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AI-Driven Decision Intelligence

Next-generation decision-making guided by data

Shift Kinrix Opt uses back-tested AI models to analyze market data in real-time, providing traders and investment decision-makers with practical strategic advantages. Logic that has been repeatedly verified using past data supports daily decisions.

Issue recognition

Confidence in vast amounts of data.

The amount of data generated by the market continues to increase year by year, and it is not easy to process price fluctuations, trading volumes, news, indicator announcements, etc. manually. Balancing the speed and accuracy of decisions is an ongoing burden for many traders and analysts.

Shift Kinrix Opt was designed to alleviate this burden. We aim to develop confidence based on data while facing the daily stresses of misjudging risks and missing the necessary information to make decisions.

  • 01

    Delay in judgment due to information overload

    Confirming data from multiple markets and time frames at the same time slows down decision-making.

  • 02

    Risk of relying on intuitive judgment

    If past winning rates and verification data are lacking, it will be difficult to maintain strategy reproducibility.

  • 03

    Delay in responding to volatility

    Without a mechanism to reevaluate risk in real time, your response to sudden market fluctuations will be delayed.

Core Features

Three functions provide consistent support from analysis to execution

We have dedicated mechanisms for each stage of decision-making: prediction, risk assessment, and execution.

Feature 01

AI predictive modeling

A model that has learned historical price patterns and changes in trading volume detects statistical regularities in market data. The purpose is to capture correlations that are difficult to see with simple technical indicators over a broader time frame.

  • Pattern detection across multiple time axes
  • Ensure reproducibility based on back-tested logic
  • Recalibration of the model in response to changes in the market environment
Predictive pattern detection engine
Feature 02

Real-time risk assessment

We continually update the risk amount for each position by comparing it with verification results from past similar situations. By comparing back-tested scenarios with current market conditions, we support decisions on how to respond when unexpected fluctuations occur.

  • Quantification of risk by comparison with past scenarios
  • Providing information as an alert in case of sudden market changes
  • Risk aggregation on a portfolio basis
Real-time Risk reassessment
Feature 03

Proposal execution support

Recommendations derived from the analysis are output in a format that is easy to incorporate into existing trading workflows. We place emphasis on reducing the time required from checking analysis results to implementing them, and reducing the time lag between judgment and action.

  • Structured output format of analysis results
  • Designed to work with existing trading environments
  • Circular structure that reflects the results after execution in the next analysis
Actionable Execution support

How it works

3 steps from data collection to proposal

By clearly separating each process, we maintain transparency that allows us to confirm the basis of our decisions later.

01

data collection

Continuously captures price, volume, and related market indicators and formats them for analysis.

02

AI analysis

Back-tested models process the acquired data and extract risks and patterns from comparisons with similar past situations.

03

Optimized suggestions

The analysis results are organized by priority and risk level, and presented in an easy-to-use format for the next decision.

Use cases

Two possible usage scenarios

Shift Kinrix Opt is aimed at everyone from corporate investment teams to individual day traders who want to improve the accuracy of their decisions.

Scenario A

Risk hedging strategy for corporations

It is assumed that a management team that owns multiple asset classes periodically checks the risk concentration of the entire portfolio. Utilizing back-tested scenario analysis, you can understand in advance how much of an impact unexpected market fluctuations will have.

Examples of quantitative results

Early identification of risk concentration points and shortening of review time before making response decisions.

Scenario B

Accuracy-oriented buying and selling for individual traders

It is assumed that an individual trader who follows short-term price movements monitors multiple signals at the same time. We aim to make decisions that do not rely solely on intuition by organizing the materials for making entry and exit decisions while referring to verification results using past data.

Examples of quantitative results

Improving the consistency of trading rules by visualizing the basis for decisions.

Shift Kinrix Opt team verifying data analysis platform

About the Platform

Design philosophy that prioritizes reliability

Rather than emphasizing flashy prediction accuracy, Shift Kinrix Opt focuses on accumulating proposals based on verifiable evidence. All models are provided after backtesting using past data, and prerequisites for actual operation are also clearly stated.

The final decision-making decision always rests with the user. What we provide is organized information and evidence to support that decision.

Add AI intelligence to your strategy.

Start your smarter investment experience with Shift Kinrix Opt. We also accept consultations and demonstrations before implementation.

Try it now for free