Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

Equity Capital Markets

Seoul Guarantee Insurance / Equity Capital Markets

<ul>
<li>Our base case valuation of Seoul Guarantee Insurance is target price of 48,052 won which is within the IPO price range of 39,500 won to 51,800 won. </li>
<li>Given the lack of upside relative to the IPO price range, we have a negative view of this deal. </li>
<li>We are not impressed with the company's lack of top-line sales growth and worsening operating profit in 2023. The valuation range as proposed by the bankers is also not attractive. </li>
</ul>


Our base case valuation of Seoul Guarantee Insurance is target price of 48,052 won which is within the IPO price range of 39,500 won to 51,800 won. 
Given the lack of upside relative to the IPO price range, we have a negative view of this deal. 
We are not impressed with the company's lack of top-line sales growth and worsening operating profit in 2023. The valuation range as proposed by the bankers is also not attractive. 


Seoul Guarantee Insurance Corp IPO Valuation Analysis

Technical Analyst, Vermilion Research

Joe Jasper

Technical Analyst

Technical and Quantitative Research

Vermilion Research

Vermilion’s objective is to deliver timely, actionable, and unique technical research to professional investors through the application of our various technical indicators.

Our research strategists seek to highlight securities which we believe are at major inflection points, based on our various technical and quantitative indicators, and offer asymmetric risk/return profiles. Our unique research methodology, centered on relative strength, enables our strategists to deliver superior investment recommendations.

Our process begins by organizing the universe of actively traded stocks into discrete sectors, then into industry groups. We then apply our technical and quantitative tools to identify developing price trends. Once attractive trends are identified within a selected sector or group, we screen for individual stocks which we believe offer the best risk/reward profile. We provide a historical perspective that often reveals, through our long-term charts, how price patterns often repeat themselves over time.

Technical Analysis

EURO STOXX 50 Price EUR / Technical Analysis

<ul>
<li>It appears the recent pullback is over, and we could see the MSCI ACWI (ACWI-US) test YTD highs at $93. We still expect $93 to cap upside in 2023.</li>
<li>Overweight Europe/UK and non-U.S., we are buyers on pullbacks as long as FTSE 100 is above 7700, STOXX Europe 50 is above 3800, and EURO STOXX 50 is above 4000.</li>
<li>As long as these support levels are holding, we are constructive from a price perspective</li>
</ul>


It appears the recent pullback is over, and we could see the MSCI ACWI (ACWI-US) test YTD highs at $93. We still expect $93 to cap upside in 2023.
Overweight Europe/UK and non-U.S., we are buyers on pullbacks as long as FTSE 100 is above 7700, STOXX Europe 50 is above 3800, and EURO STOXX 50 is above 4000.
As long as these support levels are holding, we are constructive from a price perspective


Remain Overweight Europe/UK & Non-US Equities; Pullback Over?; Buys in Industrials and Financials

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>I track a total of 141 sector pairs in Korea. Starting this insight, I grouped them into three groups: 1. Financials, 2. Retail, and 3. Industrials.</p><hr><h2>Financials</h2><p>4 pairs from the Financials group have a 180-day correlation coefficient above 0.75 (or close) and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average. Of these, <strong>Hana Financial/Shinhan Financial</strong> and <strong>Hyundai Marine/DB Insurance</strong> warrant attention.</p><table class="table table-striped">
<colgroup>
<col width="200">
<col width="200">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":2,"2":"Sigma on a 20-day moving average"}'>Sigma on a 20-day moving average</td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":2,"2":"180-day correlation coefficient"}'>180-day correlation coefficient</td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":2,"2":"Cointegration coefficient (180-day price Δ beta)"}'>Cointegration coefficient (180-day price Δ beta)</td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Mirae Asset Securities Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]">Mirae Asset Securities Co Ltd</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"Samsung Securities Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]">Samsung Securities Co Ltd</td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.222273476903716}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.22</td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.7539862250329782}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[0]C[3]">0.75</td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":0.6991098567863366}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[2]C[-3]">0.70</td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Mirae Asset Securities Co Ltd"}' data-sheets-formula="=Data!R[-2]C[3]">Mirae Asset Securities Co Ltd</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"NH Investment &amp; Securities Co Ltd"}' data-sheets-formula="=Data!R[-2]C[3]">NH Investment &amp; Securities Co Ltd</td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.1519173688233821}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.15</td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.7418291376039101}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]">0.74</td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":0.7031067314990199}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[1]C[3]">0.70</td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Hana Financial Group Inc"}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Hana Financial Group Inc</strong></td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Shinhan Financial Group Co., Ltd.</strong></td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.0788984328569544}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.08</strong></td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.9401716746799647}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]"><strong>0.94</strong></td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":1.021970873112603}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[0]C[5]"><strong>1.02</strong></td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Hyundai Marine &amp; Fire Insurance Co., Ltd"}' data-sheets-formula="=Data!R[-4]C[7]"><strong>Hyundai Marine &amp; Fire Insurance Co., Ltd</strong></td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"DB Insurance Co Ltd"}' data-sheets-formula="=Data!R[-4]C[7]"><strong>DB Insurance Co Ltd</strong></td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.0725124068124459}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.07</strong></td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.9161479896868121}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]"><strong>0.92</strong></td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":0.756650231829711}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[-1]C[7]"><strong>0.76</strong></td>
</tr>
<tr><td colspan="5" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><h2>Retail</h2><p>2 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average: <strong>Lotte Shopping/GS Retail</strong> and <strong>Lotte Shopping/Hyundai Department</strong>.</p><table class="table table-striped">
<colgroup>
<col width="200">
<col width="200">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Sigma on a 20-day moving average"}'>Sigma on a 20-day moving average</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"180-day correlation coefficient"}'>180-day correlation coefficient</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Cointegration coefficient (180-day price Δ beta)"}'>Cointegration coefficient (180-day price Δ beta)</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Lotte Shopping Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>Lotte Shopping Co Ltd</strong></td>
<td data-sheets-value='{"1":2,"2":"GS Retail Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>GS Retail Co Ltd</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.5275880593828013}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.53</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8726370244086025}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[0]C[3]"><strong>0.87</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8778679151859091}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[2]C[-3]"><strong>0.88</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Lotte Shopping Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Lotte Shopping Co Ltd</strong></td>
<td data-sheets-value='{"1":2,"2":"Hyundai Department Store Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Hyundai Department Store Co Ltd</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.126049210184334}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.13</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9181905655104922}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[1]C[3]"><strong>0.92</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8654420144103113}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[0]C[3]"><strong>0.87</strong></td>
</tr>
<tr><td colspan="5" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><h2>Industrials</h2><p>4 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 (or close) while sitting below -1.0σ on a 20-day moving average.</p><p>Of these, the Celltrion siblings are the most correlated/cointegrated ones with a substantial diversion. I mentioned their trading dynamics in the previous insight. I will cover <strong>KAI/Hanwha Aerospace </strong>and <strong>Korea Shipbuilding/Hyundai Mipo</strong> in this post.</p><table class="table table-striped">
<colgroup>
<col width="70">
<col width="70">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":2,"2":"Sigma on a 20-day moving average"}'>Sigma on a 20-day moving average</td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":2,"2":"180-day correlation coefficient"}'>180-day correlation coefficient</td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":2,"2":"Cointegration coefficient (180-day price Δ beta)"}'>Cointegration coefficient (180-day price Δ beta)</td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Korea Aerospace Industries Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>Korea Aerospace Industries Ltd</strong></td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Hanwha Aerospace Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>Hanwha Aerospace Co Ltd</strong></td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.2612782453636326}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.26</strong></td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.9151301901660448}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]"><strong>0.92</strong></td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.6164208180229479}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[2]C[1]"><strong>0.62</strong></td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Celltrion, Inc."}' data-sheets-formula="=Data!R[-2]C[3]">Celltrion, Inc.</td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Celltrion HealthCare Co Ltd"}' data-sheets-formula="=Data!R[-2]C[3]">Celltrion HealthCare Co Ltd</td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.178153322167809}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.18</td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.8365102631201596}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]">0.84</td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.7643376618440517}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[1]C[3]">0.76</td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Celltrion Pharm Inc"}' data-sheets-formula="=Data!R[-3]C[5]">Celltrion Pharm Inc</td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Celltrion HealthCare Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]">Celltrion HealthCare Co Ltd</td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.066075796850893}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.07</td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.8799929165201812}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[3]C[3]">0.88</td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.7823707069161424}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[0]C[7]">0.78</td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Korea Shipbuilding &amp;Offshore Engn Co Ltd"}' data-sheets-formula="=Data!R[-5]C[9]"><strong>Korea Shipbuilding &amp;Offshore Engn Co Ltd</strong></td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Hyundai Mipo Dockyard Co., Ltd."}' data-sheets-formula="=Data!R[-5]C[9]"><strong>Hyundai Mipo Dockyard Co., Ltd.</strong></td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.0295619383635715}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.03</strong></td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.9657685058341984}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[3]C[3]"><strong>0.97</strong></td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.6811111503062213}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[-2]C[11]"><strong>0.68</strong></td>
</tr>
<tr><td colspan="5" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>

I track a total of 141 sector pairs in Korea. Starting this insight, I grouped them into three groups: 1. Financials, 2. Retail, and 3. Industrials.Financials4 pairs from the Financials group have a 180-day correlation coefficient above 0.75 (or close) and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average. Of these, Hana Financial/Shinhan Financial and Hyundai Marine/DB Insurance warrant attention.









Comp 1 (Long)
Comp 2 (Short)
Sigma on a 20-day moving average
180-day correlation coefficient
Cointegration coefficient (180-day price Δ beta)


Mirae Asset Securities Co Ltd
Samsung Securities Co Ltd
-1.22
0.75
0.70


Mirae Asset Securities Co Ltd
NH Investment &amp; Securities Co Ltd
-1.15
0.74
0.70


Hana Financial Group Inc
Shinhan Financial Group Co., Ltd.
-1.08
0.94
1.02


Hyundai Marine &amp; Fire Insurance Co., Ltd
DB Insurance Co Ltd
-1.07
0.92
0.76

Source: KRX

Retail2 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average: Lotte Shopping/GS Retail and Lotte Shopping/Hyundai Department.









Comp 1 (Long)
Comp 2 (Short)
Sigma on a 20-day moving average
180-day correlation coefficient
Cointegration coefficient (180-day price Δ beta)


Lotte Shopping Co Ltd
GS Retail Co Ltd
-1.53
0.87
0.88


Lotte Shopping Co Ltd
Hyundai Department Store Co Ltd
-1.13
0.92
0.87

Source: KRX

Industrials4 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 (or close) while sitting below -1.0σ on a 20-day moving average.Of these, the Celltrion siblings are the most correlated/cointegrated ones with a substantial diversion. I mentioned their trading dynamics in the previous insight. I will cover KAI/Hanwha Aerospace and Korea Shipbuilding/Hyundai Mipo in this post.









Comp 1 (Long)
Comp 2 (Short)
Sigma on a 20-day moving average
180-day correlation coefficient
Cointegration coefficient (180-day price Δ beta)


Korea Aerospace Industries Ltd
Hanwha Aerospace Co Ltd
-1.26
0.92
0.62


Celltrion, Inc.
Celltrion HealthCare Co Ltd
-1.18
0.84
0.76


Celltrion Pharm Inc
Celltrion HealthCare Co Ltd
-1.07
0.88
0.78


Korea Shipbuilding &amp;Offshore Engn Co Ltd
Hyundai Mipo Dockyard Co., Ltd.
-1.03
0.97
0.68

Source: KRX



Korea Sector Pair Trade: Financials, Retail, & Industrials

<p>Concerns over perceived U.S. central bank policy missteps have been <em>somewhat alleviated </em>following dovish takeaways from Fed Chair Powell’s comments this week. However, trade tensions remain a concern for global markets despite optimism surrounding the Trump/Xi meeting at the G20 summit this week. Therefore, our outlook remains cautious and we expect consolidation to continue as global equities enjoy a bounce off of recent lows. Ultimately, we will need to see more definitive signs of bottoming throughout Europe, Asia, and the U.S. before getting positive on global equities.  We provide a technical appraisal of major markets and highlight attractive set ups in global transportation, communications, and financial sectors</p>

Concerns over perceived U.S. central bank policy missteps have been somewhat alleviated following dovish takeaways from Fed Chair Powell’s comments this week. However, trade tensions remain a concern for global markets despite optimism surrounding the Trump/Xi meeting at the G20 summit this week. Therefore, our outlook remains cautious and we expect consolidation to continue as global equities enjoy a bounce off of recent lows. Ultimately, we will need to see more definitive signs of bottoming throughout Europe, Asia, and the U.S. before getting positive on global equities.  We provide a technical appraisal of major markets and highlight attractive set ups in global transportation, communications, and financial sectors

Global Equity Strategy: Bouncing off Lows, China Perking Up

Thematic (Sector/Industry)

<ul>
<li><div class="content-highlight">In this report, we have identified 26 stocks in the Korean stock market that have announced share buyback programs so far in 2017. These stocks that have been buying back their shares have been outperforming the market in recent weeks. Share buybacks continue to be an "alpha generating" catalyst in the Korean stock market. Time and again, companies that buyback stocks in Korea tend to outperform the market.</div></li>
<li><p>For example, these 26 stocks that have announced share repurchase programs in 2017 are up…</p></li>
</ul>


In this report, we have identified 26 stocks in the Korean stock market that have announced share buyback programs so far in 2017. These stocks that have been buying back their shares have been outperforming the market in recent weeks. Share buybacks continue to be an "alpha generating" catalyst in the Korean stock market. Time and again, companies that buyback stocks in Korea tend to outperform the market.
For example, these 26 stocks that have announced share repurchase programs in 2017 are up…


Alpha Generation from Share Buybacks in Korea (2017 YTD)

South Korea

Dongbu Insurance Co., Ltd. provides a variety of non-life insurance services such as auto, long-term casualty and property, pension and retirement, fire and marine, and leisure insurance products.

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

Dongbu Insurance (005830 KS)

Seoul Guarantee Insurance Corp IPO Valuation Analysis

Seoul Guarantee Insurance's IPO price range is not attractive due to lack of upside, lack of sales growth, and worsening operating profit in 2023.

Douglas Kim

Remain Overweight Europe/UK & Non-US Equities; Pullback Over?; Buys in Industrials and Financials

Remain overweight Europe/UK and non-US equities; we are buyers on pullbacks as long as the FTSE 100 is above 7700, the STOXX Europe 50 is above...

Vermilion Research

Korea Sector Pair Trade: Financials, Retail, & Industrials

This post examines Korean sector pairs' 20-day sigma and potential entry points, as they are grouped into Financials, Retail, and Industrials.

Sanghyun Park

Global Equity Strategy: Bouncing off Lows, China Perking Up

Concerns over perceived U.S. central bank policy missteps have been somewhat alleviated following dovish takeaways from Fed Chair Powell’s comments...

Vermilion Research

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Seoul Guarantee Insurance Corp IPO Valuation Analysis

​Seoul Guarantee Insurance's IPO price range is not attractive due to lack of upside, lack of sales growth, and worsening operating profit in 2023.

Douglas Kim

Remain Overweight Europe/UK & Non-US Equities; Pullback Over?; Buys in Industrials and Financials

Remain overweight Europe/UK and non-US equities; we are buyers on pullbacks as long as the FTSE 100 is above 7700, the STOXX Europe 50 is above...

Vermilion Research

Korea Sector Pair Trade: Financials, Retail, & Industrials

This post examines Korean sector pairs' 20-day sigma and potential entry points, as they are grouped into Financials, Retail, and Industrials.

Sanghyun Park

Global Equity Strategy: Bouncing off Lows, China Perking Up

Concerns over perceived U.S. central bank policy missteps have been somewhat alleviated following dovish takeaways from Fed Chair Powell’s comments...

Vermilion Research

Alpha Generation from Share Buybacks in Korea (2017 YTD)

In this report, we have identified 26 stocks in the Korean stock market that have announced share buyback programs so far in 2017. These stocks...

Douglas Kim

Seoul Guarantee Insurance's IPO price range is not attractive due to lack of upside, lack of sales growth, and worsening operating profit in 2023.