In today’s briefing:
- Korean Pair Trades Review in 2022
- TEMC IPO Preview
- Recent IPOs Carrying Putback Option in Korea: Market’s Attention Is on WCP
- Line Parent’s VC Firm Leads $2.3m Funding for Korean ETF Startup
Korean Pair Trades Review in 2022
- In this insight, we review all the 16 Korean pair trade ideas in 2022.
- A few of the best performing pair trade ideas this year included long LG Chem/short LGES, long Doosan Corp/short Doosan Enerbility, and long KIH/short MFG.
- Going forward in 2023, as the market continues to show higher volatility, there could be continued strong interest in pair trade ideas in Korea.
TEMC IPO Preview
- TEMC is getting ready to complete its IPO in Korea in January 2023. TEMC is a materials company that produces specialty gases for the semiconductor and display production processes.
- The IPO price range is from 32,000 won to 38,000 won and the expected market cap is expected to be from 361 billion won to 429 billion won.
- The company’s sales increased at a 57.4% CAGR from 2019 to 2021. Its sales exploded higher by 254% YoY to reach 238 billion won in 1Q-3Q 2022.
Recent IPOs Carrying Putback Option in Korea: Market’s Attention Is on WCP
- WCP has the largest gap between the exercise and current prices (-16%). And its retail allocation is also the largest (5.44% of SO). In addition, it is subject to short-selling.
- The deadline is January 2nd. A large-scale option exercise will be unavoidable if the share price does not exceed ₩54,000 by that date.
- It is very likely that WCP’s share price will experience strong downward pressure for a week after January 2nd. We need to consider a position setup that actively utilizes this.
Line Parent’s VC Firm Leads $2.3m Funding for Korean ETF Startup
- Akros Technologies, a South Korea-based fintech firm, has raised US$2.3 million in a strategic funding round.
- The fundraise was led by ZVC – the investment arm of Line Corporation parent Z Holdings.
- Founded last year, Akros Technologies manages its own exchange-traded funds (ETFs) powered by machine learning models.
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