Subject: DT Annuities Variable Annuity Market Rate of Return Assumption Recommendation

Hello Ben, Lingyi, and Yinhua,

My role in DT Annuities’ Variable Annuity project was to select the projected market rate of return assumption. Our company feels that there are strong benefits to be had from entering into the variable annuity market, but only if our product is advantageous to all stakeholders. After analyzing the historical data, I recommend setting the market rate of return assumption at 10.01%. This projected market rate of return is more than 2% higher than Big Corp Financial’s and this allows our product to have lower M&E fees and higher commissions. These two qualities of our product are especially desirable to prospective clients and advisors, respectively.

Background

DT Annuities wishes to expand into the growing variable annuity market. In order to so, we must be confident that our product will be able to compete with similar products such as the one Big Corp Financial is currently selling. Our product must also appeal to the three main stakeholders involved: senior management, financial advisors, and clients. Senior management requires a 10.0% IRR and a robust product that isn’t highly susceptible to market crashes. Financial advisors wish to have a product that compensates them well with desirable commissions and has benefits that make it an easier task to sell to clients. Our clients need a trustful product with benefits and competitive fees in order to maximize their return.

Experiential Data Analysis

Our company was given experiential data from similar products within the industry. This data included 23 years (1992-2014) of historical market return from those products. Below is a visual overview of the experiential data that was provided by DT Annuities’ intern1.

19921994

19961998

20002002

20042006

20082010

20122014

-40.0%-30.0%-20.0%-10.0%

0.0%10.0%20.0%30.0%

Historical Market Rate of Return

Year

Mar

ket R

ate

of R

etur

n

As you can see from the line chart above, there have been two market crashes in the previous 23 years and also one market boom of 23.7% in 1998. Also worth taking note of is the tendency of the rate to hover near 11%.

Assumption Declaration

Conservativeness was a major factor in determining the market rate of return assumption. I strived to capture both the central tendency and dispersion of the dataset in order to reflect typical years and market crashes, respectively. In doing so, our assumption is more conservative because it takes into consideration the historical market crashes and thus makes our product more resilient. I also weighted the data points that occurred most recently heavier because I felt they are more relevant. In order to derive the assumption, I first found the average of the weighted dataset and the median of the initial dataset. The weighted average was heavily influenced by the two market crashes and thus actually reflected some of the dispersion within the dataset. On the other hand, the median in this case better represented the central tendency of the data. Since roughly 60% of the data fell within 1% of the median, I chose to give the median a weight of 60% and the weighted average a weight of 40% to calculate the final assumption. This formula is as follows:

60· Median+40 ·Weighted Average100

=60 ·11.20%+40 ·8.22%100

=10.01%

From the data and analysis above, I have settled on the market rate of return assumption of 10.01%.

Sensitivity Testing

Next, sensitivity testing was completed on this assumption in order to see the result of deviations from our projected rate. Understandably, the market rate of return has a large effect on the success of our product. And as was seen in the experiential data there can be large fluctuations in this rate, so making sure the assumption is accurate is vital. After modeling with a range of different rates of return, holding our other assumptions constant, I found there to be nearly a one to one ratio between the change in market rate of return and resulting change in IRR. A graph displaying this linear relationship can be seen below.

5.00%6.00%

7.00%8.00%

9.00%

10.00%

11.00%

12.00%

13.00%

14.00%

15.00%0.00%2.00%4.00%6.00%8.00%

10.00%12.00%14.00%16.00%

f(x) = 1.04752883044415 x − 0.00535618527213461R² = 0.999957305875357

Market Rate of Return vs. IRR

Market Rate of Return

IRR

Thus I would classify this assumption as both extremely important and highly sensitive. Its sensibility is another reason why I chose to make a conservative projection.

In Conclusion, I recommend that we project a market rate of return of 10.01%. This should help us attract clients because they should be able to gain a higher return on their investment than would be the case with Big Corp Financial and their return of 8% as well as their higher M&E fee. In addition, as a result of our higher market rate of return, we can increase some of our commissions in order to convince advisors to sell our variable annuity more frequently than our competitor’s product. I advise that we continually monitor this product after its launch to gather more data and assess how well our assumptions hold and whether or not they need to be tweaked in the future.

Let me know if you have any questions.

Thanks,

Alexander Peterson

1Spring 2015 Module – Ameriprise VA 6 Year Projection.xls