What’s Killing Value Managers – 1999

One of the biggest challenges in investing is timing a rotation from a style that is currently in favor into a style that is currently out of favor. This was the challenge in 1999 and is so again today. In April 1999, the NY Times had an article titled “Mutual Fund Report; What’s Killing the Value Managers?”; history doesn’t repeat itself but it surely does seem to rhyme.

Back to 2020. Concentration in the equity markets has been a topic of conversation in the past year. Five years ago, Apple, Amazon, Facebook, Google, and Microsoft were 9.5% of the S&P 500. At the end of the second quarter, these five companies accounted for 21.7% of the S&P 500. These same five companies account for 45.7% of the Nasdaq 100 and Amazon itself is 44.4% of the total market of all the companies in the S&P 500 Consumer Discretionary sector. The current average forward P/E of these five companies is over 40, doubling from mid-March. As a result, the forward P/E of the Russell 1000 Growth Index at the end of the second quarter was 32.7. Since 1995, the only other time the forward P/E of the Russell 1000 Growth Index was this at this level was in late 1999 and in 2000, the heart of the dot-com bubble where it reached a peak forward P/E of 43.5 in July 2000. Over the entire 1995 to present period, the average forward P/E is 20.3. While equity valuations in general have increased as a result of low nominal rates, the increase has been more pronounced in the growth factor as the spread of the forward P/E of the Russell 1000 Growth Index is 11 P/E points more than the forward P/E of the Russell 1000 Value index.


Data Source: Bloomberg


Data Source: Bloomberg

Value and Rebalancing

The temptation is strong. The strategy you have used for years has underperformed. Why take the risk? Move back to the benchmark. Like a remake of a classic film, we have seen most of this before. In early 2009, pressure was on value stock managers to change their stripes. We recall a conversation from April 2009 with a foundation client invested in our Large Cap Value strategy. We had recently rolled to a new portfolio, and one of the selections was Wyndham Hotels. They were quite agitated – after the financial crisis it was unlikely that people would be going back to hotels for years. How could we? I took the quant’s way out of the question – “the model made me do it.” Wyndham was the best performing stock in the S&P 500 over the next 12 months.

The current reckoning certainly rhymes with the financial crisis. We must confess that even our conviction was challenged this time, and I promise you, ours runs deeper than most. Last week it was time to roll our value portfolio forward. Put the names back into the hat, take a fresh look, buy what is cheapest based on the models and caveats we employ. To add to the insult, it was also time to rebalance our multi-asset portfolios. What this meant was we had to buy a portfolio of decimated value names, in some cases buy more of them. Alaska Air? Kohl’s? Valero? MGM? Who is going to fly, go to a department store, get gas or gamble? Sure, these stocks have never really been cheaper, but come on. This is wake up in the middle of the night with these ticker symbols swirling in your head stuff. And you want us to buy more!

Take a deep breath. Think for a minute. What works? Buy when others are selling, sell when others are buying. Buy zero coupon bonds in the early 1980’s. Sell tech and buy value in 2000 (value was “broken” then, too). Sell crude at $150 (that’s when people stop buying gas). Value stocks look like that right now. They have discounted the end of air travel, retail, gasoline, and gambling. Never again will there be cash flow or dividends. We aren’t blind, we get that the near term is difficult for these names. But does that justify low single digit PEs? Or should it be mid-single digit PEs? Or can you look forward a few years and imagine a world different than today. For at least part of your portfolio, don’t you need to own the cheapest assets in the world? Rebalancing works best when you have volatile assets with low correlation and positive return – pump that volatility. What you shouldn’t do is sort by near term returns top to bottom and pile into the biggest winners. That’s not a portfolio.

Value stocks at this juncture are incredibly cheap. We aren’t the first people to say this, but it bears repeating nonetheless. The chart below shows the ratio of S&P Growth PE ratios to S&P Value PE ratios. There are bargains galore on offer, right now. Great businesses that are temporarily troubled and are being penalized to extreme degrees. Take advantage of it.


Data Source: Bloomberg, Mount Lucas LP

Can News Flow Create Value?

Searching Google for “Retail Apocalypse” returns 8.8 million results (in .45 seconds!). For the better part of a decade the sector has been beaten up in the press. The headlines are not unfounded. Former staples of American consumerism such as Toys-R-Us, Radio Shack, and Payless ShoeSource are no longer, while many others struggle to find stable ground. The negative hype surrounding the Retail Apocalypse has created a fog around the whole sector and retail stocks have not been a popular pick amongst active money managers in recent memory.

Behind the retail apocalypse headlines are companies who have adapted to new market conditions, have strong balance sheets, and forward-thinking management. Looking into the fog, we see a shunned sector, overly beaten down valuations, and good potential to seek out value. Our Mount Lucas Focused Large Cap Value currently holds 4 retail names amongst its 36 total holdings. Some may view this as a high concentration of an unpopular sector for a focused strategy which holds no more than 40 stocks. However, our quantitative stock picking algorithms have no such opinions, they are programmed to seek value.

Below are the 4 retail names currently being held in the strategy, each picked for the portfolio on Sept. 22, 2017. Presented are price charts with selection date indicated and resulting price move, as well as headlines from the time preceding selection. Even positive news is tinged with negatively worded headlines. We believe this illustrates the headline fear and peer pressures that all human stock pickers face, as well as the benefit of a non-biased quantitative approach to value investing.

Mount Lucas Focused Large Cap Value Strategy Information

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Stress Testing CTA Portfolios – Impact of Volatility Adjusting Positions

In light of recent market performance, and the corresponding effect on changes in volatility on CTA returns we thought it important to give our views on the topic. Late last year, we were asked by a prospective client to see how one of our trend following models performed over several different stress environments. We highlight one particular stress that was given- a 20% stock market drop over 3 months, with 40% of move in month 1, 35% in month 2, and the last 25% of the move in month 3. A relatively straightforward exercise, but to really understand the nuances of different CTAs relative to our approach, you must look past just the change in level, but consider the potential price paths and volatility over that stress period. The difference boils down to whether one is viewing CTAs as a standalone investment, or as a piece of a larger portfolio, and the role of volatility targeting in position sizing.
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With Friends Like These…

There is a saying in our business,”the trend is your friend.” Given the recent downturn in trend following returns, I am reminded of another saying, “with friends like these, who needs enemies.” I was in a meeting recently with a consultant who asked a question we have heard many times over the years. How do you keep clients invested in managed futures in times like these? We know the history, the diversification benefits, the crisis protection, the long volatility profile…but, each time there is an extended period of challenging performance clients look to throw in the towel – because their equity investments are ripping up and managed futures is down. A good question, and the answer, I think, lies in the statement – it is a matter of faith.

Investors in the equity market have faith. They trust, and have been conditioned, that the market goes up over time, corrections are temporary. Participating in the capital formation of companies provides a risk premium to the investor and is an investment in the economic growth of a country.

Managed futures on the other hand is viewed as a trading strategy, it goes long and short, it is typically quantitative based. The perception is…I can’t have faith in a model, it can break. But this perception is misplaced, trend following measures a real economic risk premium in the market, just like equities (see older posts diving deeper on this topic, Portfolio Symmetry, Commodities are not Stocks, Benchmarking Alternative Beta). Investors in this market are rewarded by taking the price risk companies seek to shed. Faith should be in the durability of this premium, just like there is in the equity risk premium. Faith is gained by understanding this risk premium, when it works (periods of volatility and instability), and when it doesn’t (periods of low volatility and stability). Similar to equities, faith should be garnered from the underlying economics of the markets.

Algorithm Aversion: On Models and The Donald

Whatever your politics, one can’t help but be fascinated by the Trump phenomenon. One interesting aspect is how pollsters got Trump wrong. We can get insight into that mistake from Nate Silver at fivethirtyeight. To his immense credit, Silver admits he got Trump all wrong, and went back to have a look at the why and the how…. it boils down to a case of algorithmic aversion (see here and here).

Silver’s approach to forecasting, which has been extremely successful across a wide range of subjects, is based on aggregating data from multiple polls to build as big a sample as possible. It is a mechanical, quantitative, model based, statistical method. The model spits out an answer, and that is forecast. But in the Trump case, he over-rode the model. He had a bias, and in this instance he applied it to his forecast, and voila, a bad outcome. Even Silver, a devoted algorithmist if there ever was one, fell into the trap. He did not trust the model, even though it had been right so many times before.

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