South Korean (KOSPI) Software Industry Analysis

Industry Valuation and Performance

Has the South Korean Software Industry valuation changed over the past few years?

Date	Market Cap	Revenue	Earnings	PE	Absolute PE	PS
Thu, 30 Jul 2026	₩7.7t	₩8.9t	₩101.4b	10.3x	76x	0.9x
Sat, 27 Jun 2026	₩11.5t	₩9.5t	₩258.6b	10.5x	44.6x	1.2x
Mon, 25 May 2026	₩15.7t	₩9.3t	₩135.4b	15x	115.6x	1.7x
Wed, 22 Apr 2026	₩15.8t	₩9.3t	₩123.5b	16.6x	128x	1.7x
Fri, 20 Mar 2026	₩14.6t	₩9.0t	₩113.4b	15.9x	128.8x	1.6x
Sun, 15 Feb 2026	₩14.4t	₩9.1t	₩132.9b	15.8x	108.4x	1.6x
Tue, 13 Jan 2026	₩14.3t	₩9.1t	₩132.9b	14.4x	107.8x	1.6x
Thu, 11 Dec 2025	₩14.5t	₩9.0t	₩161.6b	15.6x	89.8x	1.6x
Sat, 08 Nov 2025	₩14.2t	₩8.8t	₩127.3b	15.8x	111.5x	1.6x
Mon, 06 Oct 2025	₩14.1t	₩8.8t	₩127.3b	14.8x	110.6x	1.6x
Wed, 03 Sep 2025	₩12.9t	₩8.8t	₩142.6b	16.3x	90.8x	1.5x
Fri, 01 Aug 2025	₩14.0t	₩8.6t	₩117.6b	18.7x	118.8x	1.6x
Sun, 29 Jun 2025	₩14.2t	₩8.5t	₩171.3b	18.7x	83.1x	1.7x
Tue, 27 May 2025	₩11.8t	₩8.2t	₩177.0b	17x	66.9x	1.4x
Thu, 24 Apr 2025	₩12.2t	₩8.0t	₩175.0b	15.7x	69.6x	1.5x
Sat, 22 Mar 2025	₩11.4t	₩7.9t	₩85.3b	16.1x	133.2x	1.4x
Mon, 17 Feb 2025	₩13.0t	₩7.6t	₩94.4b	15.6x	137.7x	1.7x
Wed, 15 Jan 2025	₩11.2t	₩7.5t	₩87.5b	14.5x	127.5x	1.5x
Fri, 13 Dec 2024	₩11.3t	₩7.2t	₩123.6b	16.1x	91.8x	1.6x
Sun, 10 Nov 2024	₩11.0t	₩7.0t	₩97.3b	13x	112.5x	1.6x
Tue, 08 Oct 2024	₩10.4t	₩7.0t	₩97.3b	14.1x	107x	1.5x
Thu, 05 Sep 2024	₩10.5t	₩7.0t	₩101.7b	14.9x	103.6x	1.5x
Sat, 03 Aug 2024	₩10.6t	₩6.7t	₩72.5b	15.1x	146.7x	1.6x
Mon, 01 Jul 2024	₩12.1t	₩6.8t	₩43.5b	15.6x	279.2x	1.8x
Wed, 29 May 2024	₩12.7t	₩6.7t	₩74.7b	17.6x	169.6x	1.9x
Fri, 26 Apr 2024	₩12.5t	₩6.6t	₩75.6b	15.9x	164.8x	1.9x
Sun, 24 Mar 2024	₩12.6t	₩6.4t	₩41.6b	18.7x	303.1x	2x
Tue, 20 Feb 2024	₩13.7t	₩6.3t	₩29.3b	21.3x	468.2x	2.2x
Thu, 18 Jan 2024	₩13.0t	₩6.3t	₩29.6b	21.2x	439.7x	2.1x
Sat, 16 Dec 2023	₩12.7t	₩6.4t	₩40.2b	18.7x	316.7x	2x
Mon, 13 Nov 2023	₩12.2t	₩6.1t	₩38.0b	17.1x	321.5x	2x
Wed, 11 Oct 2023	₩12.6t	₩6.1t	₩36.5b	17.9x	346.3x	2.1x
Fri, 08 Sep 2023	₩14.5t	₩6.1t	₩30.2b	19.8x	479.9x	2.4x
Sun, 06 Aug 2023	₩13.8t	₩5.9t	₩80.5b	17.4x	171.7x	2.3x

Current Industry PE

Investors are pessimistic on the South Korean Software industry, indicating that they anticipate long term growth rates will be lower than they have historically.

The industry is trading at a PE ratio of 76.0x which is lower than its 3-year average PE of 172x.

The 3-year average PS ratio of 1.7x is higher than the industry's current PS ratio of 0.86x.

Past Earnings Growth

The earnings for companies in the Software industry have grown 8.0% per year over the last three years.
Revenues for these companies have grown 15% per year.
This means that more sales are being generated by these companies overall, and subsequently their profits are increasing too.

Industry Trends

Which industries have driven the changes within the South Korean Tech industry?


KR Market	-16.51%
Tech	-21.34%
Software	-4.67%
Application Software	-2.68%
Systems Software	-7.61%

Industry PE

Investors are most optimistic about the Systems Software industry even though it's trading below its 3-year average PE ratio of 33.5x.

Analysts are expecting annual earnings growth of 53.1%, which is higher than its past year's earnings growth of 28.9% per year.

Forecasted Growth

Analysts are most optimistic on the Systems Software industry, expecting annual earnings growth of 53% over the next 5 years.
This is better than its past earnings growth rate of 29% per year.

In contrast, the Application Software industry is expected to see its earnings grow by 38% per year over the next few years.

Top Stock Gainers and Losers

Which companies have driven the market over the last 7 days?

Company	Last Price	7D	1Y	Valuation
A402030 Konan Technology	₩13.76k	18.7% +₩27.2b	-60.8%	PS5.1x
A463020 NEWEN AILtd	₩7.40k	8.7% +₩5.2b	-76.4%	n/a
A340810 SECERN AI	₩2.97k	13.8% +₩4.9b	-22.5%	PS2.5x
A054920 HancomWITH	₩3.39k	5.8% +₩4.6b	-32.4%	PE14.2x
A417860 OBZEN	₩7.30k	8.6% +₩2.7b	-59.0%	PS1.5x

Nota Ai Has Two Moe Quantization Papers Accepted At Icml 2026 Workshop

Nota AI announced that two of its papers on MoE-specific quantization algorithms have been accepted to the Resource-Adaptive Foundation Model Inference (AdaptFM) Workshop at ICML 2026. The AdaptFM Workshop focuses on technologies that enable large-scale AI models to run efficiently under limited computing resources. This achievement is significant as it recognizes Nota AI's accumulated technical expertise in optimizing Mixture-of-Experts (MoE) models, an architecture increasingly regarded as a core structure for large language models (LLMs). MoE models improve both performance and efficiency by activating only a subset of expert models as needed. However, their complex structure requires a different approach to quantization, the process of making models smaller and more efficient, compared to conventional model architectures. Nota AI previously won both its track and the overall competition at the NVIDIA Nemotron Hackathon with a data-driven MoE quantization method. With the acceptance of these two papers, Nota AI will once again present research outcomes specifically designed for MoE architectures on a global research stage. The first accepted paper, "DREAM-MoE," proposes a method to reduce changes in a model's decision flow that can occur when large-scale AI models are quantized across multiple segments. The method focuses on the fact that even a small error in an earlier segment can affect expert selection in later segments. DREAM-MoE helps the quantized model select experts in a way that remains closer to the original model. The second paper, "SRA-MoE," proposes a method that identifies and prioritizes important inputs that have a greater impact on the model's final output. Rather than treating all inputs equally, SRA-MoE is designed to prevent expert selection from being significantly disrupted for these key inputs, helping maintain model quality more effectively under limited resources. Both studies demonstrated higher performance compared to the latest MoE-specific quantization methods. This shows that large-scale AI models can be executed with less memory and fewer computing resources while reducing quality degradation. Nota AI has been proactively focusing its R&D efforts on optimizing large AI models that require substantial memory and computing resources. The company is advancing large-scale model optimization, including Solar MoE, as part of the sovereign foundation model project led by the Upstage consortium. It is also expanding its experience in quantizing NVIDIA Nemotron 3 Nano to newer large models such as Nemotron Ultra, further broadening the scope of its optimization technologies. In addition, Nota AI will host "Nota AI - Korea Efficient Days" during ICML 2026 at COEX in Seoul. The event will bring together global researchers, engineers, and business leaders visiting Korea to share research trends and industrial applications of Efficient AI. Through the event, Nota AI plans to introduce its research achievements in large-scale AI model optimization and expand opportunities for technical collaboration and business engagement.

South Korean (KOSPI) Software Industry Analysis

Industry Valuation and Performance

Industry Trends

Top Stock Gainers and Losers

Latest News

New minor risk - Share price stability

SKAI worldwide Co., Ltd. announced that it has received KRW 3 billion in funding

Investor sentiment deteriorates as stock falls 15%

Investor sentiment deteriorates as stock falls 18%

Investor sentiment deteriorates as stock falls 17%

Playgram Co., Ltd. announced that it expects to receive KRW 8.4999937 billion in funding from MDS Intelligence Inc., WIZIT Co., Ltd., Je Fur A Invest Co.,Ltd. and other investors

New major risk - Share price stability

Investor sentiment improves as stock rises 18%

Less than half of directors are independent

Nota Ai Has Two Moe Quantization Papers Accepted At Icml 2026 Workshop

New major risk - Financial position

New minor risk - Financial data availability

Investors Can Find Comfort In GaeaSoft's (KOSDAQ:051160) Earnings Quality

New minor risk - Share price stability

New major risk - Market cap size

New major risk - Financial position