PROJECT

Trading Platform for Automated Trading

Custom software development, Real-time market-data integration, Broker API integration, Automated order execution, Strategy configuration, Backtesting, Risk management, Trading dashboards

  • Industry: Financial trading
  • Czech Republic Location: Czech Republic
  • Delivery time: 16 weeks
  • Technologies: Python, JavaScript / TypeScript (Node.js)
4+ months

This client spends time on manual market-data analysis and order placement. The trading platform was made to take real-time market data and incoming signals, apply the firm’s own strategies, and return controlled trades. It gives the stock trading firm one place to test strategies, monitor execution, and manage broker-connected trading.

Summary

Problem

The client spends time connecting market analysis, strategy rules, and broker actions by hand.

Solution

The solution became a trading platform with configurable strategies, broker APIs, and live execution.

Result

The platform is made to reduce manual work and execution effort from market data to controlled trades.

Client story

The client is a stock trading firm from the Czech Republic. It works with market data, trading strategies, broker connections, and order execution.

Manual analysis and order placement cost the firm time. The operation also needs validation before live execution, risk control during trading, activity monitoring, and retained records.

The request was simple: connect real-time market data and official broker APIs, apply the firm’s own strategy rules and signals, manage risk, and test performance against historical data.

The solution was shaped as separate strategy and execution modules. Monitoring, backtesting, and audit records were provided alongside them.

This kept the strategy layer distinct from broker execution while giving the firm configurable controls and paper or live modes.

The client asked for

  1. Connect live market data and broker APIs for automated order management
  2. Apply custom strategies, indicators, candle rules, and incoming signals
  3. Set position sizing, stops, risk limits, and safety controls
  4. Back-test strategies with P&L and performance reporting

Why ready-made software did not fit

Ready-made brokerage platforms provide trading and analysis, but their descriptions do not cover this client’s custom rules, incoming signals, and broker links together. The solution was designed to keep these parts in one controlled platform instead of leaving the strategy layer and execution process split across separate tools.

Project overview

The solution was designed around a modular strategy and signal layer. It applies trading parameters, indicator or candle conditions, documented rules, and incoming signals before generating buy and sell signals.

To handle live execution, broker API connections were provided for market, limit, and stop orders. The platform manages order placement, modification, and cancellation, with selectable paper or live modes.

Special attention was paid to risk controls. Position sizing, stop-loss and take-profit settings, risk limits, and an emergency kill switch are available before and during execution.

Historical testing was provided alongside live monitoring. The platform runs strategies against historical market data and presents P&L, win rate, and drawdown.

An order blotter and event timeline address the need for retained trading records. A decision log, exception list, CSV export, and SQLite record view complete the audit trail.

Key features delivered

  • Real-time market-data capture
  • Configurable strategy and signal rules
  • Automated market, limit, and stop orders
  • Broker API integration
  • Paper and live execution modes
  • Position-size calculation
  • Risk limits and safety controls
  • Historical strategy backtesting
  • Live positions, orders, and P&L dashboard
  • Trade and audit log generation

Can be added

+ Telegram signal capture or delivery + Trade copying across exchanges + Extended risk monitoring

Who else can use this solution

These businesses have a similar task, and the same solution can be adapted to their trading operations.

An options and equities trading operation

Task It needs broker-connected automated execution for strategies across stocks and options.
How the solution helps The solution connects market data and broker APIs, applies configured rules, and manages orders and positions.

A multi-broker trading operation

Task It works with several brokers, signal feeds, or existing trading scripts.
How the solution helps The modular platform keeps signal processing, execution, monitoring, and records in one place.

A binary-options trading operation

Task It copies Telegram signals into a trading platform.
How the solution helps The solution captures signal messages and uses them within an automated trading process.

Technology stack

Python

Core trading services

Python supports the automated trading, broker connections, data processing, and execution services.

JavaScript / TypeScript (Node.js)

Data and export services

JavaScript or TypeScript supports CSV parsing, formatting, and related application services.

ccxt

Exchange API connection

ccxt (a library that connects trading software with exchange APIs) provides exchange connectivity for market data and trading actions.

pandas

Market data analysis

pandas (a Python library for tables and time series) processes market data and supports strategy analysis.

TA-Lib

Technical indicators

TA-Lib (a library of technical analysis indicators) supports indicator-based strategy conditions.

websockets

Live data streams

websockets (a library for live two-way data connections) supports real-time market-data and trading updates.

grafanalib

Dashboard definitions

grafanalib (a library for building Grafana dashboards) supports dashboard views for trading status and performance.

CSV

Records and exports

CSV stores or exports trading records, results, and audit data in a simple tabular format.

SQLite

Local trading records

SQLite keeps trading records, decisions, executions, exceptions, and position data in a local database.

Integrations

Zerodha API and Upstox API

Named broker APIs support broker-connected order placement, modification, cancellation, and position management.

Telegram

Telegram carries trading signal messages that the platform can capture or deliver.

The result

Configure strategies and risk before execution

The configuration screen brings strategy conditions, position sizing, and risk limits together before trading starts. The paper/live mode switch separates testing from live execution.

The position-size calculator and stop-loss and take-profit fields make the intended controls visible before orders reach a broker.

How it works

  1. The strategy selector loads trading strategy parameters and candle or indicator conditions.
  2. The position-size calculator processes position sizing parameters.
  3. The risk controls hold stop-loss, take-profit, risk-limit, and execution-mode settings.
  • Select a live candle price jump strategy or a day candle strategy.
  • Configure paper or live execution mode.
Note: Paper trading and configurable risk settings keep strategy validation separate from live execution.
Strategy and risk configuration

Strategy and risk configuration

Functions on this screen
Configure trading parameters Position size calculator Select live candle price jump strategy Select day candle strategy

Monitor live signals, orders, and positions

The live dashboard shows market data, trading signals, and open positions in one view. It also presents order status, P&L, and the current trading state.

Real-time execution connects signals with broker actions while the dashboard keeps activity and risk status in view.

How it works

  1. The market-data panel receives real-time market data and the signal feed shows generated buy and sell signals.
  2. The order and position modules show orders, execution status, open positions, P&L, and trading activity.
  3. The trading-status indicator shows risk status and the kill-switch module provides an emergency control.
  • Monitor market data and trading signals.
  • Review open positions and order status.
  • Track P&L and trading status.
Live trading dashboard

Live trading dashboard

Functions on this screen
Capture Market Data Generate trading signals Manage Orders Real-Time Trade Execution Implement kill switch

Test strategies against historical data

The backtesting screen compares a strategy with historical market data before live execution. Its performance summary and trade-results table show the figures needed to review a strategy.

P&L, win rate, and drawdown make the test output useful for a trading analyst.

How it works

  1. The historical-data selector provides historical market data for the test.
  2. The backtest module applies the selected strategy parameters to the historical data.
  3. The performance summary, P&L chart, and trade-results table show backtest results and performance metrics.
  • Review P&L and win rate.
  • Check drawdown and Sharpe ratio.
  • Compare slippage or hit rate.
Tip: Backtesting and paper trading provide a review path before live execution.
Backtest and performance report

Backtest and performance report

Functions on this screen
Backtest Trading Strategy

Keep orders and decisions traceable

The audit screen keeps order actions, fills, and decisions together. The order blotter and execution timeline make the trading history easier to review.

The exception list, CSV export, and SQLite record view support retained trading records.

How it works

  1. The order blotter records market or limit orders, amendments, cancellations, and execution confirmations.
  2. The event timeline and decision log show fills, trade decisions, exceptions, and audit timestamps.
  3. The CSV export and SQLite record view provide exported and retained trading records.
  • Review order amendments and cancellations.
  • Inspect execution confirmations and fills.
  • Keep decision and exception records.
Orders and audit log

Orders and audit log

Functions on this screen
Manage Orders Trade Log Generation

What the solution gives

With this solution, the trading firm can:

  • Connect market data with broker APIs
  • Apply its own trading strategies and incoming signals
  • Run paper or live automated execution
  • Set position sizing, stops, and risk limits
  • Back-test strategies before live trading
  • Review orders, P&L, decisions, and exceptions

Could ready-made systems do the job?

Before the design, the task was compared with ready-made products by their own descriptions.

What the client needs Brokerage platforms Kite, thinkorswim, E*Trade Web Platform Multi-asset trading platforms MetaTrader 5, eToro, Dotbig platform Automated trading software Galileo FX, Abbado Custom solution
Connect live data and broker APIs partly
Apply custom strategies and signals —
Set risk and safety controls partly
Back-test with performance reports partly
Fits the client's own rules: stages, roles, reports — — partly
All steps in one place —
No manual steps between programs — partly

By the public descriptions of the products and their category.

Ready-made products cover parts of automated trading, broker execution, analysis, and strategy testing. A ready-made product is enough when only one of these parts is needed.

This client needed its own software because the complete task combined custom rules, signal feeds, risk controls, broker connections, backtesting, execution monitoring, and audit records in one place. The steps between market data, strategy decisions, and broker actions also needed automation.

In the end

In the end, the solution was made to take manual work out of the path from market data and trading rules to controlled broker execution.

FAQ

Thinking about building a similar system? Read the answers below to see how the platform can combine strategies, data, execution, and records.

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