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

Sanghyun Park

Korea / Special Sits, Pairs, Index Rebalancing

Clepsydra Capital

Investigate special situations, pairs, and index rebalancing trades in Korea.

Event-Driven

<p>We know that the Korea National Pension Service (NPS) is the nation's largest institutional investor, responsible for about 7% of the local equity market. But we often overlook the fact that it is also one of the largest institutional investors in the global coal industry.</p><p>According to the joint report by several environmental organizations, including Urgewald and Reclaim France, the NPS is, in fact, the world's 11th-largest investor in the coal industry. The NPS currently invests ₩12.7T in total on the coal-related bonds and equity, of which ₩4T are invested in equity.</p><p>There is news that the NPS will introduce a negative screening on the coal investment as early as the second half of this year.</p><p>The upcoming Fund Management Committee meeting, chaired by the Minister of Health and Welfare of South Korea, is scheduled for April 30. It is the highest-level investment decision-making body within the NPS. The negative screening is officially one of the proposals to be discussed in the April 30 meeting.</p><p style="text-align: center;"><strong>The Korea NPS governance structure</strong></p><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/203/038/original/1.png?1619531424" class="editor-image img-responsive" data-smartkarma-image-id="203038"></figure></section><div class="content-caption">(Courtesy Korea NPS)</div><p>The chances are pretty high, given the current political mood under the left-winged administration. Coal will be a starter, likely followed by tobacco and mass destruction weapons soon.</p>

We know that the Korea National Pension Service (NPS) is the nation's largest institutional investor, responsible for about 7% of the local equity market. But we often overlook the fact that it is also one of the largest institutional investors in the global coal industry.According to the joint report by several environmental organizations, including Urgewald and Reclaim France, the NPS is, in fact, the world's 11th-largest investor in the coal industry. The NPS currently invests ₩12.7T in total on the coal-related bonds and equity, of which ₩4T are invested in equity.There is news that the NPS will introduce a negative screening on the coal investment as early as the second half of this year.The upcoming Fund Management Committee meeting, chaired by the Minister of Health and Welfare of South Korea, is scheduled for April 30. It is the highest-level investment decision-making body within the NPS. The negative screening is officially one of the proposals to be discussed in the April 30 meeting.The Korea NPS governance structure(Courtesy Korea NPS)The chances are pretty high, given the current political mood under the left-winged administration. Coal will be a starter, likely followed by tobacco and mass destruction weapons soon.

Shorting Alert Amid Korea NPS Negative Screening on Coal: KEPCO, GS, OCI, Kumho P, LG Int, & POSCO

<p>Kumho PetroC AGM ended with Park Chul-wan's defeat last Friday. It was a well-expected result. What was surprising was a widened price gap between 1P and ord.</p><p>Ord gained 5.99%, whereas 1P stayed at +1.65%, resulting in a nearly 2σ move in favor of ord.</p><p>1P discount is now pretty much back to the 2-yr mean.</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":-0.3336713645431289}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">-33.37%</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":1.451024967930148}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">145.10%</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":1.383964419410094}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">138.40%</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":0.9156023106109108}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">91.56%</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":-0.28025357401397377}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">-28.03%</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":-1.0565298444071825}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-26]C[7]">-105.65%</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="70">
<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":0.3857740585774059}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-35]C[2]">0.38577</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6142259414225941}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-35]C[0]">61.42%</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":0.3891208548753185}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C4:R100C4)">0.38912</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6108791451246814}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(Data!R2C3:R100C3)">61.09%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.008600917313940934}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-0.86%</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":0.38634146341463416}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C4:R100C4)">0.38634</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6136585365853658}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R100C3)">61.37%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.0014686615105024932}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-0.15%</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":0.5102040816326531}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C4:R100C4)">0.51020</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.4897959183673469}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(Data!R2C3:R100C3)">48.98%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.24388284518828449}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-24.39%</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":0.35174418604651164}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C4:R100C4)">0.35174</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6482558139534884}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(Data!R2C3:R100C3)">64.83%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.09674608388948443}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">9.67%</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":0.3910047941933641}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C4:R248C4)">0.39100</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6089952058066355}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(Data!R2C3:R248C3)">60.90%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.013377676421459561}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-1.34%</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":0.38873239436619716}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C4:R248C4)">0.38873</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6112676056338028}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R248C3)">61.13%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.007610211630586287}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-0.76%</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":0.5102040816326531}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C4:R248C4)">0.51020</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.4897959183673469}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(Data!R2C3:R248C3)">48.98%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.24388284518828449}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-24.39%</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":0.35174418604651164}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C4:R248C4)">0.35174</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6482558139534884}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(Data!R2C3:R248C3)">64.83%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.09674608388948443}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">9.67%</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":0.40209958122007}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C4:R476C4)">0.40210</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5979004187799297}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=average(Data!R2C3:R476C3)">59.79%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.04060069546237386}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-4.06%</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":0.39854545454545454}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C4:R476C4)">0.39855</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6014545454545455}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R476C3)">60.15%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.032045017255596546}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-3.20%</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":0.5102040816326531}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C4:R476C4)">0.51020</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.4897959183673469}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MIN(Data!R2C3:R476C3)">48.98%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.24388284518828449}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">-24.39%</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":0.35174418604651164}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C4:R476C4)">0.35174</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6482558139534884}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=MAX(Data!R2C3:R476C3)">64.83%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.09674608388948443}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R37C[-2]-R[0]C[-2])/R[0]C[-2]">9.67%</td>
</tr>
<tr>
<td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td>
<td></td>
</tr>
</tbody>
</table><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/197/790/original/chart+%281%29.png?1616968456" class="editor-image img-responsive" data-smartkarma-image-id="197790"></figure></section><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/197/791/original/chart.png?1616968465" class="editor-image img-responsive" data-smartkarma-image-id="197791"></figure></section>

Kumho PetroC AGM ended with Park Chul-wan's defeat last Friday. It was a well-expected result. What was surprising was a widened price gap between 1P and ord.Ord gained 5.99%, whereas 1P stayed at +1.65%, resulting in a nearly 2σ move in favor of ord.1P discount is now pretty much back to the 2-yr mean.





% of sigma

Today
-33.37%


T-1
145.10%


T-2
138.40%


T-3
91.56%


T-4
-28.03%


T-5
-105.65%

Source: KRX










Metric
Price ratio
Discount
Δ


Today
0.38577
61.42%
-


120D mean
0.38912
61.09%
-0.86%


120D median
0.38634
61.37%
-0.15%


120D high
0.51020
48.98%
-24.39%


120D low
0.35174
64.83%
9.67%


1Y mean
0.39100
60.90%
-1.34%


1Y median
0.38873
61.13%
-0.76%


1Y high
0.51020
48.98%
-24.39%


1Y low
0.35174
64.83%
9.67%


2Y mean
0.40210
59.79%
-4.06%


2Y median
0.39855
60.15%
-3.20%


2Y high
0.51020
48.98%
-24.39%


2Y low
0.35174
64.83%
9.67%


Source: KRX





Kumho PetroC Pref Arb Trade: Buy 1P Short Ord

Japan/Asia Long-Short, LightStream Research

Mio Kato

Japan/Asia Long-Short

Long-Short Analysis on Japan, Asia and the World

LightStream Research

LightStream conducts quantitatively rigorous and data-driven analysis with a focus on Japan and Asia.

We consistently cover the Tech, Consumer and Industrial sectors, and provide ECM and Events coverage more broadly.

We supplement traditional qualitative insights from company relationships with a robust quantitative foundation that examines as much historical data as is available.
We further refine the accuracy of our insights and calls through the use of alternative data to flesh out current trends, and through a valuation framework that emphasises non-superficial peer group selection and a proper attempt to understand the metrics and changes that have driven security valuations in the past.

<p>As Kumho Petrochemical faces a showdown on Friday with corporate governance in focus, we examine merits of the proposals made by both Park Chul Whan and the company management. While we disagree with Park Chul Whan’s harsh criticism of operational performance over the last decade, corporate governance could definitely be improved with some changes.</p>

As Kumho Petrochemical faces a showdown on Friday with corporate governance in focus, we examine merits of the proposals made by both Park Chul Whan and the company management. While we disagree with Park Chul Whan’s harsh criticism of operational performance over the last decade, corporate governance could definitely be improved with some changes.

Kumho Petrochem – The Asian Governance Drive Continues

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

<p>The M&amp;A fight for <a href="https://www.smartkarma.com/entities/kumho-petro-chemical-co-ltd" target="_blank" data-smartkarma-citation="entities:2014:1" rel="noopener">Kumho Petro Chemical (011780 KS)</a> is one of the most interesting M&amp;A events in Korea in the past decade involving Park Chul Wan and his uncle Park Chan Koo. In this insight, we provide a detailed analysis of what may happen in the AGM on March 26th and beyond. </p><h2>Conclusion First</h2><ul>
<li>We like the proposals made by Park Chul Wan including much higher dividends, share buyback with cancellation, new business investments that may add additional long-term value, and the separation of ownership and management. In our view, Park Chul Wan's proposals are credible, make logical business sense, and are likely to add greater long-term value to the shareholders of Kumho Petrochem than the company's existing plans. </li>
<li>However, his uncle and Chairman Park Chan Koo may have the upper hand this time in terms of getting overall higher votes in the AGM on 26 March 2021. </li>
<li>The kicker to this story is the huge inheritance taxes in Korea. Over the next several years, there is a high likelihood that Kumho Petrochem's Chairman Park Chan Koo may transfer his ownership (6.7%) to his son which at that time, his family will be burdened with an enormous inheritance tax burden of 50%+. If and when Chairman Park Chan Koo transfers his ownership to his son and his family members pay for the fat inheritance taxes, the M&amp;A fight between the Chairman's son (Park Joon Kyung) and Park Chul Wan would likely to become a lot more intense.</li>
</ul><div class="content-highlight">
<p><strong>OVERALL, WE BELIEVE TIME IS ON THE SIDE OF PARK CHUL WAN.</strong> HE IS TRYING TO "DO THE RIGHT THING" IN IMPROVING SHAREHOLDER VALUE OF KUMHO PETROCHEM BY INTRODUCING HIGHER STANDARDS CORPORATE GOVERNANCE PRACTICES AS WELL AS ENHANCE VALUE OF EXISTING ASSETS.</p>
<p>Although Park Chul Wan may not win this time, we think that over time (in the next several years, especially if there is a transfer of ownership by Chairman Park Chan Koo to his son), more investors will understand the real value creation that Park Chul Wan is trying to make in the company, which is likely to lead to higher value creation. </p>
</div>

The M&amp;A fight for Kumho Petro Chemical (011780 KS) is one of the most interesting M&amp;A events in Korea in the past decade involving Park Chul Wan and his uncle Park Chan Koo. In this insight, we provide a detailed analysis of what may happen in the AGM on March 26th and beyond. Conclusion First
We like the proposals made by Park Chul Wan including much higher dividends, share buyback with cancellation, new business investments that may add additional long-term value, and the separation of ownership and management. In our view, Park Chul Wan's proposals are credible, make logical business sense, and are likely to add greater long-term value to the shareholders of Kumho Petrochem than the company's existing plans. 
However, his uncle and Chairman Park Chan Koo may have the upper hand this time in terms of getting overall higher votes in the AGM on 26 March 2021. 
The kicker to this story is the huge inheritance taxes in Korea. Over the next several years, there is a high likelihood that Kumho Petrochem's Chairman Park Chan Koo may transfer his ownership (6.7%) to his son which at that time, his family will be burdened with an enormous inheritance tax burden of 50%+. If and when Chairman Park Chan Koo transfers his ownership to his son and his family members pay for the fat inheritance taxes, the M&amp;A fight between the Chairman's son (Park Joon Kyung) and Park Chul Wan would likely to become a lot more intense.

OVERALL, WE BELIEVE TIME IS ON THE SIDE OF PARK CHUL WAN. HE IS TRYING TO "DO THE RIGHT THING" IN IMPROVING SHAREHOLDER VALUE OF KUMHO PETROCHEM BY INTRODUCING HIGHER STANDARDS CORPORATE GOVERNANCE PRACTICES AS WELL AS ENHANCE VALUE OF EXISTING ASSETS.
Although Park Chul Wan may not win this time, we think that over time (in the next several years, especially if there is a transfer of ownership by Chairman Park Chan Koo to his son), more investors will understand the real value creation that Park Chul Wan is trying to make in the company, which is likely to lead to higher value creation. 


The M&A Fight for Kumho Petrochem - Time Is On the Side of Park Chul Wan

Cross Asset Strategy

<div class="content-highlight"><p>In this insight, we discuss about the winners and losers among the top 100 stocks in KOSPI, especially in the most recent <strong>"KOSPI Box trading range"</strong> lasting from 8 January to 10 February 2021 (see chart below). Sometimes, finding out what stocks and sectors outperform in a box trading range could lead to some<strong> clues</strong> in helping to understand what stocks and sectors could outperform in the coming weeks. From 8 January to 10 February, KOSPI has been trading in a box range and its is down slightly (1.6%) in this period. </p></div>

In this insight, we discuss about the winners and losers among the top 100 stocks in KOSPI, especially in the most recent "KOSPI Box trading range" lasting from 8 January to 10 February 2021 (see chart below). Sometimes, finding out what stocks and sectors outperform in a box trading range could lead to some clues in helping to understand what stocks and sectors could outperform in the coming weeks. From 8 January to 10 February, KOSPI has been trading in a box range and its is down slightly (1.6%) in this period. 

Winners & Losers in the KOSPI Box Trading Range & Return of Money Velocity Post End of Lock Down?

South Korea

Kumho Petrochemical Co., Ltd. manufactures synthetic rubbers, synthetic resins, and rubber chemicals.  The Company's products include styrene butadiene, acrylonitrile butadiene, polystyrene, expandable polystyrene, and antioxidant.  Kumho Petrochemical provides construction, transportation, and financial services through its subsidiaries.

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Kumho Petro Chemical (011780 KS)

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