Standard V(A) Diligence and Reasonable Basis

Diligence requires careful, consistent, and thorough work or effort. To have a reasonable basis for making a decision or taking action requires using sound judgment, understanding, care, and caution appropriate under the circumstances when undertaking an investment action or making a decision; it involves following a rational and well-considered process that is designed to remedy or address an issue or affect an outcome.

The application of Standard V(A) depends on the investment philosophy the member, candidate, or his or her firm is following, the role of the member or candidate in the investment decision-making process, and the support and resources provided by the member’s or candidate’s employer. These factors will dictate the nature of the diligence and thoroughness of the research and the level of investigation required by Standard V(A).

Members and candidates must make reasonable efforts to consider and address all pertinent issues when arriving at a recommendation.

Clients turn to members and candidates for advice and expect advisers to have more information and knowledge than the clients themselves do. This information and knowledge form the basis from which members and candidates apply their professional judgment in taking investment actions and making recommendations.

At a basic level, clients want assurance that members and candidates are putting forth the necessary effort to support the recommendations they are making. Members and candidates enhance transparency by providing supporting information to clients when making a recommendation or taking action. Communicating the level and thoroughness of the information reviewed before the member or candidate makes a judgment allows clients to understand the reasonableness of the recommended investment actions.

As with determining the suitability of an investment for the client, the necessary level of research and analysis will differ with the product, security, or service being offered. In providing an investment service, members and candidates typically use a variety of resources, including company reports, third-party research, and results from quantitative models. Members and candidates form a reasonable basis for investment recommendations and actions through consideration of a balance of these resources.

The following list includes selected examples of attributes members and candidates may consider when forming the basis for an investment recommendation:

• Global, regional, and country macroeconomic conditions
• A company’s operating and financial history
• The industry’s and sector’s current conditions and the stage of the business cycle
• A pooled fund’s fee structure and management history
• The output and potential limitations of quantitative models
• The quality of the assets included in a securitization
• The appropriateness of selected peer-group comparisons

Even though an investment recommendation may be well informed, downside risk remains for any investment. Every investment decision is based on a set of facts known and understood at the time. Members and candidates can base their decisions only on the information available at the time decisions are made. The steps taken in developing a diligent and reasonable recommendation will help minimize unexpected negative outcomes.

Members and candidates should make reasonable inquiries into the sources and accuracy of all data used in conducting their investment analysis and forming their recommendations. The sources of the information and data will influence the level of the review a member or candidate must undertake. Information and data taken from certain sources, such as blogs, independent research aggregation websites, or social media, may require a greater level of review than information from more established research organizations.

If members and candidates rely on secondary or third-party research, they must make reasonable and diligent efforts to determine that such research is sound. Secondary research is research conducted by someone else in the member’s or candidate’s firm. Third-party research is research conducted by entities outside the member’s or candidate’s firm, such as a brokerage firm, bank, or research firm. If a member or candidate has reason to suspect that either secondary or third-party research or information comes from a source that may be biased, unreliable, or otherwise deficient, the member or candidate must not rely on that information.

Criteria that a member or candidate may use in forming an opinion on whether research is sound include but are not limited to,

• assumptions used,
• rigor of the analysis performed,
• date/timeliness of the research, and
• evaluation of the objectivity and independence of the recommendations.

Members and candidates may rely on others in their firm to determine whether secondary or third-party research is sound and use the information in good faith unless they have reason to question its validity or the processes and procedures used by those responsible for the research. For example, portfolio managers may not have a choice of which data source to use, because the firm’s senior managers conducted due diligence to determine which vendor would provide information or research services. A member or candidate in this position can use the information in good faith assuming the due diligence process was deemed adequate.

Standard V(A) applies to quantitatively oriented research models and processes, such as backtesting investment strategies; computer-generated modeling, screening, and ranking of investment securities; the creation or valuation of derivative instruments; and quantitative portfolio construction techniques. Members and candidates must understand the parameters used in models and quantitative research that are incorporated into their investment recommendations. Although they are not required to become experts in every technical aspect of the models, they must understand the assumptions and limitations inherent in any model and how the results are used in the decision-making process.

Members and candidates must make reasonable efforts to test the output of investment models and other preprogrammed analytical tools they use. Such validation must occur before incorporating the process into their methods, models, or analyses.

Individuals who create new quantitative models and services must exhibit a higher level of diligence in reviewing new products than that of the individuals who ultimately use the analytical output. Members and candidates involved in the development and oversight of quantitatively oriented models, methods, and algorithms must understand the technical aspects of the products. A thorough testing of the model and resulting analysis must be completed prior to product distribution.

Although not every model tests for every factor or outcome, members and candidates must ensure that their analyses incorporate a broad range of assumptions sufficient to capture the underlying characteristics of investments. Analysis that fails to consider potentially negative outcomes or levels of risk outside the norm may not accurately measure the true economic value of an investment. In reviewing computer models or the resulting output, members and candidates must include factors and assumptions that are likely to have a substantial influence on an investment’s value to ensure that the model incorporates a wide range of possible input expectations, including negative market events.

Members and candidates must also consider the source and time horizon of the data used as inputs in financial models. The information from databases may not effectively incorporate both positive and negative market cycles. In the development of a recommendation, the member or candidate may need to test the models by using volatility and performance expectations that represent scenarios outside the observable databases.

The use of specialized managers to invest in specific asset classes or diversification strategies that complement a firm’s in-house expertise is common. Standard V(A) applies to the level of review necessary in selecting an external adviser or subadviser to manage a specifically mandated allocation. Members and candidates must review such advisers as diligently as they review individual investment opportunities.

Members and candidates who are directly involved with the use of external advisers and subadvisers should develop and use consistent, objective criteria for selecting and evaluating these advisers. Such criteria include but are not limited to,

• reviewing the adviser’s established code of ethics,
• understanding the adviser’s compliance and internal control procedures,
• assessing the quality of the published return information, and
• reviewing the adviser’s investment process and adherence to its stated strategy.

One factor in evaluating external advisers or subadvisers is whether they adhere to recognized industry standards to guide their work. Codes, standards, and guides on best practice published by CFA Institute establish practices for advisers and may be used by members and candidates as criteria for selecting external advisers or subadvisers. The following guides are available at the CFA Institute Research and Policy Center website: the CFA Institute Asset Manager Code™, the Global Investment Performance Standards (GIPS^®), and the Model Request for Proposal (for equity, credit, or real estate managers).

Often, members and candidates are part of a group or team that is collectively responsible for producing investment analysis or research. The conclusions or recommendations of a group report represent the consensus of the group but not necessarily the views of a member or candidate, even though the name of the member or candidate is included on the report. In some instances, a member or candidate will not agree with the view of the group. If, however, the member or candidate believes that the consensus opinion has a reasonable and adequate basis and is independent and objective, the member or candidate does not need to dissociate from the report even if it does not reflect his or her opinion.

Members and candidates should encourage their firms to consider the following policies and procedures to support the conduct required under Standard V(A):

• Establish policies requiring that research reports, credit ratings, and investment recommendations have a basis that can be substantiated as reasonable and adequate.
• Develop detailed, written guidance that establishes the due diligence procedures for judging whether a particular recommendation has a reasonable and adequate basis.
• Develop measurable criteria for assessing the quality of research, the reasonableness and adequacy of the basis for any recommendation or rating, and the accuracy of recommendations over time.
• Develop detailed, written guidance that establishes minimum levels of scenario testing of all computer-based models used in developing, rating, and evaluating financial instruments. The policy should contain criteria related to the breadth of the scenarios tested, the accuracy of the output over time, and the analysis of cash flow sensitivity to inputs.
• Develop measurable criteria for assessing outside providers, including the quality of information being provided, the reasonableness and adequacy of the provider’s information collection practices, and the accuracy of the information over time. The established policy should outline how often the provider’s products are reviewed.
• Adopt a consistent, objective set of criteria for evaluating the adequacy of external advisers and subadvisers. The policy should include how often and on what basis the allocation of funds to the external adviser or subadviser will be reviewed.

Hawke manages the corporate finance department of Sarkozi Securities, Ltd. The firm is anticipating that the government will soon close a tax loophole that currently allows oil-and-gas exploration companies to pass on drilling expenses to holders of a certain class of shares. Because market demand for this tax-advantaged class of stock is currently high, Sarkozi convinces several companies to undertake new equity financings at once, before the loophole closes. Time is of the essence, but Sarkozi lacks sufficient resources to conduct adequate research on all the prospective issuing companies. Hawke decides to estimate the IPO prices based on the relative size of each company and to justify the pricing later when her staff has time.

Chandler is an investment consultant in the London office of Dalton Securities, a major global investment consultant firm. One of her UK pension funds has decided to appoint a specialist US equity manager. Dalton’s global manager of research relies on local consultants to review and assess managers in their regions and, after conducting thorough due diligence, puts their views and ratings in Dalton’s manager database. Chandler accesses Dalton’s global manager research database and conducts a screen of all US equity managers on the basis of a match with the client’s desired philosophy/style, performance, and tracking-error targets. She selects the five managers that meet these criteria and puts them in a briefing report that is delivered to the client. Between the time of her database search and the delivery of the report to the client, Chandler discovers that one of the firms that she recommended for consideration lost its chief investment officer, the head of its US equity research, and the majority of its portfolio managers on the US equity product—all of whom have left to establish their own firm. Chandler does not revise her report with this updated information.

Mastakis is a junior analyst who has been asked by her firm to write a research report predicting the expected interest rate for residential mortgages over the next six months. Mastakis submits her report to the fixed-income investment committee of her firm for review, as required by the firm’s procedures. Although some committee members support Mastakis’s conclusion, the majority of the committee disagrees with her conclusion, and the report is significantly changed to indicate that interest rates are likely to increase more than originally predicted by Mastakis. Mastakis asks that her name be taken off the report when it is disseminated.

McDermott runs a two-person investment management firm. McDermott’s firm subscribes to a service from a large investment research firm that provides research reports. McDermott’s firm makes investment recommendations based on these reports.

Ostrowski’s business has grown significantly over the past few years, and some clients want to diversify internationally. Ostrowski decides to find a subadviser to handle international investments. Because this will be his first subadviser, Ostrowski uses the CFA Institute Model Request for Proposal to design a questionnaire for his search. By his deadline, he receives seven completed questionnaires from a variety of domestic and international firms trying to gain his business. Ostrowski reviews all the applications but feels unqualified in choosing the best firm. He decides to select the firm that charges the lowest fees because doing so will have the least impact on his firm’s bottom line.

Thompson provides research for the portfolio manager of the fixed-income department at his firm. The manager asks Thompson to conduct sensitivity analysis on securitized subprime mortgages. He has discussed with the manager possible scenarios to use to calculate expected returns. A key assumption in such calculations is housing price appreciation (HPA) because it drives “prepays” (prepayments of mortgages) and potential losses. Thompson is concerned with the significant appreciation experienced over the previous five years as a result of the increased availability of funds from subprime mortgages. To project a worst-case scenario, Thompson insists that the analysis should include a scenario run with an assumed HPA of –10% for Year 1, –5% for Year 2, and 0% for Years 3 through 5. The manager replies that these assumptions are too dire because there has never been a time in their available database when HPA was negative. Thompson conducts research to better understand the risks inherent in these securities and evaluates these securities in the worst-case scenario, an unlikely but possible environment. Based on the results of these scenarios, Thompson does not recommend the purchase of the investment.

Liakos works in sales for Hellenica Securities, a firm specializing in developing intricate derivative strategies to profit from particular views on market expectations. One of her clients is Carapalis, who is convinced that commodity prices will become more volatile over the coming months. Carapalis asks Liakos to quickly engineer a strategy that will benefit from this expectation. Liakos turns to Hellenica’s modeling group to fulfill this request. Because of the tight deadline, the modeling group outsources parts of the work to several trusted third parties. Liakos implements the disparate components of the strategy as the firms complete them. Within a month, Carapalis is proven correct: Volatility across a range of commodities increases sharply. But her derivatives position with Hellenica suffers huge losses, and the losses increase daily. Liakos investigates and realizes that although each of the various components of the strategy had been validated, they had never been evaluated as an integrated whole. In extreme conditions, portions of the model worked at cross-purposes with other portions, causing the overall strategy to fail dramatically.

Newbury is an investment adviser to high-net-worth clients. A client with an aggressive risk profile in his investment policy statement asks about investing in the Top Shelf hedge fund. This fund has reported 20% returns for the first three years. The fund prospectus states that its strategy involves long and short positions in the energy sector and extensive leverage. Based on his analysis of the fund’s track record, the principals involved in managing the fund, the fees charged, and the fund’s risk profile, Newbury recommends the fund to the client and secures a position in it. Six months later, the fund announces that it has suffered a loss of 60% of its value and is suspending operations and redemptions until after a regulatory review.

Cannon is the lead quantitative analyst at CityCenter Hedge Fund. He is responsible for the development, maintenance, and enhancement of the proprietary models the fund uses to manage its investors’ assets. Cannon reads several high-level mathematical publications and blogs to stay informed of current developments. One blog, run by “Expert CFA,” presents some intriguing research that may benefit one of CityCenter’s current models. Cannon is under pressure from the firm’s executives to improve the model’s predictive abilities, and he incorporates the factors discussed in the online research. The updated output recommends several new investments to the fund’s portfolio managers.

Stefansson is a performance analyst at Artic Global Advisers, a firm that manages global equity mandates for institutional clients. Her supervisor asks her to review five new performance attribution systems and recommend one that would best explain the firm’s investment strategy to clients. On the list is a system she recalls learning about when visiting an exhibitor booth at a recent conference. The system is highly quantitative and opaque in how it calculates the attribution values. Stefansson recommends this option without researching the others on the basis of the impressive discussion she had at the exhibitor booth with company representatives.

Jackson works for Armaniams Partners, Inc., and is assigned to select a hedge fund subadviser to improve the diversification of the firm’s large fund-of-funds product. The allocation must be in place before the start of the next quarter. Jackson uses a consultant database to find a list of suitable firms that claim compliance with the GIPS standards. He calls more than 20 firms on the list to confirm their potential interest and to determine their most recent quarterly and annual total returns. Because of the short turnaround, Jackson recommends the firm with the greatest total returns for selection.

Dupont works for the credit research group of XYZ Asset Management, where he is in charge of developing and updating credit risk models. In order to perform accurately, his models need to be regularly updated with the latest market data. Dupont does not interact with or manage money for any of the firm’s clients. He is in contact with the firm’s US corporate bond fund manager, Reichardt, who has only very superficial knowledge of the model.

Dupont’s recently assigned objective is to develop a new emerging market corporate credit risk model. The firm is planning to expand into emerging credit, and the development of such a model is a critical step in this process. Because Reichardt seems to follow the model’s recommendations without much concern for its quality as he develops his clients’ investment strategies, Dupont decides to focus his time on the development of the new emerging market model and neglects to update the US model.

After several months without regular updates, Dupont’s diagnostic statistics start to show alarming signs with respect to the quality of the US credit model. Instead of conducting a long and complicated data update, Dupont introduces new codes into his model with some limited new data as a quick “fix.” He thinks this change will address the issue without needing to complete the full data update.

Several months later, another set of diagnostic statistics reveals nonsensical results, and Dupont realizes that his earlier change contained an error. He quickly corrects the error and alerts Reichardt, who has made trades based on the erroneous model’s results.