How To Boost Returns In Closed-End Funds (Part 2)

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Includes: AWP, BIZD, BTT, CAF, CEFL, EMD, ESD, ETJ, EVV, HTD, IGD, IQI, MLPX, MMT, NEA, NXJ, RNP, RQI, SPY, YMLP, YYY
by: Fred Piard

Summary

Summary of Part 1: a turbocharged CEF portfolio strategy.

Consistency of excess return.

How to cut the risk without going in cash during recessions.

Previous episode summary

I have described a systematic portfolio strategy in closed-end funds. It ranks CEFs using the discount to NAV, its potential mean-reversion, the dividend yield and momentum (click here to read the details). The next chart shows the theoretical performance of a portfolio including the top 15 ranks of this model, rebalanced in equal weight every week from 05/01/2000 to 04/07/2016, reinvesting dividends and without trading costs.

Click to enlarge

Data and charts by portfolio123

As an example, here is the list of holdings on 4/13/2016:

Ticker

Name

Asset Class

AWP

Alpine Global Premier Properties Fund

Equity

BTT

BlackRock Municipal Target Term Trust

Fixed Income

CAF

Morgan Stanley China A Share Fund

Equity

EMD

Western Asset Emerging Markets Income Fund

Fixed Income

ESD

Western Asset Emerging Markets Debt Fund

Fixed Income

ETJ

Eaton Vance Risk-Managed Diversified Equity Income Fund

Equity

EVV

Eaton Vance Limited Duration Income Fund

Fixed Income

HTD

John Hancock Tax-Advantaged Dividend Income Fund

Mixed Assets

IGD

Voya Global Equity Dividend and Premium Opportunity Fund

Equity

IQI

Invesco Quality Municipal Income Trust

Fixed Income

MMT

MFS Multimarket Income Trust

Fixed Income

NPM

Nuveen Premium Income Municipal Fund 2

Fixed Income

NXJ

Nuveen New Jersey Dividend Advantage Municipal Fund

Fixed Income

RNP

Cohen & Steers REIT and Preferred Income Fund

Equity

RQI

Cohen & Steers Quality Income Realty Fund

Equity

Click to enlarge

The model turnover makes it sensitive to trading costs. The previous article shows that a total trading cost between 0.2% and 0.3% is realistic with Interactive Brokers' (NASDAQ:IBKR) fees and basic precautions to avoid slippage. I have calculated a realistic annualized return on this 16-year period between 14% and 17% for a weekly rebalancing, between 13% and 15% for a 2-week rebalancing, and around 12-13% for a monthly rebalancing. Of course, past performance is not a guarantee of future returns.

Excess return consistency

A reader asked if the simulated excess return is consistent along the years. There are 2 components: the excess return of CEFs over the stock market, and the excess return of the strategy over a CEF benchmark. The former has been documented in academic research and has survived to arbitrage, but it has had bad periods. The last 2 years is one of them. The explanation is simple: a significant portion of equity CEFs select their holdings in high yield stocks - mostly oil & gas infrastructure and BDCs. MLP indices are in a drawdown between 40% MLPX and 70% YMLP. BDC indices have also underperformed the market BIZD.

The second component of excess return can be checked by comparing the portfolio on different periods with a benchmark of tradable CEFs (my criteria are share price above $5 and average daily liquidity in $ above 1 million).

Annual. Returns* for

2001-2005

2005-2009

2009-2013

2013-now

15 CEFs Portfolio

18.3%

1.5%

23.5%

12.1%

CEF benchmark

9.6%

-7.8%

20.3%

1.9%

Excess return

8.7%

9.3%

3.2%

10.2%

Click to enlarge

* taking into account a 0.25% trading cost and 4-week rebalancing. Excess returns vary with trading costs and turnover.

The excess return of the strategy over the CEF benchmark has been positive in the four 4-year periods. It has even been increasing except in 2009-2013. As it was the best period, it is not really a concern. For an active investor, this strategy looks a good alternative to an index fund of CEFs like YYY, or its leveraged sibling CEFL.

Cutting the risk with a scaled hedge

Market timing is the most popular way to limit the market risk, but it raises several problems:

  • If you rely on only one indicator, you are 100% wrong when it is wrong.
  • Going to cash is a serious issue in high dividend strategies like this one: a large part of the return comes from dividends and reinvesting them.
  • False signals are expensive in transaction costs for a 15-holding portfolio.

I prefer scaled hedging and multi-valued risk indicators. I will give now examples of hedging tactics based on MTS4. To understand them, you just need to know this: MTS4 formula gives an integer between 0 and 4. The higher it is, the riskier is the market. For more details you can read here the definition and calculation guidelines.

Three hedging tactics A, B, C are defined hereafter. Each value of MTS4 corresponds to a hedging percentage. For example, if you follow the tactic A and MTS4=1, the hedge is 25%. It means a short position in the S&P 500 index of 25% of the CEF portfolio value.

MTS4=0

MTS4=1

MTS4=2

MTS4=3

MTS4=4

A

0

25%

50%

75%

100%

B

0

0

50%

75%

100%

C

0

0

0

50%

100%

Click to enlarge

The next table gives the annualized returns and maximum drawdowns for the portfolio with the 3 hedging tactics on 16 years (with 0.25% trading cost and weekly rebalancing). MaxDD is measured on rebalancing (it is larger in real time). The hedge is modeled as a short position in SPY on margin. Other hedging instruments are possible (options, futures, CFDs, inverse/leveraged ETFs).

Ann. Ret

MaxDD

No Hedge

16.7%

-46%

A

17.6%

-22%

B

18.3%

-22%

C

19.8%

-22%

Click to enlarge

The best hedging tactic in the past might not be the best in the future. The choice should be based on a personal perception of risk, not on such a short difference in performance through only 2 market cycles.

The most interesting point in scaled hedging is not the marginal improvement in return, but the drastic reduction in risk. Risk is not only a statistical concept. If it is necessary, withdrawing money from a portfolio to overcome a personal situation is easier at -22% in drawdown than at -46%.

For a real portfolio following the model, a good approach is updating the list of holdings every 2-5 weeks and adjusting the hedge every week. CEF position sizes should be rebalanced only when the difference between the smallest and largest ones is above 15%. These empirical rules limit the cost and hassle of trading and stay close to the original model.

If you are interested in the CEF portfolio updates, tell me by clicking "Send Message" at the top of this article. It is available on another platform, not in my SeekingAlpha Premium Service.

Disclosure: I am/we are long RQI.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.