Total Fund Management Parts 5.2 and 5.3: Doing TFM Right

These are Parts 5.2 and 5.3 (continuation of last week's Part 5.1) of a seven part series on integrated Total Fund Management brought to you by Mihail Garchev, the former VP and Head of Total Fund Management at BCI and I.  As discussed last week, this is the nexus of TFM and we decided to break Part 5 down into three parts because it was a lot of material. 

Please take the time to read Mihail's synopsis below on case studies followed by my comments and clips where he delves deeply into today's topic (added emphasis is mine):

This week, we continue our journey into the various practical uses of the Total Fund Management ("TFM") framework and process to solve real-life problems related to total fund decision-making. Before we proceed with the topics today, let us summarize the key takeaways from Episode 5.1.

Key takeaways from the first set of case studies in Episode 5.1 last week

Last week, we looked at the first set of case studies focused specifically on expected returns and their term structure. Expected returns and the term structure are not only the core capability of the integrated TFM but are also central to any total fund decision-making.

As such, before reviewing specific aspects of TFM decision-making, it is instructive to understand better what differentiates the concept of the Term Structure of Expected Returns ("TSER") from the more mainstream textbook definition of expected returns. How is the TSER derived and the informational content's value to further improve decision-making and portfolio outcomes?

In Case Studies 1 through 3, we first demonstrated that the expected returns and the term structure vary significantly through time, compared to the static (hence, the title of the case study referring to the "flat earth" analogy) expected return version typically used for strategic asset allocation. Furthermore, the expected returns of the various maturities within the term structure also vary significantly over time. In other words, the TSER continually changes its shape. It changes its slope, flattens, inverts, changes its curvature and even twists. All this is excellent news because, as in life, change means opportunity in the world of expected returns.

Change alone, however, is not enough to lead to opportunities. As in real life, one needs to have the potential and the knowledge, and timing (and luck, I have to admit), to rise to the opportunities. Similarly, even if expected returns change if there is no informational content (think of it as "knowledge") in these expected returns, that could translate into actionable and profitable portfolio decisions.

There are two keywords in the notion above: "informational content" and "timing." Even if there is informational content in the expected returns about the subsequent realized returns, this might be of little use because everybody might be quickly exploiting the informational content advantage. As such, we further tested the value of the TSER using a realistic portfolio-testing approach. We concluded that the expected returns and the term structure contain informational content. This information content could be further transformed into meaningful excess returns (enough "timing" effect). 

Also, regarding the informational content, the process that generates the expected returns is a unique source of value-added because it is mostly similar to the way global macro hedge funds process information and further develop investment strategies. Another aspect was that combining multiple horizons (effectively, using the term structure) instead of using a single horizon leads to a notable improvement in the outperformance.

In simple words, this means that using the combination of short-, medium- and long-term expected returns to manage the short-term is superior to using just short-term returns. Similar conclusions also support the use of absolute and relative expected returns (what matters is not the absolute number, but which asset class performs better than which). We also concluded that the expected returns term structure is best identifying vulnerable markets and, together with the global macro type of a process, exhibit definitive risk mitigation characteristics, which are very well suited for using dedicated risk mitigation processes.

All the insights from the case study confirmed the central role of the TSER for the ability to manage the short terms to improve long term outcomes. As the avid readers of this series would know, the long-term is a series of short terms in the presence of liabilities. Managing these short terms is an integral part of wealth maximization, a key outcome for pension sustainability. As part of the case studies, we also demonstrated the process of deriving the expected returns. 

Importantly, this is not a "black box," but rather, a "white box" method that uses theory and time tested approaches combined with new alternative data sources. We emphasized the importance of an integrated process to start with, in addition to any advanced techniques that might be used, such as machine learning and artificial intelligence, due to the multiplicative network effect of achieving optimality in multiple connected total fund processes. Such an integrated process, supported by the TSER, is central to the core TFM capability and ultimately leads to achieving the economies of scale over the long term.

The above means that even if one does not have the most advanced approaches yet, instituting an integrated process that leads to multiple optimal decisions for the various parts of the total fund process ultimately translates into improved outcomes. I am tempted here to cite the Law of Transformation of Quantitative into Qualitative Changes. A change in an object's quality occurs when the accumulation of quantitative changes reaches a specific limit, first formulated by Hegel and later creatively used by Marx and Engels.

Episodes 5.2 and 5.3 case studies

Understanding better the expected returns and their value opens up the way to continue the journey and look at various practical uses of the TFM framework for various total portfolio decisions at the investment committee ("IC") or by the chief investment officers ("CIOs"). Many of the case studies in Episodes 5.2 and 5.3 are inspired by actual real-life challenges and experiences and are common topics of interest and long conversations among investment professionals.

Case Study 5—Rebalancing Decisions: The Nexus of Multitude of TFM Decisions

Our first case study today is about rebalancing decisions. Of all total fund activities, rebalancing is probably the one that is linked to most aspects of TFM, such as asset allocation decisions, risk decisions, leverage and liquidity decisions, private versus public asset classes, to name a few.

More importantly, one can view rebalancing as a "mini-TFM" not only because it incorporates typical TFM decisions but also because it requires these decisions to be consistent and coherent with each other. While one could rebalance the portfolio in a heuristic manner, a well-thought rebalancing process prompts the ability to consider short- and medium-term expectations about assets, market environments, cash flows, liquidity, and balance sheet decisions. At the center of all these decisions is the TFM framework and process (see the reference from previous Episode 4 here: Rebalancing and TFM framework).

While many decisions need to made regarding various aspects of rebalancing, in Case Study 5, we focused on the following primary decisions: (i) to rebalance or not; (ii) to increase or decrease liquidity and equitize cash; (iii) how to use the TSER for rebalancing, and (iv) optimal rebalancing trades given the TSER and tracking error ("TE").

To better understand the rebalancing decisions and the role of the TFM framework and core capability (the TSER and the risk matrices; for more discussion, please refer to the previous Episode 5.1 here: Core TFM capability), it is required to understand the critical steps of a rebalancing decision process. To do this, the case study briefly walks the audience through the main types of rebalancing (calendar, fixed-bands, and tracking-error), as well as the rebalancing process and methodology.

Notably, the core TFM capability is at the core of most rebalancing methodology inputs related to cash flow projection, how to rebalance private assets, risk, correlation, and transaction cost inputs, as well the ability to include the short- and medium-term expected returns (the short part of the term structure in the rebalancing decisions), the risk matrices (macro and market conditions) and scenario analysis as illustrated below.

Using the insights from the risk matrices allows for making the critical decision to rebalance or not. Rebalancing is an optimal decision only in specific market conditions when the environment is not either risk-on, or very bullish, or risk-off, or very bearish. In these conditions, it is better to postpone rebalancing. As you recall from the previous Episode 5.1, risk matrices are derived from the assets' expected returns and reflect the agreement across different asset classes, geographies, capital structure, and capitalizations about the prevailing market environment in the short and medium-term.

Risk matrices also inform the critical decision to increase or decrease the overall liquidity following a disciplined market environment-linked process. Effectively, as the market environment deteriorates, one increases the percentage of liquid assets as per a specific schedule, and vice versa, in strong markets, excess liquidity needs to be equitized to maximize the utility of the assets. Finally, if one has any insight into the short- and medium-term expected returns, one will make different rebalancing decisions. In such a case, the rebalancing would yield materially better results than the industry standard practice of ignoring any expected returns when performing fixed-band rebalancing (or the various permutations of it) or tracking-error rebalancing. If you recall from Episode 5.1 and the summary, the expected returns have informational content that could be further transformed into portfolio outperformance.

This is a relatively comprehensive case study, and the discussion above is just a brief outline. The case study's insights are drawn from years of experience and actual implementation of such a process and provide a detailed guidance wealth of examples in the complete video presentation.

Case Study 6— Balance Sheet Decisions: Ensuring optimal adequate resources for current operations and financing future growth

Our next case study is about using the TFM framework and its core capability for various balance sheet decisions such as leverage, liquidity, use of derivatives and contingency. The topic of balance sheet management (unduly) receives fewer headlines than other trendier topics. However, understanding its role and scope is the first step toward realizing that it is a critical requirement for the portfolio's success today and tomorrow, and second, balance sheet decisions are deeply interweaved in the total fund decisions. Importantly, it is not only that such decisions need to be coherent and consistent. Having the TFM framework (itself already coherent and consistent) allows for making many balance sheet decisions. The presentations further shed light on the various decisions related to each of the balance sheet elements (leverage, liquidity, use of derivatives and contingency).

To further illustrate the intersection of TFM and balance sheet management, the case study provides a real-life example where a decision to rebalance Emerging market equities is compared to the desire to enter a total return swap, which pays a risk-free premium for the fund. Should the CIO rebalance or collect the total return swap premium? How to make and account for such a decision? While the question is undoubtedly essential and might have created opposing views at times, it might seem "too practical." Let me assure you that is not. Because precisely through such practical situations, more significant and broader issues resurface.

The first one is the ability to illustrate an example of the "hidden costs" that we discussed at length in Episode 1 and the ability of TFM to bring the economies of scope and second-order efficiencies. You have to watch the presentation but let me give you a snippet of it: in the case study, the fund could have sacrificed 10-15% loss for the client to gain 180 basis points of risk-free alpha.

This "hidden cost" might be an issue on its own and highlight even more significant possible governance and performance evaluation challenges. Because ultimately, TFM is not only an efficient and decision process but also an important governance tool. This governance aspect of TFM is to evaluate decisions and adequately account for these decisions and their consequences, properly communicate internally and with the stakeholders, and have the feedback loop to reevaluate prior strategies and decisions and adjust.

Case Study 7— "Dry Powder" Deployment: A decision that separates exceptional from average

Given the significant market move and dislocations, "dry powder" deployment is often mentioned in various publications. And rightfully so because such decisions could indeed separate exceptional from the average performance. An excellent example of this would be the difference in the performance of the various vintages of private equity funds around significant events and, even better, the timing and performance of strategies and funds related to distressed assets and credit.

That said, "dry powder" deployment decisions would often be ad-hoc by their very nature. As such, having an additional ability to complement the decision by supporting relative expectations about assets and these expectations through time would be beneficial to the process. The TFM core capability, and the expected returns and their term structure provide a direct ability to make such "dry powder" decisions – not only in which asset classes to deploy the capital but also the deployment plan (timing, expected levels, as well as exit conditions if expectations do not materialize). In the case study, we provide a concrete example, an extension of the previous rebalancing and balance sheet case studies, to illustrate the process and how to think of the specific decisions around it.

Case Study 8— Leverage Decisions: Which assets to lever and when?

Leverage decisions are part of the overall balance sheet management and are interrelated to many aspects of TFM – liquidity, rebalancing, risk mitigation, to name a few. Several questions need to be answered: which assets to lever, when to lever, what type of leverage to use, what should be the duration term of this leverage, and pricing. There is also the aspect of where such decisions are made –at the asset class level or the total fund level.

Outside specific leverage uses (e.g. achieving alignment with partners at the asset level, for example, or even higher level asset-liability considerations as in the LDI approach or similar), generally, the market environment in conjunction with what assets are being levered matters for the leverage decisions. Put bluntly, levering risky assets in bad market conditions would magnify losses. Levering bonds or other negatively correlated assets (to the extent these exist) would act as risk mitigation. Leverage also has a term, so it is also essential to consider both near-term and short-to-medium-term expected environments. This points to the conclusion about the value of assessing the alignment of market conditions and horizons we talked about in the previous case studies. Another aspect of the leverage decision is that it is only worth levering (unless there is some other specific reason) when the asset returns are higher than cash. Also, all else being equal, assets with higher relative returns are better to lever. Of course, there could be many reasons, implementation, availability, etc., why other decisions could be made.

It is also vital to ensure that the leverage's economical intent is correctly transformed in the performance measurement and evaluation output from a governance perspective. For example, implementing total portfolio leverage does not end up being accounted for as an asset class leverage, thus creating unintended consequences for the asset class performance while "doing" good for the overall portfolio. Of course, there is also the element of adequately accounting for leverage in the benchmarking and the performance evaluation. This could be a problem in portable alpha and similar strategies where the effect may not be directly observable or embedded in other structures. A proper risk-adjusted evaluation is then required to capture the overall impact without overly-complicating the benchmark process.

Combining the answers to the decisions about the market environment, the considerations about the timing, and the assets then lead to determining how to implement the leverage: whether recourse or non-recourse, asset-level or a total portfolio, and the technology behind it – repos, commercial paper or medium-term notes, or some form of asset-back financing, as well as any aspects related to contingency financing (e.g. credit facilities, and the ability to de-lever in a timely fashion).

Finally, there are also considerations about the organization's credit rating requirements and marketplace participation and reputation.

As you probably already deduced from the discussion above, the TFM framework and core capability provide the necessary toolbox to make direct decisions or support implementation considerations – assessment of short- and medium-term market conditions, absolute and relative expected returns and the returns vs. cash over multiple horizons. In the case study, we use specific examples to consider what assets to lever, what environments to lever, and the timing and, by extension, the implementation considerations.

Case Study 9— Deal Pipeline Management: Important part of the rebalancing process

Given the number of private assets in pension funds' portfolios and the constant flow of transactions, it is surprising how, in many instances, there is no specific deal pipeline management process. This process is often done in isolation, driven by the private asset classes as the deal moves through the various stages until closing.

However, to many, it might be surprising that deal pipeline management is at the intersection of private asset classes, liquidity, rebalancing, and currency decisions. While some decisions might be right in isolation (again, this notion of local optimality), there are resulting impacts that may or may not be optimal to the total portfolio (global optimality). This is yet another potential source to minimize the "hidden costs (the unexpected and undesired, or unmanaged outcomes).

In the case study, we use a fictitious private equity transaction within a broader rebalancing process and demonstrate how critical decisions could be made using the core TFM capability.

Case Study 10— Private Assets and Hedge Funds: What if we focus on RETURNS while still thinking of RISK?

Private assets are always a problem in institutional portfolios because it is difficult to treat them in a unified framework. Many of the discussions about private assets are about how one can measure these assets' risks and aggregate these risks in a total portfolio context. How about we turn the conversation to returns, not risk? How can we use the TFM framework and process to decide the private assets, and by extension, hedge funds?

This is again the topic of the economies of scope. Doing TFM right gives us the ability to manage many other things, including private assets and hedge funds. It is not only about allocation decisions (to invest or not, and when) but also a myriad of other decisions such as leverage, liquidity, rebalancing, "dry powder" deployment, hedging, valuation and performance measurement. In the case study, we demonstrate how one can convert the expected returns and their term structure for private asset classes and various hedge funds categories. Everything we said so far about public asset classes and all the various decisions could now be applied to private asset classes and make decisions for the portfolio's totality, without excluding private asset classes.

If you recall, in Episode 5.1 Case Study 2, we showed an actual implementation of expected returns at different horizons across a multitude of asset classes, sectors, capital structure, capitalizations and factors in real-time. Imagine if one can add to this all the private asset classes and hedge funds, this would be a compelling, integrated, coherent and consistent, TFM framework. Following the case study, we also provide a list of possible applications for allocation and cash flow and liquidity decisions.

Case Study 11— Risk Mitigation: Not for its own sake but as part of the TFM process and decisions

So far in the series, we have been mentioning risk mitigation in different contexts but never explicitly focused on it. We talked about risk mitigation as one way to maximize wealth and the" cruel math" that downside protection matters more than upside growth. We also pointed out that managing adverse outcomes becomes increasingly crucial for pension clients due to the combination of cash outflows and market conditions. We also discussed the management of the path of returns as a form of risk mitigation. As part of the case studies, we demonstrated that the signals behind the expected returns and the term structure are similar to a global macro hedge fund process and can identify vulnerable markets – all of these being risk mitigation characteristics.

The immediate focus of risk mitigation is liquidity and contingency, with questions about rebalancing and "dry powder" waiting in line. However, when the dust settles, it is ultimately all about the possibility of contribution rate increases, one of the critical pension sustainability outcomes.

Is risk mitigation only about the markets, or are there other ways to look at it? As part of the presentation, we put forward the idea of managing risk mitigation and view it as a combination of structural and market sides.

The structural side is related to the embedded risk mitigation properties via the actuarial smoothing and surplus, and we describe in detail the benefits and challenges of these. The market risk mitigation is related to the elements of portfolio construction and related to the ability to de-risk/increase bonds, increase private assets, or use various portfolio construction methodologies (risk parity, targeted volatility, among others), including the path-dependent allocation approach we have been focusing on in the series. In addition to the portfolio construction aspect, there is also the dedicated risk mitigation strategies approach. We specifically use a dynamic (conditional) risk mitigation to illustrate the risk mitigation's impact on the funding ratio and its specific properties.

There are challenges to market risk mitigation as well. Because the bonds are no longer the same hedging asset they once were (low level of yield, correlation, less efficiency in a fiscal policy setting, extreme valuations, low "dry powder," etc.), investors need to rethink the portfolio construction.

A natural inclination would be to increase private assets and alternatives, and these do help, primarily because of the accounting mark-to-market diversification. Still, there is a limit to how many private assets a portfolio can have, and this limit is dictated by liquidity and in relation to the liabilities. Most funds are at the 40% privates mark, so there is a bit more room to expand but not much. As one approaches, the 50% liquidity starts to break (of course, this depends on individual fund circumstances).

So, what is left are two other approaches to complement the hedging properties of bonds?

First, to adopt path-dependent outcome-oriented portfolio management (which is what TFM is; it is meant to avoid adverse outcomes and maximize end wealth (what we care about, not returns). Another way to avoid adverse outcomes and maximize wealth is to have a dedicated and dynamically managed multi-asset asset class called "risk mitigation" and have it as a line in the policy portfolio to complement bonds. This is an outcome-oriented asset class and not an asset-based one.

Most importantly, structural mitigation does not provide dry powder. This is important because if the portfolio dollar size becomes $100 to $80 dollars, even if one does the heroic thing of rebalancing, the weights are right, but the dollars are not. One still has an $80 dollar portfolio. What is needed is something that will give a dry powder to give back the $20 lost. It then self-destructs but fulfills its function.

Based on the discussion so far, we provide a guide for evaluating potential risk mitigation instruments and strategies.

Finally, we conclude the topic with two short case studies showcasing the value of the TFM process and framework as part of designing a global macro capability as part of a broader risk mitigation solution, and an example of how to use the expected returns and the term structure for pricing the value of protection.

Overall Episode 5 Takeaways:

  • The core capability of the TFM process related to the Term Structure of Expected Returns ("TSER") is central to managing and making decisions on most of the Total Fund processes (e.g. asset allocation, efficient portfolio maintenance, as well as inform decisions around the balance sheet, liquidity, and leverage, among others) 
  • Many of these decisions are critically dependent on such a core capability, as decisions, but also as sound risk management, and creating effectiveness and efficiency by economies of scope 
  • The core capability requires a data-driven, structured, disciplined, and transparent process 
  • Such a process further leads to practical informational content in the TSER and the related conclusions about the macro and market environment to enhance the outcomes of the investment process This concludes the complete Episode 5. 

Next Thursday will continue with Episode 6. We will talk about actual real-life implementation and capability – the nexus of organizational structure, methodology and technology. 


I thank Mihail Garchev for writing another great comment.

After reading it, I decided to change the title to "Doing TFM Right" because that's what he provides you, concrete examples and deep insights on how to do total fund management right.

I'm not going to go into a deep analysis of everything Mihail wrote above, mainly because I received a phone call from an old friend late this afternoon and we ended up chatting quite a bit, catching up.

But the other reason why is because Mihail lays it all out very nicely above going over economies of scope and how doing TFM right gives pension fund managers the ability to manage many things, including private assets and hedge funds. 

As he states:

It is not only about allocation decisions (to invest or not, and when) but also a myriad of other decisions such as leverage, liquidity, rebalancing, "dry powder" deployment, hedging, valuation and performance measurement. In the case study, we demonstrate how one can convert the expected returns and their term structure for private asset classes and various hedge funds categories. Everything we said so far about public asset classes and all the various decisions could now be applied to private asset classes and make decisions for the portfolio's totality, without excluding private asset classes.

What else caught my attention. At the end when he discusses risk mitigation and states this:

There are challenges to market risk mitigation as well. Because the bonds are no longer the same hedging asset they once were (low level of yield, correlation, less efficiency in a fiscal policy setting, extreme valuations, low "dry powder," etc.), investors need to rethink the portfolio construction.

A natural inclination would be to increase private assets and alternatives, and these do help, primarily because of the accounting mark-to-market diversification. Still, there is a limit to how many private assets a portfolio can have, and this limit is dictated by liquidity and in relation to the liabilities. Most funds are at the 40% privates mark, so there is a bit more room to expand but not much. As one approaches, the 50% liquidity starts to break (of course, this depends on individual fund circumstances).

With long bond yields at record ultra-low levels, it's more important than ever to understand the benefits of diversifying into private markets, but also understand the limits, respecting liquidity needs/ risks.

Investors are rethinking portfolio construction and realizing diversifying into private markets in a record low bond yield environment isn't enough, you need the right approach, the right partners, the right platform, etc.

Anyway, take the time to watch the episodes below, they're both excellent and we should all thank Mihail for the incredible work he's done putting this important series together.

Below, Episodes 5.2 and 5.3 of the seven episode series "Introduction to Integrated Total Fund Management" presented to you by Mihail Garchev, former VP and Head of Total Fund Management of BCI. Great stuff, please share these comments with your network.