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PKSHA Technology Inc.(3993) Summary

3993
TSE Prime
PKSHA Technology Inc.
3,245
JPY
-25
(-0.76%)
Jan 29, 2:57 pm JST
21.20
USD
Jan 29, 12:57 am EST
Result
PTS
outside of trading hours
3,250.5
Jan 29, 2:56 pm JST
Summary Chart Historical News Financial Result
PER
35.3
PBR
2.92
Yield
ー%
Margin Trading Ratio
4.37
Stock Price
Jan 29, 2026
Opening Jan 29, 9:00 am
3,250 JPY 21.22 USD
Previous Close Jan 28
3,270 JPY 21.42 USD
High Jan 29, 2:56 pm
3,255 JPY 21.27 USD
Low Jan 29, 10:18 am
3,215 JPY 20.96 USD
Volume
127,600
Trading Value
0.41B JPY 2.70M USD
VWAP
3235.68 JPY 21.14 USD
Minimum Trading Value
324,500 JPY 2,120 USD
Market Cap
0.10T JPY 0.68B USD
Number of Trades
429
Liquidity & Number of Trades
As of Jan 29, 2026
Liquidity
High
1-Year Average
1,396
1-Year High Jan 29, 2025
6,749
Margin Trading
Date Short Interest Long Margin Positions Ratio
Jan 23, 2026 284,500 1,775,200 6.24
Jan 16, 2026 178,300 1,713,700 9.61
Jan 9, 2026 242,000 1,717,500 7.10
Dec 26, 2025 248,100 1,714,000 6.91
Dec 19, 2025 246,600 1,827,700 7.41
Company Profile
PKSHA Technology Inc. is an AI venture company focusing on deep learning technology development, including image recognition and automated dialogue. The company collaborates with Toyota.
Sector
Information & Communication
PKSHA Technology Inc. develops algorithm modules centered on machine learning, natural language processing, and deep learning as an AI venture. Utilizing these technologies, the company supports client businesses in improving operational efficiency and enhancing added value. In its AI Research & Solution business, PKSHA Technology conducts comprehensive services from joint research and development to solution provision with partner companies. The AI SaaS business offers products such as automated response engines, FAQ systems, and RPA software, enabling automation and efficiency in corporate customer touchpoints and internal operations. Through partnerships with industry-leading companies, PKSHA Technology develops high-quality software. The company achieves high retention rates and profitability through accuracy improvements based on data feedback and a monthly subscription model.