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/meituan-dianping" target="_blank" data-smartkarma-citation="entities:26970:1" rel="noopener">Meituan (3690 HK)</a>, <a href="https://www.smartkarma.com/entities/byd-electronic-international-co-ltd" target="_blank" data-smartkarma-citation="entities:1927:1" rel="noopener">BYD Electronics (285 HK)</a>, <a href="https://www.smartkarma.com/entities/china-mobile-ltd" target="_blank" data-smartkarma-citation="entities:27:1" rel="noopener">China Mobile (941 HK)</a> and <a href="https://www.smartkarma.com/entities/country-garden-services-holdings-company-limited" target="_blank" data-smartkarma-citation="entities:27343:1" rel="noopener">Country Garden Services Holdings (6098 HK)</a> while there was short covering on <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/pccw-ltd" target="_blank" data-smartkarma-citation="entities:873:1" rel="noopener">PCCW Ltd (8 HK)</a>, <a href="https://www.smartkarma.com/entities/hang-seng-bank-ltd" target="_blank" data-smartkarma-citation="entities:24:1" rel="noopener">Hang Seng Bank (11 HK)</a> and <a href="https://www.smartkarma.com/entities/china-merchants-bank-co-ltd-3388a037-4214-4997-b45d-520518cfdb57" target="_blank" data-smartkarma-citation="entities:10987:1" rel="noopener">China Merchants Bank H (3968 HK)</a>. Shorts increased in Industrials, Consumer Discretionary and Real Estate stocks and decreased in Financial names.</p></div><div><p>In Japan, stocks that saw the most shorts were <a href="https://www.smartkarma.com/entities/rakuten-inc" target="_blank" data-smartkarma-citation="entities:31:1" rel="noopener">Rakuten Inc (4755 JP)</a>, <a href="https://www.smartkarma.com/entities/anritsu-corp" target="_blank" data-smartkarma-citation="entities:3700:1" rel="noopener">Anritsu Corp (6754 JP)</a>, <a href="https://www.smartkarma.com/entities/ms-ad-insurance-group-holdin" target="_blank" data-smartkarma-citation="entities:631:1" rel="noopener">Ms&amp;Ad Insurance Group Holdin (8725 JP)</a> and <a href="https://www.smartkarma.com/entities/mitsui-co-ltd" target="_blank" data-smartkarma-citation="entities:20799:1" rel="noopener">Mitsui &amp; Co Ltd (8031 JP)</a> while shorts decreased on <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>, <a href="https://www.smartkarma.com/entities/taiyo-yuden-co-ltd" target="_blank" data-smartkarma-citation="entities:9924:1" rel="noopener">Taiyo Yuden (6976 JP)</a>, <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> and <a href="https://www.smartkarma.com/entities/credit-saison-co-ltd" target="_blank" data-smartkarma-citation="entities:6123:1" rel="noopener">Credit Saison (8253 JP)</a>. Sectorally, shorts increased on Consumer Discretionary, Industrials and Financials, while shorts were covered on Real Estate and Materials names.</p></div><div><p>In Korea, the biggest increase in shorts were on <a href="https://www.smartkarma.com/entities/celltrion-inc" target="_blank" data-smartkarma-citation="entities:991:1" rel="noopener">Celltrion Inc (068270 KS)</a> and <a href="https://www.smartkarma.com/entities/hyundai-motor-co" target="_blank" data-smartkarma-citation="entities:155:1" rel="noopener">Hyundai Motor Co (005380 KS)</a>, while shorts were covered on <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>, <a href="https://www.smartkarma.com/entities/korean-air-lines-co-ltd" target="_blank" data-smartkarma-citation="entities:11048:1" rel="noopener">Korean Air Lines (003490 KS)</a>, <a href="https://www.smartkarma.com/entities/kakao-corp" target="_blank" data-smartkarma-citation="entities:15002:1" rel="noopener">Kakao Corp (035720 KS)</a> and <a href="https://www.smartkarma.com/entities/samsung-biologics-co-ltd" target="_blank" data-smartkarma-citation="entities:22932:1" rel="noopener">Samsung Biologics Co., (207940 KS)</a>. </p></div><div><p>Stocks in Taiwan that saw the highest increase in shorts were <a href="https://www.smartkarma.com/entities/acer-inc" target="_blank" data-smartkarma-citation="entities:15726:1" rel="noopener">Acer Inc (2353 TT)</a>, <a href="https://www.smartkarma.com/entities/au-optronics-corp" target="_blank" data-smartkarma-citation="entities:6704:1" rel="noopener">Au Optronics (2409 TT)</a>, <a href="https://www.smartkarma.com/entities/unimicron-technology-corp" target="_blank" data-smartkarma-citation="entities:18778:1" rel="noopener">Unimicron Technology (3037 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> while shorts were covered on <a href="https://www.smartkarma.com/entities/yageo-corporation" target="_blank" data-smartkarma-citation="entities:13212:1" rel="noopener">Yageo Corporation (2327 TT)</a>, <a href="https://www.smartkarma.com/entities/ta-chen-stainless-pipe-co" target="_blank" data-smartkarma-citation="entities:2519:1" rel="noopener">Ta Chen Stainless Pipe Co (2027 TT)</a>, <a href="https://www.smartkarma.com/entities/ase-technology-holding-co-ltd" target="_blank" data-smartkarma-citation="entities:27270:1" rel="noopener">ASE Technology Holding Co Ltd (3711 TT)</a> and <a href="https://www.smartkarma.com/entities/nan-ya-printed-circuit-board-corporation" target="_blank" data-smartkarma-citation="entities:2699:1" rel="noopener">Nan Ya Printed Circuit Board (8046 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 Meituan (3690 HK), BYD Electronics (285 HK), China Mobile (941 HK) and Country Garden Services Holdings (6098 HK) while there was short covering on Ping An Insurance (H) (2318 HK), PCCW Ltd (8 HK), Hang Seng Bank (11 HK) and China Merchants Bank H (3968 HK). Shorts increased in Industrials, Consumer Discretionary and Real Estate stocks and decreased in Financial names.In Japan, stocks that saw the most shorts were Rakuten Inc (4755 JP), Anritsu Corp (6754 JP), Ms&amp;Ad Insurance Group Holdin (8725 JP) and Mitsui &amp; Co Ltd (8031 JP) while shorts decreased on Nippon Building Fund (8951 JP), Taiyo Yuden (6976 JP), Showa Denko K.K. (4004 JP) and Credit Saison (8253 JP). Sectorally, shorts increased on Consumer Discretionary, Industrials and Financials, while shorts were covered on Real Estate and Materials names.In Korea, the biggest increase in shorts were on Celltrion Inc (068270 KS) and Hyundai Motor Co (005380 KS), while shorts were covered on Samsung Electronics (005930 KS), Korean Air Lines (003490 KS), Kakao Corp (035720 KS) and Samsung Biologics Co., (207940 KS). Stocks in Taiwan that saw the highest increase in shorts were Acer Inc (2353 TT), Au Optronics (2409 TT), Unimicron Technology (3037 TT) and Mediatek Inc (2454 TT) while shorts were covered on Yageo Corporation (2327 TT), Ta Chen Stainless Pipe Co (2027 TT), ASE Technology Holding Co Ltd (3711 TT) and Nan Ya Printed Circuit Board (8046 TT). 

Asia Short Interest Weekly: Rising Shorts in HK, Japan and Taiwan

Founder & CEO Bond Angle, LLC, Bond Angle, LLC

Vicki Bryan

Founder & CEO Bond Angle, LLC

Bond Angle, LLC

Insightful commentary and analysis on bond markets and market movers, including financial, economic, and industry catalysts and management shenanigans. 

High yield market investment research

Credit

<p><strong><a href="https://www.smartkarma.com/entities/tesla-motors-inc" target="_blank" data-smartkarma-citation="entities:20279:1" rel="noopener">Tesla Motors (TSLA US)</a> has<a href="https://www.smartkarma.com/compose/insight/44419/Germany,%20France,%20Italy,%20the%20Netherlands,%20Portugal,%20Switzerland%20and%20Sweden" target="_blank" rel="noopener"> shipped 7,000</a> Made-In-China Model 3s to Europe</strong>, with expected distribution upon arrival next month to Germany, France, Italy, the Netherlands, Portugal, Switzerland, and Sweden.</p><p><strong>Interestingly, this news comes after Tesla managed to top reduced market consensus estimates for revenue and profits reported for its third quarter</strong>, released after the market closed Wednesday and projected <strong>full year deliveries up 30-40%</strong>.</p><p>However, as I projected, Tesla again needed a sizable <strong>boost from energy credits and accounting maneuvers</strong> to increase operating revenue and profits sufficiently to mask yet another loss because its <strong>car business</strong>, its <strong>energy generation &amp; storage business</strong>, and its <strong>parts &amp; service business are still losing money after 17 years</strong> (see <a href="https://www.smartkarma.com/insights/what-to-expect-in-tesla-s-critical-q3" target="_blank" data-smartkarma-citation="insights:43768" rel="noopener">What To Expect in Tesla's Critical Q3</a> on 10/19/20).</p><p>This didn't seem to worry Tesla's fans who initially boosted the stock up by 5% the following Thursday,<strong> though it should. </strong></p><p>Because <strong>Tesla has failed to overcome persistent weakness in core demand </strong>that I have been tracking for two years persist despite multiple rounds of price cuts and expensive discounting to boost sales. <strong>It has happened with every Tesla model in every key market.</strong></p><p><strong>And now Tesla is trying to find new markets for excess inventory out of its new Shanghai plant </strong>versus the existing China market which CEO Elon Musk had projected last year would be so strong for Tesla it would need <strong><a href="https://bloom.bg/3otCEDy" target="_blank" rel="noopener">several China plants to supply it</a>.</strong></p><p><strong>So what's really going on with Tesla's demand?</strong></p><div class="content-highlight"><p><em>Read on for <strong>Bond Angle</strong><strong>analysis of</strong> Tesla's <strong>multi-year demand trends and prospects across markets.</strong></em></p></div>

Tesla Motors (TSLA US) has shipped 7,000 Made-In-China Model 3s to Europe, with expected distribution upon arrival next month to Germany, France, Italy, the Netherlands, Portugal, Switzerland, and Sweden.Interestingly, this news comes after Tesla managed to top reduced market consensus estimates for revenue and profits reported for its third quarter, released after the market closed Wednesday and projected full year deliveries up 30-40%.However, as I projected, Tesla again needed a sizable boost from energy credits and accounting maneuvers to increase operating revenue and profits sufficiently to mask yet another loss because its car business, its energy generation &amp; storage business, and its parts &amp; service business are still losing money after 17 years (see What To Expect in Tesla's Critical Q3 on 10/19/20).This didn't seem to worry Tesla's fans who initially boosted the stock up by 5% the following Thursday, though it should. Because Tesla has failed to overcome persistent weakness in core demand that I have been tracking for two years persist despite multiple rounds of price cuts and expensive discounting to boost sales. It has happened with every Tesla model in every key market.And now Tesla is trying to find new markets for excess inventory out of its new Shanghai plant versus the existing China market which CEO Elon Musk had projected last year would be so strong for Tesla it would need several China plants to supply it.So what's really going on with Tesla's demand?Read on for Bond Angleanalysis of Tesla's multi-year demand trends and prospects across markets.

<p><strong><a href="https://www.smartkarma.com/entities/tesla-motors-inc" target="_blank" data-smartkarma-citation="entities:20279:1" rel="noopener">Tesla Motors (TSLA US)</a> w</strong>ill <a href="https://ir.tesla.com/press-release/tesla-announces-date-third-quarter-2020-financial-results-and-webcast" target="_blank" rel="noopener">report third quarter results</a> after the market closes <strong>Wednesday</strong>, <strong>October 21st</strong>.</p><p>Tesla recently reported <strong>third quarter deliveries up 43% </strong>versus last year, again thanks to <strong>incremental sales from market expansion </strong>which continue to offset <strong>sharply lower same-store sales I've been tracking since last year </strong>(as I last discussed in <a href="https://www.smartkarma.com/insights/things-people-believe-flat-earth-faked-moon-landings-and-tesla-2100" target="_blank" data-smartkarma-citation="insights:42439" rel="noopener">Things People Believe: Flat Earth, Faked Moon Landings, and Tesla $2100</a> <span class="dummy">on 8/23/20).</span></p><p>That distinction is a major reason Tesla goes to so much trouble to keep comparable numbers muddled so <strong>demand erosion is harder to spot</strong>. <strong>Severe price cuts and weaker mix</strong> over the past year also mean <strong>revenue growth from auto sales significantly trails reported deliveries</strong>.</p><p>This will figure heavily into how much padding Tesla will likely add with energy credit sales, nonoperating &amp; unusual items, and accounting maneuvers to inflate <strong>consolidated revenue and "profits"</strong> it reports for the quarter.</p><p>After all, another creatively reported profit could set up another <a href="https://markets.businessinsider.com/news/stocks/tesla-stock-elon-musk-payout-earnings-pocket-billions-hits-goals-2020-10-1029657370?utm_campaign=browser_notification&amp;utm_source=desktop" target="_blank" rel="noopener">$3 billion payday</a> for CEO Elon Musk and finally get Tesla into the <strong><a href="https://www.smartkarma.com/entities/s-p-500" target="_blank" data-smartkarma-citation="entities:22886:1" rel="noopener">S&amp;P 500 (SPX INDEX)</a></strong>.</p><div class="content-highlight"><p><strong><em>Continue reading for Bond Angle revenue and profit estimates for Tesla's third quarter.</em></strong></p></div>

Tesla Motors (TSLA US) will report third quarter results after the market closes Wednesday, October 21st.Tesla recently reported third quarter deliveries up 43% versus last year, again thanks to incremental sales from market expansion which continue to offset sharply lower same-store sales I've been tracking since last year (as I last discussed in Things People Believe: Flat Earth, Faked Moon Landings, and Tesla $2100 on 8/23/20).That distinction is a major reason Tesla goes to so much trouble to keep comparable numbers muddled so demand erosion is harder to spot. Severe price cuts and weaker mix over the past year also mean revenue growth from auto sales significantly trails reported deliveries.This will figure heavily into how much padding Tesla will likely add with energy credit sales, nonoperating &amp; unusual items, and accounting maneuvers to inflate consolidated revenue and "profits" it reports for the quarter.After all, another creatively reported profit could set up another $3 billion payday for CEO Elon Musk and finally get Tesla into the S&amp;P 500 (SPX INDEX).Continue reading for Bond Angle revenue and profit estimates for Tesla's third quarter.

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

Sanghyun Park

Korea / Special Sits, Pairs, Index Rebalancing

Event-Driven

<p>It seems that the Glovis/Mobis pair's ongoing diversion wouldn't stop here. This morning, Glovis is again up 5%, whereas Mobis isn't moving anywhere.</p><p>On a 20D MA, the duo is pretty much at +3σ favoring Glovis.</p><table class="table table-striped">
<colgroup>
<col width="300">
<col width="300">
</colgroup>
<tbody>
<tr><td colspan="2" 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":2.79721147999682}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">279.72%</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":2.90408093225351}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">290.41%</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":3.040840873644037}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">304.08%</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":2.181493534187003}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">218.15%</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":2.858730552874526}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">285.87%</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":1.2348493042227517}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">123.48%</td>
</tr>
<tr><td colspan="2" 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/000/165/349/original/chart.png?1602726889" class="editor-image img-responsive" data-smartkarma-image-id="165349"></figure></section><p>Price ratio-wise, Glovis is practically sitting at the 2-yr peak over Mobis, up 23% from the median.</p><table class="table table-striped">
<colgroup>
<col width="300">
<col width="150">
<col width="150">
</colgroup>
<tbody>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Price ratio"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Price ratio</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7607758620689655}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-21]C[1]">0.76078</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":"20D MA"}'>20D MA</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6404340532612001}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-22]C[2]">0.64043</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":"σ"}'>σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.04302206310403898}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-23]C[5]">0.04302</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":"+1 σ"}' data-sheets-formula='="+1 σ"'>+1 σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6834561163652391}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-24]C[3]">0.68346</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":"-1 σ"}' data-sheets-formula='="-1 σ"'>-1 σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5974119901571611}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-25]C[4]">0.59741</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":0.5756111894671158}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R100C3)">0.57561</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.321683587793472}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">32.17%</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":0.5641025641025641}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R100C3)">0.56410</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.34864811912225707}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">34.86%</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":0.7607758620689655}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R100C3)">0.76078</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="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">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":0.5127610208816705}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R100C3)">0.51276</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.483685052270245}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">48.37%</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":0.5837054277414029}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R248C3)">0.58371</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.30335581255894983}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">30.34%</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":0.5833333333333334}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R248C3)">0.58333</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.30418719211822653}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">30.42%</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":0.7607758620689655}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R248C3)">0.76078</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="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">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":0.5127610208816705}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R248C3)">0.51276</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.483685052270245}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">48.37%</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":0.6205364418447589}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R476C3)">0.62054</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.22599707409172706}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">22.60%</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":0.6187363834422658}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R476C3)">0.61874</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.22956380524526473}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">22.96%</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":0.7777777777777778}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R476C3)">0.77778</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.021859605911330054}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-2.19%</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":0.5127610208816705}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R476C3)">0.51276</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.483685052270245}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">48.37%</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><p>Glovis and Mobis are the most correlated stocks among the HMG subsidiaries despite the recent diversion (30D correlation coefficient at 0.36).</p><table class="table table-striped">
<colgroup>
<col width="300">
<col width="150">
<col width="150">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Correlation"}'>Correlation</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"Component 1"}'>Component 1</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"Component 2"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Component 2</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Name"}'>Name</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"Hyundai Glovis Co Ltd"}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula='=googlefinance(R[1]C[0], "name")'>Hyundai Glovis Co Ltd</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula='=googlefinance(R[1]C[0], "name")'>HYUNDAI MOBIS CO., LTD.</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Ticker"}'>Ticker</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"086280"}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula='="086280"'>086280</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"012330"}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula='="012330"'>012330</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Market cap (₩B)"}'>Market cap (₩B)</td>
<td style="text-align: center;" data-sheets-value='{"1":3,"3":6318.75}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-1]C[0], "shares")*googlefinance(R[-1]C[0], "price")/1000000000'>6,318.8</td>
<td style="text-align: center;" data-sheets-value='{"1":3,"3":22005.161661}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-1]C[0], "shares")*googlefinance(R[-1]C[0], "price")/1000000000'>22,005.2</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y"}'>2Y</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.831919620239351}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[-3]C[7]:R[489]C[7], PR!R[-3]C[8]:R[489]C[8])">0.83192</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y"}'>1Y</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.9318592319326688}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[261]C[7]:R[488]C[7], PR!R[261]C[8]:R[488]C[8])">0.93186</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"180D"}'>180D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.9199477136645406}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[308]C[7]:R[487]C[7], PR!R[308]C[8]:R[487]C[8])">0.91995</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D"}'>120D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.8692936956427101}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[367]C[7]:R[486]C[7], PR!R[367]C[8]:R[486]C[8])">0.86929</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"90D"}'>90D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.8637633940567214}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[396]C[7]:R[485]C[7], PR!R[396]C[8]:R[485]C[8])">0.86376</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"30D"}'>30D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.3569896000118052}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[455]C[7]:R[484]C[7], PR!R[455]C[8]:R[484]C[8])">0.35699</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Source: KRX</td></tr>
</tbody>
</table><table class="table table-striped">
<colgroup>
<col width="300">
<col width="150">
<col width="150">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Liquidity (₩B)"}'>Liquidity (₩B)</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Hyundai Glovis Co Ltd"}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-58]C[0]">Hyundai Glovis Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-58]C[0]">HYUNDAI MOBIS CO., LTD.</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"MC"}'>MC</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":6318.75}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-58]C[0], "price")*googlefinance(R[-58]C[0], "shares")/1000000000'>6,318.8</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":22005.161661}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-58]C[0], "price")*googlefinance(R[-58]C[0], "shares")/1000000000'>22,005.2</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Avg. DTV"}'>Avg. DTV</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":211359}' data-sheets-numberformat='{"1":2,"2":"#,##0"}' data-sheets-formula='=googlefinance(R[-59]C[0], "volumeavg")'>211,359</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":428067}' data-sheets-numberformat='{"1":2,"2":"#,##0"}' data-sheets-formula='=googlefinance(R[-59]C[0], "volumeavg")'>428,067</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Value"}'>- Value</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":35.6139915}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=R[-1]C[0]*googlefinance(R[-60]C[0], "price")/1000000000'>35.6</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":99.0975105}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=R[-1]C[0]*googlefinance(R[-60]C[0], "price")/1000000000'>99.1</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - % of SO"}'>- % of SO</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.00563624}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula='=R[-2]C[0]/googlefinance(R[-61]C[0], "shares")'>0.56%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.004503375709146989}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula='=R[-2]C[0]/googlefinance(R[-61]C[0], "shares")'>0.45%</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>

It seems that the Glovis/Mobis pair's ongoing diversion wouldn't stop here. This morning, Glovis is again up 5%, whereas Mobis isn't moving anywhere.On a 20D MA, the duo is pretty much at +3σ favoring Glovis.





% of sigma

Today
279.72%


T-1
290.41%


T-2
304.08%


T-3
218.15%


T-4
285.87%


T-5
123.48%

Source: KRX

Price ratio-wise, Glovis is practically sitting at the 2-yr peak over Mobis, up 23% from the median.






Price ratio

Today
0.76078
-


20D MA
0.64043
-


σ
0.04302
-


+1 σ
0.68346
-


-1 σ
0.59741
-


120D mean
0.57561
32.17%


120D median
0.56410
34.86%


120D high
0.76078
0.00%


120D low
0.51276
48.37%


1Y mean
0.58371
30.34%


1Y median
0.58333
30.42%


1Y high
0.76078
0.00%


1Y low
0.51276
48.37%


2Y mean
0.62054
22.60%


2Y median
0.61874
22.96%


2Y high
0.77778
-2.19%


2Y low
0.51276
48.37%

Source: KRX

Glovis and Mobis are the most correlated stocks among the HMG subsidiaries despite the recent diversion (30D correlation coefficient at 0.36).







Correlation
Component 1
Component 2


Name
Hyundai Glovis Co Ltd
HYUNDAI MOBIS CO., LTD.


Ticker
086280
012330


Market cap (₩B)
6,318.8
22,005.2


2Y
0.83192


1Y
0.93186


180D
0.91995


120D
0.86929


90D
0.86376


30D
0.35699

Source: KRX









Liquidity (₩B)
Hyundai Glovis Co Ltd
HYUNDAI MOBIS CO., LTD.


MC
6,318.8
22,005.2


Avg. DTV
211,359
428,067


- Value
35.6
99.1


- % of SO
0.56%
0.45%

Source: KRX



Glovis/Mobis Diversion Is Reaching an Extreme for Three Reasons: Time to Trade on Reversion

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

Equity Capital Markets

Myoung Shin Industrial Co.,Ltd / Equity Capital Markets

<p><strong>Myungshin Industrial, which is one of the Korean auto parts suppliers to Tesla, is getting ready to complete its IPO in November.</strong> The IPO price range is from 4,900 won to 5,800 won. The IPO base deal size is from $67 million to $79 million. Mirae Asset Daewoo Securities is the lead underwriter of the IPO. The book-building for the institutional investors starts on 5 November 2020.</p>
<p>The company has experienced tremendous growth in sales and profits in the past five years. Its sales jumped by 42.9% CAGR from 2016 to 2019. Its operating profit surged from 9.5 billion won in 2016 to 59.6 billion won in 2019. In 1H 2020, the company generated sales of 354.8 billion won (down 6.4% YoY), and an operating profit of 22.8 billion won (down 24.5% YoY). </p>

Myungshin Industrial, which is one of the Korean auto parts suppliers to Tesla, is getting ready to complete its IPO in November. The IPO price range is from 4,900 won to 5,800 won. The IPO base deal size is from $67 million to $79 million. Mirae Asset Daewoo Securities is the lead underwriter of the IPO. The book-building for the institutional investors starts on 5 November 2020.
The company has experienced tremendous growth in sales and profits in the past five years. Its sales jumped by 42.9% CAGR from 2016 to 2019. Its operating profit surged from 9.5 billion won in 2016 to 59.6 billion won in 2019. In 1H 2020, the company generated sales of 354.8 billion won (down 6.4% YoY), and an operating profit of 22.8 billion won (down 24.5% YoY). 

Myungshin Industrial IPO Preview - A Korean Hot Stamping Auto Parts Supplier to Tesla

South Korea

Hyundai Motor Company manufactures, sells, and exports passenger cars, trucks, and commercial vehicles. The Company also sells various auto parts and operates auto repair service centers throughout South Korea. Hyundai Motor provides financial services through its subsidiaries.

Price Gauge
52-week Range	0.00 - 0.00
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Hyundai Motor (005385 KS)

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