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PKSHA Technology Inc.(3993) Summary

3993
TSE Prime
PKSHA Technology Inc.
3,045
JPY
-15
(-0.49%)
Mar 13, 3:30 pm JST
19.10
USD
Mar 13, 2:30 am EDT
Result
PTS
outside of trading hours
3,030.5
Mar 13, 11:57 pm JST
Summary Chart Historical News Financial Result
PER
33.1
PBR
2.67
Yield
ー%
Margin Trading Ratio
4.37
Stock Price
Mar 13, 2026
Opening Mar 13, 9:00 am
3,000 JPY 18.84 USD
Previous Close Mar 12
3,060 JPY 19.24 USD
High Mar 13, 10:26 am
3,085 JPY 19.39 USD
Low Mar 13, 9:04 am
2,972 JPY 18.68 USD
Volume
671,000
Trading Value
2.04B JPY 0.01B USD
VWAP
3035.24 JPY 19.04 USD
Minimum Trading Value
304,500 JPY 1,910 USD
Market Cap
0.10T JPY 0.61B USD
Number of Trades
1,010
Liquidity & Number of Trades
As of Mar 13, 2026
Liquidity
High
1-Year Average
1,341
1-Year High Aug 15, 2025
4,063
Margin Trading
Date Short Interest Long Margin Positions Ratio
Mar 6, 2026 329,800 1,741,900 5.28
Feb 27, 2026 337,800 1,774,700 5.25
Feb 20, 2026 322,100 1,967,700 6.11
Feb 13, 2026 303,000 1,943,500 6.41
Feb 6, 2026 296,500 1,846,500 6.23
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.