**XRT vs. GLUX.MI vs. ^IXIC**

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This report examines whether investing in luxury brands ETF is more profitable than investing in mass brands producers (retail brands ETF) or the Nasdaq composite (INDEXNASDAQ: IXIC) (ETF: NASDAQ: ONEQ).

The objective is to assess past performance data to identify the most profitable investment amongst the three. The returns and the risk profiles of the three are analyzed in this report for definitive answers.

Luxury brands, of course, have a higher profit margin compared to mass brands. The obvious reason being that their products, in terms of competitive advantage and value proposition, offer "more for more." This means that while they provide goods that, arguably, are differentiated from the mass market producers, spuriously or otherwise, they also charge comparatively higher amounts for every marginal labor input (per hour of labor worked). However, does this increase their profits and growth? Are they a better investment compared to mass brands or Nasdaq composite index?

Mass goods producers, on the other hand, usually operate on the strategy of price leadership, and face highly competitive markets compared to other highly differentiated brands. Their value proposition, and competitive advantage, generally, can be stated as 'same for less,' or even "less for less" for some. This means that due to competitive pressures, comparatively, they shouldn't be able to charge more money per marginal labor input, and their profits, per unit sold, should be lower compared to luxury brands.

Mass goods, of course, attract more people, and more people consume goods from brands producing affordable consumer products. Nonetheless, incomes have been steadily rising around the globe, and if this means that purchasing power has increased as well, luxury goods should have seen booming profits and growth. . . is this the case though? We shall examine this in this report. What about the broader Nasdaq composite index, shouldn't it provide equivalent profits and a more diversified exposure and thus lower risk? Which one amongst the three is a better investment?

For investing in specific sectors under scrutiny in this report, some investors and family offices may be able to pick and choose individual stocks; for most investors, the ETF approach is the most likely to be implemented. Thus, for the luxury goods, **Ammundi S&P Global Luxury ETF (GLUX.MI)** is used as a proxy for luxury brands manufacturers, and it compared against SPDR S&P Retail ETF (XRT), which is used as a proxy for the mass brands manufacturers; arguably, there are the two most prominent ETFs in the sectors in question. **Nasdaq composite index (INDEXNASDAQ: .IXIC) is also compared against (GLUX.MI).**

These questions are answered in this report utilizing 2+ decades of data altogether. Hypothesis testing is implemented to test the returns and the risk of the three in question (below, after the key takeaways section, which provides a summary):

**Long term growth rate (geometric mean) of the 3:**

**1. Long-term growth rate for **Ammundi S&P Global Luxury ETF (GLUX.MI) is 12%.

**2. Long-term growth rate for **SPDR S&P Retail ETF (XRT) is 13.3%

**3. Long-term growth rate for **Nasdaq composite (INDEXNASDAQ:. IXIC) is 16.5%

### Key Takeaways

The data reveals that the returns of the three in question are identical; this means that statistical evidence, with a 98% confidence level, shows that the returns of GLUX, XRT, and Nasdaq have been statistically identical in the data examined. It would thus be logical to expect the returns to remain the same in the future.

The capital growth rate provided by the retail sector, as measured by the retail goods ETF (standing at 13.3%) and the luxury goods ETF (standing at 12%), are practically identical, with retail having a slight edge of 1.3%. Nasdaq's growth rate for the same period stands at 16.5%; this means that, while statistically identical, incremental smaller movements in Nasdaq's favor have, over time, resulted in its growth rate being slightly higher than the other two in question.

Analysis of the three risk profiles reveals that the retail goods ETF and the Luxury goods ETF **do not have **a similar level of risk associated with returns, as measured by the variance. Surprisingly, the luxury goods ETF has a lower level of risk associated with returns, compared to the retail sector ETF. This condition may be considered paradoxical by some, as luxury products producing firms should have a higher beta than the overall retail sector and thus a higher risk than mass retail brands; this, of course, isn't what the data suggests.

This condition illustrates that the demand for the luxury goods of the firms included in the ETF, is relatively stable, and thus, their returns do not experience a level of variance as the retail firms do. It is, however, also important to note that the difference in risk isn't very high.
Does this mean that GLUX is a good investment? Well, let's not jump to conclusions just yet. The returns of all three, as explained earlier, are statistically similar; however, overall, comparing Nasdaq **(IXIC) with the three, it does stand out as a superior option** when assessing past performance. Its long-term growth rate 0f 16.5 percent is slightly higher than the other two, yet its risk, as measured by the variance of returns, is similar to GLUX; it thus stands out as the superior investment.

Presently, other than specific exposure requirements to the retail sector, or the companies in the luxury goods ETF, buying and holding XPT or GLUX ETFs doesn't seem like a good general investing strategy. Buying the Nasdaq composite index provides exposure to lower risk compared to the retail sector specifically and similar risk as the Luxury goods manufacturers.

Furthermore, while raising incomes over time may result in greater demand for high-end products, demand increase is expected to be incremental. While some names in the broader ^IXIC (ETF: NASDAQ: ONEQ), especially tech names, may, through innovation, increase their growth at a rate much higher than the incremental demand increase for high-end products, the same cannot be said about high-end brands.

Finally, it is also important to assess the P/E ratio of the ETF of interest before committing long-term. Investors should examine whether the P/E ratio is exorbitantly high compared to the past figures. It wouldn't be prudent to buy or hold an investment that is acutely overvalued and thus may experience a price readjustment event. Presently, the P/E ratio of Nasdaq is on the higher end.

That being said, in terms of this analysis, the Nasdaq composite index stands out (ETF:NASDAQ: ONEQ) compared to the other two. If the P/E ratio is near historical levels, the investor should favor it, compared to the other two assessed in this report.

The two tests conducted in this report for the three in question are the pooled variance test and F test.

The pooled variance test is conducted as:

Pooled variance test is conducted as:

H0: µ1 -µ2 = 0, vs H1: µ1 -µ2 ≠ 0

The mean returns of 1st minus 2nd (comparison) are analyzed for equivalence.

F test is conducted as:

F test has been conducted as:

H0: σ1 = σ2, vs H1: σ1 ≠ σ2

The variance of the returns of 1st is compared to the variance of the returns of 2nd (comparison) to assess equivalence.

**Comparison of returns and risk of Ammundi S&P Global Luxury ETF (GLUX.MI) vs SPDR S&P Retail ETF (XRT), Pooled variance test, and F test, and long-term growth rate (results):**

__Two sample t-test (pooled variance), using T distribution (DF=750.0000) (two-tailed) (validation)__

** 1. H0 hypothesis**
Since p-value > α, H0 is accepted.
The average of

**GLUX's**population is considered to be

**equal to**the average. of the

**XRT's**population. In other words, the difference between the average of the

**two**populations is not big enough to be statistically significant.

**p-value equals**

__2. P-value__**0.870848**, ( p(x≤T) = 0.435424 ). This means that if we would reject H0, the chance of type I error (rejecting a correct H0) would be too high: 0.8708 (87.08%). The larger the p-value the more it supports H0.

**The test statistic T equals**

__3. The statistics__**-0.162637**, is in the 98% critical value accepted range: [-2.3313 : 2.3313]. x1-x2=-0.00038, is in the 98% accepted range: [-0.005500 : 0.001775]. The statistic S' equals 0.00234

**The observed standardized effect size is**

__4. Effect size__**small**(0.012). That indicates that the magnitude of the difference between the average and average is small.

**F TEST assessing risk:**

__F test for variances, using F distribution (dfnum=375,dfdenom=375) (two-tailed) (validation)__

** 1. H0 hypothesis**
Since p-value < α, H0 is rejected.
The sample standard deviation (S) of

**GLUX's**population is considered to be

**not equal to**the sample standard deviation (S) of

**XRT's**population. In other words, the difference between the sample standard deviation (S) of the

**two**populations is big enough to be statistically significant.

**The p-value equals**

__2. P-value__**0.00005223**, ( p(x≤F) = 0.00002611 ). It means that the chance of type I error (rejecting a correct H0) is small: 0.00005223 (0.0052%). The smaller the p-value the more it supports H1.

**The test statistic F equals**

__3. The statistics__**0.6573**, which is not in the 98% region of acceptance: [0.7861 : 1.2722]. S1/S2=0.81, is not in the 98% region of acceptance: [0.8866 : 1.1279]. The 98% confidence interval of σ12/σ22 is: [0.5167 , 0.8362].

**Comparison of returns and risk of Ammundi S&P Global Luxury ETF (GLUX.MI) vs Nasdaq composite index **(INDEXNASDAQ: .IXIC)**, Pooled variance test, and F test, and long-term growth rate (results):**

__Two sample t-test (pooled variance), using T distribution (DF=750.0000) (two-tailed) (validation)__

** 1. H0 hypothesis**
Since p-value > α, H0 is accepted.
The average of

**GLUX's**population is considered to be

**equal to**the average. of the ^

**IXIC's**population. In other words, the difference between the average of the

**two**populations is not big enough to be statistically significant.

**p-value equals**

__2. P-value__**0.720915**, ( p(x≤T) = 0.360458 ). This means that if we would reject H0, the chance of type I error (rejecting a correct H0) would be too high: 0.7209 (72.09%). The larger the p-value the more it supports H0.

** 3. The statistics**
The test statistic T equals

**-0.357370**, is in the 98% critical value accepted range: [-2.3313 : 2.3313]. x1-x2=-0.00070, is in the 98% accepted range: [-0.004600 : 0.001775]. The statistic S' equals 0.00197

**The observed standardized effect size is**

__4. Effect size__**small**(0.026). That indicates that the magnitude of the difference between the average and average is small.

**F TEST assessing risk:**

__F test for variances, using F distribution (dfnum=375,dfdenom=375) (two-tailed) (validation)__

** 1. H0 hypothesis**
Since p-value > α, H0 is accepted.
The sample standard deviation (S) of

**GLUX's**population is considered to be

**equal to**the sample standard deviation (S) of

**IXIC's**population. In other words, the difference between the sample standard deviation (S) of the

**two**populations is not big enough to be statistically significant.

**The p-value equals**

__2. P-value__**0.02144**, ( p(x≤F) = 0.9893 ). It means that the chance of type I error, rejecting a correct H0, is too high: 0.02144 (2.14%). The larger the p-value the more it supports H0.

**The test statistic F equals**

__3. The statistics__**1.2687**, which is in the 98% region of acceptance: [0.7861 : 1.2722]. S1/S2=1.13, is in the 98% region of acceptance: [0.8866 : 1.1279]. The 98% confidence interval of σ12/σ22 is: [0.9973 , 1.614].

DATA:

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