**A New Approach to Portfolio Construction**

Hey Fellow Slopers,

Last month, I posted here about a new feature we were working on at Portfolio Armor (“The Hedged Returns Approach”). In that post, I mentioned a couple of problems with typical, long-only, unhedged portfolios:

- Uncapped systemic risk – for example, the risk many passive investors experienced when their SPY shares dropped 50% during the financial crisis.
- Modest long term returns – for example, the 3.5% average annual return SPY has generated for those same investors over the past 10 years.

Risking ~50% drops for ~3.5% average annual returns sounds like a shit deal, right? Hence our new, “hedged returns” approach which breaks down to these steps, in broad strokes:

- Find securities with high expected returns.
- Find securities that are relatively inexpensive to hedge.
- Buy a handful of securities that score well on the first two criteria; in other words, buy a handful of securities with high expected returns net of their hedging costs (or, ones with high net expected returns).
- Hedge them.
- Sell the underlying securities shortly before their hedges expire.
- Repeat.

The potential benefits of this approach are twofold:

- If you are successful at the first step (finding securities with high expected returns), and you hold a concentrated portfolio of them, your portfolio should generate decent returns over time.
- If you are hedged, and your return estimates are occasionally completely wrong — or the market moves against you — your downside will be strictly limited.

**Implementing This Approach**

Portfolio Armor’s tool to automate this approach went live this week, so let’s look at a couple of examples of it in action. For our first example, consider an investor with $500,000 in cash who wants to maximize his potential return over the next six months while limiting his downside risk to a maximum drawdown of no more than 8%.

For the purposes of this example, we’ll assume that this investor doesn’t have a list of favored securities to start with, so he’ll leave the first field below (“Tickers”) blank, and enter “500000” in the “Dollar Amount Of Portfolio” field and “8” in the Threshold field. If our hypothetical investor did have ideas he found (on Benzinga, for example), he could enter their ticker symbols in the first field below, and he would then be given the choice of entering his own expected returns for them, or letting Portfolio Armor use its expected return calculations (every trading day, Portfolio Armor calculates expected returns for more than 3,000+ stocks and ETFs. These estimates are based on analysis of historical returns as well as option market sentiment, which provides a forward-looking element).

Note that the descriptions of the fields above include question marks – if a subscriber hovers his mouse pointer over them, he’ll see explanatory text, such as the one here explaining the strategy field.

After the few minutes it took Portfolio Armor to sort through and analyze the necessary financial data, our investor would have seen this result had he created this portfolio at the close on February 7th, 2014 (results could, of course, differ at different times based on market conditions):

**Three Types of Hedges**

The underlying securities in this portfolio are hedged in one of three different ways. The first, Biogen (BIIB), is hedged as what we call a cash substitute. A cash substitute is a security that, when hedged with an optimal collar[i] with a cap set at 1% (or the current 7-day yield on a leading money market fund, whichever is higher) has a maximum downside risk less than or equal to the investor’s threshold, a low hedging cost, and a net expected return greater than the current 7-day yield on a leading money market fund. The idea is to get better-than-cash returns while limiting portfolio risk per the investor’s specification. The cap is the level of appreciation beyond which the underlying security will be called away: in a collar, you are selling someone else the right to buy your underlying security if it appreciates beyond that cap; the income you get from selling that right (the call options) offsets the cost of your downside protection (the put options).

The next two securities in the portfolio, Celgine (CELG) and FedEx (FDX), are hedged with optimal collars with the cap percentages set at their six month expected returns (the reason the numbers in the expected return column are slightly lower for these two stocks is that they have been adjusted downward because their hedges expire in less than six months; the assumption here is that investors will hold these underlying securities for six months, until they are called away, or until shortly before their hedges expire, whichever comes first).

Cheniere Energy (LNG) is also hedged with an optimal collar with its cap set at its six month expected return (the expected return for LNG is the same in this case, because its hedge expires in more than six months). Northrop Grumman (NOC), and Raytheon (RTN) have no caps, because they are hedged with optimal puts[ii]. If you select the “maximize return” strategy, Portfolio Armor will consider both securities hedged with puts as well as securities hedged with optimal collars, ranking them by their net expected returns. In both cases, it will seek to include the securities with the highest net expected returns given your risk tolerance and portfolio size

**Max Drawdown**

Turning to the portfolio level data, we see that the maximum drawdown for this portfolio is 7.18%. That’s the most this portfolio will decline in the worst case scenario. If each of the underlying securities above went to zero before their hedges expired, the portfolio would only decline 7.18%.

**Potential Return**

The potential return of this portfolio was 12.89%. That potential return is what the portfolio would return, net of hedging costs, if each of its underlying securities achieved its expected return within six months (or before its hedge expired, whichever came first). As you might expect, all else equal, the larger the max drawdown you are willing to risk (i.e., the larger your “threshold”), the higher your potential returns.

**Hedging Cost**

Note also that the hedging cost of this portfolio was 4.67%. Let’s say our hypothetical investor considered this hedging cost to be too high. For our second example, we’ll have him enter the same dollar value of his portfolio, and same threshold, but select “Minimize Hedging Cost” in the strategy field. A few minutes after clicking the “Create” button, he would have been presented with this portfolio as of the close on February 7th:

**Two Types of Hedges**

In this portfolio, D.R. Horton (DHI) is hedged with an optimal collar with its cap set at DHI’s six month expected return. The rest of the stocks are hedged as cash substitutes.

**Max Drawdown**

Turning to the portfolio level data, the maximum drawdown here is slightly higher than in the previous portfolio, but still below our investor’s threshold. So, in a worst case scenario, if each of the underlying securities in his portfolio went to zero before their hedges expired, the investor would only be down 7.89%.

**Potential Return**

His potential return with this portfolio, at 5.00%, is lower than the potential return of the first portfolio, but that’s to be expected given that the strategy the tool used in this case was primarily to minimize hedging costs and only secondarily to maximize return.

**Hedging Cost**

The hedging costs are also significantly lower in this portfolio -3.50%, meaning that the investor would effectively be getting paid to hedge this portfolio.

[i] *Optimal collars** the ones that will give you the level of protection you want at the lowest net cost, while not limiting your potential upside by more than you specify. Portfolio Armor’s algorithm to scan for optimal collars was developed in conjunction with a post-doctoral fellow in the financial engineering department at Princeton University.*

[ii] *Optimal* *puts are the ones that will give you the level of protection you want at the lowest possible cost. Portfolio Armor uses an algorithm developed by a finance PhD to sort through and analyze all of the available puts for your stocks and ETFs, scanning for the optimal ones.*