Managing directional risk

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1 This document should not be reproduced in any form without prior written approval. January 21 Risk management within a multi-asset strategy One approach towards multi-asset investing involves blending the active management of directional risk across a range of asset classes with non-directional sources of return. Potential sources of return can be split into broad categories. For example, they could vary between the following categories: Fixed income: alpha and beta Equity: mainly beta Real assets: alpha and beta Total return strategies: mainly alpha Approximately of a portfolio s returns might be derived from asset allocation and the remainder from investment selection, although these proportions could vary over time. When conditions are conducive for beta to perform, one might expect a strategy to run more directional risk and beta would be likely to contribute more than half of portfolio returns. Conversely, when conditions are more challenging (and beta is less attractive), there may be more opportunities for the portfolio to generate returns from alpha. Managing investment risk across such a portfolio requires thinking in multiple dimensions: At a portfolio level to ensure appropriate levels of diversification. At an asset class level, specifically, being mindful of drawdown risk when running directional exposure. At an individual position or strategy level to ensure that risk is not overly concentrated and that downside in the event of extreme moves is within tolerance levels. When managing directional risk, some form of downside protection is sensible for assets with material downside potential. When it comes to managing individual positions and strategies, and also overall portfolio risk, incorporating strategies that involve non-directional sources of return can help deliver a better distribution of returns. Managing directional risk The most volatile elements within a multi-asset portfolio dominate the portfolio s risk/return characteristics. It is reasonable to anticipate that asset class exposures are likely to be an important contributor to aggregate portfolio risk, and the most volatile assets (equities and commodities) are likely to be at the top of that list. Biases towards these asset classes can be driven by a fundamental understanding of how they are influenced by macroeconomic factors, such as monetary policy, fiscal policy, growth and inflation. Looking at a range of valuation indicators in the context of an assessment of the macroeconomic environment, alongside proprietary indicators of market positioning, is one way of forming a view on their likely performance. But how much exposure is finally incorporated into a portfolio should also be guided by risk considerations. A specific asset class approach could be deployed to limit downside. This can be illustrated with regard to equity exposure. As Chart 1 shows, equity returns can be attractive but the left hand tail (the risk of an extreme negative outcome) is large. The same is true of a number of other risk assets. Chart 1: distribution of returns: watch the left hand tail of time occured since <-3-3 to -2-2 to -2-2 to -1-1 to -1-1 to - - to to to 1 1 to 1 1 to 2 2 to 2 2 to 2 >3 Source: Insight as of December 31, 214. For illustrative purposes only. This is not intended to be taken as investment advice.

2 Improving the distribution of those returns, reducing the fat tail at the left is obviously attractive. There are many ways of providing downside protection. One simple approach, shown in Chart 2, is to use a put protection strategy with the aim of limiting downside beyond a predetermined level. Chart 3 illustrates the potential impact of employing this strategy. It can be effective, but can come with a cost in terms of return generation. More dynamic approaches to downside protection can improve meaningfully on simple put protection. One example is synthetic option replication, a variant discussed here that helps to increase the probability of a portfolio achieving an outcome and seeks to reduce the probability of significant drawdowns, even in deep bear markets. The principles which guide the process are: Scale initial investment in individual positions in accordance with conviction and tolerance for downside performance (by reference to historic and expected volatility). Dynamically manage the position size in accordance with changes in conviction and the performance of the investment. If the investment loses money, then the dynamic asset allocation framework will guide towards reducing the exposure, looking to contain the risk of further downside. If the position makes money, the portfolio manager may have the scope to increase the position size because it has moved further away from the tolerated loss level set when the position was initiated. Isolating the risk management process within this approach, the charts below show how this may improve on the more simplistic option-based strategy. Chart 4 illustrates the principle behind this approach to dynamic risk management. Chart shows that the resulting distribution could offer better downside protection and greater upside participation than the previous example. Chart 2: Simple put protection P&L at expiry () OTM put option Put protection benefit Put protection cost Change in underlying equity index () Chart 3: Simple put protection: possible benefits versus costs of time occured since <-3-3 to -2-2 to -2-2 to -1-1 to -1-1 to - - to to to 1 1 to 1 1 to 2 2 to 2 2 to 2 >3 12-month return + put option 1 OTM Chart 4: Dynamic approach to risk budgeting for cyclical assets Probability density function 4 P&L falls, risk 4 tolerance decreases P&L rises, risk 2 tolerance increases Return () Period 1 (cumulative return= ) Period 2 (cumulative return= 2.) Period 3 (cumulative return= -2.) Chart : Dynamic risk management versus simple put protection <-3-3 to -2-2 to -2-2 to -1-1 to -1-1 to - - to to to 1 1 to 1 1 to 2 2 to 2 2 to 2 >3 + put option 1 OTM Dynamic risk management of equity exposure (DRM) Source: Insight as of December 31, 214.

3 Managing individual positions and strategies This dynamic approach to risk management can work for some investible assets, but not all. There are asset classes without a fat left hand tail or ones which exhibit mean reverting characteristics. Alternative approaches to risk management are more appropriate for assets that fall within these categories and also for strategies that are designed to generate returns through alpha and have a limited requirement for beta management. One example is relative value positions that aim to capture the difference between two similar assets, where a long position is held in the investment believed to offer a better relative return and an offsetting short position in the one which is expected to underperform. The volatility (historic and expected) of the relative position must be taken into consideration when identifying the potential profit target, as well as the acceptable tolerance for loss. This approach aims to ensure the monitoring of position performance against pre-determined expectations. The simplicity and rigour of this approach applies once a profit target has been reached if the fundamental rationale remains valid, one could continue running positions while also locking in profits and re-setting higher stop-review levels to account for this, as can be seen in Charts 6 and 7 below. Other strategies require alternative approaches to risk management, for example, derivative strategies where economic exposures can move in a non-linear fashion. By combining put and call options, an investor can seek to be precise about the trading ranges viewed as likely across a variety of asset classes (see, for example, Charts 8 and 9). Different strategies can also isolate the particular characteristics viewed as desirable: directional views, volatility, carry, time value decay and skew can all be expressed using combinations of strikes and expiries. When structuring an options trade, the position can be sized for a profit target, while also setting a stop-review level that reflects an acceptable level of downside risk. Chart 6: US 3 year vs year treasuries Chart 7: Euro vs US dollar Jun 13 Sep 13 US 3 year vs year Price target Dec 13 Mar 14 Jun 14 Breakeven Stop Loss review Sep 14 Dec Jun 13 Sep 13 Euro vs US dollar Price target Dec 13 Mar 14 Jun 14 Breakeven Stop Loss review Sep 14 Dec 14 Chart 8 : Option strategy put spread collar: benefiting from a market fall.1.1 P&L (). Current. -. Initial Index level P&L at expiration Linear P&L Chart 9 : Option strategy call spread collar: capturing a market rise with an element of downside protection P&L at expiration ().4 Current.2. Initial Index level P&L at expiration Linear P&L Source: Insight as of December 31, 214.

4 Managing overall portfolio risk Multi-asset portfolios aim to deliver returns by investing across a range of asset classes and strategies. This enables them to generate returns in different market conditions. Some investments may work better (or, indeed, worse) in different environments; a strategy that has a broad mandate and the flexibility to take advantage of such opportunities can enhance its return potential. A multi-asset opportunity set can also be used to diversify risk. When managing a multi-asset portfolio, it is crucial to understand the potential risks that are embedded within that portfolio and to seek to ensure that it is sufficiently diversified. This sometimes involves thinking beyond historic statistical relationships: inter-relationships and correlations can change over time. It is important to have not only an accurate picture of overall portfolio risk (measured by volatility, value-at-risk (VaR) and other appropriate risk metrics), but also to appreciate the decomposition of risk among portfolio positions. If risk were inappropriately skewed, portfolio adjustments would need to be made to secure more balanced risk distribution. This could then ensure that the portfolio had sufficient diversification from a fundamental perspective. In Chart 1, the potential benefits of diversification are illustrated by showing the contribution to risk of the various strategies deployed within a diversified multi-asset portfolio and then comparing the aggregation of these individual positions with the realised volatility of the overall portfolio. The difference between the two gives a sense of the possible benefits that can be derived from a diversified multi-asset approach to return generation. This kind of multi-faceted approach to risk management seeks to provide confidence that a broad opportunity set can be used with the aim of further improving the distribution of portfolio returns. Chart 11 shows the return profile of a 1 equity portfolio adjusted to incorporate the dynamic risk management strategy described above. The distribution achieved by an actively managed multi-asset portfolio is then overlaid on this return profile. Chart 12 illustrates the same distribution, but compared with global equities. It shows precisely how combining a wider opportunity set (including non-directional strategies), with an active asset allocation overlay may improve on the distribution of returns. Chart 1: Illustrative profile of a diversified multi-asset strategy Emerging market equity European equity US equity UK equity Japanese equity Asian equity Government bonds Investment grade Emerging market bonds High yield Infrastructure Real estate Commodities Dividends Absolute return funds Relative value Range bound strategies Breakout strategies Diversification benefits Portfolio volatility Equity market strategies Fixed income strategies Real assests Total return strategies Result Chart 11: Building a better distribution of returns Chart 12: The desired outcome: a better distribution of returns of time occured since <-3-3 to -2-2 to -2-2 to -1-1 to -1-1 to - - to to to 1 1 to 1 1 to 2 2 to 2 2 to 2 >3 Dynamic risk management of equity exposure (DRM) DRM with active asset allocation and alpha strategies of time occured since <-3-3 to -2-2 to -2-2 to -1-1 to -1-1 to - - to to to 1 1 to 1 1 to 2 2 to 2 2 to 2 >3 DRM with active asset allocation and alpha strategies Source: Insight as of December 31, 214.

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