Overseas Chinese Equities, Aequitas Research

Ming Lu

Overseas Chinese Equities

IPOs and Placements coverage across Asia Pacific

Aequitas Research

We cover all listing across the Asia Pacific along with follow-up placements. As of Dec 2020, our team had covered 539 IPOs with a hit rate of 73.5% and 685 placements with a hit rate of 66.8%.

We combine fundamental bottom-up views with our proprietary quantitative framework to provide a holistic coverage across new listings and placements. Our coverage includes pre-IPO notes before the deal is launched, follow-up analysis once the deal is live and post-listing trading analysis as well.

Equity Bottom-Up

<ul>
<li>The main competitor, Huawei Group, decided to sell one of its two smartphone brands.</li>
<li>Xiaomi took all the smartphone market share that Huawei Group left behind.</li>
<li>Xiaomi’s revenue growth rate jumped to 35% yoy in 3Q20 versus 3% yoy in 2Q20.</li>
<li>However, so far, we believe the company is slightly overvalued.</li>
</ul>


The main competitor, Huawei Group, decided to sell one of its two smartphone brands.
Xiaomi took all the smartphone market share that Huawei Group left behind.
Xiaomi’s revenue growth rate jumped to 35% yoy in 3Q20 versus 3% yoy in 2Q20.
However, so far, we believe the company is slightly overvalued.


Xiaomi (1810 HK): Taking Advantage of Huawei’s Sale of Smartphone Brand, But Overvalued

Korea / Special Sits, Pairs, Index Rebalancing, Clepsydra Capital

Sanghyun Park

Korea / Special Sits, Pairs, Index Rebalancing

Event-Driven

Samsung Electronics Pref Shares / Event-Driven

<p>Samsung 1P now sits at a 5.6% discount, which is, of course, an all-time low.</p><p>The 20D sigma is +2.5, making a 3 sigma move just on two trading days.</p><table class="table table-striped">
<colgroup>
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"% of sigma"}'>% of sigma</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.517259424016804}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">251.73%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-1"}'>T-1</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.9255158585598584}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">192.55%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-2"}'>T-2</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.4760512302132772}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">-47.61%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-3"}'>T-3</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.4911350310822193}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">49.11%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-4"}'>T-4</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.2395746114046869}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">23.96%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-5"}'>T-5</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.33902659344623726}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">33.90%</td>
</tr>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><table class="table table-striped">
<colgroup>
<col width="210">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Metric"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Metric</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Price ratio"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Price ratio</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Discount"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Discount</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Δ"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Δ</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.944141689373297}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-35]C[2]">0.94414</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.055858310626702996}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-35]C[0]">5.59%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D mean"}'>120D mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8807517345708635}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C4:R100C4)">0.88075</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.11924826542913641}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(Data!R2C3:R100C3)">11.92%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.07197255743506373}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">7.20%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D median"}'>120D median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8724137931034482}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C4:R100C4)">0.87241</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.12758620689655173}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R100C3)">12.76%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.08221774671247488}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">8.22%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D high"}'>120D high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.944141689373297}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C4:R100C4)">0.94414</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.1552901023890785}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(Data!R2C3:R100C3)">15.53%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">0.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D low"}'>120D low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8447098976109215}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C4:R100C4)">0.84471</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.055858310626702996}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(Data!R2C3:R100C3)">5.59%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.11771117166212532}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">11.77%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y mean"}'>1Y mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8631967757116901}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C4:R248C4)">0.86320</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.13680322428831074}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(Data!R2C3:R248C3)">13.68%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.09377341984956945}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">9.38%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y median"}'>1Y median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8611955420466059}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C4:R248C4)">0.86120</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.13880445795339413}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R248C3)">13.88%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.09631511460169902}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">9.63%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y high"}'>1Y high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.944141689373297}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C4:R248C4)">0.94414</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.19375}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(Data!R2C3:R248C3)">19.38%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">0.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y low"}'>1Y low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.80625}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C4:R248C4)">0.80625</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.055858310626702996}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(Data!R2C3:R248C3)">5.59%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.17102845193587224}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">17.10%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y mean"}'>2Y mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8403504527382868}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C4:R476C4)">0.84035</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.15964954726171324}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(Data!R2C3:R476C3)">15.96%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.1235094671476714}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">12.35%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y median"}'>2Y median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8325991189427313}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C4:R476C4)">0.83260</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.16740088105726872}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R476C3)">16.74%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.13396911898274294}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">13.40%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y high"}'>2Y high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.944141689373297}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C4:R476C4)">0.94414</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.21040723981900453}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(Data!R2C3:R476C3)">21.04%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">0.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y low"}'>2Y low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7895927601809954}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C4:R476C4)">0.78959</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.055858310626702996}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(Data!R2C3:R476C3)">5.59%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.19573245473638193}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">19.57%</td>
</tr>
<tr><td colspan="4" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/178/161/original/chart%20%282%29.png?1607898160" class="editor-image img-responsive" data-smartkarma-image-id="178161"></figure></section><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/178/162/original/chart%20%283%29.png?1607898169" class="editor-image img-responsive" data-smartkarma-image-id="178162"></figure></section>

Samsung 1P now sits at a 5.6% discount, which is, of course, an all-time low.The 20D sigma is +2.5, making a 3 sigma move just on two trading days.





% of sigma

Today
251.73%


T-1
192.55%


T-2
-47.61%


T-3
49.11%


T-4
23.96%


T-5
33.90%

Source: KRX










Metric
Price ratio
Discount
Δ


Today
0.94414
5.59%
-


120D mean
0.88075
11.92%
7.20%


120D median
0.87241
12.76%
8.22%


120D high
0.94414
15.53%
0.00%


120D low
0.84471
5.59%
11.77%


1Y mean
0.86320
13.68%
9.38%


1Y median
0.86120
13.88%
9.63%


1Y high
0.94414
19.38%
0.00%


1Y low
0.80625
5.59%
17.10%


2Y mean
0.84035
15.96%
12.35%


2Y median
0.83260
16.74%
13.40%


2Y high
0.94414
21.04%
0.00%


2Y low
0.78959
5.59%
19.57%

Source: KRX



Samsung 1P Discount Sets a New All-Time Low at 5.6%: Main Factor Behind It

24 local brokerages cover Samsung Electronics. FnGuide tracks them, and the consensus now sits at a ₩37.01T full-year OP.










FnGuide consensus (₩B)
2020. 12. 14
T-1M
T-3M
T-6M
T-1Y


Sales
238,193.5
238,680.4
233,927.8
231,198.0
255,507.1


OP
37,013.8
37,207.4
32,862.2
32,261.0
37,529.6


NP to controlling stake
27,564.8
27,710.8
24,778.3
24,912.5
29,005.9


EPS (₩)
4,058
4,080
3,648
3,668
4,270


PER (x)
18.10
15.50
16.20
14.30
12.80


12M PER (x)
14.30
12.50
12.94
11.85
12.81


TP (₩)
81,967
76,400
72,592
65,000
61,477

Source: FnGuide

How Samsung would calculate FCF remains a secret. But the below widely-accepted formula shows that Samsung will likely be 10%p short of hitting the 3-yr 50% target.It will leave a ₩6.5T room to fill up. Assuming full allocation to special dividends, I expect a ₩950 special dividend for ord (₩951 for 1P).* The median FCF of the 24 local brokerages also falls on ₩6.8T.









3-yr shareholder return as a % of FCF (₩T)
2018
2019
2020E
3-yr total


FCF
28.9
14.1
27.6
70.7


1. OCF
91.1
62.3
79.7
233.1


1.1 After-tax OP
42.7
19.8
26.4
-


- OP
58.9
27.8
37.0
-


- Effective tax rate
27.49%
28.57%
28.57%
-


1.2 Expenses not involving cash outflows
48.4
42.4
53.3
-


2. Investment
62.2
48.1
52.1
-


2.1 Invested capital
36.4
36.1
38.2
-


- Non-current assets (ending)
164.7
171.2
179.7
-


- Non-current assets (beginning)
154.8
164.7
171.2
-


- D&amp;A
26.5
29.6
29.6
-


2.2 Δ NOWC
25.8
12.0
14.0
-


- Current assets
174.7
181.4
193.4
-


- Current liabilities
69.1
63.8
61.9
-


- NOWC
105.6
117.6
131.6
-


Dividends
9.6
9.6
9.6
28.9


- Dividends as a % of FCF
33.24%
68.00%
34.87%
40.83%


Buyback
0
0
0
0.0


- Buyback as a % of FCF
0.00%
0.00%
0.00%
0.00%


Dividends+buyback
9.6
9.6
9.6
28.9


- Dividends+buyback as a % of FCF
33.24%
68.00%
34.87%
40.83%

Source: DART, SEIBro, &amp; FnGuide







3-yr shareholder return as a % of FCF (₩T)

FCF
70.7


: 50%
35.3


Dividends+buyback
28.9


: Room to fill up
6.5

Source: DART, SEIBro, &amp; FnGuide







Special dividends (₩T)

Room to fill up
6.5


Common DPS
₩950


: Dividends
5.7


1P DPS
₩951


: Dividends
0.8


Total dividends
6.5

Source: DART, SEIBro, &amp; FnGuide

Full-year div yield will be 3.22% for ord and 3.42% for 1P. Interim div-adjusted yield will sit at 1.78% for ord and 1.88% for 1P.





Special div-adjusted div yield (₩T)

Common DPS (incl. special div)
₩2,366


: Price
₩73,400


: Dividend yield
3.22%


1P DPS
₩2,368


: Price
₩69,300


: Dividend yield
3.42%

Source: DART, SEIBro, &amp; FnGuide







Special &amp; interim div-adjusted div yield

Common DPS (incl. special div)
₩1,304


: Price
₩73,400


: Dividend yield
1.78%


1P DPS (incl. special div)
₩1,306


: Price
₩69,300


: Dividend yield
1.88%

Source: DART, SEIBro, &amp; FnGuide



Founder/CEO of ROK Advisory, ROK Advisory LLC

Ken S. Kim

Founder/CEO of ROK Advisory

ROK Advisory LLC

ROK is an independent research advisory firm. We guide you to minimize the information gap between foreign and local investors in Northeast Asia with a focus in Korea, Taiwan and Japan.

Independent Research Advisory Firm

Thematic (Sector/Industry)

<p>There has been talks that Sammy capital expenditure ("capex) will be lower vs. their original guide due to an equipment manufacturers conservative guidance due to uncertainty in 2H21.   Is <a href="https://www.smartkarma.com/entities/samsung-electronics-co-ltd" target="_blank" data-smartkarma-citation="entities:191:1" rel="noopener">Samsung Electronics (005930 KS)</a> cutting up to 20% of their original capital expenditure guidance or is there something else to this? The latter in my view. </p>

There has been talks that Sammy capital expenditure ("capex) will be lower vs. their original guide due to an equipment manufacturers conservative guidance due to uncertainty in 2H21.   Is Samsung Electronics (005930 KS) cutting up to 20% of their original capital expenditure guidance or is there something else to this? The latter in my view. 

Is Samsung Electronics Cutting 2021 Capex with Its New Leadership Change?

Managing Director

Elan Gore

TMI Data Science

TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade & traditional media.  Our proprietary software, TMI Machine, is a text-mining platform designed with the buy-side & capital markets professional in mind, text-mining the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income & individual equities.  TMI provides custom leading indicators and systematic trading strategies, operating at the nexus of linguistics & statistics drawing on vast experience in investment banking and hedge fund settings in senior quantitative and fundamental roles.  

TMI Data Science was founded by Elan Gore, an award-winning Senior Global Basic Materials Equity Analyst & China Economist with 15 years of experience in North American hedge funds & institutional managers; and Alessandro Porrino, Ph.D., an Algorithmic Trading Analyst and Programmer with 10 years of front-office experience ranging from complex FX option pricing to auto-hedging strategies at Bank of America Merrill Lynch and Standard Chartered.  Mr. Gore holds an MBA in Finance from New York University Stern School of Business, and Mr. Porrino holds a Ph.D. in Systems Engineering from Brunel University London.

Cross Asset Strategy

<ul>
<li>While short-term data has been out of favour as the market envisions a post-vaccine supercycle, our text-mining detects greater relative concern on Korean in the financial media over KRW strength and COVID case counts in recent weeks</li>
<li>Japan, for example, saw similar concerns emerge on surging case counts, but news sentiment has been supported by the recent 40tr JPY stimulus package vs. limited Korean measures</li>
<li>KRW/USD's +10% move is equivalent +2x STDEVs, similar to the magnitude of CNY appreciation in the same period, vs. low single-digit moves in JPY and TWD</li>
<li>Consensus suggests foreign inflows associated with a strong KRW are likely to push the KOSPI higher even if exporter earnings (and exports) are hampered by the currency</li>
<li>While we acknowledge the macro impact of COVID resurgence is merely transitory, a key driver in our recent news attribution is the sharp decline in Korean credit card spending as reported by Shinhan for the second half of November</li>
<li>Less transitory is the KRW, and 801 Korean exporters recent polled by the Korea International Trade Association (KITA) suggested the currency is already beyond their pain threshold</li>
</ul><div class="content-highlight"><p>TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. </p></div>


While short-term data has been out of favour as the market envisions a post-vaccine supercycle, our text-mining detects greater relative concern on Korean in the financial media over KRW strength and COVID case counts in recent weeks
Japan, for example, saw similar concerns emerge on surging case counts, but news sentiment has been supported by the recent 40tr JPY stimulus package vs. limited Korean measures
KRW/USD's +10% move is equivalent +2x STDEVs, similar to the magnitude of CNY appreciation in the same period, vs. low single-digit moves in JPY and TWD
Consensus suggests foreign inflows associated with a strong KRW are likely to push the KOSPI higher even if exporter earnings (and exports) are hampered by the currency
While we acknowledge the macro impact of COVID resurgence is merely transitory, a key driver in our recent news attribution is the sharp decline in Korean credit card spending as reported by Shinhan for the second half of November
Less transitory is the KRW, and 801 Korean exporters recent polled by the Korea International Trade Association (KITA) suggested the currency is already beyond their pain threshold
TMI Data Science utilizes Natural Language Processing to build custom leading indicators using unstructured data sourced from the global financial, trade &amp; traditional media. Our proprietary software text-mines the global media to discern and quantify nuanced qualitative shifts in press coverage as they apply to macroeconomics, equity indexes/ETFs, commodities, currencies, fixed income &amp; individual equities. 

TMI Snapshot:  Text-Mining Detects Potential Pullback in Korea Sentiment on KRW Rally & COVID Surge

South Korea

Samsung Electronics Co., Ltd. manufactures a wide range of consumer and industrial electronic equipment and products such as semiconductors, personal computers, peripherals, monitors, televisions, and home appliances including air conditioners and microwave ovens. The Company also produces Internet access network systems and telecommunications equipment including mobile phones.

Price Gauge
52-week Range	0.00 - 0.00
Market Cap (USDm)	0.00
P/E	0.00
Dividend (Yield)	0.00

Samsung Electronics (005930 KS)

Xiaomi (1810 HK): Taking Advantage of Huawei’s Sale of Smartphone Brand, But Overvalued

The main competitor, Huawei Group, decided to sell one of its two smartphone brands. Xiaomi took all the smartphone market share that Huawei Group...

Ming Lu

Samsung 1P Discount Sets a New All-Time Low at 5.6%: Main Factor Behind It

This insight examines the main factor behind Samsung Electronics' pref discount, which sets a new all-time low at 5.6% last Friday.

Sanghyun Park

Samsung Yr-End Special Dividend Update

This insight is an update on Samsung Electronics' year-end special dividend situation with a focus on the local street mood.

Sanghyun Park

Is Samsung Electronics Cutting 2021 Capex with Its New Leadership Change?

Is Samsung Electronics cutting 2021 capital expenditure in memory due to their leadership change or is there something else to it?

Ken S. Kim

TMI Snapshot: Text-Mining Detects Potential Pullback in Korea Sentiment on KRW Rally & COVID Surge

Our text-mining detects a potential pullback in Korea macro sentiment on rapid KRW appreciation and the COVID surge impacting credit card spending,...

Elan Gore

Price Gauge

52-week Range

Market Cap (USDm)

P/E

Dividend (Yield)