My previous articles show how to design a bias-free dividend strategy (Part 1 and Part 2). This one compares some management rules to protect a dividend portfolio in bad times. Hedging and market timing rules are simulated on a 10-year period, then I propose another kind of solution that gives better results.

First, here is the basic strategy I will use for this demonstration:

I scan the current **S&P 500 index members** to find companies that are **not in the Utilities sector** and whose **average annual yield the last five years is above 5%**, then I select the **ten with the highest latest annual yield**.

In other words, I pick the big caps with the highest yields after applying two filtering rules. The 5-year average rule eliminates too unstable yields. Eliminating Utilities increases significantly the average return. My focus here is not on the strategy itself, there is no doubt you can find better ones. This is a simple and decent example to discuss the best ways to protect a dividend portfolio.

The portfolio capital is equally shared between the selected stocks and a maximum of 10% can be invested on each one. So, if less than 10 stocks are selected, a part of the money is kept in cash. The portfolio is rebalanced quarterly. Capital plus gains or minus losses, plus dividends, is reinvested on each rebalancing.

The following simulations are executed from 1/1/2002 to 11/8/2012 with a 0.2% rate for slippage and fees.

Here is the equity curve of this strategy (in red), compared with SPY including dividends (in blue):

The compounded annualized return is 12.3%

I have simulated four protection tactics on this strategy.

**1) Permanent hedging**

For each dollar bought in a stock, a dollar is sold short on SPY, on margin if necessary. An annual rate of 1.5% is applied for borrowing SPY.

Here is the new equity curve:

The compounded annualized return is 6.7%

**2) Market timing**

On each rebalancing, I check if the S&P 500 index 50-day moving average is below the 200-day moving average. If it is, I sell the portfolio and stay out of the market.

The compounded annualized return is 11.9%

**3) Timed hedging**

For each rebalancing, I check if the S&P500 index 50-day moving average is below the 200-day moving average. If it is, I apply the hedging rules of 1).

The compounded annualized return is 12.8%

**4) Short interest filter**

I go back to the basic strategy, adding a filter before looking for the 10

highest yields: only stocks with a short interest below 5% of the float can be selected.

The compounded annualized return is 12.7%

Investors focused on the return may conclude that the 3rd and the 4th solution are the best and equivalent. It would be a mistake. The average return makes no sense without looking at the robustness of the strategies and their maximum drawdowns.

The robustness is evaluated by statistical criteria. I think the most appropriate here is the Sortino ratio. It is a modified Sharpe ratio, more pertinent because only the "bad" volatility is accounted (the returns above the target don't lower the ratio).

For the drawdown, let me open a parenthesis to describe two aspects of its cost:

-The **recovery effort**, which is the gain necessary to make up for a loss. If the drawdown is x, the formula is f(x) =x/(1-x) .

For example, when a portfolio has a 30% drawdown, it needs a 43% gain to recover: 0.30/(1-0.30)= 0.4286. When it has a 50% drawdown, it needs a 100% gain: 0.5/(1-0.5)= 1. I consider the recovery effort as the **drawdown cost**.

-The **marginal recovery effort**, which is the additional gain necessary to make up for an additional loss. The formula is: df(x)/dx = 1/(1-x)^{2}.

For example, when a portfolio has a 30% drawdown, an additional 1% loss needs a 2% additional gain to recover: 1/(1-0.30)^{2}= 2.04. At a 50% drawdown, an additional 1% loss needs a 4% additional gain to recover: 1/(1-0.50)^{2}= 4. I consider it as the **drawdown marginal cost**. It is an indicator of the risk if the drawdown goes beyond its maximum historical value.

The following table shows the annualized return, the maximal drawdown and the Sortino ratio for the four solutions, compared with SPY and the basic strategy.

CAGR (%) | DDMax (%) | Sortino | |

SPY | 3.7 | -55 | 0 |

Basic strategy | 12.3 | -55 | 0.47 |

Hedging | 6.7 | -18 | 0.26 |

Market Timing | 11.9 | -18 | 0.67 |

Timed Hedging | 12.8 | -26 | 0.67 |

Short Interest Filter | 12.7 | -17 | 1.02 |

In fact, the market timing is better than the timed hedging because of a significantly lower drawdown. Moreover, no hedging means no need of margin.

The best solution is the short interest filter. It is the only one with a Sortino ratio above one. Its average return is close to the best and its drawdown is the lowest.

This short interest filter does much more than selecting companies. Combined with the 10%-by-position rule, it acts as an adaptive market timing rule.

Here is how the number of positions is evolving during the simulation:

In a bear market the short interest is growing for most companies. The number of S&P 500 stocks below 5% of short interest is falling. Following the rules, the portfolio would have been 60% to 100% in cash from June 2007 to June 2009. The short interest filter adapts the exposition to the situation.

**Conclusion**

To protect this S&P 500 high dividend portfolio, simulations show that a simple market timing based on two moving averages gives a higher average return than hedging, for a similar drawdown.

Moreover, a filter on the short interest gives almost the best return, the lowest drawdown and the highest Sortino ratio. Keeping in the portfolio only the stocks with a short interest below 5% of float dramatically lowers the drawdown with no significant impact on the average return of the original strategy. I have successfully tested the same filter with another strategy on high-yield small caps (not described here). Income-oriented investors may be interested in checking if it could apply to their own portfolios.

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**Disclosure: **I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. 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.