A Pioneering Approach To Earnings Season - Q1 2017

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Includes: CRF, DDM, DIA, DOG, DXD, EEH, EPS, EQL, FEX, FWDD, HUSV, IVV, IWL, IWM, JHML, JKD, OTPIX, PPLC, PPSC, PSQ, QID-OLD, QLD, QQEW, QQQ, QQQE, QQXT, RSP, RWL, RWM, RYARX, RYRSX, SBUS, SCAP, SCHX, SDOW, SDS, SFLA, SH, SMLL, SPDN, SPLX, SPSM, SPUU, SPXE, SPXL, SPXN, SPXS, SPXT, SPXU-OLD, SPXV, SPY, SQQQ, SRTY, SSO, SYE, TNA, TQQQ, TWM, TZA, UDOW, UDPIX, UPRO, URTY, USSD, USWD, UWM, VFINX, VOO, VTWO, VV
by: Julien Messias

Summary

We are still in a very low earnings-volatility mood.

Outperformance from small caps and high-beta sectors.

A positive momentum can be exhibited as Post Earnings Drift.

As for the former earnings season, signals are rather positive until the next Q2 2017 season.

Summary

US Q4 2016 earnings season was one of the quietest ever. What about Q1 2017 (from 2017, Apr 1st to 2017, May 31st)? Things tend to keep calm. Let's have a more precise look:

We presented in the previous article our Pioneering Quantitative Approach focusing on prices and not on fundamental data:

Our analysis provides a guide per sector and per capitalization.

For more information, you can refer to the original paper by the author, Post Earnings Announcement Drift, a Price Signal?

Important: in the following development, return always refers to relative actuarial return of the stock versus its index (total-return).

NASDAQ COMPOSITE - CCMP: average capitalization (<1BlnUSD excluded):13.7Bln

Our sample - before cleaning for the 1Bn$ capitalization takes 1607 earnings into account. After the filter, only 631 remain.

Raw statistics

On average, return is +0.31%, median is +0.34%, meaning that the distribution seems to be quite symmetrical. In absolute terms, the average move is 4.19% (vs. 4.06% for Q4 2016, 4.77% for Q3 2016, 4.42% for Q2 2016, 4.16% for Q1 2016, 5.42% for Q4 2015, 4.86% for Q3 2015 and 4.52% for Q2 2015). This is one of the quietest earnings season since the beginning.

Q2 2015

Q3 2015

Q4 2015

Q1 2016

Q2 2016

Q3 2016

Q4 2016

Q1 2017

Average volatility

4.52%

4.86%

5.42%

4.16%

4.42%

4.77%

4.06%

4.19%

Source: Bloomberg, Uncia AM.

Source: Bloomberg, Uncia AM.

By capitalization

Source: Bloomberg, Uncia AM. The bar chart lays between the 1st and 3rd quartile for each market capitalization percentile. The grey spot stands for the median.

Earnings signals

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), on a weekly basis, as a weekly compilation of buy and sell signals since Ytd (in red, LHS), since 2003, Jan 3rd (in red, RHS).

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), compared to the relative returns (absolute return of the stock minus the return of the total return index return) between the first price taking the full earnings information into account to the close price of 2017, Jun 02nd.

We can notice that:

- Volatility is quite low compared to historical data

- Small capitalizations and high-beta sectors (such as IT) perform best

- A positive momentum can be exhibited as Post Earnings Drift

RUSSELL 2000 - RTY: average capitalization (<1BlnUSD excluded):2.2Bln

Our sample - before cleaning for the 1Bn$ capitalization takes 1.441 earnings into account. After the filter, only 669 remain.

Raw statistics

On average, return is +0.27%, median is +0.35%, meaning that the distribution for this small caps is, as for CCMP, quite symmetrical: more negative large moves than negative. In absolute terms, the move is 4.23% (vs. 4.19% for Q4 2016, 4.78% for Q3 2016, 4.51% for Q2 2016, 4.10% for Q1 2016, 5.44% for Q4 2015, 5.01% for Q3 2015 and 4.49% for Q2 2015).

Q2 2015

Q3 2015

Q4 2015

Q1 2016

Q2 2016

Q3 2016

Q4 2016

Q1 2017

Average volatility

4.49%

5.01%

5.44%

4.10%

4.51%

4.78%

4.19%

4.23%

Source: Bloomberg, Uncia AM.

By capitalization

Source: Bloomberg, Uncia AM. The bar chart lays between the 1st and 3rd quartile for each market capitalization percentile. The grey spot stands for the median.

By Bloomberg sectors

Source: Bloomberg, Uncia AM. We only keep sectors for which we have at least 30 earnings.

Earnings signals

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), on a weekly basis, as a weekly compilation of buy and sell signals since Ytd (in red, LHS), since 2003, Jan 3rd (in red, RHS).

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), compared to the relative returns (absolute return of the stock minus the return of the total return index return) between the first price taking the full earnings information into account to the close price of 2017, Jun 02nd.

Same conclusions as the ones for CCMP:

- Volatility is quite low compared to historical data

- Small capitalizations and high-beta sectors (such as IT) perform best

- A positive momentum can be exhibited as Post Earnings Drift

S&P 500 - SPX: average capitalization: 44.6Bln

Our sample is composed by 461 earnings releases.

Raw statistics

On average, return is -0.17%, median is +0.36%, meaning the distribution is left-skewed (different from CCMP and RTY). In absolute terms, the average move is 3.21% (vs. 3.01% for Q42016, 3.51% for Q3 2016, 3.00% for Q2 2016, 3.17% for Q1 2016, 3.87% for Q4 2015, 3.47% for Q3 2015 and 3.20% for Q2 2015), and in absolute terms, blue chips from SPX tend to move less than other companies.

Q2 2015

Q3 2015

Q4 2015

Q1 2016

Q2 2016

Q3 2016

Q4 2016

Q1 2017

Average volatility

3.20%

3.47%

3.87%

3.17%

3.00%

3.51%

3.01%

3.21%

Source: Bloomberg, Uncia AM.

By capitalization

Source: Bloomberg, Uncia AM. The bar chart lays between the 1st and 3rd quartile for each market capitalization percentile. The grey spot stands for the median.

By Bloomberg sectors

Source: Bloomberg, Uncia AM. We only keep sectors for which we have at least 30 earnings.

Earnings signals

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), on a weekly basis, as a weekly compilation of buy and sell signals since Ytd (in red, LHS), since 2003, Jan 3rd (in red, RHS).

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), compared to the relative returns (absolute return of the stock minus the return of the total return index return) between the first price taking the full earnings information into account to the close price of 2017, Jun 02nd.

We can notice that:

- Volatility is quite low compared to historical data

- SPX is a large cap index, so it exhibits lower earnings returns than CCMP or RTY, with a left-skewed pattern

- Outperformance of high-beta sectors (NYSE:IT)

- A positive momentum can be exhibited as Post Earnings Drift

NASDAQ 100 - NDX: average capitalization: 74.0Bln

Our sample is only composed by 99 earnings releases, making the analysis by far more difficult, out of 107 components as of May 2017.

Raw statistics

On average, return is +0.05%, median is +0.45%, meaning that the distribution is - as for SPX - negatively skewed. In absolute terms, the average move is 3.93% (vs. 3.54% for Q4 20164.08% for Q3 2016, 3.97% for Q2 2016, 4.54% for Q1 2016, 4.95% for Q4 2015, 4.41% for Q3 2015 and 4.72% for Q2 2015).

Q2 2015

Q3 2015

Q4 2015

Q1 2016

Q2 2016

Q3 2016

Q4 2016

Q1 2017

Average volatility

4.72%

4.41%

4.95%

4.54%

3.97%

4.08%

3.54%

3.93%

Source: Bloomberg, Uncia AM.

By capitalization

Not relevant as we have not enough data.

By Bloomberg sectors

Not relevant as we have not enough data.

Earnings signals

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), on a weekly basis, as a weekly compilation of buy and sell signals since Ytd (in red, LHS), since 2003, Jan 3rd (in red, RHS).

Source: Bloomberg, Uncia AM. This chart shows the earnings signal (according to the methodology explained in the paper [1]), compared to the relative returns (absolute return of the stock minus the return of the total return index return) between the first price taking the full earnings information into account to the close price of 2017, Jun 02nd.

We can notice that:

- Volatility is quite low compared to historical data

- As for SPX, NDX is a large cap index, so it exhibits lower earnings returns than CCMP or RTY, with a left-skewed pattern

- A positive momentum can be exhibited as Post Earnings Drift

CONCLUSION

This empirical study emphasizes many things:

1/ We are still in a very low earnings-volatility mood

2/ Out-performance from small caps and high-beta sectors

3/ A positive momentum can be exhibited as Post Earnings Drift

4/ As for the former earnings season, signals are rather positive until the next Q2 2017 season.

Disclosure: I/we 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. I have no business relationship with any company whose stock is mentioned in this article.