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
Fri, 10 Jul 2026	₩12.0t	₩9.4t	₩197.5b	10.7x	60.8x	1.3x
Sun, 07 Jun 2026	₩14.0t	₩9.5t	₩259.9b	12.8x	54x	1.5x
Tue, 05 May 2026	₩15.6t	₩9.3t	₩123.5b	15.6x	126x	1.7x
Thu, 02 Apr 2026	₩14.3t	₩9.3t	₩152.8b	15.9x	93.7x	1.5x
Sat, 28 Feb 2026	₩14.9t	₩9.1t	₩133.1b	15.6x	112.2x	1.6x
Mon, 26 Jan 2026	₩14.7t	₩9.1t	₩132.9b	16.1x	110.9x	1.6x
Wed, 24 Dec 2025	₩14.3t	₩9.1t	₩132.9b	15x	107.4x	1.6x
Fri, 21 Nov 2025	₩13.8t	₩8.9t	₩136.9b	14.4x	100.6x	1.5x
Sun, 19 Oct 2025	₩13.4t	₩8.8t	₩127.3b	14.3x	105.2x	1.5x
Tue, 16 Sep 2025	₩13.7t	₩8.8t	₩140.0b	16.9x	97.7x	1.6x
Thu, 14 Aug 2025	₩13.2t	₩8.5t	₩123.9b	17.3x	106.9x	1.6x
Sat, 12 Jul 2025	₩14.7t	₩8.4t	₩163.3b	19.2x	90.2x	1.7x
Mon, 09 Jun 2025	₩13.1t	₩8.4t	₩168.0b	16x	78x	1.6x
Wed, 07 May 2025	₩11.9t	₩8.0t	₩175.0b	15.7x	68x	1.5x
Fri, 04 Apr 2025	₩11.0t	₩8.0t	₩176.3b	14.8x	62.4x	1.4x
Sun, 02 Mar 2025	₩12.0t	₩7.6t	₩95.2b	15.5x	126.3x	1.6x
Tue, 28 Jan 2025	₩11.7t	₩7.6t	₩94.4b	15.7x	124x	1.5x
Thu, 26 Dec 2024	₩11.1t	₩7.2t	₩124.0b	15.1x	89.1x	1.5x
Sat, 23 Nov 2024	₩11.0t	₩7.2t	₩101.0b	14.5x	109.3x	1.5x
Mon, 21 Oct 2024	₩10.1t	₩7.0t	₩97.3b	14x	104x	1.4x
Wed, 18 Sep 2024	₩10.5t	₩6.5t	₩127.4b	12.5x	82.6x	1.6x
Fri, 16 Aug 2024	₩10.5t	₩6.7t	₩72.5b	15x	144.6x	1.6x
Sun, 14 Jul 2024	₩11.8t	₩6.7t	₩72.6b	15x	162.7x	1.8x
Tue, 11 Jun 2024	₩12.5t	₩6.8t	₩38.5b	16.9x	323.1x	1.8x
Thu, 09 May 2024	₩12.7t	₩6.6t	₩86.1b	16.8x	147x	1.9x
Sat, 06 Apr 2024	₩12.4t	₩6.6t	₩64.6b	16.4x	192.8x	1.9x
Mon, 04 Mar 2024	₩13.0t	₩6.3t	₩29.3b	20.4x	442.2x	2.1x
Wed, 31 Jan 2024	₩13.8t	₩6.3t	₩29.6b	21.3x	466.5x	2.2x
Fri, 29 Dec 2023	₩12.8t	₩6.4t	₩40.2b	19.4x	318.4x	2x
Sun, 26 Nov 2023	₩12.9t	₩6.2t	₩56.6b	18.1x	227.5x	2.1x
Tue, 24 Oct 2023	₩11.8t	₩6.1t	₩34.3b	16.8x	343.5x	1.9x
Thu, 21 Sep 2023	₩13.7t	₩6.1t	₩24.9b	19.1x	547.5x	2.2x
Sat, 19 Aug 2023	₩13.1t	₩5.9t	₩79.7b	17.7x	164.6x	2.2x
Mon, 17 Jul 2023	₩13.1t	₩5.9t	₩91.8b	17.6x	142.1x	2.2x

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 60.8x which is lower than its 3-year average PE of 174x.

The 3-year average PS ratio of 1.7x is higher than the industry's current PS ratio of 1.3x.

Past Earnings Growth

The earnings for companies in the Software industry have grown 29% per year over the last three years.
Revenues for these companies have grown 17% 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	-4.86%
Tech	-3.13%
Software	-1.75%
Application Software	-0.56%
Systems Software	-2.65%

Industry PE

Investors are most optimistic about the Systems Software industry even though it's trading below its 3-year average PE ratio of 33.8x.

Analysts are expecting annual earnings growth of 18.5%, which is lower than the prior year's growth of 30.1% per year.

Forecasted Growth

Analysts are most optimistic on the Application Software industry, expecting annual earnings growth of 39% over the next 5 years.
This is better than its past earnings decline of 0.5% per year.

In contrast, the Systems Software industry is expected to see its earnings grow by 18% 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
A477850 MakinaRocks	₩29.60k	26.5% +₩108.8b	n/a	PS38.9x
A263800 Datasolution	₩7.30k	55.0% +₩42.0b	27.6%	PE39.4x
A189330 XIIlabLtd	₩12.23k	23.0% +₩21.5b	55.6%	PS10.8x
A205100 EXEM	₩1.65k	16.6% +₩16.6b	-31.1%	PE13.8x
A053800 AhnLab	₩55.50k	3.0% +₩15.3b	-16.8%	PE9.5x

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

Now 22% overvalued

Investor sentiment improves as stock rises 19%

New minor risk - Share price stability

Investor sentiment improves as stock rises 17%

Investor sentiment improves as stock rises 18%

Investor sentiment improves as stock rises 17%

Now 20% undervalued after recent price drop

Investor sentiment deteriorates as stock falls 25%

New minor risk - Market cap size

New minor risk - Market cap size

Investor sentiment deteriorates as stock falls 15%

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

New major risk - Financial position

AhnLab's (KOSDAQ:053800) Profits Appear To Have Quality Issues

New minor risk - Share price stability

XIIlab Co.,Ltd to Report Q1, 2026 Results on May 28, 2026