The Consumer Discretionary Sector encompasses those businesses that tend to be the most sensitive to economic cycles. Its manufacturing segment includes automotive, household durable goods, leisure equipment, and textiles & apparel. The services segment includes hotels, restaurants and other leisure facilities, media production and services, and consumer retailing and services.

Table 4.1: 10 largest companies in the S&P 500 Consumer Discretionary sector

Table 4.2: Individually relevant factors: S&P 500 Consumer Discretionary

Table 4.3 provides the strategy summary.

Table 4.3: Strategy description: S&P 500 Consumer Discretionary

The choice of factors has been made by testing. However, I want to verify that it is a reasonable hypothesis (see my definition of quantitative investing in Part I). In other words, it can be rationalised and interpreted. Here, the interpretation is to select companies that don’t pay a dividend, and have a high gross margin. They are companies more focused on growing their business than on paying shareholders an income.

It may look strange that the individually relevant factor (POR) is used only as a filter, and Gross Margin to rank companies. However simulation shows that the first rule used alone brings an additional annualised return of 3% to the reference set, and the second rule an additional annualised return under 1%. Together, they bring an additional annualised return of 5%. It means that the filter on POR is the primary source of gain.

Note that four of them have disappeared from the stock market as publicly traded companies: FTLAQ in 2002, KWP in 1999, MIR in 2000, RBK in 2006. However they are taken into account in simulations as long as they have been a part of the S&P 500 Index at one time.

Holdings and allocations are recalculated every four weeks. In case the rebalancing date is a holiday, it is done the next trading day. The buying and selling prices are taken on market opening. As a consequence, the approximation is made that all orders are simultaneous. In this case, “all orders” means two or less: the maximum turnover is 20% and less than 10% on average. S&P 500 companies are very liquid, so it is realistic to think that orders can be filled at open price or very close to it, at least for most individual investors. For a fund with a larger money allocation by holding, techniques can be used to optimise the average cost. I do not address this subject here.

[This short explanation is given as an example to show how it works – this explanation won’t be repeated for the following simulations.]

The total return is 696% (this takes into account transaction costs: about 24% for the whole period if we assume 0.1% per trade). The 61% drawdown is measured between the 2007 top and the 2008 low.

Two quick observations:

1. It would be impossible to obtain the same return by leveraging SPY: a 100% loss would be reached before the 2009 recovery.
2. The strategy recovers faster than the benchmark: it makes a new high as soon as early 2010, whereas SPY makes it in 2013.

It is said that the best fund managers have a Sharpe ratio around 0.8 on periods over a decade (in the real world, not in simulations). So, a Sharpe ratio of 0.44 is not amazing, but it is very good compared with SPY. The fact that the Sortino ratio is higher than the Sharpe ratio is also good: it shows that the deviations from the mean are stronger upward than downward. The risk (standard deviation) is higher than SPY, but it stays in the same 5% range. For a stock strategy, I consider that the correlation with the benchmark is really high above 0.7. Here, at 0.64, it is moderately high. The stock market moves are a prominent factor in the strategy performance, but not overly prominent.

Fig 4.1: Simulation data and equity curve: S&P 500 Consumer Discretionary

NB: due to a graphical issue, there is a gap in the time axis on all charts: all simulations end on 1/1/2014.

The return is much better than the non-hedged version, but the most impressive difference is in the max drawdown: it is divided by more than two (-61% previously, -27% here). Hedging has considerably smoothed market downturns. The Sharpe ratio is good, the Sortino ratio even better. Below 0.5, I consider that the correlation with SPY is low.

Fig 4.2: Simulation data and equity curve: S&P 500 Consumer Discretionary, Hedged

Table 4.4: Consistency over five-year periods

It looks a robust strategy for the long term, but Consumer Discretionary stocks are sensitive to economic cycles. As a consequence, the return may vary significantly over shorter terms.

Here are the factors from my working list that are individually relevant for the Russell 2000 Consumer Discretionary reference set:

Table 4.5: Individually relevant factors: Russell 2000 Consumer Discretionary

Table 4.6: Strategy description: Russell 2000 Consumer Discretionary

The rationalised interpretation is to select relatively cheap companies regarding their earnings estimate and free cash flow.

Russell 2000 companies are less liquid, thus a higher figure is used to model the transaction costs.

• The annualised return. Every investor has a different idea of what is a good return. Moreover, the return alone makes little sense without looking at the max drawdown and standard deviation. For strategies using a four-week rebalancing, my opinion is that an annualised return is attractive above 20%.
• The max drawdown. In absolute value, each investor must determine an acceptable threshold. I consider that a max drawdown beyond -40% is scary on an individual strategy. When designing a real portfolio combining various strategies, I try to keep it below 20%, knowing that it might be worse in the future.
• The Sharpe and Sortino ratios. In this context I consider that below 0.5 is bad, above 0.8 is good, above 1.5 is very good.
• The standard deviation alone makes little sense without looking at the annualised return. However you can compare it with the benchmark’s standard deviation: here 20% on the period. It gives a limit for separating relatively safe and relatively risky strategies.
• The correlation with the benchmark is not good or bad in itself. But as holding SPY all the time is a very risky strategy, a low correlation should be a positive clue. It is confirmed here: the best strategies in terms of risk-adjusted performance have a low correlation with SPY. Nevertheless, don’t make this a rule in all contexts.

Fig 4.3: Simulation data and equity curve: Russell 2000 Consumer Discretionary

Table 4.7: Consistency over five-year periods

The Consumer Staples Sector comprises companies whose businesses are less sensitive to economic cycles. It includes manufacturers and distributors of food, beverages and tobacco and producers of non-durable household goods and personal products. It also includes food & drug retailing companies as well as hypermarkets and consumer super centers.

Table 5.1: Stock examples: S&P 500 Consumer Staples

Table 5.2: Individually relevant factors: S&P 500 Consumer Staples

Table 5.3: Strategy description: S&P 500 Consumer Staples

The rationalised interpretation is to choose companies that are cheap relative to their earnings estimates, and with a good net profit margin.

Table 5.4: Consistency over five-year periods

The annualised return by five-year periods stays between 18% and 29%, which is remarkably stable. The sector is dominated by daily consumption products: it explains why companies are less sensitive to economic cycles.

Table 5.5: Individually relevant factors: Russell 2000 Consumer Staples

Table 5.6: Strategy description: Russell 2000 Consumer Staples

The rationalised interpretation is to select small companies that are not yet well known by institutional investors, and are cheap relative to earnings and expected growth.

Table 5.7: Consistency over five-year periods

We note the same stability in five-year performance. Conservative investors might consider overweighting the Consumer Staples sector in their stock portfolio.

The Energy Sector comprises companies engaged in exploration & production, refining & marketing and storage & transportation of oil & gas and coal & consumable fuels. It also includes companies that offer oil & gas equipment and services.

Table 6.1: Stock examples: S&P 500 Energy

Table 6.2: Individually relevant factors: S&P 500 Energy

Table 6.3: Strategy description: S&P 500 Energy

The rationalised interpretation is to select stocks that are cheap relative to the company’s accounting value.

Table 6.4: Consistency over five-year periods

It is a sector theoretically sensitive to economic cycles, nevertheless the hedged version shows an impressive stability for annualised returns in the three, five-year periods. In fact, it hides big differences from one year to another, especially since 2009: 2011 was a very bad year with a large drawdown and a negative annual return.

Table 6.5: Individually relevant factors: Russell 2000 Energy

Table 6.6: Strategy description: Russell 2000 Energy

The rationalised interpretation is to select companies that are focused on shareholders’ income, and that are cheap relative to sales. This is quite typical of energy infrastructure companies.

Table 6.7: Consistency over five-year periods

The Financials Sector contains companies involved in banking, thrifts & mortgage finance, specialized finance, consumer finance, asset management and custody banks, investment banking and brokerage and insurance. This Sector also includes real estate companies and REITs.

Table 7.1: Stock examples: S&P 500 Financials

Table 7.2: Individually relevant factors: S&P 500 Financials

Table 7.3: Strategy description: S&P 500 Financials

This rule selects the cheapest companies relative to their earnings.

Table 7.4: Consistency over five-year periods

Table 7.5: Individually relevant factors: Russell 2000 Financials

Table 7.6: Strategy description: Russell 2000 Financials

The rationalised interpretation is to pick the most profitable companies relative to their assets.

Table 7.7: Consistency over five-year periods

The Health Care Sector includes health care providers & services, companies that manufacture and distribute health care equipments & supplies and health care technology companies. It also includes companies involved in the research, development, production and marketing of pharmaceuticals and biotechnology products.

Table 8.1: Stock examples: S&P 500 Health Care

Table 8.2: Individually relevant factors: S&P 500 Health Care

Table 8.3: Strategy description: S&P 500 Health Care

The rationalised interpretation is to select cheap stocks relative to the next year’s earnings estimate.

Table 8.4: Consistency over five-year periods

1. an aging population and the baby-boom generation boosts the consumption of health care products and services in developed countries, and
2. the fast growth of a global middle class has the same effect in developing countries.

These phenomena should continue to lift the sector in the next decade, with possible bubbles on the way, especially in the biotechnology industry.

Table 8.5: Individually relevant factors: Russell 2000 Health Care

Table 8.6: Strategy description: Russell 2000 Health Care

Rationalised interpretation: this strategy selects cheap companies relative to sales. Because of the reference to sales, it excludes de facto young companies that are in a pure research and development stage. It prefers companies with an existing flow of products and services.

Table 8.7: Consistency over five-year periods

The Industrials Sector includes manufacturers and distributors of capital goods such as aerospace & defense, building products, electrical equipment and machinery and companies that offer construction & engineering services. It also includes providers of commercial & professional services including printing, environmental and facilities services, office services & supplies, security & alarm services, human resource & employment services, research & consulting services. It also includes companies that provide transportation services.

Table 9.1: Stock examples: S&P 500 Industrials

Table 9.2: Individually relevant factors: S&P 500 Industrials

Table 9.3: Strategy description: S&P 500 Industrials

The rationalised interpretation is to select companies that are cheap relative to their earnings.

Table 9.4: Consistency over five-year periods

Table 9.5: Individually relevant factors: Russell 2000 Industrials

The rationalised interpretation is to select companies that are cheap relative to their sales and free cash flow.

Table 9.6: Strategy description: Russell 2000 Industrials

Table 9.7: Consistency over five-year periods

The Information Technology Sector comprises companies that offer software and information technology services, manufacturers and distributors of technology hardware & equipment such as communications equipment, cellular phones, computers & peripherals, electronic equipment and related instruments and semiconductors.

Table 10.1: Stock examples: S&P 500 Information Technology

Table 10.2: Individually relevant factors: S&P 500 Information Technology

Table 10.3: Strategy description: S&P 500 Information Technology

Rationalised interpretation: this strategy selects companies that are cheap regarding first their accounting value and second their earnings.

Table 10.4: Consistency over five-year periods

Table 10.5: Individually relevant factors: Russell 2000 Information Technology

Table 10.6: Strategy description: Russell 2000 Information Technology

Rationalised interpretation: this strategy selects companies that are cheap relative to their cash flow, among those that have the best gross margin. Because of the reference to margin and cash flow, it excludes pure development-stage companies. In the following simulation, you can see that it would have resisted very well the dot-com crash (2000–2002) by avoiding weak business models. It should also help in case history repeats itself.

Table 10.7: Consistency over five-year periods

The Materials Sector includes companies that manufacture chemicals, construction materials, glass, paper, forest products and related packaging products, and metals, minerals and mining companies, including producers of steel.

Table 11.1: Stock examples: S&P 500 Materials

Table 11.2: Individually relevant factors

The rationalised interpretation is to select cheap companies relative to the free cash flow.

Table 11.3: Strategy description: S&P 500 Materials

Table 11.4: Consistency over five-year periods

Table 11.5: Individually relevant factors: Russell 2000 Materials

Table 11.6: Strategy description: Russell 2000 Materials

As in the S&P 500 version, the rationalised interpretation is to select cheap stocks regarding the price to free cash flow ratio.

Table 11.7: Consistency over five-year periods

The Telecommunication Services Sector contains companies that provide communications services primarily through a fixed-line, cellular or wireless, high bandwidth and/or fiber optic cable network.

Table 12.1: Stock examples: S&P 500 Telecommunication

This set of stocks is too small for elaborate statistical strategies. For this sector, I therefore propose a unique strategy with 10 holdings in the Russell 3000 index. At the time I write this, there are 39 telecommunication services companies in the Russell 3000.

Table 12.2: Individually relevant factors: Russell 3000 Telecommunication

Table 12.3: Strategy description: Russell 3000 Telecommunication

Rationalised interpretation: this strategy selects the cheapest companies relative to earnings estimate. The telecom sector was globally the hardest hit in the dot-com crash: taking all Russell 3000 Telecom stocks in equal weight, it is the only sector that is still in drawdown since the 2000 bubble.

Table 12.4: Consistency over five-year periods

The Utilities Sector comprises utility companies such as electric, gas and water utilities. It also includes independent power producers & energy traders and companies that engage in generation and distribution of electricity using renewable sources.

Table 13.1: Stock examples: S&P 500 Utilities

Table 13.2: Individually relevant factors: S&P 500 Utilities

Table 13.3: Strategy description: S&P 500 Utilities

This is a contrarian strategy because the second rule selects the companies with the weakest growth rate. But the first rule excludes companies that are significantly losing their market. The thinking behind this strange strategy is that among large Utilities companies, stability pays for the shareholder. In this reference set, the more boring the business, the better for investors. An element of importance is that this sector has a higher concentration of companies paying a high dividend.

Table 13.4: Consistency over five-year periods

Table 13.5: Individually relevant factors: Russell 2000 Utilities

Table 13.6: Strategy description: Russell 2000 Utilities

The selection is focused on cheap companies regarding their projected earnings.

Table 13.7: Consistency over five-year periods

Table 14.2: Individually relevant factors: DJ 30

Table 14.3: Strategy description: DJ 30

In other words, this means excluding the 10 most expensive companies regarding the PE ratio, then keeping the 10 most profitable regarding the return on assets.

Table 14.4: Consistency over five-year periods

To give a comparison, I have simulated a monthly version of the famous “Dogs of the Dow” strategy. It consists in selecting every four weeks the 10 stocks with the highest dividend yield (the original strategy is based on an annual rotation). The monthly Dogs of the Dow with my hedging tactics gives on the same period an average annual return of 15% (vs. 16% for our “lazy” DJ 30), a max drawdown of -34% (-23% for us) and a standard deviation of 17% (15% for us).

Our DJ 30 portfolio has a slightly higher return, and is significantly safer regarding drawdown and volatility. This conclusion is limited to the last 15 years, no claim is made for a longer period or for the future. Both strategies are comparable: they can be executed in a few minutes without the help of software, and have the same number of holdings in the same reference set.

All components of the S&P 500 are classified in their respective GICS sector, except for the Telecommunication Services sector which is grouped with Information Technology.

As a consequence:

• These indexes are based on the same classification as the S&P 500 lazy strategies, with the exception that IT also contains telecommunication stocks.
• They are more diversified as they hold all stocks in each sector.
• They are static: the membership is linked to the S&P 500 membership. A company enters or exits a sector index when it enters or exits the global index.

Table 15.1: Tickers of the Select Sector SPDR Fund series for GICS sectors

The annual net expense ratio is 0.17%. The nine ETFs have traded since 16 December 1998, which allows for a comparison on the whole backtest period.

Fig 15.1: Comparison of returns for lazy strategies v S&P Select Sector ETFs

It can be seen in Fig 15.1 that all the S&P 500 lazy strategies have superior annualised returns than their benchmarks. The minimum additional annualised return is 6%. The Financials and Information Technology sectors have the best results: more than 14% of additional annualised return.

Looking at Fig 15.2, lazy strategies have a lower or equal risk (standard deviation) in five sectors: Consumer Discretionary, Consumer Staples, Materials and Utilities. When the risk is higher, the maximum difference in standard deviation is 4%.

Fig 15.2: Comparison of standard deviation for lazy strategies v S&P Select Sector ETFs

Fig 15.3: Comparison of max drawdown for lazy strategies v S&P Select Sector ETFs

In five cases out of nine, lazy strategies have a deeper drawdown. The maximum difference in drawdown is 15% in Health Care.

The following bar chart compares the risk-adjusted returns measured by the Sortino ratio.

Fig 15.4: Comparison of Sortino ratios with static sector benchmarks

All the S&P 500 lazy strategies have a better risk-adjusted performance than their benchmarks. The minimum difference in Sortino ratio is 0.3.

Every quarter, all stocks in the Russell 1000 universe are given a growth score and a value score based on three price momentums and four quantitative fundamental factors. For a stock classified by Russell only as growth or only as value, the selection score is the score of its style. Otherwise, it is the best of both scores. In each sector, the bottom 25% is eliminated and the rest is ranked regarding the selection score and split into five subsets. The top subset has a capital allocation of 33.3%, the second has an allocation of 26.7%, the third has 20%, the fourth has 13.3%, the last has 6.7%. Within a subset, stocks have an equal weight.

There are notable differences with our lazy S&P 500 strategies:

• The reference sets are the Russell 1000 sectors, which are larger than the reference sets of S&P 500 lazy strategies.
• StrataQuant indexes are more diversified: they hold 75% of stocks in each sector.
• They are rebalanced quarterly, three times less frequently.
• The rules are more complicated.
• The rules are the same for all sectors.

Table 15.2: Tickers of the AlphaDEX fund series for GICS sectors

The annual net expense ratio for the funds is 0.7%. The nine AlphaDEX ETFs have traded since 8 May 2007. This is a shorter period, however it does include a bear market (2008–2009) and a bull market (2009–2013).

The logic of the bar charts is the same as in the previous section.

Fig 15.5: Comparison of returns for lazy strategies v AlphaDEX sector ETFs

In spite of using simpler rules and a smaller set of stocks, almost all the S&P 500 lazy strategies have a better or equal annualised return than the respective AlphaDEX sector ETFs. The only exception is the Information Technology sector, with a relative loss of -1.3%. The best relative gain is in Consumer Staples and Energy with a 7.5% difference in annualised returns.

Fig 15.6: Comparison of standard deviation for lazy strategies v AlphaDEX sector ETFs

Even more interesting, the volatility (standard deviation) of lazy strategies is mostly below the volatility of corresponding AlphaDEX funds, despite having fewer holdings. When lazy strategies have a higher volatility (Financials, Health Care and Industrials), the maximum difference is 1.3%. When lazy strategies are less volatile, the maximum difference in volatility is 6.5%. It represents a significantly lower risk.

Looking at Fig 15.7, in four cases out of nine, lazy strategies have a deeper drawdown. The maximum difference in drawdown is 19% in Health Care.

Fig 15.7: Comparison of max drawdown for lazy strategies v AlphaDEX sector ETFs

The following chart reports the Sortino ratios (no visible bar means ratio=0).

The S&P 500 lazy strategies have a better Sortino ratio than the AlphaDEX ETFs for five sectors. In the four other sectors they are equal. The largest advantage is in Consumer Staples.

Fig 15.8: Comparison of Sortino ratio for lazy strategies v AlphaDEX sector ETFs