June 2015
Contents Executive summary... 3 1. Introduction... 4 2. Analysis and methodology... 5 3. Results and model profiles... 7 4. Summary... 11 Appendix A: Investment assumptions... 12 Appendix B: Index data... 14 Appendix C: Risk Profile boundaries... 15 2 Distribution Technology Ltd
Executive summary Distribution Technology ( DT ) has reviewed and profiled a range of portfolios offered by Management ( OCM ) within the risk profiles used on the DT Dynamic Planner platform. The main objective of the DT risk profiles and fund risk profiling service is to provide financial advisers and their clients with a meaningful measure of the long-term investment risk of fund strategies and a mechanism for selecting funds appropriate for investor risk appetites and capacity for risk. The profiles which DT has assigned to the portfolios are set out in table 1. Table 1: Fund risk profiles Portfolio DT risk profiles OBI 5 3 OBI 6.5 4 OBI 8 5 OBI 10 6 The information contained in this report supplements methodologies used on the Platform. The report should be used in the context of these methodologies and advice provided on the Platform and not in isolation. 3 Distribution Technology Ltd
1. Introduction This report was commissioned by Management ( OCM ), who contracted Distribution Technology Ltd ( DT ) to assess the appropriate risk profiles for four portfolios within the risk profiles used in the Distribution Technology Dynamic Planner platform. The following portfolios are reviewed in this report: OBI 5 OBI 6.5 OBI 8 OBI 10 The profiles provided in this report are based on DT s investment planning assumptions. The assumptions used are those set for the first financial quarter of 2015, which are given in appendix A. The risk bands based on DT s assumptions are set out in appendix C. DT provides this analysis on the understanding that investors will access the funds through a regulated advice process. The recommendation on whether or not to include these funds in an investor s portfolio and the amount to include should be made by advisers with the necessary Financial Conduct Authority permission to give advice on investments. DT accepts no liability in respect of any advice given to investors relating to investment strategy or the purchase of specific products. The analysis in this report has been based on data and information provided by OCM and other third parties as set out in appendix B. Data received has been assumed by DT to be correct as of the date of this report. The following section sets out the results of our analysis and subsequent sections set out the methodology and assumptions in more detail. 4 Distribution Technology Ltd
2. Analysis and methodology One of the key tasks for an investor is to determine how much investment risk to take on. This decision will depend on psychological, financial and other factors. The investor will want to maximise the reward for taking on this risk through the selection of optimal weights for each asset category included in the investment portfolio. DT s asset allocation methodology is based on the principles of modern portfolio theory. The risk profiles provided by DT are risk profiles of the long-term strategic asset allocation adopted for a fund. The actual riskiness of a fund over the long term will depend on, among other things, the level of flexibility in the manager s mandate and how far the fund deviates from the strategic position and for how long. The measure of risk DT has used for each fund is the fund s estimated volatility as determined using the fund s internal asset allocations and estimates of the returns, volatilities and correlations of the DT primary asset classes. The analysis assumes that the actual holdings in each asset class can be broadly represented by the benchmark adopted for that asset. The investment assumptions used in this review are those set by DT at the end of the first financial quarter of 2015. Risk bands based on DT s assumptions (as set out in appendix C) were used to ensure that the profiles assigned to each fund are consistent with profiles and practices adopted within the implementation of DT s Dynamic Planner application. This ensures that the profiles can be used with outputs from psychometric risk profiling instruments used within the Dynamic Planner application. For the purposes of constructing the efficient frontier, estimating return distributions and rating funds, DT splits the investment universe into the following asset classes, called the primary asset classes: Cash UK Corporate Bonds UK Index Linked Gilts International Bonds UK Gilts Global High Yield Bonds UK Equity Europe ex UK Equity North American Equity Japanese Equity Pacific ex Japan Equity Emerging Markets Equity UK Commercial Property Commodities Hedge Fund For each of these asset classes, DT periodically reviews the appropriate set of investment assumptions for forecasting future returns and return distributions. The assumptions are derived from historical and market 5 Distribution Technology Ltd
data at each review date. Appendix A provides a summary of the methodology used to derive the investment planning assumptions used on the DT platform. Further details can be found in DT s Capital Markets Assumption reports. Volatilities and correlations are derived from historical data on a representative index for each asset class. The indices used for each asset class, along with the inception date for each index, are set out in appendix B. For the purpose of this review, we derived additional assumptions for the funds. These assumptions are also included in appendix A. 6 Distribution Technology Ltd
3. Results and model profiles OCM offers a range of discretionary portfolios which invest in underlying funds to meet their performance objectives. The DT risk profiles assigned to these funds are based on the historical asset allocations and historical performance as provided by the manager. In addition, we have ensured that the proposed profiles remain consistent with OCM s estimates for maximum drawdown. 4.1 Analysis of asset allocations OCM provided the historical asset allocations for the four portfolios on a monthly basis since the start of 2014. We have mapped the allocations to our standard asset allocations and calculated the volatilities using our DT assumptions. These are summarised in the table below; the numbers in brackets denote the frequency of allocations in the relevant profiles. Table 2: Historical asset allocation positions Portfolio Asset allocations OBI 5 DT 3 (8) / DT 4 (4) OBI 6.5 DT 4 (12) OBI 8 DT 4 (1) / DT 5 (8) / DT 6 (3) OBI 10 DT 5 (1) / DT 6 (11) These are the volatilities and return expectations based on asset allocation alone. OCM will seek to manage the return expectations through its use of fund selection. Each fund invests in an underlying collection of equity, bond and alternative investments. Equities include exposure to different geographical regions and also include some specialist equity holdings. Fixed income holdings include some high yield exposure and the use of strategic bond vehicles. Alternatives comprise investments in property and infrastructure. In addition, each fund invests in a suite of multi-asset managed products. OCM 5 is primarily composed of fixed income and alternative assets, with most equity content through the use of multi-asset funds. We calculate the volatility of most allocations to be of DT 3; there were some occurrences of DT 4 but these remained at the lower end of the risk bracket. All of the positons for OCM 6.5 resulted in a calculation of DT 4. This portfolio has an explicit equity content of around 20% in equities, with some additional exposure within the multi asset funds. There was more of a spread in distribution for the OCM 8 portfolio, which saw explicit equity exposure range between 36% and 50% of assets. Although some occurrences of DT 6 were observed, most allocations were at the high end of DT 5 or lower. For OCM 10, comprised predominantly of equities and property, we calculate DT 6 for most allocations. 7 Distribution Technology Ltd
Expected real return (% pa) June 2015 The figures from table 2 and are illustrated in chart 1 in which we show each allocation plotted on the riskreward spectrum. We also show the location of the standard asset allocations for each DT profile. The vertical gridlines indicate the boundaries of the DT profiles. Chart 1: Asset allocations against DT s efficient frontier 7.0% 6.0% 5.0% 4.0% 3.0% 2.0% 1.0% 0.0% -1.0% -2.0% 0.0% 2.1% 4.2% 6.3% 8.4% 10.5% 12.6% 14.7% 16.8% 18.9% 21.0% Expected volatility (% pa) DT profiles OBI 5 OBI 6.5 OBI 8 OBI 10 8 Distribution Technology Ltd
4.2 Historical performance Based on monthly performance figures provided by OCM until end 2014 ( a total of 29 months), we analysed the performance of the OCM portfolios. These are summarised in the table below. We compare this to some of the returns of the DT asset allocations ( AA ) over the same period. Table 3: Historical performance Portfolio Volatility (% pa) OBI 5 4.0% OBI 6.5 4.6% OBI 8 6.4% OBI 10 7.8% AA 2 3.4% AA 3 5.1% AA 4 5.8% AA 5 6.8% AA 6 8.0% AA 7 9.1% Over a short performance history, we can compare the volatilities experienced by each of the individual portfolios to that of the relevant DT asset allocation. For instance, OBI 5 had a volatility of 4.0% pa over the period analysed; this falls between the volatility achieved by AA 2 and AA 3. As the previous section suggested a volatility of DT 3 based on the asset allocation of the portfolio, we argue that DT 3 is the best measure of risk for this portfolio based on these two measures. Similarly, it can be seen that the volatilities of performance for all portfolios remains consistent with the view expressed in the previous section for asset allocation. 9 Distribution Technology Ltd
4.3 Maximum drawdown OCM provides indicative loss figures which express OCM s view on the maximum expected loss in each portfolio over rolling 12 month periods. This allows OCM to quantify the risk in its portfolios and to put protection on capital during times unexpected market events. Although not a direct comparison to the DT model, it remains useful to compare these expected losses to the expectations of each of the DT risk models. DT routinely provides worse than average numbers for each risk level based on the 95% VaR figure over one year. In the following table we show the maximum drawdowns as stated by OCM for each portfolio. We subsequently show the 95% VaR for the respective DT profile. We also show the actual maximum drawdown figures over the fund s five year history. Table 4: Maximum expected losses Portfolio OCM maximum drawdown Proposed DT profile 95% VaR of DT profile Actual fund drawdown OBI 5 5.0% 3 7.6% 4.6% OBI 6.5 7.5% 4 9.5% 4.3% OBI 8 12.5% 5 11.8% 7.4% OBI 10 17.5% 6 13.8% 7.4% For OBI 5 and 6.5 it can be seen that the maximum drawdowns as stated by OCM are less than the worst case expected for the relevant risk level. This is supportive of the proposed profiles. For OBI 8, the OCM stated maximum drawdown is comparable to the 95% VaR for DT 5. The OBI 10 portfolio has a maximum drawdown of 17.5%, compared to a 95% VaR of 13.8% for DT 6. Although this could suggest that a higher profile could be more appropriate, we would put greater weight on the results of the two sections (based on the DT model) which do support DT 6. For all portfolios, the actual drawdown over the last five years has been significantly lower than the limits imposed by OCM. 10 Distribution Technology Ltd
4. Summary In table 5 below, we summarise the risk profiles of the portfolios based on the different measures set out above. Table 5: Summary of DT risk profiles Portfolio Asset allocation Performance DT assigned risk profiles OBI 5 3 3 3 OBI 6.5 4 4 4 OBI 8 5 6 5 5 OBI 10 6 6 6 Each of the portfolios has been assigned a risk profile consistent with both their asset allocations and performance history. The portfolios have limited track history and so these profiles will be reviewed as the performance history is established. We have noted that most of OCM s maximum drawdowns remain broadly consistent with DT s calculation of the 95% VaR for each risk level. The one exception is for OBI 10 where the maximum drawdown is more than we would expect for DT 6. We remain comfortable with this profile though due to the other evidence. 11 Distribution Technology Ltd
Appendix A: Investment assumptions This appendix sets out the method used to generate the planning assumptions used on the DT platform. The correlations and volatilities used on the DT platform are derived mainly from the last 15 years of historical index data for a representative index for each asset class. The estimate of returns for property and hedge funds are calculated as a premium over gilts and then expressed as real returns (i.e. returns in excess of inflation). In addition to analysing historical index data, DT also use the following market data to arrive at expected return assumptions: Yields on UK Gilts; conventional and index-linked, UK corporate bond yields, Yields on global bonds, Equity earnings and dividend yields, Economic growth forecasts. Full details of the DT estimation methodology can be found in DT s Capital Markets Assumption report, which is available on request. Table 6 shows the real return and volatility assumptions for the first quarter of 2015, under the revised methodology, used to model assets for the DT standard and additional asset classes for the purpose of profiling the funds. 12 Distribution Technology Ltd
Table 6: Asset class returns and volatilities Assets Expected Real Returns Volatility Cash -1.0% 1.5% UK Corporate Bonds 0.5% 6.3% UK Index Linked Gilts -0.9% 7.5% International Bonds -1.1% 8.3% UK Gilts -0.5% 5.9% Global High Yield Bonds 2.4% 10.8% UK Equity 4.4% 13.8% Europe ex UK Equity 4.0% 19.0% North American Equity 4.1% 15.5% Japanese Equity 2.7% 16.8% Pacific ex Japan Equity 5.4% 18.6% Emerging Market Equity 6.2% 21.4% UK Commercial Property 1.9% 11.5% Commodities 3.8% 21.3% Hedge Funds 0.7% 8.7% Strategic bonds -0.4% 5.5% Infrastructure 1.9% 11.5% 13 Distribution Technology Ltd
Appendix B: Index data Table 7 below set out the indices used for each asset class. Table 7: Indices used for each asset class Region Index Cash Bank of England, Monthly Average of UK banks' base rates UK Corporate Bonds iboxx Corporate Index UK Index Linked Gilts Barclays Capital UK Government Inflation-Linked Bond Index International Bonds Merrill Lynch Global Broad Market Index UK Gilts Barclays Capital UK Government All Maturities Gilt Index Global High Yield Bonds Barclays Capital Global High Yield Bond Index UK Equity MSCI UK Total Return Index Europe ex UK Equity MSCI Europe (ex UK) Total Return Index North American Equity MSCI North America Total Return Index Japanese Equity MSCI Japan Total Return Index Pacific ex Japan Equity MSCI Pacific (ex Japan) Total Return Index Emerging Market Equity MSCI Emerging Markets Total Return Index UK Commercial Property IPD UK Monthly Property Index 14 Distribution Technology Ltd
Appendix C: Risk Profile boundaries The following table sets out the lower and upper volatility boundary for each risk profiles used in the implementation of DT s Dynamic Planner application. Table 8: DT Risk Profile boundaries Risk Profile Volatility of Asset allocation Lower Boundary Upper Boundary 1 1.5% 0.0% 2.1% 2 3.3% 2.1% 4.2% 3 5.4% 4.2% 6.3% 4 7.2% 6.3% 8.4% 5 9.4% 8.4% 10.5% 6 11.2% 10.5% 12.6% 7 13.1% 12.6% 14.7% 8 15.1% 14.7% 16.8% 9 17.1% 16.8% 18.9% 10 19.1% 18.9% 23.0% 15 Distribution Technology Ltd
Copyright Distribution Technology Ltd 2015 onwards. All rights reserved. The opinions expressed in this report are those formed by Distribution Technology and do not represent investment advice or a recommendation to buy or sell units or shares in a particular fund or portfolio. A significant part of this report and its results are dependent on information supplied by third parties and specifically information supplied by the manager of the funds analysed. The information does not indicate a promise, forecast or illustration of future volatility or returns. Distribution Technology is not liable for the data in respect of direct or consequential loss attaching to the use of or reliance upon this information. Distribution Technology does not warrant or claim that the information in this document or any associated form is compliant with obligations governing the provision of advice or the promotion of products as defined by the Financial Service Act. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or any means, electronic or mechanical, including photocopying and recording for any purpose other than the purchaser s personal use without the written permission of Distribution Technology. This publication may not be reproduced in full or in part without the express written permission of Distribution Technology. Its findings may only be shared, along with all caveats and assumptions with professional investment advisers. Source of information Management, Bank of England, Barclays Capital Inc., Bloomberg LLC, Heriot Watt University Gilt database and Office of National Statistics Trademarks Distribution Technology may have patents or pending patent applications, trademarks, copyrights or other intellectual property rights covering subject matter in this document. The furnishing of this document does not give you any license to these patents, trademarks, copyrights or other intellectual property rights except as expressly provided in any written license agreement from Distribution Technology. All other companies and product names are trademarks or registered trademarks of their respective holders. Publication date 23/06/2015 www.distribution-technology.com 16 Distribution Technology Ltd