Representative image of Ongshoiyon real-time market data analysis dashboard

Data-driven investment analysis

Real-time analysis across 500+ trading pairs, before decisions

Ongshoiyon converts each market signal into verifiable numbers. As a result, even first-time investors can make decisions based on constructive logic rather than guesswork.

Pear under observation500+
Data refresh intervalat the second-level
Risk classification3 layers

Parallel monitoring of over 500 trading pairs

The table below is a simplified sample of an analysis structure — an example of how data is categorized into a comparable structure.

Sample Snapshot — Image for illustrative purposes, not live value

pairchange (24h)Volume levelsignal
Pair A/USD+2.34%highobservation
Pair B/USD-1.12%the middleneutral
Pair C/USD+0.48%lowerneutral
Pair D/USD-3.09%highwarning

Analysis at this scale means comparisons can be done automatically, which are not possible by hand. Abnormal volumes, price deviations and co-related patterns are identified from among 500+ pairs, so that important signals are not lost in the crowd.

Representative image of Ongshoiyon's data analysis environment

A structured path from numbers to conclusions

Ongshoiyon is built on the idea that the key to reducing market complexity is to properly organize data. Each module is based on real-time feeds, historical patterns and predefined risk rules.

The purpose of the platform is not to make definitive predictions about market movements, but to present existing information quickly and comparably — so that even first-time investors can make rational decisions.

How raw data turns into verifiable signals

  1. Data collection. Price, volume and order-book data from 500+ pairs are collected at second-level intervals.
  2. Noise filtering. Pattern-based changes are identified by isolating short-term random fluctuations.
  3. Risk Scoring. Each pair is given a numerical score based on historical volatility and current liquidity.
  4. signal presentation. The final result is shown as a ranked list, with a brief reason explanation.
Real-time feed (500+ pairs)
↓
Noise filter module
↓
Risk Scoring Model
↓
Ranked signal list

Risk assessment and recommendation module

The following metrics show how the system measures the risk position of a selected pair or portfolio.

Volatility Index the middle

Determined based on last 24 hours price deviation.

liquidity level high

Derived from order-book depth and recent volume analysis.

Co-relationship risk lower

A measure of the value relationship of the selected portfolio with other pairs.

exposure limits can be set

User can set the limit as per their tolerance.

Recommendation engine — sample output

Based on the selected risk profile, the system makes a proposal to redistribute exposure, with a brief reason for each change. The user can accept, modify or reject each recommendation individually — decisions are not automatically implemented.

Detailed explanation about model and data source

It's important to know before making decisions — what data is coming from where and how the system reaches its conclusions. Below is a summary of that explanation.

Where the data is collected from

Price, volume and order-book information for each pair is collected directly from the exchange feed. No data is input manually, thereby reducing the possibility of deviations caused by human error.

How the model determines the signal

The model makes comparisons between historical patterns and current market behavior. No single signal is considered conclusive — a score is created by combining multiple indicators.

What are the system limitations?

Analysis is based on historical and current data; It does not guarantee the future. The impact of sudden and unprecedented market events cannot be fully predicted.

How User Data is Used

Personal portfolio information is used only for making personalized recommendations. Detailed policies are explained in the Privacy Policy.

How investors of different profiles use the platform

New investors

One of the biggest hurdles when first entering the market is information overload and lack of understanding of what is important. Ongshoiyon in this case breaks down complex data into simplified risk levels, so that there is at least basic context before making decisions.

3 layersRisk classification
in plain languageCause of each signal

Active Trader

Time is of the essence for short-term decisions. Second-level refresh of 500+ pairs and abnormal volume detection help active traders monitor multiple markets at once.

second-leveldata refresh
automaticDetection of volume deviations

Portfolio Manager

Understanding the co-relation and combined risk between multiple pairs is manually complex. The recommendation engine suggests exposure redistribution, which the manager can verify and implement at his own discretion.

Consolidated viewFor multiple portfolios
verifiableReasons for each recommendation

The first step toward data-supported decisions

Creating an account on Ongshoiyon gives you access to real-time analysis, risk scoring and recommendation modules of 500+ pairs. The registration process is simple and takes a few minutes.

Register account
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