Pan-Asia Index Rebalances/ Events/ Delta One, Periscope Analytics

Brian Freitas

Pan-Asia Index Rebalances/ Events/ Delta One

Quantitative Analysis

<div><p>The Asia Short Interest weekly looks at moves in market wide short interest and highlights movements in stock specific short interest across Hong Kong, Japan, Korea and Taiwan using the last available data published by the relevant authorities.</p></div><div><p>Hong Kong saw shorts rise on <a href="https://www.smartkarma.com/entities/tencent-holdings-ltd" target="_blank" data-smartkarma-citation="entities:26:1" rel="noopener">Tencent Holdings (700 HK)</a>, <a href="https://www.smartkarma.com/entities/ping-an-insurance-grp-co-of-china-ltd" target="_blank" data-smartkarma-citation="entities:12880:1" rel="noopener">Ping An Insurance (H) (2318 HK)</a>, <a href="https://www.smartkarma.com/entities/wuxi-apptec" target="_blank" data-smartkarma-citation="entities:23679:1" rel="noopener">Wuxi Biologics (2269 HK)</a> and <a href="https://www.smartkarma.com/entities/haier-electronics-group-co" target="_blank" data-smartkarma-citation="entities:4877:1" rel="noopener">Haier Electronics Group Co (1169 HK)</a> while there was short covering on <a href="https://www.smartkarma.com/entities/alibaba-group" target="_blank" data-smartkarma-citation="entities:28434:1" rel="noopener">Alibaba Group (9988 HK)</a>, <a href="https://www.smartkarma.com/entities/meituan-dianping" target="_blank" data-smartkarma-citation="entities:26970:1" rel="noopener">Meituan (3690 HK)</a>, <a href="https://www.smartkarma.com/entities/xiaomi-corp" target="_blank" data-smartkarma-citation="entities:24409:1" rel="noopener">Xiaomi Corp (1810 HK)</a> and <a href="https://www.smartkarma.com/entities/want-want-china-holdings-ltd" target="_blank" data-smartkarma-citation="entities:355:1" rel="noopener">Want Want (151 HK)</a>. Shorts increased in Real Estate, Health Care, Communication Services and Financial stocks, and decreased on Information Technology and Consumer Discretionary names.</p></div><div><p>In Japan, stocks that saw the most shorts were <a href="https://www.smartkarma.com/entities/showa-denko-k-k" target="_blank" data-smartkarma-citation="entities:1496:1" rel="noopener">Showa Denko K.K. (4004 JP)</a>, <a href="https://www.smartkarma.com/entities/pigeon-corp" target="_blank" data-smartkarma-citation="entities:3294:1" rel="noopener">Pigeon Corp (7956 JP)</a>, <a href="https://www.smartkarma.com/entities/change-inc" target="_blank" data-smartkarma-citation="entities:27414:1" rel="noopener">Change Inc (3962 JP)</a> and <a href="https://www.smartkarma.com/entities/nippon-building-fund-inc" target="_blank" data-smartkarma-citation="entities:1900:1" rel="noopener">Nippon Building Fund (8951 JP)</a> while shorts decreased on <a href="https://www.smartkarma.com/entities/fast-retailing-co-ltd" target="_blank" data-smartkarma-citation="entities:751:1" rel="noopener">Fast Retailing (9983 JP)</a>, <a href="https://www.smartkarma.com/entities/advantest-corp" target="_blank" data-smartkarma-citation="entities:18107:1" rel="noopener">Advantest Corp (6857 JP)</a>, <a href="https://www.smartkarma.com/entities/tdk-corp" target="_blank" data-smartkarma-citation="entities:18847:1" rel="noopener">TDK Corp (6762 JP)</a> and <a href="https://www.smartkarma.com/entities/aozora-bank-ltd" target="_blank" data-smartkarma-citation="entities:6483:1" rel="noopener">Aozora Bank Ltd (8304 JP)</a>. Sectorally, shorts increased on Materials, Industrials, Real Estate and Consumer Discretionary names.</p></div><div><p>In Korea, the biggest increase in shorts were seen on <a href="https://www.smartkarma.com/entities/lg-chem-ltd" target="_blank" data-smartkarma-citation="entities:3583:1" rel="noopener">LG Chem Ltd (051910 KS)</a> and <a href="https://www.smartkarma.com/entities/doosan-infracore-co-ltd" target="_blank" data-smartkarma-citation="entities:3982:1" rel="noopener">Doosan Infracore (042670 KS)</a> while shorts were covered on <a href="https://www.smartkarma.com/entities/amorepacific-corp" target="_blank" data-smartkarma-citation="entities:20854:1" rel="noopener">Amorepacific Corp (090430 KS)</a>, <a href="https://www.smartkarma.com/entities/celltrion-inc" target="_blank" data-smartkarma-citation="entities:991:1" rel="noopener">Celltrion Inc (068270 KS)</a>, <a href="https://www.smartkarma.com/entities/lg-display-co-ltd" target="_blank" data-smartkarma-citation="entities:7145:1" rel="noopener">LG Display (034220 KS)</a> and <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>. </p></div><div><p>Stocks in Taiwan that saw the highest increase in shorts were <a href="https://www.smartkarma.com/entities/largan-precision-co-ltd" target="_blank" data-smartkarma-citation="entities:9126:1" rel="noopener">Largan Precision (3008 TT)</a>, <a href="https://www.smartkarma.com/entities/pegatron-corp" target="_blank" data-smartkarma-citation="entities:12852:1" rel="noopener">Pegatron Corp (4938 TT)</a>, <a href="https://www.smartkarma.com/entities/pan-jit-international-inc" target="_blank" data-smartkarma-citation="entities:12501:1" rel="noopener">Pan Jit International (2481 TT)</a> and <a href="https://www.smartkarma.com/entities/elite-semiconductor-memory" target="_blank" data-smartkarma-citation="entities:9373:1" rel="noopener">Elite Semiconductor Memory (3006 TT)</a> while shorts were covered on <a href="https://www.smartkarma.com/entities/taiwan-semiconductor-manufacturing-company" target="_blank" data-smartkarma-citation="entities:11230:1" rel="noopener">TSMC (2330 TT)</a>, <a href="https://www.smartkarma.com/entities/macronix-international" target="_blank" data-smartkarma-citation="entities:3247:1" rel="noopener">Macronix International (2337 TT)</a>, <a href="https://www.smartkarma.com/entities/yageo-corporation" target="_blank" data-smartkarma-citation="entities:13212:1" rel="noopener">Yageo Corporation (2327 TT)</a> and <a href="https://www.smartkarma.com/entities/mediatek-inc" target="_blank" data-smartkarma-citation="entities:772:1" rel="noopener">Mediatek Inc (2454 TT)</a>. </p></div>

The Asia Short Interest weekly looks at moves in market wide short interest and highlights movements in stock specific short interest across Hong Kong, Japan, Korea and Taiwan using the last available data published by the relevant authorities.Hong Kong saw shorts rise on Tencent Holdings (700 HK), Ping An Insurance (H) (2318 HK), Wuxi Biologics (2269 HK) and Haier Electronics Group Co (1169 HK) while there was short covering on Alibaba Group (9988 HK), Meituan (3690 HK), Xiaomi Corp (1810 HK) and Want Want (151 HK). Shorts increased in Real Estate, Health Care, Communication Services and Financial stocks, and decreased on Information Technology and Consumer Discretionary names.In Japan, stocks that saw the most shorts were Showa Denko K.K. (4004 JP), Pigeon Corp (7956 JP), Change Inc (3962 JP) and Nippon Building Fund (8951 JP) while shorts decreased on Fast Retailing (9983 JP), Advantest Corp (6857 JP), TDK Corp (6762 JP) and Aozora Bank Ltd (8304 JP). Sectorally, shorts increased on Materials, Industrials, Real Estate and Consumer Discretionary names.In Korea, the biggest increase in shorts were seen on LG Chem Ltd (051910 KS) and Doosan Infracore (042670 KS) while shorts were covered on Amorepacific Corp (090430 KS), Celltrion Inc (068270 KS), LG Display (034220 KS) and Samsung Electronics (005930 KS). Stocks in Taiwan that saw the highest increase in shorts were Largan Precision (3008 TT), Pegatron Corp (4938 TT), Pan Jit International (2481 TT) and Elite Semiconductor Memory (3006 TT) while shorts were covered on TSMC (2330 TT), Macronix International (2337 TT), Yageo Corporation (2327 TT) and Mediatek Inc (2454 TT). 

Asia Short Interest Weekly: Tencent, Want Want, Showa Denko, NBF, LG Chem, AmoreCorp, Pegatron

Semiconductor & Technology Specialist, Ingenuity

William Keating

Semiconductor & Technology Specialist

Ingenuity

Our focus is exclusively on in-depth research & consulting in the broader semiconductor industry. We focus on the key players, namely Intel, Micron, Qualcomm, Apple, Samsung, NVIDIA, AMD, TSMC & Global Foundries - as well as some of the lesser known, but nonetheless critical, companies such as ASML (for EUV), Mellanox, Cavium, Xilinx etc. We specialise in their products, roadmaps, process technologies, competitive advantages & threats etc. We also help our clients understand the implications of new and emerging technologies, e.g. 3D X-Point, 3D NAND, Carbon Nanotubes, Autonomous Driving, Graphene, Silicon Photonics, Wafer-Level Optics, Artificial Intelligence, FPGA, GPU, ASIC etc. 

Semiconductor Analysis & Research

Thematic (Sector/Industry)

<p>Semiconductor wafer fab equipment sales are on track to grow by over 20% sequentially in 2020 with the broader foundry segment growing by around 20% and TSMC more than 30%. Yet, silicon wafer area shipments will struggle to increase by more than 2% and revenues are set to remain flat to slightly down. How do we explain the seeming discrepancy between these growth numbers? Here's our thoughts on the matter. </p>

Semiconductor wafer fab equipment sales are on track to grow by over 20% sequentially in 2020 with the broader foundry segment growing by around 20% and TSMC more than 30%. Yet, silicon wafer area shipments will struggle to increase by more than 2% and revenues are set to remain flat to slightly down. How do we explain the seeming discrepancy between these growth numbers? Here's our thoughts on the matter. 

Silicon Wafers. Why The Tepid Growth Despite Strength in WFE, Foundry & Logic?

President

Thomas Coughlin

Coughlin Associates

Equity Bottom-Up

<p>Recent Kioxia developments, and in particular, the development of its Ethernet native SSDs for a EBOF and the KumoScale block, file and object storage container storage are innovations that could drive additional value for the company and help in getting a better price in a future IPO, when the overall NAND flash industry is in a more profitable part of its cycle.</p>

Recent Kioxia developments, and in particular, the development of its Ethernet native SSDs for a EBOF and the KumoScale block, file and object storage container storage are innovations that could drive additional value for the company and help in getting a better price in a future IPO, when the overall NAND flash industry is in a more profitable part of its cycle.

Kioxia Announcements Enhance Company Value

<p><a href="https://www.smartkarma.com/entities/micron-technology-inc" target="_blank" data-smartkarma-citation="entities:13382:1" rel="noopener">Micron</a> last week made the surprise announcement that the company had begun volume shipments of the world’s first 176-layer 3D NAND flash memory chips. Separately, the company this week made some very interesting and frank disclosures at the Sanford C Bernstein Operational Decisions Broker Conference. Here's our thoughts on both of these recent developments. </p>

Micron last week made the surprise announcement that the company had begun volume shipments of the world’s first 176-layer 3D NAND flash memory chips. Separately, the company this week made some very interesting and frank disclosures at the Sanford C Bernstein Operational Decisions Broker Conference. Here's our thoughts on both of these recent developments. 

Micron. Leapfrogging Competitors With A Surprise 176-Layer NAND Flash Chip Announcement.

Korea / Special Situations, Clepsydra Capital

Sanghyun Park

Korea / Special Situations

Event-Driven

<p>Samsung ordinary made a runaway move last Friday and yesterday. The price soared by 8.69%.</p><p>But 1P didn't quite catch up, resulting in a -3σ move. The duo is now at -0.55σ on a 20D MA.</p><table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
</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":-0.5499853563680831}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[0]C[6]">-55.00%</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":0.6927528044703176}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[0]C[6]">69.28%</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":2.563178938243168}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[0]C[6]">256.32%</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":2.5805710317954222}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[0]C[6]">258.06%</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":2.8262933260411462}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[0]C[6]">282.63%</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":2.920387008236654}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[0]C[6]">292.04%</td>
</tr>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><section class="figure"><p>The 1P discount hit the historic low at 6.07% last Thursday. Now, it sits at 11.31%.</p>
<figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/172/170/original/chart.png?1605567861" class="editor-image img-responsive" data-smartkarma-image-id="172170"></figure></section><table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Pref discount"}'>Pref discount</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.11312217194570136}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=RP!R[445]C[5]">11.31%</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":0.12598859994735367}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(RP!R396C7:R494C7)">12.60%</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":0.12949640287769784}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(RP!R396C7:R494C7)">12.95%</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":0.1552901023890785}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(RP!R396C7:R494C7)">15.53%</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":0.060655737704918035}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(RP!R396C7:R494C7)">6.07%</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":0.14435834982293952}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(RP!R248C7:R494C7)">14.44%</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":0.14299610894941633}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(RP!R248C7:R494C7)">14.30%</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":0.197196261682243}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(RP!R248C7:R494C7)">19.72%</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":0.060655737704918035}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(RP!R248C7:R494C7)">6.07%</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":0.16432294665613392}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(RP!R2C7:R494C7)">16.43%</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":0.1720183486238532}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(RP!R2C7:R494C7)">17.20%</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":0.21040723981900453}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(RP!R2C7:R494C7)">21.04%</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":0.060655737704918035}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(RP!R2C7:R494C7)">6.07%</td>
</tr>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><p>Still, 1P is outperforming the ordinary share by nearly 3% in a 120D horizon.</p><table class="table table-striped">
<colgroup>
<col width="200">
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"RP ratio"}'>RP ratio</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D today"}'>120D today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.0281833100922997}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=RP!R[50]C[14]">1.02818</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":3,"2":"0.00%","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":1.0121053942624505}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=AVERAGE(RP!R2C16:R81C16)">1.01211</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.015885614206774992}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R31C[-1]-R[0]C[-1])/R[0]C[-1]">1.59%</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":1.007786798540668}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(RP!R2C16:R81C16)">1.00779</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.0202389151963162}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R31C[-1]-R[0]C[-1])/R[0]C[-1]">2.02%</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":1.089009176203732}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(RP!R2C16:R81C16)">1.08901</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.055854319174306895}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R31C[-1]-R[0]C[-1])/R[0]C[-1]">-5.59%</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":0.9792967995363515}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(RP!R2C16:R81C16)">0.97930</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.04992001462589637}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R31C[-1]-R[0]C[-1])/R[0]C[-1]">4.99%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y today"}'>1Y today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.08045027159399}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=RP!R[193]C[9]">1.08045</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>-</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":1.0465088281511457}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=AVERAGE(RP!R2C11:R229C11)">1.04651</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.03243302161416868}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R36C[-1]-R[0]C[-1])/R[0]C[-1]">3.24%</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":1.0457601535399466}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(RP!R2C11:R229C11)">1.04576</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.0331721551415168}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R36C[-1]-R[0]C[-1])/R[0]C[-1]">3.32%</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":1.1443681770053673}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(RP!R2C11:R229C11)">1.14437</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.055854319174306624}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R36C[-1]-R[0]C[-1])/R[0]C[-1]">-5.59%</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":0.9822243875278397}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(RP!R2C11:R229C11)">0.98222</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.10000350766424677}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R36C[-1]-R[0]C[-1])/R[0]C[-1]">10.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y today"}'>2Y today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.0720501218238787}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=RP!R[453]C[2]">1.07205</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>-</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":1.0101590754706078}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=AVERAGE(RP!R2C4:R494C4)">1.01016</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.06126861388087557}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R41C[-1]-R[0]C[-1])/R[0]C[-1]">6.13%</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":1.000856941223914}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(RP!R2C4:R494C4)">1.00086</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.07113222446447229}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R41C[-1]-R[0]C[-1])/R[0]C[-1]">7.11%</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":1.1354710862907595}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(RP!R2C4:R494C4)">1.13547</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.05585431917430671}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R41C[-1]-R[0]C[-1])/R[0]C[-1]">-5.59%</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":0.954452787031973}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(RP!R2C4:R494C4)">0.95445</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.12320916905444201}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R41C[-1]-R[0]C[-1])/R[0]C[-1]">12.32%</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>

Samsung ordinary made a runaway move last Friday and yesterday. The price soared by 8.69%.But 1P didn't quite catch up, resulting in a -3σ move. The duo is now at -0.55σ on a 20D MA.





% of sigma

Today
-55.00%


T-1
69.28%


T-2
256.32%


T-3
258.06%


T-4
282.63%


T-5
292.04%

Source: KRX

The 1P discount hit the historic low at 6.07% last Thursday. Now, it sits at 11.31%.






Pref discount

Today
11.31%


120D mean
12.60%


120D median
12.95%


120D high
15.53%


120D low
6.07%


1Y mean
14.44%


1Y median
14.30%


1Y high
19.72%


1Y low
6.07%


2Y mean
16.43%


2Y median
17.20%


2Y high
21.04%


2Y low
6.07%

Source: KRX

Still, 1P is outperforming the ordinary share by nearly 3% in a 120D horizon.






RP ratio

120D today
1.02818
-


120D mean
1.01211
1.59%


120D median
1.00779
2.02%


120D high
1.08901
-5.59%


120D low
0.97930
4.99%


1Y today
1.08045
-


1Y mean
1.04651
3.24%


1Y median
1.04576
3.32%


1Y high
1.14437
-5.59%


1Y low
0.98222
10.00%


2Y today
1.07205
-


2Y mean
1.01016
6.13%


2Y median
1.00086
7.11%


2Y high
1.13547
-5.59%


2Y low
0.95445
12.32%

Source: KRX



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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.

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