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Veqorix overview of the investment tracking analytics platform

Smarter investing through data

Automatic recognition of entry points for long-term portfolio construction

Veqorix combines systematic periodic investing (DCA method) with predictive modeling of market conditions. The result is an optimized position entry, adapted for periods when you don't have time for daily market monitoring between projects.

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Example display illustrative data
  • Signal statusInput active
  • Deviation from the average-2.4%
  • Risk levelModerate
  • Last update3 min ago

Mechanism

How the system recognizes entry points and allocates investments

Instead of one-time investment decisions, Veqorix tracks selected market indicators and divides the total amount intended for investment into smaller, time-spaced roles. Predictive modeling assesses current market conditions and determines when the placement of stakes is statistically more favorable, rather than making payments strictly according to a fixed calendar.

Automatic recognition of entry points

The model analyzes the volatility and movement of the price in short intervals and adjusts the moment of execution of each payment.

Adjustable stake size

The amount of the individual payment decreases in periods of increased volatility, and increases in more stable conditions, within predefined limits.

Periodic scheduling (DCA)

The basic rhythm of payments remains periodic, which maintains investment discipline regardless of short-term market movements.

Transparent record of decisions

Each payment made is recorded together with the parameters that influenced the selected moment of execution.

Veqorix interface for viewing spread payments and risk parameters
An overview of the parameters that the model takes into account when allocating payments.
Input data
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Predictive model
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Risk check
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Payment execution

Data overview

Overview of risk assessment signals and parameters

The diagram below illustrates the form and density of data that the platform works with. The values ​​are an example interface and not actual market readings.

Instrument / portfolio Signal Volatility (30d) Risk assessment Last update
Portfolio A — Broader Market Index Input active 12.3% Low 3 min ago
Portfolio B — bond fund Waiting 4.1% Low 1 min ago
Portfolio C — Diversified ETF Input active 18.7% Moderate 5 min ago
Portfolio D — sector fund Paused 27.9% Tall 2 min ago

Volatility (30 days)

The range of price fluctuations in the observed period, the basic input for estimating the moment of execution.

Maximum drop in value

The limit of the allowable short-term fall (drawdown) before the deployment is automatically slowed down.

Correlation with the reference index

A measure of compliance of the instrument's movement with the selected market reference indicator.

Liquidity of the instrument

Assessment of the possibility of payment or withdrawal without significant impact on the price.

Methodology

The process from data collection to payment execution

Each step follows pre-defined rules, so the procedure can be checked at any time.

01

Data collection

Market data is pulled from available sources at regular intervals and stored for further processing.

02

Predictive modeling

Statistical models estimate the probability of short-term price movements based on historical patterns and current conditions.

03

Risk assessment

The modeling result is checked against predefined risk parameters before any execution decision.

04

Determining the entry point

If the conditions are favorable, the system determines the moment and size of the next payment within the existing DCA schedule.

05

Monitoring and recording

Each completed or delayed payment is recorded with the associated parameters for subsequent verification and analysis.

Technical notes

  • The models are updated based on new market data at intervals of several minutes.
  • Decisions on the schedule of payments are based exclusively on pre-defined statistical rules.
  • Portfolio parameters are set before the first payment is made and can be changed afterwards.

Algorithm security fences

  • The upper limit of a single payment, regardless of the model signal.
  • Automatic deployment pause if volatility exceeds a defined threshold.
  • Ability to manually stop or change the schedule at any time.
  • Limitation of exposure to an individual instrument within the portfolio.

For freelancers

Solutions for irregular income rhythm and limited time

Three situations that independent professionals most often encounter when trying to invest regularly.

Irregular inflow of fees

The problem

Fees arrive at different intervals, so it is difficult to determine a fixed monthly amount to invest in advance.

Access

The payment schedule can be tied to available funds after each payment, instead of a fixed calendar date.

The goal: investing without manual calculation after each payment received.

Limited time to monitor the market

The problem

Between projects, there is little time left for daily analysis of charts, news and market announcements.

Access

Predictive modeling takes over monitoring of market conditions, and an overview of executed decisions is available through a periodic summary.

Goal: less than 10 minutes per month to review the payments made.

Tendency to make decisions under the influence of the moment

The problem

Sudden price changes often encourage premature decisions to buy or sell, contrary to the long-term plan.

Access

The parameters for entering a position are defined in advance and do not change under the influence of short-term reactions to the market.

The goal: consistent adherence to pre-set scheduling rules.

Safety and reliability

Questions about data protection and risk management

Answers to the most frequently asked questions before setting up your first portfolio.

How is my data protected?

Data is transmitted via an encrypted connection and stored with limited access according to the principle of the necessary minimum. Access to internal systems is limited to personnel involved in platform maintenance.

Who has access to my financial information?

Access is limited to systems necessary to perform analysis and schedule payments. Data is not shared with third parties for purposes that are not directly related to the operation of the platform.

How long does it take to set up the analysis?

The initial setting of portfolio parameters and risk limits usually takes a few minutes, after which the system begins to monitor market conditions according to a defined schedule.

Can I stop automated payments at any time?

Scheduling can be manually paused or adjusted without losing previously recorded data on payments made.

What happens during periods of extreme market volatility?

When the volatility exceeds a predefined threshold, the deployment is automatically slowed down or temporarily stopped, until the parameters are brought back into line with the set risk limits.

Review how the payment schedule would look on your portfolio

Setting the initial parameters does not require prior experience with algorithmic investing. The model can be adjusted to the amount and frequency of your income.

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