MPI Research Corner http://markovprocesses.com/blog Innovative research articles, news and opinions Mon, 24 Mar 2014 02:31:41 +0000 en-US hourly 1 http://wordpress.org/?v=3.8.3 The Taper at the Beach: Pimco, the Fed and a Quantitative Approach to the World’s Largest Bond Fund http://markovprocesses.com/blog/2014/03/pimco_quant_approach/?utm_source=rss&utm_medium=rss&utm_campaign=pimco_quant_approach http://markovprocesses.com/blog/2014/03/pimco_quant_approach/#comments Sat, 22 Mar 2014 16:05:16 +0000 http://markovprocesses.com/blog/?p=2748

In the WSJ’s February 24th exposé of the turmoil at the helm of Pimco, we saw a curious bit about tension at “the Beach” increasing in the summer of 2013. During this period, according to the Journal, conflict between then co-CIOs Bill Gross and Mohamed E-Erian became apparent to staff, and Gross restricted trading at the firm.

We wanted to see what insights a quantitative analysis of Pimco Total Return Fund (PTTRX) could offer about the summer and Total Return’s recent performance, a topic of increasing scrutiny amongst the investment community.

To conduct our analysis on Pimco Total Return, MPI analysts ran the fund’s daily net asset values (NAVs) through our proprietary quantitative model to identify the set of factor exposures that best mimic the fund’s return with the highest predictability[1]. The factors used in this analysis were selected based on their ability to produce the most predictive results. For a fund with over ten thousand positions, this returns-based approach is categorically different than a holdings-based assessment of such a massive portfolio. Our quantitative method is top-down, allowing an investor (armed with sophisticated tools and methods) to see how the fund behaves as a whole on a daily basis, rather than by painstakingly constructing the exact replica portfolio as reported with a lag, a task that few, if any, investors would have resources for if it is possible at all.

PIMCO
Our analysis indicates that the fund’s returns behaved as though it was short cash and long bonds in 2013, and that the short cash exposure increased during May, peaking in June. Negative cash exposure in the model often represents implicit leverage, which could be the result of either using derivatives or more risky securities than the ones chosen for this analysis. The model also shows the fund to have long bond exposure, around 130%. In a historical context, however, this should not be a surprise, either to those looking at public statements and reported holdings or using returns-based models. Indeed, PTTRX has behaved as if it were levered at greater levels in recent years.

The portfolio’s exposure had negative consequences on performance in the summer of 2013, and beyond (more later, and in below charts). On May 22nd, in testimony to Congress, then Fed Chairman Bernanke suggested the central bank could begin to taper purchases of mortgage securities and U.S. Treasuries in coming months under its Quantitative Easing program. Through the summer months following this announcement, volatility and a market sell-off in many fixed income classes resulted in increased yields, and, conversely, decreased prices. Long factor exposures that the analysis detects, including TIPS and mortgages, suffered during this period. The fund behaves as if it curtails the short cash/leveraged bonds position by the end of September.

When looking at performance attribution from the beginning of May 2013 through March 14th 2014, mortgages as an asset class recovered, more or less, but not TIPS. TIPS appear to be the factor that had the biggest drag on performance, though the model shows the exposure level to remain largely unchanged through the period. Additionally, while high yield bonds have performed comparatively well, the portfolio behaves as if exposure to this asset class was pared, thus limiting Total Return’s upside. While the short cash/interest rate risk exposure looks to be reined in after the June peak (a month when the WSJ reported $9.6B in outflows from Total Return), the portfolio’s composition to date has not turned out to be optimally positioned for performance improvement. (see charts below)

IndexPerformancePimcoattribCumulativeattTo put this in perspective over this short term, Gross’ Southern California neighbor Jeffrey Gundlach’s DoubleLine Total Return Bond Fund behaves like it had significant exposure to cash going into the turmoil following the first “taper talk”. While the model shows their mortgage strategy to be more elaborate than what we see with PTTRX, with a number of asset classes picked up, including PO/Inverse Floaters and CMOs, their cash exposure trends down and perceived exposures to mortgages and distressed debt increase through the back half of the year. Performance-wise, this turned out to be to their advantage; they’re up 1.9% over the past 12 months through March 14th. PTTRX remains down .20% over the period, lagging behind it’s intermediate term index, Barclays U.S. Aggregate Bond Index, up .56%, and its average peer in the intermediate term bond fund category, up .72%, according to Morningstar and as reported by the WSJ’s Daisy Maxey.DoublelinePerformance

This analysis is performed in hindsight over a short time horizon that has been under a magnifying glass. While leverage in such a large fund, and whatever its origin, could be reason for some concern (and a challenge for the industry to address), it was not a significant loss and should not detract from the manager’s longer term track record, which is one of the best in the industry.

For investors keen to take greater oversight of their fixed income portfolios, however, especially in light of Fed action and resultant market impact, this instance can serve as a call to action to institute quantitative monitoring on a regular basis to better understand their manager’s thinking, short term bets and potential risks incurred in a portfolio. We have seen an uptick in interest from clients looking to conduct reviews and analysis of fixed income portfolios, particularly alternative bond funds, and we look forward to continuing the discussion here.

 


[1]DISCLAIMER: MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.

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Challenges in Analyzing PIMCO Total Return and Other Liquid Alternatives http://markovprocesses.com/blog/2014/02/challenges-in-analyzing-pimco-total-return-and-other-liquid-alternatives/?utm_source=rss&utm_medium=rss&utm_campaign=challenges-in-analyzing-pimco-total-return-and-other-liquid-alternatives http://markovprocesses.com/blog/2014/02/challenges-in-analyzing-pimco-total-return-and-other-liquid-alternatives/#comments Wed, 05 Feb 2014 20:20:56 +0000 http://markovprocesses.com/blog/?p=2719

Is a given hedge fund manager generating alpha?  Can that alpha be captured through more liquid alternative vehicles?  How can an investor truly reveal a portfolio’s net factor exposures when traditional assets are often being intermingled with credit default swaps, options, futures and leverage?  These questions continue to stymie investors – even though answers may be available right under their noses.  MPI’s patented “Dynamic Style Analysis” (DSA) model has revolutionized the foundations first laid by Nobel laureate Bill Sharpe, moving beyond his groundbreaking returns-based style analysis (RBSA) to reveal exposures in complex funds that are not well explained by traditional RBSA.  Just as RBSA was created to fill in the gaps that result from holdings-based analysis, DSA now serves to provide additional transparency beyond RBSA in a world of increasingly complex investment vehicles.

Extracting exposures in liquid alternatives may seem complex, but our clients have used MPI’s DSA technology for the past decade to provide transparency and risk analysis while meeting compliance standards and staying true to their investment policies.

These clients know that complex problems require powerful tools, and together we have worked to address the issues that will come to an investor’s door time and time again.  Using DSA technology, investors gain transparency despite the presence of derivatives and other fund positions providing only point-in-time or lagged  information; navigate investment flexibility where multi-manager offerings create unintended netting and style overlap; remain in compliance with investment policies while seeking to increase allocation to products that do not offer position-level transparency; and design and rebalance portfolios to achieve optimal blends of assets that run the full spectrum of liquidity.

DSA moves beyond the ability to provide net exposures created by portfolios that combine traditional and complex alternative assets.  The results of DSA analysis may be used in forward-looking simulations and assessing how funds may behave in different market scenarios. Likewise, DSA may reveal how a manager reacted to previous market events.  Lastly, DSA can even provide transparency on funds with very short performance histories.

The Case of PIMCO Total Return

To demonstrate the benefits of our model with liquid alternatives, we analyzed the PIMCO Total Return fund using a set of broad Merrill Lynch fixed income indices (Exhibit 1). In this chart, you can see the resulting exposures at any point in time by looking at each vertical slice, while the short cash position shows the fund’s implied leverage.  We were able to deduce that these factors accurately mimic the portfolio’s returns over the selected time horizon (Exhibit 2).  This is shown below with the green line representing PIMCO TR and the yellow line representing the return of the style portfolio of exposures shown on the graph in Exhibit 1.   Also shown in Exhibit 2 is the R2 of 96.82 and our proprietary Predicted R2 validation statistic which was 95.12 – indicating a very good fit.

Exhibit 1

Exibit 1a - Asset Loadings

Exhibit 2

Exibit 2a - Cum PerformanceExibit 2a - R2

 

Out of Sample Test

Our next test was to test the predictive ability of our factor exposures by running an out-of-sample test.  To do this, we took the factor exposures from the end of March 2013 and using a simple buy-and-hold strategy attempted to project the fund’s return (Exhibit 3).  Our model was able to predict a good portion of the magnitude and direction of the funds movement during this volatile period of “Taper Talk” and shows how our factor exposures can be used for risk management

Exhibit 3

Exibit 3a - Returns vs Buy Hold

Common Style

A report at the beginning of the year in Bloomberg revealed that most PIMCO funds invest based on a uniform firm outlook on everything from the global economy to interest rates, but can be altered following economic data releases or new statements from the Federal Reserve.  Our proprietary “Common Style” analysis below, which provides the degree of overlap in returns-based exposures between multiple investment vehicles, confirms these common bets.  This type of analysis across fixed income managers, whether from a single fund family or from multiple providers, provides investors with essential information on diversification within a portfolio or lineup (Exhibit 4).

Exhibit 4

Exibit 5 - Common Style Matrix

Conclusion:

As investors are increasingly eyeing liquid alternatives, they need to use the same techniques that sophisticated investors use to analyze hedge funds.  MPI’s Dynamic Style Analysis can effectively provide them with answers to their questions.  Investors can better assess the way in which managers created their net exposures, receive adequate transparency into these vehicles, employ sound risk management procedures, ensure compliance with  investment guidelines and finally, achieve optimal portfolio rebalancing from both an asset class and liquidity perspective.

Furthermore, investors also need to look at a firm’s macro views when allocating within a fund family or constructing portfolios from multiple management companies to further avoid potential risks.  In testing our approach on PIMCO, it became evident that a number of their funds had common exposures, including highly similar ones to the same fixed-income factors.  Specifically, the highest overlaps were between PIMCO All Asset All Authority and PIMCO High Yield and between PIMCO Total Return and the PIMCO Low Duration.

 

 

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Chart of the Week: Update on Bridgewater All Weather http://markovprocesses.com/blog/2013/07/chart-of-the-week-update-on-bridgewater-all-weather/?utm_source=rss&utm_medium=rss&utm_campaign=chart-of-the-week-update-on-bridgewater-all-weather http://markovprocesses.com/blog/2013/07/chart-of-the-week-update-on-bridgewater-all-weather/#comments Thu, 11 Jul 2013 18:58:02 +0000 http://markovprocesses.com/blog/?p=2603

In recent weeks risk parity[1] funds have been the focus of particularly unfavorable reports on their performance.  Bridgewater’s All Weather Portfolio, the original and most famous risk parity fund, is often held up as an example.

The risk parity approach has performed particularly well over the past decade, minimizing losses during both the tech bubble and the financial crisis, as observed in this earlier post. As with any (relatively) new strategy it has yet to prove itself outside of simulation in a broad spectrum of economic environments[2].  This combination of popularity and novelty can increase the desire for close monitoring of performance in situations like the one we now observe.

With the majority of risk parity assets invested in hedge funds, the need for close observation poses a problem in terms of data frequency and timeliness.  A solution can be found by forecasting daily performance based on exposure estimates from the previous month, following the unique approach developed by MPI in collaboration with Prof. Russ Wermers.

For this, we performed a quantitative analysis of All Weather returns[3] using MPI’s proprietary Dynamic Style Analysis (DSA) technique, similar to that performed on the Pure Alpha fund, the flagship fund of Bridgewater Associates, last year[4].  Although the fund return data is monthly, the underlying factor data is daily which allows us to create the intra-month hypothetical track record of the fund even though the current month’s return is not yet available.

BW_AllWeather_June13

The chart above shows the cumulative performance of the All Weather Fund YTD as well as daily estimates using a synthetic portfolio consisting of daily frequency market factors[5] for the intra-month periods.   Estimates up to May 31st are in-sample, while all subsequent estimates are out of sample.

The daily forecast implies a June return of approximately -6.4% and a YTD loss for the fund of approximately -8.6%.  Also indicated is a drawdown of approximately 14% between May 3rd and June 25th.

As always, please feel free to share this post, leave a comment, or reach out to us directly with any questions you may have



[1] Risk parity is based on the observation that traditional balanced portfolios are in fact highly concentrated in terms of risk.  To address this, the risks of different asset classes can adjusted to be comparable by leveraging or deleveraging and a more diversified portfolio can be produced.  Rather than using correlation to achieve diversification, most risk parity funds allocate risk to the asset classes that are expected to outperform in four equally probably economic regimes.

[2] Please note that the strategy has been simulated historically by Bridgewater Associates, and current performance is within expectations.  Where risk is matched to a traditional 60/40 portfolio the All Weather strategy exhibits several drawdowns greater than those of the traditional portfolio while outperforming significantly in terms of total performance over the full period.

[3] Data source HFR

[4] MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.

[5] Factors include TIPS, Government Debt, Commodities and Equities.  Please contact us to obtain a detailed factor breakdown.


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Chart of the Week: Bridgewater All Weather and Permanent Portfolio http://markovprocesses.com/blog/2013/02/chart-of-the-week-bridgewater-all-weather-and-permanent-portfolio/?utm_source=rss&utm_medium=rss&utm_campaign=chart-of-the-week-bridgewater-all-weather-and-permanent-portfolio http://markovprocesses.com/blog/2013/02/chart-of-the-week-bridgewater-all-weather-and-permanent-portfolio/#comments Wed, 13 Feb 2013 14:02:22 +0000 http://markovprocesses.com/blog/?p=2576

bridgewater_gr_small

Progenitors of risk parity and TIPS, facilitators of the Chicken McNugget, and managers of the world’s largest hedge fund, Bridgewater Associate’s now $65bn All Weather Fund has become legend amongst institutional investors (to say nothing of other asset management firms) looking to weatherproof their beta and modernize their portfolios. Predicated on Ray Dalio, Bob Prince and Greg Jensen’s belief that there will always be surprises, and guessing which will be next is a fool’s errand, the strategy apparently balances a portfolio’s risk in an effort to perform in any economic environment “the machine” can throw at an investor.

Seeking to ensure the world’s largest hedge fund strategy doesn’t outgrow its ability to meet its objectives, Bridgewater will launch an alternative version of the All Weather fund later this year, according to the Wall Street Journal. The fund will be called All Weather Major Markets.

On this occasion, we got to thinking about other funds that employed passive strategic asset allocation to balance risks in an unpredictable world for the investor focused on a long term horizon.[1] That brought us to a fund we’ve long admired, the Permanent Portfolio Fund (PRPFX). According to the fund’s prospectus, PRPFX “does not attempt to anticipate short-term market activity or predict future economic events, but rather it tries to limit downside risk while providing for profit potential in any environment.”

In keeping with Bridgewater’s ethos, we won’t seek to overcomplicate things; above is a simple chart showing cumulative performance (growth of $1000, net of fees) of PRPFX and All Weather 12% through multiple economic environments and surprises since inception (Permanent Portfolio dates back further to 1982), alongside the S&P 500 to proxy the returns of an equity portfolio.[2]

Additionally, and perhaps more telling, below is a rolling (3 yr) performance chart. Both products exhibit similar performance until the Financial Crisis – though All Weather participated in more of the upside of the irrational exuberance late in the decade. In the Crisis, Permanent Portfolio’s ability to perform, preserving and growing capital, is notable. All Weather has staged a fortitudinous recovery, turning in especially impressive performance in the most recent 3 year period.

bridgewater_roll_small

If attention merits, we’ll provide more on performance attribution, risk and returns-based factor analysis of the two. As always, please feel free to reach out to discuss and/or inquire further.

For our previous analysis of Bridgewater Pure Alpha II, the firm’s actively-traded strategy, see here to download the paper.


[1] MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.

[2] Data sources are Eurekahedge and Morningstar, respectively.

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Chart of the Week: Sector Underperformance Can Hit Even Top Stock Pickers http://markovprocesses.com/blog/2013/02/chart-of-the-week-sector-underperformance-can-hit-even-top-stock-pickers/?utm_source=rss&utm_medium=rss&utm_campaign=chart-of-the-week-sector-underperformance-can-hit-even-top-stock-pickers http://markovprocesses.com/blog/2013/02/chart-of-the-week-sector-underperformance-can-hit-even-top-stock-pickers/#comments Fri, 01 Feb 2013 17:15:43 +0000 http://markovprocesses.com/blog/?p=2553

Investors with Vontobel Asset Management’s Rajiv Jain, Morningstar’s 2012 International-Stock Fund Manager of the Year, have a lot to be happy about. His 40 Act funds under the Virtus label performed very well in 2012 – to say nothing of their longer-term performance – and his Virtus Foreign Opportunities Fund (JVIAX) outperformed the MSCI All Country World Index by 4% for the year.[1]

vont_excess

While Jain consistently beat the benchmark on shorter (monthly) intervals throughout the year, significant underperformance on the bookends of the year detracted some from what was an award winning year (see above excess performance chart).

Some investors have been wondering “what happened in January and December?”, so we decided to take a look using returns-based style analysis (RBSA).

The fund, like Bruce Berkowitz’ much-watched Fairholme, features a high concentration, high conviction portfolio. Its top 5 holdings comprise over a quarter of the portfolio and over 40% was recently in the top 10. As well, it is regularly overweight certain sectors, including consumer staples.[2] Indeed, Jain has professed his proclivity for beer, tobacco, and, more recently, banks. Using style analysis, this is apparent in the below sector exposures chart that compares the fund to MSCI ACWI[3]. As we see, the fund behaves as if it has major concentrated sector bets. The model picks up major overexposure to Consumer Staples – Tobacco, Food and Beverage segments –  and major underweights in Financials, Industrials, and Tech.

vont_sectors

With such relatively low diversification levels – and high Active Style™ (over 70%) – it shouldn’t come as a surprise that periods of such high volatility can be encountered.

Performance attribution highlights Jain’s chops as a stock selector; his selection[4] skill was mostly positive in 2012. Perceived sector allocation bets (what we call timing[5]), however, were detrimental to the fund’s performance. Our model shows January and December’s underperformance to be entirely timing-driven, though prodigious Selection skill ultimately more than offset its impact to finish in positive territory (vs. bmk) for the year.

vont_attrib

Digging a little deeper into the attribution of the sector bets, the below detailed breakdown points to Bev and Tobacco overweight as the main issue behind the fund’s poor relative performance during these months. Indeed, Tobacco and Beverages were the worst performing sectors in December.

vont_attrib_detail

In a nutshell, even the best active stock-pickers can be overrun in certain periods by sector underperformance. It shouldn’t be surprising, and with the right quantitative tools at your disposal, it shouldn’t be a mystery.


[1] While JVIAX is officially benchmarked to MSCI EAFE, due to its stated exposure to global companies in the Americas, MSCI AC World Index can provide us a more fair comparison. The results do not differ much, however, if MSCI EAFE is selected instead.

[2] MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.

[3] For our factor map, we used MSCI ACWI Economic sectors for the analysis. We broke down Consumer Goods into sub-sectors for more granularity given the fund’s stated Tobacco and Beverage exposure. We used daily NAV and index return data for better precision and timeliness.

[4] Selection = Fund – Style Performance (within-style/sector bets)

[5] Timing = Style – Benchmark Performance (between style/sector bets)

 

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The View from the Top: Gundlach, TCW and MetWest http://markovprocesses.com/blog/2013/01/the-view-from-the-top-gundlach-tcw-and-metwest/?utm_source=rss&utm_medium=rss&utm_campaign=the-view-from-the-top-gundlach-tcw-and-metwest http://markovprocesses.com/blog/2013/01/the-view-from-the-top-gundlach-tcw-and-metwest/#comments Thu, 17 Jan 2013 17:28:14 +0000 http://markovprocesses.com/blog/?p=2475

 

 

28 Week Total Performance

 

 

Nominated as fixed income fund manager of the decade by Morningstar and now leading the fastest growing mutual fund (by assets) in history, Jeffrey Gundlach has enjoyed no shortage of accolades. Indeed, many investors and industry watchers suggest the bond king crown belongs on his head.

With the growing chorus telling us that the fixed income bull market (and perhaps too a very robust asset-gathering period for fixed income fund managers) is nearing a close, we took a minute to chart performance of the Total Return funds the storied manager has headed, TCW Total Return Bond Fund (TGLMX; blue line) and DoubleLine Total Return Bond Fund (DBLTX; purple line).

At the risk of putting mutual fund observers to sleep, we quickly recap: TCW summarily brought on Metropolitan West (whose Total Return Bond Fund MWTRX is also displayed in the corresponding charts) and put its team in charge of TGLMX after dismissing Gundlach in late 2009. Gundlach then formed DoubleLine with many of his defecting TCW colleagues. The reputation and prodigious performance of DoubleLine brought in a torrent of assets since inception, with DBLTX holding over $35 billion and the firm managing more than $50 billion at present.

While DoubleLine’s star power and asset gathering prowess since inception is irreducible, what is less trumpeted – though which shouldn’t be surprising for long time investors – is that the team at TCW under Tad Rivelle have shown they are more than capable at putting up numbers as well.

When we look no further than total performance of these 3 funds against the backdrop of the Intermediate Term Bond Fund universe[1] and a benchmark of the Barclays Capital Aggregate Bond Index over a 5 year (above) and 10 year (below) period, we note a few observations:

  1. The range of fund performance – and therefore opportunities in the fixed income market – greatly widens during volatile periods.
  2. Gundlach has spent a significant amount of time at or near the top of the ITBF class, with remarkable relative performance during the chaos of 2008 and the Credit Crunch.
  3. MWTRX and TGLMX pre-merger often enjoyed simultaneous position at or near the top of the category, though in 2002 and 2003 they vacillated between the bottom and the top of the pack, respectively.
  4. While nearly always in the top quartile since inception, DBLTX experienced its best performance as the first capital was put to work – in a market where opportunities look to have narrowed from the chaos of 2008 and 2009.
  5. The new TCW team under the tutelage of CIO Tad Rivelle has done quite well for themselves too, especially over 2012. Indeed, Morningstar nominated Rivelle and team as finalists for Fixed Income Fund Manager of 2012, a distinction they won in 2005.
  6. Post-merger performance of MWTRX and TGLMX has been very similar since Q4 2010.

 

 

28 Week Total Performance

 

 

 


[1] As classified by Morningstar. The Peer Group ranges from 71 starting in Jan 2000 up to 109 in Dec 2012. The funds come into the sample as soon as there is enough data. Data is daily; Currency is USD; Oldest Share Class; AUM >= $1billion

 

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Russell Stability Indexes™: Usage in Fund and Portfolio Analysis http://markovprocesses.com/blog/2013/01/russell-stability-indexes/?utm_source=rss&utm_medium=rss&utm_campaign=russell-stability-indexes http://markovprocesses.com/blog/2013/01/russell-stability-indexes/#comments Wed, 16 Jan 2013 15:51:42 +0000 http://markovprocesses.com/blog/?p=2420

What are they?

Russell IndexesIn 2010, Russell launched the Russell Stability Indexes. We believe that the index series is very useful for investment practitioners and fund analysts looking to better understand exposures and risk factors – particularly those associated with sensitivity to economic cycles and price of stocks – exhibited by funds and portfolios.

The Russell Stability Indexes are constructed by splitting the Russell Indexes (both U.S. and Global) by level of stability; the more stable half of stocks is deemed the Russell Defensive Index™, the less stable half is called the Russell Dynamic Index™.

The intention for Russell Stability (Defensive and Dynamic) Style Indexes is not to replace the traditional Russell Valuation (Growth and Value) Style Indexes, but to provide a third dimension of style. A stock is both Growth or Value, as well as Defensive or Dynamic, and they are not synonymous. And a further combination of Growth, Value and Defensive, Dynamic indexes provides deeper analysis into style.

When categorizing stocks by stability, Russell takes into account the quality (debt/equity, earnings variability and ROA) and price volatility of stocks. They are not merely measures of value or volatility alone. In this regard, they reflect valuable risk factors for practitioners.

Why use them?

Risk Factor Analysis: Russell’s Stability Style Indexes are compelling for the insight they offer as risk factors in equities, managers and portfolios. This can give MPI Stylus users a better understanding of the sensitivity to economic and market cycles that the funds and portfolios they analyze behave as if they are exposed to, and which drive performance. A more complete picture of risk can emerge when combining such analysis with forward-looking forecasting.

Fit and Explanatory Power: For over 80% of equity funds MPI tested, Russell Stability Indexes marginally improve fit, providing a higher R2 than the traditional Valuation Style Indexes oft-used in returns-based style analysis. Going beyond fit to look at predictability of returns – measured by MPI’s proprietary measure of explanatory power, Predicted R2 (PR2) – Stability Style Indexes lead to heightened explanation in Blend funds, as well as International, Emerging Markets and Regional equity funds.

Simpler Analysis: Thirdly, MPI’s Research team has found that using a factor map of Russell Stability Style Indexes leads to simpler analysis for 2/3 of funds – simpler meaning analyses that require fewer factors to explain a fund or portfolio’s behavior while not compromising fit or explanatory power significantly.

Certainly, analysis with traditional Valuation Style Indexes is still applicable to a significant proportion of funds. Indeed, about 1/3rd of analyzed funds can be described as well or better with a traditional map.

At a higher level, it’s important to note that the expansion of the index universe – especially those that reflect investment strategies and risk factors – and the adoption of new series encourages the evolution of performance attribution and returns-based analysis. The increased ability to explain the sources of a fund’s returns with new factors suggests formerly unidentifiable portions of a manager’s alpha can become identifiable as betas.

Here are a few examples of funds analyzed with both factor maps, i.e., Russell U.S. Stability Style Indexes and Russell U.S. Valuation Style Indexes, which show marked differences in complexity of model and explanatory power:

GMO Quality VI (GQLOX)

GMO Quality VI (GQLOX)

Vanguard Dividend Growth Inv Fund (VDIGX)

Vanguard Dividend Growth Inv Fund (VDIGX)

For additional information, please see:

http://www.russell.com/indexes/data/stability/russell-stability-indexes.asp

http://www.russell.com/indexes/documents/research/third-dimension-style-russell-stability-indexes-January2011.pdf

http://www.russell.com/indexes/documents/research/where-manager-styles-intersect.pdf

http://www.russell.com/indexes/data/US_Equity/Russell_US_index_returns.asp

For more information and any inquiries on accessing and utilizing Russell Stability Indexes in Stylus, please contact us.

Special thanks go out to Catherine Yoshimoto, Senior Product Manager, Sara Wilson, Regional Director, Tricia O’Connell, Strategic Marketing Manager, and Barry Feldman, Senior Research Analyst, Ph.D., CFA, with Russell Investments for their assistance and guidance.

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Chart of the Week: FB – Change in Estimated Mutual Fund Exposure Since IPO http://markovprocesses.com/blog/2013/01/chart-of-the-week-fb-change-in-estimated-mutual-fund-exposure-since-ipo/?utm_source=rss&utm_medium=rss&utm_campaign=chart-of-the-week-fb-change-in-estimated-mutual-fund-exposure-since-ipo http://markovprocesses.com/blog/2013/01/chart-of-the-week-fb-change-in-estimated-mutual-fund-exposure-since-ipo/#comments Fri, 04 Jan 2013 18:32:41 +0000 http://markovprocesses.com/blog/?p=2405

fb_est_change_mf

As we say “goodbye” to 2012, we turn back to the year’s biggest IPO and history’s largest tech IPO, Facebook (NASDAQ: FB).

The intention of the original post on FB was to see what quantitative analysis of a galaxy of mutual funds using daily data over a very short time period can actually show a savvy fund investor. The applications for such single security detection were mostly for risk management purposes, understanding exposure to a new security whose value was of much debate, as evinced by its stock price.

In this follow-up, we utilize our patented Dynamic Style Analysis (DSA) model to look at how estimated[1] exposure to FB has changed from the IPO to the end of the year across the large-cap growth galaxy of mutual funds. The Y-axis shows estimated exposure as a percentage of each fund’s portfolio at the end of the year (to remove noise associated with daily data, we average exposure over the final 2 weeks of the year), while the X-axis shows estimated exposure at IPO (again, average exposure over the initial 2 weeks of trading following May 18th IPO).

In general, we note what appears to be a trend amongst these funds to growing exposure since FB began trading.  It’s worth noting that FB was added to the NASDAQ 100 just prior to the second period under analysis.

Additionally, the continued media attention and coverage of the iconic company’s investor base makes FB a good case to highlight the accuracy of such quantitative analysis. It must be reiterated though that, much like a water reflection on a calm morning that sees occasional wind, this analysis is purely returns-based[2] and aberrations are inherent between what shows up in a returns-based model and what fund is actually holding.

As shown in the chart, we highlight all funds listed within the large-cap growth category from the asset management divisions of FB’s three primary underwriters – Morgan Stanley, Goldman Sachs and J.P. Morgan. What the analysis shows appears to generally match what has been reported from a holdings perspective – while there has been selling reported in MS funds, they appear to maintain significant exposure to FB[3]; GS funds have reported some selling as well but we still see exposure showing up (i.e. GSGCX). J.P. Morgan funds, whom the Wall Street Journal in the above hyperlinked story (from Dec.31st)suggests has sold all of their FB, suggest the only significant aberration in our model and what we’ve seen reported, as exposures aren’t really detected post IPO, though one fund (JGASX) shows some exposure currently.

We also highlight other outliers like Turner Concentrated Growth (TTOPX), whose second largest reported position is FB, and Fidelity OTC (FOCPX), whose third largest holding as of 11/30/12 is reportedly FB.

Again, the insight that investors can ascertain into their funds and portfolios intra-reporting periods utilizing advanced quantitative analysis is striking, and more accessible than many imagine.



[1] MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.

[2] The factor map utilized comprises FB, the 10 S&P 500 Sectors & Cash. In this case, the factor map gives the model a chance to differentiate between FB and the broader IT sector.

[3] This chart also has an MS-subadvised fund, Transamerica Capital Growth (TFOIX), whose 4th largest reported holding on 9/30 appears to be FB.

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Chart of the Week: Are Managers Preparing to Repel Down the Fiscal Cliff? http://markovprocesses.com/blog/2012/12/chart-of-the-week-are-managers-preparing-to-repel-down-the-fiscal-cliff/?utm_source=rss&utm_medium=rss&utm_campaign=chart-of-the-week-are-managers-preparing-to-repel-down-the-fiscal-cliff http://markovprocesses.com/blog/2012/12/chart-of-the-week-are-managers-preparing-to-repel-down-the-fiscal-cliff/#comments Wed, 26 Dec 2012 14:01:52 +0000 http://markovprocesses.com/blog/?p=2395

single_qrt_change

With 5 days until deadline, are there any indications mutual fund managers are systematically acting on the broadcasted hysteria and preparing their portfolios for a less sudden descent down an ominous Fiscal Cliff (or maybe just locking-in handsome double digit market gains YTD)?[1] Or are they broadly in the market, sanguine about the prospects for a deal (or perhaps just captivated by a continued rising QE-fueled tide and promise of further inventive “Gangnam Style” monetary maneuvers?

In an attempt to look beyond daily market activity we surveilled the mutual fund universe in our monitoring templates to see if our returns-based models perceived changes in defensive behavior, in this case measured by conservative factor exposures of cash and bonds, over a three month period (Y-axis as of 12.21.12, X-axis 90 days prior).[2]

As the above chart shows, managers do appear to be adjusting one way or the other, i.e. changing their defensive exposure. But all the Cliff ballyhoo does not exactly match the narrow, albeit growing, majority of managers with a perceived increasingly defensive tilt (as the rising post-election market and relatively muted volatility would indicate). We’ll see if the last trading days of the year show a more pronounced systematic shift as the Cliff approaches.

The model does pick up a number of outliers on both sides. Amongst those funds behaving more defensive, we count Matthew 25 (MXXVX), Clipper Fund (CFIMX), Fidelity Advisor Capital Development O (FDETX), Federated Strategic Value Dividend A (SVAAX). Of those behaving more ‘in the market’, we note both Yacktman Funds (YAFFX and YACKX).

To see our prior look at QE3’s winners, click here.

For more information on MPI Stylus Pro and how you can utilize its applications in a like manner, please contact us.


[1] MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.

[2] Using Daily NAV data of entire Lipper Large and multi-cap fund universe in our patented Dynamic Style Analysis (DSA) model.

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Assessing Investment Style Similarity of Top Mutual Funds with MPI Common Style Analysis http://markovprocesses.com/blog/2012/12/assessing-investment-style-similarity-of-top-mutual-funds-with-mpi-common-style-analysis/?utm_source=rss&utm_medium=rss&utm_campaign=assessing-investment-style-similarity-of-top-mutual-funds-with-mpi-common-style-analysis http://markovprocesses.com/blog/2012/12/assessing-investment-style-similarity-of-top-mutual-funds-with-mpi-common-style-analysis/#comments Fri, 14 Dec 2012 15:29:22 +0000 http://markovprocesses.com/blog/?p=2361

As we’ve recently written, it has become platitudinous to say that markets are and have been highly correlated. And it is past due to move beyond simple linear measures of performance, such as correlation, when performing manager searches, diligence, selection, monitoring and replacement.

It is with this thought in mind that we are proud to bring to market our new investment style metrics – Common and Active Style – to assess product and portfolio similarity and difference. Our clients – from investment managers to product development teams, from institutions to their consultants and advisors – are excited to implement our new metrics to the field in a variety of ways to better inform analysis, decision making and communication through reporting.

Given that many of these clients are involved in the defined contribution space, we are introducing a new research feature we will update regularly (probably quarterly) in which we will calculate the Common and Active Style of the top 10 Domestic Equity mutual funds by DC AUM[1]. To demonstrate the utility of this robust measure[2], we then show a correlation matrix for the same funds.

The below charts are YTD using daily data of fund NAVs.[3] While an assortment of returns-based models in Stylus can be used, we utilize our Dynamic Style Analysis (DSA) model for extra precision. The same factor map, or style outline, was used for all analyses.[4] Predicted R2, MPI’s proprietary measure of explanatory power, was highly credible – averaging about 95%.

While we see very high Common Style between the index funds amongst the top 10, the rest are considerably different (average Common Style of 54%), a level of scrutiny which is completely missed by just looking at a correlation matrix (average correlation is 96%), reiterating the need to look beyond such linear measures. In an extreme case, we see Vanguard Institutional Index Inst Pl (VIIIX, #6) has correlations of 1.00 and .99 with Vanguard 500 Index Investor (VFINX,#9) and American Funds Fundamental Investors (ANCFX, #10), while maintaining considerable differentiation from an investment style perspective, with Common Style of .81 and .71, respectively.

For further information on MPI’s style metrics, please email us at sales@markovprocesses.com.

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correlation_matrix


[1] Per data gathered by Pensions & Investments. See the list here: Top 10 Domestic Equity Funds

[2] MPI conducts performance-based analyses and, beyond any public information, does not claim to know or insinuate what the actual strategy, positions or holdings of the funds discussed are, nor are we commenting on the quality or merits of the strategies. This analysis is purely returns-based and does not reflect actual holdings. Deviations between our analysis and the actual holdings and/or management decisions made by funds are expected and inherent in any quantitative analysis. MPI makes no warranties or guarantees as to the accuracy of this statistical analysis, nor does it take any responsibility for investment decisions made by any parties based on this analysis.

[3] Since it is nearly end of the calendar year, we’ll use YTD now, though we’ll present past 12 months in future posts.

[4] The map consists of the Russell-6 U.S. Equity Indexes, an international equity map based on 6 MSCI style indices, and a 9 index map of bond indices.

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