# Portfolio Analytics

In the Deep Alpha Advisory platform have the capability to perform a wide range of portfolio analysis. The purpose is to provide talking points to the advisors and insight to the investors. The portfolio analysis is available in the proposal page of the full advisory flow, in the order page in the order execution flow and in the holistic view tool. Currently, we have the following portfolio analytics components available in DAAP:

- Portfolio
- Expected path
- Expected value
- Cost
- Efficient frontier
- Historical return
- Cashflow
- Order summary
- Sustainability

These analytics components can be found at different places in the platform:

- Advisory page
- Proposal page
- Risk finder
- Holistic view

The objective of the analytics components “Portfolio” is to give insight in the asset allocation of the selected investment portfolio. This is presented using pie-charts. The analytics component has three views: • Broad asset allocation • Asset allocation • Fund asset allocation

The broad asset allocation pie-chart shows the allocation between equity and fixed income. This allocation is configured by your admins on category level. The pie-chart looks like this:

The asset allocation pie-chart shows the allocation on asset class / category level. Examples of asset classes are global equities, Norwegian equities, money market, corporate bonds, etc. You will see asset classes relevant for your investment universe, as it is configured by you admins. The pie-chart looks like this:

The fund allocation pie-chart shows the allocation on instrument level of the selected portfolio. The pie-chart looks like this.

The objective of the analytics component “Expected path” is to visualize the potential "sample space" for the selected saving plan, and it looks like this:

For calculating the expected path, we are using the expected return of the portfolio, the volatility of the portfolio (calculated on category level and the correlation between the instruments (categories) in the portfolio. Furthermore, we assume log-normal distribution and use a 90 % confidence interval for calculating the upper- and lower bound.

The objective of the expected value component is to project the expected value development of the saving plan, across the goals and compare it a 1 % return (illustrating the return on a bank account). The expected value analysis looks like this:

You can look at each goal´s portfolio individually by using the filter function, or you can look at the saving plan as a whole. Note: If the investor´s goals has different time horizon, you will observe a drop in the graph at the end of the time period for the specific goal. The reason for this is that we only project the goals based. The projection period for each time-horizon may differ based on your configuration of the tool.

For projection purposes, we use the expected value for the portfolios, configured by your admins.

The objective of the cost analytics component is to visualize the effect of cost, for the investment plan, over a span of 10 years. The purpose is to ensure full transparency related to the:

- Estimated costs
- Effect of costs, including missed return

The cost analytics component is required by regulations, and it works on top of the cost model configured by your site admin. You can read more about our cost functionality here: Cost Model

The analytics component consists of a chart showing the expected value before and after cost, in addition to the effect of cost. Furthermore, there are different views that can be used to provide insight to the expected cost:

- Summary
- Year 1
- Year 10
- Fund details, kr
- Fund details, %

You can read a summary below or visit the more detailed description here: Cost analysis in Deep Alpha

**Summary tab: **

The summary tab provides you with a summary of the cost and insight into which cost components we are using for projection purposes. It can consist of three tables:

- Ongoing fees
- One time fees
- Custody fees

The tables will change and adapt to reflect your cost model, and it looks like this:

**Year 1 tab: **
The year 1 tab serves the purpose of giving insight into the expected cost and cost effect the first year. Here you will find information about:
*Aggregated cost effect after 1 year *

- Shows the aggregated deposit over the period, given by the sum of monthly deposits and initial deposits over 1 year.**Deposit**- Shows the expected value before cost. Calculated by using the expected value of the saving plan.**Expected value before cost**- Shows the expected value after cost. Calculated by subtracting the costs on monthly basis.**Expected value after cost**-**Reduction in return**Shows the monetary difference between the expected value before and after cost, and gives insight into the cost effect in amount.- Expected return after cost shows the expected return after cost. Calculated by the expected return divided with the deposits**Expected return after cost (%)**- This field shows the expected return in monetary terms, calculated with expected return after cost – deposit**Expected return**

Aggregated fee tables for the following fee types:

- Ongoing fees
- One time fees
- Return commission paid to advisor

These tables shows the estimated fee in amount plus the % of this value, measured in relation to the expected value before cost. The tab looks like this:

**Year 10 tab:
**
Shows the same analysis as for year 1, except that we look for the time horizon of 10 years.
The tab looks like this:

**Fund details, kr: **

This tab shows the detailed snapshot of the expected cost per fund, in monetary terms. It uses the initial deposit (if available) per investment goal to calculate the cost per instrument.

The tab looks like this:

**Fund details, %: **

Shows the cost per instrument in %, as defined in your configuration.

The tab looks like this:

__Oversteer fund-related costs__

We have functionality for oversteering the cost. If turned on cost cells in the table will be replaced with inputs for allowing changing the cost ( see illustration below ).

It is possible to oversteer 4 fund related cost types:

- fund management fee
- fund transaction cost
- fund purchasing fee
- fund return commission paid to the client

In addition, it is possible to oversteer the portfolio related fees.

Oversteered costs can be documented, and configured as a mandatory or non-mandatory note. Advisor's notes with the reasoning will be presented on the investment proposal PDF.

Your cost model is configured by you site admins. Therefore, what you see can differ from the examples above. Contact you site admin if you have any questions.

The historical return analytics component has the objective of showing the historical performance of the portfolio selected. The analysis is detached from the saving plan and assumes an start sum of 100. If you have multiple portfolios in the saving plan, the graph will show multiple lines. For each portfolio selected, we will show the historical return for the given period. The following look back periods are available:

- 3M
- YTD
- 1Y
- 3Y
- 5Y
- 10Y

If there is less than 80 % data availability for one of the funds in the portfolio, for the select look-back period, we will not show any data. If there is between 80% and 100 % data coverage, we will patch the instrument time series with the correlating

The analysis looks like this:

Moreover historical return offer statistic metrics for each of the look back periods.

There can be up to 20 metrics selected from the list of 35. These metrics are:

- Total return
- CAGR
- Max drawdown
- Best year
- Worst year
- Best month
- Worst month
- Monthly sharpe
- Yearly sharpe
- Monthly sortino
- Yearly sortino
- Monthly mean return
- Monthly kurt
- Monthly skew
- Monthly volatility
- Yearly mean return
- Yearly kurt
- Yearly skew
- Yearly volatility
- Average drawdown
- Average drawdown days
- Average down month
- Average up month
- Win year percent
- 12 month win percent
- Year to date return
- Calmar
- Five year return
- Month to date return
- Year win percent
- Three year return
- Three month return
- Ten year return
- Six month return

The cashflow analysis has the objective of visualizing the aggregated withdrawal plan across the investment goals of the advisors in addition to show whether the capital need is expected to be met. The usage of this analysis tool requires that you have our goal based investing feature turned on. The analysis component looks like this:

Each of the goals will have a pie-chart with related information about capital need and estimated goal achievement:

- The pie-chart reflects the estimated goal achievement. If the estimated goal achievement is larger than 100%, the pie-chart will be full
- Estimated goal achievement is given by the
*expected value of the saving plan per goal*/*capital need* - Capital need depend on the withdrawal type:
- If withdrawal type = no planned withdrawal, the capital need is set to N/A
- If withdrawal type = one time withdrawal, the capital need is set equal to the withdrawal amount defined for the investment goal
- If withdrawal type = monthly withdrawal, the capital need is given by the net present value of the planned monthly withdrawal, for the defined period, at the time of withdrawal start

The graph shows the aggregated build-up and withdrawal plan for the portfolios and compare it to a withdrawal plan with no expected return.

The cashflow analysis can be used to visualize the effect of saving and give insight in how the saving plan will help the investor with reaching their goals.

In DAAP you have the opportunity to make multi goal saving plans, where each goal will have a dedicated portfolio. In order to give an overview of the aggregated orders, across the different saving goals, we have built the order summary analysis. In the order summary you can see two types of orders: Buy orders and monthly orders. This will be expanded with sell and switch orders in the future.

Both buy and monthly orders is displayed in amount and percent.

The analytics component looks like this:

- It makes it simple for you to register orders in your back office systems
- It gives a great overview of the different portfolios aggregated

Sustainability alignment analytics creates transparency into what extent investor's sustainability preferences are covered in the suggested portfolio. Sustainability Assessment