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

The measures recommended by the financial authorities to pay dividends to banks within 20% of their net profit will likely end at the end of this month. Korea's financial holding companies will prepare for a semi-annual or quarterly dividend as soon as they pass a stress test (financial soundness assessment) to be implemented by the financial authorities soon.In this connection, the attention is being on Shinhan Financial Group, which laid the groundwork for a quarterly dividend by amending the articles of incorporation at the general shareholders' meeting earlier this year. Accordingly, Shinhan Financial Group plans to review quarterly dividends at the earliest possible.

The measures recommended by the financial authorities to pay dividends to banks within 20% of their net profit will likely end at the end of this month. Korea's financial holding companies will prepare for a semi-annual or quarterly dividend as soon as they pass a stress test (financial soundness assessment) to be implemented by the financial authorities soon.In this connection, the attention is being on Shinhan Financial Group, which laid the groundwork for a quarterly dividend by amending the articles of incorporation at the general shareholders' meeting earlier this year. Accordingly, Shinhan Financial Group plans to review quarterly dividends at the earliest possible.

Shinhan Financial Quarterly Dividends: Procedural Issues, Stress Test, & Payment Size

Korea's financial regulators, the Financial Services Commission, had advised the local banks and bank holding companies to keep a dividend payout ratio below 20%. The purpose was clear. It was to secure a sufficient capital buffer to absorb potential losses resulting from COVID-19.This recommendation for the 20% cap is effective until the end of this month.The market widely expects the FSC to not renew this 20% dividend cap after this month amid the fast-rebounding economy.

Korea's financial regulators, the Financial Services Commission, had advised the local banks and bank holding companies to keep a dividend payout ratio below 20%. The purpose was clear. It was to secure a sufficient capital buffer to absorb potential losses resulting from COVID-19.This recommendation for the 20% cap is effective until the end of this month.The market widely expects the FSC to not renew this 20% dividend cap after this month amid the fast-rebounding economy.

Korea Banks 20% Dividend Cap Scrapping: Projected Div Payout & Yield of 8 Bank Stocks

Korea's local banks are still going strong as an inflation hedge stock. In particular, the sector leaders continue to shine the most, which is understandable.Shinhan Financial Group has outperformed most of its local peers of late, causing a harsh diversion vs. several names.<table class="table table-striped">
<colgroup>
<col width="200">
<col width="70">
<col width="70">
<col width="200">
<col width="70">
<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 style="text-align: right;" data-sheets-value='{"1":2,"2":"Ticker"}'>Ticker</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Market cap"}'>Market cap</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":"Ticker"}'>Ticker</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Market cap"}'>Market cap</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":"Sigma on a 20-day moving average"}'>Sigma on a 20-day moving average</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Woori Financial Group Inc"}'>Woori Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":316140}'>316140</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":7981.05789715}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩7,981.1B</td>
<td data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}'>Shinhan Financial Group Co., Ltd.</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"055550"}'>055550</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":21826.3311565}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩21,826.3B</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9223855252672568}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.92</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.7434864364413833}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>-1.74</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hana Financial Group Inc"}'>Hana Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"086790"}'>086790</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":13676.0259241}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩13,676.0B</td>
<td data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}'>Shinhan Financial Group Co., Ltd.</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"055550"}'>055550</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":21826.3311565}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩21,826.3B</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9415706574402087}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.94</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.6583215542673198}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>-1.66</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"KB Financial Group Inc"}'>KB Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"105560"}'>105560</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":23701.05144}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩23,701.1B</td>
<td data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}'>Shinhan Financial Group Co., Ltd.</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"055550"}'>055550</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":21826.3311565}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩21,826.3B</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9610188453950309}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.96</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.5589371642688024}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>-1.56</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"BNK Financial Group Inc"}'>BNK Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"138930"}'>138930</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2591.1852057}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩2,591.2B</td>
<td data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}'>Shinhan Financial Group Co., Ltd.</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"055550"}'>055550</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":21826.3311565}' data-sheets-numberformat='[null,2,"₩#,##0.0B"]'>₩21,826.3B</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.972704739094366}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.97</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.0491776745143695}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>-1.05</td>
</tr>
<tr><td colspan="8">Source: KRX 
</td></tr>
</tbody>
</table>The harshest diversion at this point goes to Woori Financial Group. The current sigma is -1.74 on a 20-day moving average. Its price ratio relative to Shinhan is now 9.55% below the 180-day average. In fact, it is at a 180-day low.<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":"Price ratio"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]'>Price ratio</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"%Δ to 180-day mean"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]'>%Δ to 180-day mean</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"%Δ to 180-day high"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]'>%Δ to 180-day high</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"%Δ to 180-day low"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]'>%Δ to 180-day low</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Woori Financial Group Inc"}' data-sheets-formula="=R[-16]C[0]">Woori Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.09551050492215632}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-9.55%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.158687466379774}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-15.87%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">0.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hana Financial Group Inc"}' data-sheets-formula="=R[-16]C[0]">Hana Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.007327297625351524}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-0.73%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.10178905429741551}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-10.18%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.14368007113294015}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">14.37%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"KB Financial Group Inc"}' data-sheets-formula="=R[-16]C[0]">KB Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.022657232352227285}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-2.27%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.1009918086293668}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-10.10%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.08257600627747405}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">8.26%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"BNK Financial Group Inc"}' data-sheets-formula="=R[-16]C[0]">BNK Financial Group Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.037819100378221324}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">3.78%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.048692073349346776}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-4.87%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.12800025002083512}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">12.80%</td>
</tr>
<tr><td colspan="4">Source: KRX</td></tr>
</tbody>
</table><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/210/024/original/Woori+Financial+Group+Inc+vs.+Shinhan+Financial+Group+Co.%2C+Ltd.png?1622371064" class="editor-image img-responsive" data-smartkarma-image-id="210024"></figure></section>

Korea's local banks are still going strong as an inflation hedge stock. In particular, the sector leaders continue to shine the most, which is understandable.Shinhan Financial Group has outperformed most of its local peers of late, causing a harsh diversion vs. several names.












Comp 1 (long)
Ticker
Market cap
Comp 2 (short)
Ticker
Market cap
180-day correlation coefficient
Sigma on a 20-day moving average


Woori Financial Group Inc
316140
₩7,981.1B
Shinhan Financial Group Co., Ltd.
055550
₩21,826.3B
0.92
-1.74


Hana Financial Group Inc
086790
₩13,676.0B
Shinhan Financial Group Co., Ltd.
055550
₩21,826.3B
0.94
-1.66


KB Financial Group Inc
105560
₩23,701.1B
Shinhan Financial Group Co., Ltd.
055550
₩21,826.3B
0.96
-1.56


BNK Financial Group Inc
138930
₩2,591.2B
Shinhan Financial Group Co., Ltd.
055550
₩21,826.3B
0.97
-1.05

Source: KRX 


The harshest diversion at this point goes to Woori Financial Group. The current sigma is -1.74 on a 20-day moving average. Its price ratio relative to Shinhan is now 9.55% below the 180-day average. In fact, it is at a 180-day low.








Price ratio
%Δ to 180-day mean
%Δ to 180-day high
%Δ to 180-day low


Woori Financial Group Inc
-9.55%
-15.87%
0.00%


Hana Financial Group Inc
-0.73%
-10.18%
14.37%


KB Financial Group Inc
-2.27%
-10.10%
8.26%


BNK Financial Group Inc
3.78%
-4.87%
12.80%

Source: KRX



Korea Financials: Woori Vs. Shinhan Price Ratio at a 180-Day Low

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.<hr><h2>Financials</h2>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, Hana Financial/Shinhan Financial and Hyundai Marine/DB Insurance warrant attention.<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]">Hana Financial Group Inc</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}' data-sheets-formula="=Data!R[-3]C[5]">Shinhan Financial Group Co., Ltd.</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]">-1.08</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]">0.94</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]">1.02</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]">Hyundai Marine &amp; Fire Insurance Co., Ltd</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"DB Insurance Co Ltd"}' data-sheets-formula="=Data!R[-4]C[7]">DB Insurance Co Ltd</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]">-1.07</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]">0.92</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]">0.76</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>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: Lotte Shopping/GS Retail and Lotte Shopping/Hyundai Department.<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]">Lotte Shopping Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"GS Retail Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]">GS Retail Co Ltd</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]">-1.53</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]">0.87</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]">0.88</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Lotte Shopping Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]">Lotte Shopping Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"Hyundai Department Store Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]">Hyundai Department Store Co Ltd</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]">-1.13</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]">0.92</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]">0.87</td>
</tr>
<tr><td colspan="5" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><h2>Industrials</h2>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.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.<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]">Korea Aerospace Industries Ltd</td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Hanwha Aerospace Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]">Hanwha Aerospace Co Ltd</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]">-1.26</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]">0.92</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]">0.62</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]">Korea Shipbuilding &amp;Offshore Engn Co Ltd</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]">Hyundai Mipo Dockyard Co., Ltd.</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]">-1.03</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]">0.97</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]">0.68</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

Financials Credit Analyst

Hank Calenti, CFA

CreditContinuum

Credit

Executive Summary: Friday’s jobs report shocker capped off a week which included US Treasury Secretary Janet Yellen needing to be Mirandized. This was followed by the Fed stating the obvious in its financial stability report. Unmentioned in this report is that the role of this Fed is no longer to take away the punchbowl, but instead it is the bartender. The week ended with a jobs report that was the biggest miss in nominal terms, ever.The report was at odds with recent PMI surveys in which respondents stated that it was difficult to hire. This may be the result of frictions in hiring as unemployment benefits as well as child-care needs and postponed school re-openings delay employee re-entry. The truth serum for the US economy may occur around September when extended unemployment payments expire.The market impact was an immediate 10 basis point (bp) drop in the 10-year Treasury while the 2-year note even fell 1bp. Prices on the 10-year gave up these gains as the day progressed, but the smart money, that is the bond market, may be correct with the recent dampening of interest rates suggesting a longer time period to a less accommodative Fed.  The US Treasury bond curve ended the week flatter with short-end yields falling by much less than the longer part of the curve.With rates continuing to push credit spreads, Asia- and European-headquartered banks generated negative total returns in all but the lowest duration notes. There was a clear preference for Additional Tier 1 (AT1) bond issuance over the past week while over US$11 billion equivalent was raised by financial institutions globally in USD and Euros. In what may have been the busiest AT1 bond issuance weeks of the year, five institutions brought over US$6.5 billion in six securities.Nonetheless, this is a great credit environment and spreads which could go even tighter into year-end. A single piece of data, such as April’s non-farm payroll figure, is unlikely to change investor positioning. It may be a little too early to fade the market as fundamentals catch-up.Next week we will get a record-matching $126 billion slate of Treasury auctions. We may also see a robust serving of corporate and financials debt issuance. US consumer-price data is set to be published on Tuesday, 12 May. A sharp annual acceleration is forecast, although the market is likely to dismiss the figure as resulting from a comparison to depressed levels of a year earlier.With peak Q1 earnings season now behind us, Japanese banks will deliver their year-end results over the next week while several other stragglers pepper the remainder of the month. US banks signaled that they anticipate significantly higher interest rates by raising record breaking amounts in the debt capital markets following their Q1 earnings announcements. Other banks may follow with material debt issuance over the next few weeks after reporting earnings.Market Outlook: The question is whether the over-heating narrative will make a comeback and bring rate and tapering expectations closer. Financial stability risks appear binary from here. Either the Fed is over-accommodative, and it sits on its hands too long while asset bubbles over-inflate so that it gets nasty when it moves, or the Fed gets impatient, and it lowers accommodation unexpectedly which creates a risk off reaction. In both cases, curves flatten in a risk-off environment. We suspect the former is more likely, and for now, the Fed remains the bartender.

Executive Summary: Friday’s jobs report shocker capped off a week which included US Treasury Secretary Janet Yellen needing to be Mirandized. This was followed by the Fed stating the obvious in its financial stability report. Unmentioned in this report is that the role of this Fed is no longer to take away the punchbowl, but instead it is the bartender. The week ended with a jobs report that was the biggest miss in nominal terms, ever.The report was at odds with recent PMI surveys in which respondents stated that it was difficult to hire. This may be the result of frictions in hiring as unemployment benefits as well as child-care needs and postponed school re-openings delay employee re-entry. The truth serum for the US economy may occur around September when extended unemployment payments expire.The market impact was an immediate 10 basis point (bp) drop in the 10-year Treasury while the 2-year note even fell 1bp. Prices on the 10-year gave up these gains as the day progressed, but the smart money, that is the bond market, may be correct with the recent dampening of interest rates suggesting a longer time period to a less accommodative Fed.  The US Treasury bond curve ended the week flatter with short-end yields falling by much less than the longer part of the curve.With rates continuing to push credit spreads, Asia- and European-headquartered banks generated negative total returns in all but the lowest duration notes. There was a clear preference for Additional Tier 1 (AT1) bond issuance over the past week while over US$11 billion equivalent was raised by financial institutions globally in USD and Euros. In what may have been the busiest AT1 bond issuance weeks of the year, five institutions brought over US$6.5 billion in six securities.Nonetheless, this is a great credit environment and spreads which could go even tighter into year-end. A single piece of data, such as April’s non-farm payroll figure, is unlikely to change investor positioning. It may be a little too early to fade the market as fundamentals catch-up.Next week we will get a record-matching $126 billion slate of Treasury auctions. We may also see a robust serving of corporate and financials debt issuance. US consumer-price data is set to be published on Tuesday, 12 May. A sharp annual acceleration is forecast, although the market is likely to dismiss the figure as resulting from a comparison to depressed levels of a year earlier.With peak Q1 earnings season now behind us, Japanese banks will deliver their year-end results over the next week while several other stragglers pepper the remainder of the month. US banks signaled that they anticipate significantly higher interest rates by raising record breaking amounts in the debt capital markets following their Q1 earnings announcements. Other banks may follow with material debt issuance over the next few weeks after reporting earnings.Market Outlook: The question is whether the over-heating narrative will make a comeback and bring rate and tapering expectations closer. Financial stability risks appear binary from here. Either the Fed is over-accommodative, and it sits on its hands too long while asset bubbles over-inflate so that it gets nasty when it moves, or the Fed gets impatient, and it lowers accommodation unexpectedly which creates a risk off reaction. In both cases, curves flatten in a risk-off environment. We suspect the former is more likely, and for now, the Fed remains the bartender.

Bank Credit Weekly: Jobs Report Shocker Flattens Curves

South Korea

Shinhan Financial Group Co., Ltd., a holding company, provides a full range of consumer and commercial banking-related financial services.  The company's main businesses include banking, securities brokerage, trust banking, and assets management to individuals, businesses, and other financial institutions.

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