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Integrating Water Risk Analysis Into Portfolio Management

By Monika Freyman, CFA My previous article, ” Liquidity Risks of the H2O Variety ,” explored growing investor awareness about water risks within their portfolios and how that awareness plays into their investment decision making. Here, I will examine some of the increasingly sophisticated approaches that investors can take to integrate water risks into portfolio management. My recent survey of 35 institutional investors’ water integration practices found that while many investors think their methods, tools, and databases need to improve and evolve, they also found it worthwhile to integrate water into their research processes. And no wonder. As population pressures create competition for water, global groundwater supplies are declining and climate variability is increasing – leading to longer droughts and more intense flood events. All these factors pose risks that are hard to ignore. Water risk analysis happens at different stages of investment decision making, from the initial asset allocation strategies, to portfolio level analysis, through to the buy/sell decision. For example, one pension fund brought together portfolio managers from different asset classes to study how different markets, investment instruments, and geographic regions are exposed to the global water crisis. A few investors were also consistently analyzing their portfolio’s water risk exposure or its water footprint. Although far from a perfect approach – often missing location specific data or wastewater production metrics – portfolio water footprinting can be helpful in flagging companies and sectors with high water risk exposure relative to a benchmark and highlighting where further analysis is warranted. Various forms of portfolio analysis and attribution software allow managers to run water use metrics versus an index. For an example of water footprinting, see this South African study . At the individual security level, investors identified three critical research steps to obtain a comprehensive picture of water risk exposure: Understand Corporate Water Dependency: This varies by sector and, of course, company, with some industries relying heavily on access to abundant freshwater suppliers directly or in their supply chain. Corporate water dependency is not always easy to assess, but some companies are making the task easier by reporting their water use and wastewater trend data more consistently on their websites, in their annual reports, SEC filings or to data aggregating organizations, such as CDP Worldwide’s Water Program . Combine Water Dependency Data with an Assessment of Water Security: This gives a more comprehensive picture of corporate water risk exposure. A company may have high water needs but have their operations located in relatively water abundant regions. Another company, however, may be operating in regions of high water competition and drought. Such assessments are not simple to perform, but evolving tools, such as World Resources Institute (WRI)’s Aqueduct corporate water risks map , the World Wildlife Fund (WWF)’s Water Risk Filter , and other efforts are seeking to make the task easier. Get a Sense of Corporate Water Risk Awareness and Response: This step is essential because a company may have high water needs and poor water security, but mitigate the risks very effectively by elevating water issues to strategic decision making and putting water management and reporting systems in place. Tools such as The Ceres Aqua Gauge can be used to assess how well companies are managing their water and their exposure to water risks. For a more comprehensive list of third-party water tools and analytics, An Investor Handbook for Water Risk Integration is a helpful resource. Once water risk analysis is conducted on a corporation or security, our research found that fund managers use this information in a variety of ways, from avoiding high water risk industries or companies, to influencing internally created company environment, social, and governance (ESG) scores, to clarifying corporate engagement priorities. Several managers use their corporate water risk assessments to influence or modify financial projections or their weighted average cost of capital assumptions. For example, one fund manager studying companies in Brazil conducted scenario analysis modeling regarding how much the market cap of companies would be impacted if they had to absorb more of the costs of treating their wastewater discharges, especially as drought intensified and communities and regulators were becoming less tolerant of water use and pollution. Once impacts to market cap were assessed and shared with the management of those companies, engagement on those issues was far more pointed and productive. Other managers were trying to get a deeper understanding of the probability of large financial losses due to strategic risks related to water, such as not being able to grow revenue, access new markets, or develop new facilities. No matter what methodology one chooses to deepen water risk analysis practices, the most critical things to keep in mind are that water risks can lead to unlimited financial impact and loss. If a company loses access to water, a community kicks them out of a region due to water concerns, or permission to discharge wastewater is denied, the financial and strategic implications can be immense. For example, Newmont Mining (NYSE: NEM ) has postponed a $5 billion project in Peru due to community concerns over its water practices. In addition, it is important to look at sector specific issues, as water risks related to mining are obviously very different to those in semi-conductor manufacturing and so on. An Investor Handbook for Water Risk Integration includes a sector-specific cheat sheet on these issues. And most important of all: No matter how incomplete your water risk analysis starts off, it will likely provide a better understanding of sector or company risks (and opportunities) – which ultimately should add predictive power to your existing research processes. The goal is not to be perfect in your methods from the outset, but to begin including water risk analysis into your portfolio management practices. Disclaimer: Please note that the content of this site should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute.

My ‘Preferred’ Preferred Closed-End Funds

Summary Closed-end funds provide a great way to invest in preferred securities. FFC and PDT have beaten the S&P 500 over the past 10 years. The Preferred CEFs outperformed the lower cost ETF iShares US Preferred Stock Fund. Traditional preferred stocks provide a fixed dividend payment and generally do not mature but can be called on or after a specified call date. Some preferred stocks can adjust to floating rates (LIBOR plus a given percentage). It is possible to invest in individual preferred stock or select a fund that invests in preferred stocks. I invest in both individual preferred stocks and closed-end funds that focus on preferred stocks. The CEF approach will be more volatile but can provide diversification and higher income due to the leverage. iShares US Preferred Stock Fund (NYSEARCA: PFF ) provides a lower cost ETF alternative but it has lagged behind its closed-end fund cousins in performance. Over the last 5 years, the S&P 500 has outperformed my preferred closed-end funds, but if you look at the past 10 years, the picture looks quite different. Assuming that the stock prices are a bit toppy, the next 5 years maybe favorable for collecting the nice income from preferred stocks without missing out on a super-hot stock market appreciation. Fund 5 yr Month End average annual return 10 yr Month End average annual return John Hancock Premium Dividend Fund (NYSE: PDT ) 11.86% 10.87% Flaherty and Crumrine Preferred Securities Income Fund (NYSE: FFC ) 13.56% 10.49% SPDR S&P 500 (NYSEARCA: SPY ) 14.29% 7.40% iShares US Preferred Stock 6.49% n/a Below is the investment objective summary for the three preferred stock closed-end funds from Fidelity: John Hancock Premium Dividend Fund: The fund will invest in common stocks of issuers whose senior debt is rated investment grade or, in the case of issuers that have no rated senior debt is considered by the Adviser to be comparable quality. 80% of funds total assets consist of preferred stocks and debt obligations rated A or higher. Leverage ratio 34.1% Flaherty & Crumrine Preferred Securities Income Fund Inc: The fund invests normally at least 80% of its total assets in preferred securities that are mainly hybrid or taxable preferred securities. At least 80% of the preferred securities are investment grade quality. Up to 20% may be invested in securities rated below investment grade. It may also invest up to 20% of its assets in other debt securities and up to 15% in common stocks. Leverage ratio 34.65% First Trust Intermediate Duration Preferred and Income Fund (NYSE: FPF ): Under normal market conditions, the Fund will invest at least 80% of its Managed Assets in a portfolio of preferred and other income-producing securities issued by U.S. and non-U.S. companies, including traditional preferred securities, hybrid preferred securities that have investment and economic characteristics of both preferred securities and debt securities, floating rate and fixed-to-floating rate preferred securities, debt securities, convertible securities and contingent convertible securities. All three funds pay monthly distributions, have a positive NAV return, and a positive UNII Symbol 3 yr return on NAV 12 month return on NAV Distribution (Market) Discount Discount 52 wk average UNII Expense Ratio adjusted PDT 9.81% 3.42% 8.31% -9.95% -10.28% $0.0046 1.44% FFC 8.26% 3.13% 8.06% 8.35% 2.04% $0.0208 0.88% FPF n/a 6.00% 9.19% -9.32% -8.08% $0.1029 1.33% Year to Date, FPF’s NAV performance was quite a bit better than the S&P 500: Symbol YTD Price perf NAV perf PDT 5.25 2.86 FFC 14.21 3.95 FPF 2.41 6.21 SPY 3.02 2.95 Obviously, for long term investors a single year is not that meaningful. The table below shows the 5 yr and 10 yr returns of PDT and FFC compared to the S&P 500 index fund and the ETF preferred PFF. FPF does not have that much historic data available yet. Fund 5 yr Month End average annual return 10 yr Month End average annual return John Hancock Premium Dividend Fund 11.86% 10.87% Flaherty and Crumrine Preferred Securities Income Fund 13.56% 10.49% SPDR S&P 500 14.29% 7.40% iShares US Preferred Stock ( PFF ) 6.49% n/a Risks With Preferred Stock investments: Any investment carries risk and preferred stocks are interest rate sensitive. Preferred stocks are not appropriate if you believe that the rate increases by the Federal Reserve will continue or accelerate. Conclusion: The three preferred closed-end funds shown in this article may be a good addition to a diversified portfolio under the assumption that the interest rates will not rise drastically. They will not outperform the stock market in a bull market scenario but if the market drops or stays range-bound, the consistent income from the closed-end funds can then be channeled into other stock purchases or dividend reinvestments. FPF’s current discount is attractive. When looking at the 3 yr average discount, I would want to buy PDT at or below 13.44 and FFC at or below 18.97. FFC definitely has the best expense ratio of the three.

Reducing Portfolio Risk With Help From Momentum Model

Reduce portfolio risk by activating momentum model. Reduce portfolio risk based on security volatility. Reduce portfolio risk through the use of stop-loss orders. Controlling portfolio risk is every bit as important as seeking portfolio return, particularly when markets are high and volatile. The following analysis takes readers through a process of controlling portfolio risk with help from a tranche momentum spreadsheet. Main Menu: We begin with the following Main Menu where the basic assumptions are laid out by the portfolio manager. In the following example we are using twelve (12) ETFs plus SHY as the cutoff security. Hence the name, Baker’s Dozen. Many of the ETFs carry low correlations with each other, an important factor to consider when identifying securities to populate a momentum oriented portfolio. In the follow screen-shot we set the number of offset portfolios to 8 and the period between offsets to two (2). What this means is that the securities are ranked multiple times (8) on different dates (separated by 2 days) based on two different look-back periods plus volatility. Using these three metrics, the ETFs are ranked each review period. My preference is to review a portfolio every 33 days so the review is rotated throughout the month. Not only are the ETFs ranked based on current data, but they are ranked two, four, six, eight, and etc. days ago so we know what the rankings looked like up to sixteen (8 x 2) days ago. The look-back periods are 60 and 100 trading days. A 20% weight is assigned to the volatility as we are looking for securities with low volatility. Only two securities are selected for each offset portfolio. This becomes more apparent in the second screen-shot so move down to that slide. (click to enlarge) Tranche Recommendations: Here we have what is called the Tranche Momentum model worksheet. This is the first of three risk reducing mechanisms. The tranche model is designed to reduce the “luck-of-trading-day” as this is a problem inherent in all back-tests as well as real portfolio management. Instead of splitting the portfolio into 50% VNQ and 50% MTUM , as the current offset recommends, we note that offset 3 recommended divisions between VNQ and TLT . Offset portfolio #5 recommended 50% allocation to SHY and 50% to VNQ. Using eight (8) portfolio offsets ends up dividing the portfolio into four securities where the percentages are based on the number of times the ETF shows up in one of the eight rankings. The worksheet permits as many as 12 portfolio offsets, but I tend to favor using eight. The following worksheet ranks the ETFs using both absolute and relative momentum principles. Readers will note that the current portfolio holds 200 shares in VTI, but the tranche momentum model recommends none as VTI is under-performing SHY, our “circuit breaker ETF.” Momentum becomes one of our risk reducing mechanisms as under-performing securities are screened out of the active portfolio. (click to enlarge) Risk Reduction Recommendations: The following worksheet combines recommendations from the above tranche data and adds a volatility factor to come up with a list of recommended ETFs. In the following slide the Maximum Trade Position Risk percentage is set to 2.0% so the total portfolio is not exposed to more than a 6% draw-down until the next review period. The still leaves individual ETFs at unacceptable risk levels which we control in the final screen-shot. Before moving to the final slide, look at the individual recommendations. Shares held in VTI and PCY are sold out of the portfolio as VTI is under-performing SHY and PCY has not shown up as a recommended ETF in any of the last 8 offset portfolios. The recommendations are to hold the following four ETFs. 75 shares of SHY – round up from 74. 300 shares of VNQ – rounded to the nearest 100 shares. 100 shares of TLT – rounded to the nearest 100 shares. 350 shares of MTUM – rounded to nearest 50 shares. (click to enlarge) Manual Risk Reduction Recommendations: For the final risk reduction activity the recommendations from the above worksheet are followed which still leaves a few ETF exposed to excess risk. The final step is to place stop-loss or Trailing Stop Loss Orders (TSLOs) on VNQ and MTUM. VTI is either sold at market or a 6% TSLO is used. While the current portfolio holds $8,000 in cash, the recommendation is to increase it to $32,500. Note that the current portfolio carries a risk of 4.8%, but if the suggested adjustments are made, the risk drops to 3.4%. (click to enlarge) With the aid of the tranche momentum spreadsheet we limit portfolio risk through absolute and relative momentum principles as these keep us out of deep bear markets. Further portfolio risk is controlled by placing stop-loss orders as a way of clamping down on excess draw-downs. Granted, these procedures work when we have an orderly market. Guarding against “flash crashes” is an entirely separate problem.