Note: If the required observation day of the year or month is not a week day for the second period observation start date, enter it as the required date anyway, to prevent all the other dates being calculated from the wrong date, e.g. if the observation start date should be on September 18th of each year starting from 2011, enter the first date as September 18th (Sunday) and not the 19th (Monday). The tool will handle any dates that don't fall on a week day by shifting them automatically to the next business day, e.g. September 19th 2011 for the first one.
The last period start price observation start date, which is calculated from the second period observation start date but, unlike the other period observation start dates, is also editable.

Finally, in the positive return data part, it is possible to specify up to 5 lock-in levels. A lock-in level is required if it is possible to lock-in any observed growth during the course of plan to specify a minimum on the additional return calculated at maturity. For each required lock-in, it is necessary to provide the following information:

The lock-in level, which is the relative performance level that must be exceeded during the observation period for the lock-in to be applicable, with the relative performance being determined by comparing the lock-in observation price to the plan start price, e.g. if the lock-in level is 114% then the lock-in will be applicable if the observed price is more than 14% higher than the start price. This level is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The lock-in minimum return, which if the lock-in level is exceeded, gives a minimum additional return that will be received at maturity. This often matches the lock-in level, e.g. 14% with a lock-in level of 114%, but not always, which is the reason it can be specified separately. This return is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The lock-in observation type, which is the average, highest or lowest of the observed market values.
The lock-in observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly or yearly, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all these types, the closing value of the market (or markets) is obtained for each observation. In the highest or lowest observation type cases, the observation frequency can also be continuous. In the continuous observation case, the highest or lowest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
The lock-in observation start date, which is either inputted or calculated. If inputted, the tool calculates the number of observations from the observation start and end dates and the observation frequency.
The lock-in observation end date.
The number of lock-in observations, which is either inputted or calculated. If inputted, the tool calculates the observation start date from the number of observations, the observation end date and the observation frequency. Note: In the continuous observation case, the number of observation days is used instead of the number of observations.

The fifth part of the information required for the historical performance calculations is the negative return data, which is used to determine any reduction in the return (risk) that will be received at maturity (reduced from the base return described above).

There are three basic types of negative return data. The first type is a put return, which requires the following information:

The put strike. If the relative market performance, comparing the calculated end price to the calculated start price, is less than the put strike, then the return received at maturity will be reduced, e.g. if the put strike is 100%, then any decrease in price will lead to a return reduction. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The put gearing. If the put strike is breached, the gearing provides the multiplying factor on the performance loss to determine how much reduction there is on the return received, e.g. if the put strike is 100% and the gearing is -200% then any price decrease is multiplied by 2 when calculating the return reduction. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The second negative return type is a floored put return, which requires the following information:

The floored put strike. If the relative market performance, comparing the calculated end price to the calculated start price, is less than the put strike, then the return received at maturity will be reduced, e.g. if the put strike is 100%, then any decrease in price will lead to a return reduction. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The floored put gearing. If the floored put strike is breached, the gearing provides the multiplying factor on the performance loss to determine how much reduction there is on the return received, e.g. if the put strike is 100% and the gearing is -200% then any price decrease is multiplied by 2 when calculating the return reduction. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
Either the floor strike or the return floor, with the other one being calculated:
- The floor strike, which specifies a minimum strike level on the relative market performance in the return reduction calculation, with any further price decrease being ignored, e.g. if the put strike is 100% and the floor strike is 50% but the calculated end price is 75% lower than the calculated start price, only the first 50% of the performance loss is relevant. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
- The return floor, which specifies the maximum reduction in the return that will be received at maturity, e.g. if the return floor is -50%, this is the maximum reduction even if the calculated return reduction from the put strike and gearing would exceed this. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The third negative return type is a digital return, which requires the following information:

The digital strike. If the relative market performance, comparing the calculated end price to the calculated start price, is less than the digital strike, then there will be a fixed reduction in the return received at maturity, e.g. if the digital strike is 100%, then any decrease in price will lead to the same fixed return reduction. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The digital return, which specifies the fixed reduction in the return that will be received if the digital strike is breached, e.g. if the digital return is -42% and the digital strike is 100%, then any decrease in price will lead to a 42% return reduction. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

In all negative return cases, it is possible to specify a negative removal level, which is a level that if exceeded during the specified observation period, removes any negative return factor from the overall return calculation and thus cancels any possible reduction in the return that will be received at maturity. This negative removal option requires the following information:

The removal level, which is the relative performance level that when exceeded during the removal observation period, removes any negative return factor permanently, with the relative performance being determined by comparing the removal observation price to the plan start price. This level is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The removal observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly, yearly or continuous, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all the non-continuous types, the closing value of the market (or markets) is obtained for each observation. In the continuous observation case, the highest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
The removal observation start date, which is either inputted or calculated. If inputted, the tool calculates the number of observations from the observation start and end dates and the observation frequency.
The removal observation end date.
The number of observations, which is either inputted or calculated. If inputted, the tool calculates the observation start date from the number of observations, the observation end date and the observation frequency. Note: In the continuous observation case, the number of observation days is used instead of the number of observations.

Finally, in the negative return data part, it is possible to specify negative return protection, which prevents any negative return factor being applied, and thus protects the maturity return from any possible reduction, unless the condition to remove the protection is breached. There are two types of negative return protection:

The first type is soft protection, which requires the following information:

The protection level, which is the relative performance level that when breached during the protection observation period, removes any negative return protection, with the result that the negative return factor, and thus any calculated maturity return reduction, applies. For this level, the relative performance is determined by comparing the protection observation price to the plan start price, e.g. if the protection level is 50% then the protection will be removed if the observed price is more than 50% lower than the start price. This level is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The protection observation type, which is the lowest or average of the observed market values.
The protection observation frequency, which consists of two parts: a frequency number and a frequency type. The type is daily, weekly, monthly or yearly, with the frequency number indicating the type spacing, e.g. 3 daily specifies a frequency of every 3 days. For all these types, the closing value of the market (or markets) is obtained for each observation. In the lowest observation type case, the observation frequency can also be continuous. In the continuous observation case, the lowest value of the market (or markets) over the observation range is found, which can be at any time during the day and not just at the close. Note: In the continuous case, the observation frequency number is not relevant.
The protection observation start date, which is either inputted or calculated. If inputted, the tool calculates the number of observations from the observation start and end dates and the observation frequency.
The protection observation end date.
The number of observations, which is either inputted or calculated. If inputted, the tool calculates the observation start date from the number of observations, the observation end date and the observation frequency. Note: In the continuous observation case, the number of observation days is used instead of the number of observations.

The second type is hard protection, which requires the following information:

The protection level, which is the performance level that if breached at maturity, removes any negative return protection, with the result that the negative return factor, and thus any calculated maturity return reduction, applies. For this level, the relative performance is determined by comparing the plan end price to the plan start price, e.g. if the protection level is 50% then the protection will be removed if the end price is more than 50% lower than the start price. This level is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The sixth part of the information required for the historical performance calculations is the price source data, which is used to specify the price source/underlying market(s) for the plan. If the product only has one underlying market (UK or US stock market), the basic price source can be used. Otherwise, the advanced option is required. In the advanced option, it is necessary to specify:

The underlying type, which is average, best or worst, and determines how the overall relative market performance is calculated from the relative market performance for each underlying market.
The underlying markets, noting that currently there is only a choice of 2 (UK or US stock market).

Note: In this tool, a level is only breached if the relative performance, depending on the direction, exceeds or falls below it, i.e. being equal to the level is not treated as a breach. If a particular product requires that the equals to case also counts as a level breach, there are a couple of options for handling this with the tool. The first option is to simply ignore it, as being equal to a level is an unlikely event and the effect on the overall results would thus be slight. The second option is to enter a level value that is a little bit smaller or bigger than the actual value and thus distinguish the products where being equal to a level counts as a breach from those where it does not, e.g. if the level is 100%, type in 99.999999% for the greater than or equals to case.

While not necessary for the historical performance calculations, it is also possible to attach the following additional product information to the plan by opening up the product information section:

The product provider.
The closing date of the plan.
Any additional product information.

As an addition to the full historical performance calculations, the tool also provides the possibility of running the plan data through a small number of historical tests, with an optional trace. This allows the calculations and logic used in the tool to be checked if required. To run the product in tester mode, open up the advanced options, switch the product test mode on and enter the following information:

The tester start date, which is the date at which the testing starts. This date must be after 01/01/1990.
The number of tests, which cannot be greater than 10.
Whether a trace file should be generated or not. If it should be generated, a link is provided in the browser to the trace file once the tests have been completed.

As mentioned at the beginning of this information page, a wide range of historical performance results are calculated and displayed:

The first start date for the historical performance test.
The last start date for the historical performance test.
The length of the historical performance test in years, i.e. the difference between the first and last start dates.
The number of times the plan is tested.
The average return over all the performance tests.
The average term in years over all the performance tests.
The average return as an annualised value over all the performance tests.
The average AER (annual equivalent rate) over all the performance tests.
The median AER (annual equivalent rate) over all the performance tests.
The worst return over all the performance tests.
The frequency of this worst return during the performance tests.

In addition, a results table is also displayed showing the average AER and average return for the worst 0.1%, 1%, 5%, 10% and 25% of results. If any of the historical tests show losses, an additional column is included, giving the percentage of results which indicated losses and the average AER and return for these loss making tests.

In addition, a results table is also displayed showing the average AER and average return for the best 0.10%, 10-20%,..., 90-100% of results.

Furthermore, depending on the plan input data, some additional historical test results are calculated and displayed:

The frequency (percentage) of performance tests that result in neither loss nor gain.
The frequency (percentage) of performance tests that result in gains. Adding this percentage to the percentage of loss making results and the percentage of results with neither loss nor gain should give a total of 100%.
The frequency (percentage) of performance tests in which the maturity return is reduced, i.e. the percentage of tests which have a non-zero negative return.
If the plan has negative return soft protection, the frequency (percentage) of performance tests in which this soft protection barrier is breached.

Finally, for comparison purposes, the historical results of investing in the underlying stock markets over the plan period can be calculated and shown. Two inputs are required for this stock market investment comparison:

The annual expenses rate. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).
The total investment spread. This is usually expressed in percentage terms (unless the formatting is explicitly set to express it as a decimal).

The stock market investment comparison results are split into three sections.

The first section shows the average return, average AER, median AER and worst return for each underlying market over all the historical tests.

The second section shows a table for each underlying market, displaying the average AER and average return for the worst 0.1%, 1%, 5%, 10% and 25% of results. If any of the historical investment tests show losses, an additional column is included, giving the percentage of results which indicated losses and the average AER and return for these loss making tests.

The third section shows the average AER and average return for the best 0.10%, 10-20%,..., 90-100% of results, for each underlying market.

Note: If you are using this tool with JavaScript disabled, it is necessary to press Calculate to open up a section for data entry after choosing the required option from a drop down, e.g. for entering advanced start price data or capped call return data.

Disclaimer: Historical performance is not necessarily a good guide to future performance. The historical data used in the calculation of the performance results has been compiled using a variety of sources and statistical techniques.

Associated tool link: http://www.coggit.com/tools/risky_growth_plan.html