Qantova lets remote professionals copy-trade AI strategies that have already proven themselves, so your capital follows a tested approach instead of your own screen-time.
Remote work already demands sustained focus. Watching charts on top of that is rarely a sustainable way to manage money.
Most independent investors are not short of data; they are short of time to interpret it. Price movements, macro news and sentiment shifts arrive continuously, and manual analysis struggles to keep pace while you are focused on client work or billable hours.
The result is often reactive decision-making: entering positions late, holding them too long, or avoiding the market altogether out of caution.
Qantova processes market data continuously and converts it into a small set of validated strategies. Rather than asking you to interpret signals yourself, it lets you allocate to strategies that have already passed a defined set of performance and risk checks.
Each strategy available on Qantova is built on three connected components, each measured against clear, outcome-based criteria.
Models are trained on historical and live market data to identify patterns with a measurable edge. Each strategy is scored on consistency across different market conditions before it is listed for copy-trading, not just on peak performance.
Position sizing, exposure limits and drawdown thresholds are built into every strategy. You set the maximum allocation and risk tolerance; the system applies those limits automatically rather than leaving enforcement to discretion.
Strategy performance is reported with the same metrics used for selection, updated as new data arrives. If a strategy's risk profile changes materially, you are notified so you can review your allocation.
The lifecycle below is the same for every strategy on the platform, regardless of asset class.
Market feeds, pricing data and relevant indicators are collected continuously and standardised so the models work from a consistent, up-to-date dataset.
Before any signal reaches your account, it is checked against the strategy's own risk rules and against your personal allocation limits. Signals that fail either check are discarded.
Validated trades are mirrored into your account at the sizing you have approved. You retain the ability to pause a strategy or adjust its allocation at any time; the automation handles execution, not your overall risk settings.
Many of the people using Qantova are consultants, developers or freelancers working across time zones. The appeal of copy-trading AI strategies is not speed; it is the ability to step away from the markets without stepping away from your financial plan.
Because risk parameters and allocation limits are set in advance, strategies continue operating within those boundaries whether you are in a client meeting, asleep, or simply offline for the day.
Weekly summaries and threshold-based alerts are designed to replace constant screen-checking, not add another dashboard to watch.
These are the questions we are asked most often, answered without marketing language.
Account data is handled under B2B-grade security practices, including encryption in transit and at rest, and role-based access to internal systems. Qantova does not take custody of your funds directly; trades are executed through regulated brokerage connections, and you retain visibility and control over your own account at all times.
No predictive model performs identically in every market condition, and past results do not guarantee future ones. What Qantova controls for is consistency: strategies are evaluated across multiple market regimes before listing, and ongoing performance is reported using the same risk-adjusted metrics used in selection, so you can judge a strategy on the same basis it was approved.
You connect a supported brokerage account, set your risk tolerance and maximum allocation per strategy, then choose which validated strategies to follow. The platform mirrors trades within those limits from that point onward. You can pause, adjust or stop copying a strategy at any time.
Set your risk parameters once, choose the strategies that fit your comfort level, and review performance on your own schedule.