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

<ul>
<li>In Korea's local stock market, intense short-covering at the yearend dividend season has been consistently observed since mid-November. So, this post screens potential short-covering stocks.</li>
<li>KOSPI stocks meeting these screening factors include Kumho Petro Chemical, SK Inc, Lotte Shopping, Mirae Asset Securities, CJ Corp, and HiteJinro.</li>
<li>In the KOSDAQ, we can obtain the following results if the same screening factors are applied: LX Semicon, BH Co Ltd, and Seegene.</li>
</ul>


In Korea's local stock market, intense short-covering at the yearend dividend season has been consistently observed since mid-November. So, this post screens potential short-covering stocks.
KOSPI stocks meeting these screening factors include Kumho Petro Chemical, SK Inc, Lotte Shopping, Mirae Asset Securities, CJ Corp, and HiteJinro.
In the KOSDAQ, we can obtain the following results if the same screening factors are applied: LX Semicon, BH Co Ltd, and Seegene.


Potential Yearend Short-Covering Stocks in Korea

CEO, A. Stotz Investment Research

Dr. Andrew Stotz, CFA

Quantamental Investing to beat Benchmarks

A. Stotz Investment Research

We pick stocks. We construct portfolios. All our effort is focused on how to better pick stocks and construct portfolios. We serve fund management companies, family offices, and high net worth individuals.

Thematic (Sector/Industry)

We highlight 14 stocks in Asia that look interesting to us based upon our FVMR Methodology. Our research team constantly reviews the Asian markets to try to find interesting ideas based on Fundamentals or Valuation or Momentum or Risk or some combination thereof.

We highlight 14 stocks in Asia that look interesting to us based upon our FVMR Methodology. Our research team constantly reviews the Asian markets to try to find interesting ideas based on Fundamentals or Valuation or Momentum or Risk or some combination thereof.

Shares outstandingThe total shares of each company are fixed. There will be no change to it.








Share structure
Pre-split
LG Corp
LX Holdings


Outstanding shares
175,871,808
160,322,613
77,745,975


Common
172,557,131
157,300,993
76,280,690


- Name
LG Corp
LG Corp
LX Holdings


- Ticker
003550
003550
-


- Current price
₩126,500
₩126,500
₩25,300


Pref
3,314,677
3,021,620
1,465,285


- Name
LG Corp 1P
LG Corp 1P
LX Holdings 1P


- Ticker
003555
003555
-


- Current price
₩99,500
₩99,500
₩19,900


Treasury shares - common
0
0
0


Treasury shares - pref
0
0
0


Common excl. treasury shares
172,557,131
157,300,993
76,280,690

Source: DART &amp; KRX

Discount to NAVLG Corp's previous closing price gives a 59.08%discount to the NAV at the last close, translating into a 61.67% discount for LG Corp and a 35.40% premium for LX Holdings.I made some changes in my calculation of NAV. I estimated each holding company's operating operation based on their latest de-consolidated operating profit. It is mostly brand royalty and office rental income. I used operating profit to exclude dividend income. 








Discount to NAV
Pre-split
LG Corp
LX Holdings


Value of listed holdings
₩41,155.3B
₩39,988.2B
₩1,167.1B


- % of Holdco market cap
188.54%
200.96%
60.48%


Value of unlisted holdings
₩2,631.7B
₩2,516.3B
₩115.4B


Stub value
-₩21,958.5B
-₩22,606.0B
₩647.4B


Stub value per share
-₩127,254
-₩143,712
₩8,488


Value of operating assets
₩7,940.0B
₩7,940.0B
₩0.0B


GAV
₩51,727.0B
₩50,444.6B
₩1,282.5B


GAV per share
₩299,767
₩320,688
₩16,812


Discount to GAV
57.80%
60.55%
-50.48%


Holdco net cash/debt
₩1,941.8B
₩1,770.0B
₩172.0B


Value of pref shares
₩329.8B
₩300.7B
₩29.2B


NAV
₩53,339.0B
₩51,913.9B
₩1,425.3B


NAV per share
₩309,109
₩330,029
₩18,685


Discount to NAV
59.08%
61.67%
-35.40%

Source: DART &amp; KRX

NAV compositionLG Corp has four major listed subsidiaries, accounting for 76.89% of the NAV. LX Holdings features three major listed subsidiaries, responsible for 81.89% of the NAV at the last close.








NAV composition
Pre-split
LG Corp
LX Holdings


LG Chem Ltd
39.36%
40.44%
-


LG Household &amp; Healthcare Ltd
15.03%
15.44%
-


LG Electronics Inc.
15.86%
16.29%
-


LG Uplus Corp
4.59%
4.72%
-


LG HAUSYS, LTD.
0.54%
-
20.29%


LG International Corp
0.59%
-
21.96%


Silicon Works Co Ltd
1.06%
-
39.64%


G II R Inc
0.07%
0.07%
-


LS Electric Co Ltd
0.06%
0.06%
-


LG CNS
2.81%
2.89%
-


Other - unlisted
2.12%
1.96%
8.09%


Operation
14.89%
15.29%
0.00%


Holdco net cash/debt
3.64%
3.41%
12.07%


Value of pref shares
-0.62%
-0.58%
-2.05%

Source: DART &amp; KRX



LG Corp Post-Spinoff NAV Update & Relisting Day Trade Approach

LG Corp is currently in trade suspension. It will resume trading on May 27.<table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="2" data-sheets-value='{"1":2,"2":"Corporate action schedule"}'>LG Corp (003550) spinoff schedule</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Trade suspension begins"}'>Trade suspension begins</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"4/29/21"}'>4/29/21</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Trade suspensino ends"}'>Trade suspension ends</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"5/26/21"}'>5/26/21</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Re-listing"}'>Re-listing</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"5/27/21"}'>5/27/21</td>
</tr>
<tr><td colspan="2" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><div>The re-listing day base price is calculated as follows:</div><div><div><ul>
<li>Base price: (Market cap on the last trading day X Split ratio) / total shares</li>
<li>Opening price band: 50% &lt; Base price &lt; 200%</li>
</ul></div></div><div>
At the current market cap, LG Corp's base price comes at ₩126,500, giving a ₩19.90T market cap. LX Holdings' base price arrives at ₩25,300 with a ₩1.93T market cap.
<table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"Re-listing day base price calculation"}'>Re-listing day base price calculation</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":2,"2":"LG Corp"}'>LG Corp</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":2,"2":"LX Holdings"}'>LX Holdings</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"Last trading day MC"}'>Combined market cap on the last trading day</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":21828.4770715}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula='=googlefinance(Table!R3C2, "price")*googlefinance(Table!R3C2, "shares")/1000000000'>₩21,828.5B</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":21828.4770715}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula='=googlefinance(Table!R3C2, "price")*googlefinance(Table!R3C2, "shares")/1000000000'>₩21,828.5B</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"LG Corp split ratio"}'>Split ratio</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":0.9115879}' data-sheets-formula="=R[13]C[-4]">0.9115879</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":0.0884121}' data-sheets-formula="=R[13]C[-4]">0.0884121</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"LG Corp SO"}'>Total shares</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":157300992.6783149}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=NAV!R[-1]C[1]">157,300,993</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":76280691.6084255}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=NAV!R[-1]C[6]">76,280,692</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"LG Corp base price"}'>Base price</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":126500.00000000001}' data-sheets-numberformat='{"1":4,"2":"[$₩-412]#,##0"}' data-sheets-formula="=R[-3]C[0]*R[-2]C[0]/R[-1]C[0]*1000000000">₩126,500</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":25300}' data-sheets-numberformat='{"1":4,"2":"[$₩-412]#,##0"}' data-sheets-formula="=R[-3]C[0]*R[-2]C[0]/R[-1]C[0]*1000000000">₩25,300</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"- Market cap"}'>- Market cap</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":19898.575573806836}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula="=R[-1]C[0]*R4C[0]/1000000000">₩19,898.6B</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":1929.901497693165}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula="=R[-1]C[0]*R4C[0]/1000000000">₩1,929.9B</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"Opening price at 50%"}'>Opening price at 50%</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":63250.00000000001}' data-sheets-numberformat='{"1":4,"2":"[$₩-412]#,##0"}' data-sheets-formula="=R[-2]C[0]/2">₩63,250</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":12650}' data-sheets-numberformat='{"1":4,"2":"[$₩-412]#,##0"}' data-sheets-formula="=R[-2]C[0]/2">₩12,650</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"- Market cap"}'>- Market cap</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":9949.287786903418}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula="=R[-1]C[0]*R4C[0]/1000000000">₩9,949.3B</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":964.9507488465825}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula="=R[-1]C[0]*R4C[0]/1000000000">₩965.0B</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"Opening price at 200%"}'>Opening price at 200%</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":253000.00000000003}' data-sheets-numberformat='{"1":4,"2":"[$₩-412]#,##0"}' data-sheets-formula="=R[-4]C[0]*2">₩253,000</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":50600}' data-sheets-numberformat='{"1":4,"2":"[$₩-412]#,##0"}' data-sheets-formula="=R[-4]C[0]*2">₩50,600</td>
</tr>
<tr>
<td style="width: 253.636px;" data-sheets-value='{"1":2,"2":"- Market cap"}'>- Market cap</td>
<td style="text-align: right; width: 214.545px;" data-sheets-value='{"1":3,"3":39797.15114761367}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula="=R[-1]C[0]*R4C[0]/1000000000">₩39,797.2B</td>
<td style="text-align: right; width: 213.636px;" data-sheets-value='{"1":3,"3":3859.80299538633}' data-sheets-numberformat='{"1":2,"2":"₩#,##0.0B"}' data-sheets-formula="=R[-1]C[0]*R4C[0]/1000000000">₩3,859.8B</td>
</tr>
<tr><td colspan="3" rowspan="1" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>
</div><hr><h2>Pre-spinoff NAV</h2>The last closing price before the suspension kicked in on April 29 gives a 52.41% discount to its NAV. It is still a harsh discount, but at the same time, it is a substantial improvement from a +60% NAV discount not that long ago.<table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"NAV (₩B)"}' data-sheets-note="Sang Hyun Park: Cases when a company's net cash position and the value of its publically traded interests are worth more than its market cap create the opportunity of a stub trade, in which investors can take a view that the company's core business will rise by shorting the minority stakes whilst going long the underlying. Such an opportunity has arisen in the wake of the Alibaba listing which has seen early investing company Yahoo trade at a discount to the value of its stake in Alibaba.">Pre-spinoff NAV (₩B)</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Value of listed holdings"}'>Value of listed holdings</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":41626.31228257122}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=SUM(R[34]C[2]:R[42]C[2])">₩41,626.3B</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - % of Holdco market cap"}'>- % of Holdco market cap</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.9069728110771385}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=R[-1]C[0]/((R[-12]C[0]*R[-15]C[0])/1000000000)">190.70%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Value of unlisted holdings"}'>Value of unlisted holdings</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2631.699}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=SUM(R[41]C[2]:R[42]C[2])">₩2,631.7B</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Stub value"}'>Stub value</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-22429.53421107122}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=(R[-14]C[0]*R[-17]C[0]/1000000000)-R[-3]C[0]-R[-1]C[0]">-₩22,429.5₩</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Stub value per share"}'>Stub value per share</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-129983.23558747172}' data-sheets-numberformat='[null,2,"[$₩-412]#,##0",1]' data-sheets-formula="=R[-1]C[0]*1000000000/R[-18]C[0]">-₩129,983</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Value of operating assets"}'>Value of operating assets</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=SUM(R[60]C[2])">0.0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"GAV"}'>GAV</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44258.01128257122}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=R[-6]C[0]+R[-4]C[0]+R[-1]C[0]">₩44,258.0B</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"GAV per share"}'>GAV per share</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":256483.23558747175}' data-sheets-numberformat='[null,2,"[$₩-412]#,##0",1]' data-sheets-formula="=R[-1]C[0]/R[-11]C[0]*1000000000">₩256,483</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Discount to GAV (excl. treasury shares)"}'>Discount to GAV (excl. treasury shares)</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5067903767267545}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[-1]C[0]-R[-19]C[0])/R[-1]C[0]">50.68%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Holdco net cash/debt (de-consolidated)"}'>Holdco net cash/debt</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1941.8010390000002}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=R[57]C[2]">₩1,941.8B</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Value of pref shares"}'>Value of pref shares</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":329.8103615}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=(R[-20]C[0]*R[-17]C[0])/1000000000">₩329.8B</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"NAV"}'>NAV</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":45870.00196007122}' data-sheets-numberformat='[null,2,"#,##0.0"]' data-sheets-formula="=R[-5]C[0]+R[-2]C[0]-R[-1]C[0]">₩45,870.0B</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"NAV per share (excl. treasury shares)"}'>NAV per share (excl. treasury shares)</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":265825.0151369938}' data-sheets-numberformat='[null,2,"[$₩-412]#,##0",1]' data-sheets-formula="=R[-1]C[0]/R[-16]C[0]*1000000000">₩265,825</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Discount to NAV"}'>Discount to NAV</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5241230403586817}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[-1]C[0]-R[-24]C[0])/R[-1]C[0]">52.41%</td>
</tr>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX &amp; DART","6":1}'>Source: KRX &amp; DART</td></tr>
</tbody>
</table>

LG Corp is currently in trade suspension. It will resume trading on May 27.





LG Corp (003550) spinoff schedule

Trade suspension begins
4/29/21


Trade suspension ends
5/26/21


Re-listing
5/27/21

Source: KRX

The re-listing day base price is calculated as follows:
Base price: (Market cap on the last trading day X Split ratio) / total shares
Opening price band: 50% &lt; Base price &lt; 200%

At the current market cap, LG Corp's base price comes at ₩126,500, giving a ₩19.90T market cap. LX Holdings' base price arrives at ₩25,300 with a ₩1.93T market cap.








Re-listing day base price calculation
LG Corp
LX Holdings


Combined market cap on the last trading day
₩21,828.5B
₩21,828.5B


Split ratio
0.9115879
0.0884121


Total shares
157,300,993
76,280,692


Base price
₩126,500
₩25,300


- Market cap
₩19,898.6B
₩1,929.9B


Opening price at 50%
₩63,250
₩12,650


- Market cap
₩9,949.3B
₩965.0B


Opening price at 200%
₩253,000
₩50,600


- Market cap
₩39,797.2B
₩3,859.8B

Source: KRX


Pre-spinoff NAVThe last closing price before the suspension kicked in on April 29 gives a 52.41% discount to its NAV. It is still a harsh discount, but at the same time, it is a substantial improvement from a +60% NAV discount not that long ago.





Pre-spinoff NAV (₩B)

Value of listed holdings
₩41,626.3B


- % of Holdco market cap
190.70%


Value of unlisted holdings
₩2,631.7B


Stub value
-₩22,429.5₩


Stub value per share
-₩129,983


Value of operating assets
0.0


GAV
₩44,258.0B


GAV per share
₩256,483


Discount to GAV (excl. treasury shares)
50.68%


Holdco net cash/debt
₩1,941.8B


Value of pref shares
₩329.8B


NAV
₩45,870.0B


NAV per share (excl. treasury shares)
₩265,825


Discount to NAV
52.41%

Source: KRX &amp; DART



LG Holdings Post-Spinoff NAV Discounts & Stub Synthetic Pair Trading

I grouped Korea's closely correlated sector pairs within the same GICS sub-category. I applied the additional filtering: 1. a market cap of ₩1T or more and 2. stocks eligible to short-selling (KOSPI 200 and KOSDAQ 150). This grouping returns 141 sector pairs worthy of close monitoring for a long/short trade.<div class="content-highlight">You can find all the 141 sector pairs with the 180-day correlation coefficients and the sigma on a 20-day moving average in the attached file.</div><hr>Below are the top 10 most correlated sector pairs above a 180-day correlation coefficient of 0.95 or higher. They are mostly cyclical stocks, which are in line with our conventional thinking that cyclical stocks have a stronger tendency to move together than growth stocks.<table class="table table-striped">
<colgroup>
<col width="200">
<col width="200">
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Comp 1"}'>Comp 1</td>
<td data-sheets-value='{"1":2,"2":"Comp 2"}'>Comp 2</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":"Business type"}'>Business type</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hyundai Mipo Dockyard Co., Ltd."}'>Hyundai Mipo Dockyard Co., Ltd.</td>
<td data-sheets-value='{"1":2,"2":"Korea Shipbuilding &amp;Offshore Engn Co Ltd"}'>Korea Shipbuilding &amp;Offshore Engn Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.97405}'>0.97405</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Shipbuilding"}'>Shipbuilding</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hyundai Department Store Co Ltd"}'>Hyundai Department Store Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"Lotte Shopping Co Ltd"}'>Lotte Shopping Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.97033}'>0.97033</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Retail"}'>Retail</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"GS Engineering &amp; Construction Corp"}'>GS Engineering &amp; Construction Corp</td>
<td data-sheets-value='{"1":2,"2":"Hyundai Engineering &amp; Construction Co."}'>Hyundai Engineering &amp; Construction Co.</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.96379}'>0.96379</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Construction"}'>Construction</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}'>HYUNDAI MOBIS CO., LTD.</td>
<td data-sheets-value='{"1":2,"2":"Hyundai Motor Co"}'>Hyundai Motor Co</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.96145}'>0.96145</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Automotive"}'>Automotive</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}'>Shinhan Financial Group Co., Ltd.</td>
<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":3,"3":0.95989}'>0.95989</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Commercial bank"}'>Commercial bank</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"LG Innotek Co., Ltd."}'>LG Innotek Co., Ltd.</td>
<td data-sheets-value='{"1":2,"2":"LG Electronics Inc."}'>LG Electronics Inc.</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.95986}'>0.95986</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"IT"}'>IT</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hansol Chemical Co Ltd"}'>Hansol Chemical Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"Posco Chemical Co Ltd"}'>Posco Chemical Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.95374}'>0.95374</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Chemical"}'>Chemical</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hanwha Aerospace Co Ltd"}'>Hanwha Aerospace Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"Korea Aerospace Industries Ltd"}'>Korea Aerospace Industries Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.95243}'>0.95243</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Aerospace"}'>Aerospace</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"KG DongbuSteel Co Ltd"}'>KG DongbuSteel Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"POSCO"}'>POSCO</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.95174}'>0.95174</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Steel"}'>Steel</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"KG DongbuSteel Co Ltd"}'>KG DongbuSteel Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"Hyundai Steel Co"}'>Hyundai Steel Co</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.94972}'>0.94972</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Steel"}'>Steel</td>
</tr>
<tr><td colspan="4" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>Below are the top 10 stocks suffering the harshest diversion on a 20-day moving average among those having a 180-day correlation coefficient of 0.80 or higher. E-Mart and Lotte Shopping top the list with a -3.27σ and a correlation coefficient of 0.85. Silicon Works/LG Electronics and BGF Retail/E-Mart follow as they are also in a heavy diversion at +2.79σ and +2.58σ, respectively. Woori Financial/KB Financial and Pan Ocean/HMM aren't far away either.<table class="table table-striped">
<colgroup>
<col width="200">
<col width="200">
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Comp 1"}'>Comp 1</td>
<td data-sheets-value='{"1":2,"2":"Comp 2"}'>Comp 2</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":"E-Mart Inc"}'>E-Mart Inc</td>
<td data-sheets-value='{"1":2,"2":"Lotte Shopping Co Ltd"}'>Lotte Shopping Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8512795053699035}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.85128</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-3.2691212591928522}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>-3.27</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Silicon Works Co Ltd"}'>Silicon Works Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"LG Electronics Inc."}'>LG Electronics Inc.</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8241051481549174}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>0.82411</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.794228170493331}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>2.79</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"BGF Retail Co Ltd"}'>BGF Retail Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"E-Mart Inc"}'>E-Mart Inc</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.847331528848073}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>0.84733</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.5786176868102397}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>2.58</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Woori Financial Group Inc"}'>Woori Financial Group Inc</td>
<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":3,"3":0.8451741524292201}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.84517</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-2.465145723060455}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>-2.47</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Pan Ocean Co Ltd"}'>Pan Ocean Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"HMM Co Ltd"}'>HMM Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.935905540581882}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.93591</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-2.33130934144712}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>-2.33</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hyundai Mipo Dockyard Co., Ltd."}'>Hyundai Mipo Dockyard Co., Ltd.</td>
<td data-sheets-value='{"1":2,"2":"Korea Shipbuilding &amp;Offshore Engn Co Ltd"}'>Korea Shipbuilding &amp;Offshore Engn Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9740462682980674}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.97405</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.2401490556241117}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>2.24</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"SK Innovation Co Ltd"}'>SK Innovation Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"Samsung SDI Co Ltd"}'>Samsung SDI Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9458691690353619}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>0.94587</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.1867120471913637}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>2.19</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hanwha Aerospace Co Ltd"}'>Hanwha Aerospace Co Ltd</td>
<td data-sheets-value='{"1":2,"2":"Korea Aerospace Industries Ltd"}'>Korea Aerospace Industries Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9524282780324967}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.95243</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.086128932784612}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>2.09</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Hyundai Mipo Dockyard Co., Ltd."}'>Hyundai Mipo Dockyard Co., Ltd.</td>
<td data-sheets-value='{"1":2,"2":"Daewoo Engineering &amp; Construction Co Ltd"}'>Daewoo Engineering &amp; Construction Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8206840084895756}' data-sheets-numberformat='[null,2,"#,##0.00000",1]'>0.82068</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.9737577992711182}' data-sheets-numberformat='{"1":2,"2":"#,##0.00","3":1}'>1.97</td>
</tr>
<tr>
<td>Woori Financial Group Inc</td>
<td>Shinhan Financial Group Co., Ltd.</td>
<td style="text-align: right;">0.87902</td>
<td style="text-align: right;">-1.93</td>
</tr>
<tr><td colspan="4" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>

I grouped Korea's closely correlated sector pairs within the same GICS sub-category. I applied the additional filtering: 1. a market cap of ₩1T or more and 2. stocks eligible to short-selling (KOSPI 200 and KOSDAQ 150). This grouping returns 141 sector pairs worthy of close monitoring for a long/short trade.You can find all the 141 sector pairs with the 180-day correlation coefficients and the sigma on a 20-day moving average in the attached file.Below are the top 10 most correlated sector pairs above a 180-day correlation coefficient of 0.95 or higher. They are mostly cyclical stocks, which are in line with our conventional thinking that cyclical stocks have a stronger tendency to move together than growth stocks.








Comp 1
Comp 2
180-day correlation coefficient
Business type


Hyundai Mipo Dockyard Co., Ltd.
Korea Shipbuilding &amp;Offshore Engn Co Ltd
0.97405
Shipbuilding


Hyundai Department Store Co Ltd
Lotte Shopping Co Ltd
0.97033
Retail


GS Engineering &amp; Construction Corp
Hyundai Engineering &amp; Construction Co.
0.96379
Construction


HYUNDAI MOBIS CO., LTD.
Hyundai Motor Co
0.96145
Automotive


Shinhan Financial Group Co., Ltd.
KB Financial Group Inc
0.95989
Commercial bank


LG Innotek Co., Ltd.
LG Electronics Inc.
0.95986
IT


Hansol Chemical Co Ltd
Posco Chemical Co Ltd
0.95374
Chemical


Hanwha Aerospace Co Ltd
Korea Aerospace Industries Ltd
0.95243
Aerospace


KG DongbuSteel Co Ltd
POSCO
0.95174
Steel


KG DongbuSteel Co Ltd
Hyundai Steel Co
0.94972
Steel

Source: KRX

Below are the top 10 stocks suffering the harshest diversion on a 20-day moving average among those having a 180-day correlation coefficient of 0.80 or higher. E-Mart and Lotte Shopping top the list with a -3.27σ and a correlation coefficient of 0.85. Silicon Works/LG Electronics and BGF Retail/E-Mart follow as they are also in a heavy diversion at +2.79σ and +2.58σ, respectively. Woori Financial/KB Financial and Pan Ocean/HMM aren't far away either.








Comp 1
Comp 2
180-day correlation coefficient
Sigma on a 20-day moving average


E-Mart Inc
Lotte Shopping Co Ltd
0.85128
-3.27


Silicon Works Co Ltd
LG Electronics Inc.
0.82411
2.79


BGF Retail Co Ltd
E-Mart Inc
0.84733
2.58


Woori Financial Group Inc
KB Financial Group Inc
0.84517
-2.47


Pan Ocean Co Ltd
HMM Co Ltd
0.93591
-2.33


Hyundai Mipo Dockyard Co., Ltd.
Korea Shipbuilding &amp;Offshore Engn Co Ltd
0.97405
2.24


SK Innovation Co Ltd
Samsung SDI Co Ltd
0.94587
2.19


Hanwha Aerospace Co Ltd
Korea Aerospace Industries Ltd
0.95243
2.09


Hyundai Mipo Dockyard Co., Ltd.
Daewoo Engineering &amp; Construction Co Ltd
0.82068
1.97


Woori Financial Group Inc
Shinhan Financial Group Co., Ltd.
0.87902
-1.93

Source: KRX



Korea Sector Long/Short Pairs Trade Ideas

South Korea

LX Semicon Co., Ltd. designs, develops, and markets mixed-signal semiconductors. The Company utilizes its own algorithm and technologies to enhance the features and capabilities of flat panel displays that are used in electronic devices and mobile handsets. LX Semicon markets its products worldwide.

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LX Semicon (108320 KS)

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