TechBerlinQuary Visualization of a data-supported risk model for capital investments
AI-powered risk control

Smart stop loss: precise protection for long-term capital

TechBerlinQuary analyzes market data in real-time and triggers rule-based protection mechanisms before losses compound. The decisions follow comprehensible, documented rules - without gut feeling and without constant market monitoring.

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The graphic shows an example of how price trends are continuously compared with historical volatility patterns in order to determine threshold values for protective measures based on data.
Initial situation

Market fluctuations place a greater burden on private investors than on institutional portfolios

  • Price declines often occur at short notice and without clear warning.
  • Manual sales decisions are often driven by emotions rather than data.
  • Classic static stop losses do not react to changing volatility.
  • Constant market monitoring is hardly affordable for working families.
Solution: TechBerlinQuary's Smart Stop-Loss System continuously adjusts protection thresholds based on current market volatility. It acts in the background, documents every decision and only intervenes when predefined, rule-based criteria are met.
TechBerlinQuary team of analysts reviewing data-driven risk models
Technical basis

A rules-based system, not a black box

TechBerlinQuary's forecast models are based on historical market data, volatility metrics and defined sets of rules. Each adjustment of a stop loss level can be traced back to a specific, documented condition.

Volatility analysis

The models continuously evaluate the fluctuation ranges of individual positions and recognize when the risk profile of a security changes.

Dynamic thresholds

Stop-loss marks are not set permanently, but are recalculated regularly based on current market conditions.

Rule-based triggering

An intervention only takes place if previously defined, documented criteria are met - comprehensible and repeatable.

feature Description
Database Historical price and volatility data of exchange-traded securities
Update logic Continuous recalculation of the protection thresholds in the event of relevant market changes
Decision type Rules-based, documented, without discretionary interventions
Scope of application Long-term portfolio positions and pension portfolios
Every second Update frequency of the risk metrics in the core model
Procedure

How the system comes to a decision

01

Data collection

Price data and volatility indicators are continuously recorded and processed.

02

Risk assessment

Each position is assigned to a current risk level based on defined key figures.

03

Threshold adjustment

The stop loss mark is readjusted according to the calculated risk level.

04

Logging

Every adjustment is documented with the time and reason and can be viewed.

Example risk classification by asset class

Bonds
Stock ETFs
Individual shares

TechBerlinQuary publishes the underlying control parameters in an understandable form. Investors can see at any time which condition triggered an adjustment - there is no hidden decision logic.

Use cases

Two typical situations from practice

Building wealth over several decades

A family saves regularly in a broadly diversified ETF savings plan. Instead of manually observing the market, it leaves ongoing risk control to the Smart Stop-Loss System, which automatically hedges positions in the event of unusually high volatility.

Scenario A · Value creation
  • Automatic adjustment of protection thresholds in the event of market turbulence
  • Reduced observation effort in everyday life
  • Traceable logging of every adjustment

Protection during the payout phase of retirement provision

Anyone who already lives from their portfolio can hardly afford any major setbacks. Here, the system reduces the so-called drawdown risk by hedging positions at an early stage if market developments continue to be negative.

Scenario B · Withdrawal phase
  • Focus on capital preservation rather than short-term return maximization
  • Limiting drawdowns in crucial market phases
  • Rules-based response without emotional delay
A simulation overview is available in the customer area, which shows how different risk settings would have historically affected the value development of an example portfolio.
Frequently asked questions

Answers about security and functionality

How does the Smart Stop-Loss system differ from a classic stop-loss?

A classic stop loss is a fixed price value. The Smart Stop-Loss system continuously adjusts this value to the current volatility so that normal price fluctuations do not lead to a premature sale.

Can the system also trigger incorrectly?

Like any rule-based model, false signals can occur, for example in the case of short-term, atypical price fluctuations. The control parameters are therefore regularly checked and documented based on historical data.

Will my investment data be passed on to third parties?

No. Depot data is used exclusively to calculate risk metrics and is not passed on to third parties for advertising purposes.

Which asset classes is the system suitable for?

The system is suitable for exchange-traded securities such as ETFs, stocks and bonds for which price data of sufficient quality is continuously available.

Does TechBerlinQuary replace personal investment advice?

No. TechBerlinQuary provides data-driven risk control as a supplement to the existing investment strategy, not individual financial advice.

Data protection: All processed portfolio data is stored encrypted and used exclusively for risk calculation within the platform. Details are governed by our data protection declaration.

Get an overview of your current risk profile

  • Free initial analysis of your existing portfolio
  • Transparent representation of the current risk classification
  • No obligation to transfer the deposit
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