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Backtesting is a crucial part of a software development process that allows developers to simulate a trading strategy through specific historical data sets. By looking at the past results of the simulation, a Backtesting Developer can further refine and polish a trading system to ensure maximum efficiency and accuracy. This allows clients to optimize the entire process and give their strategies the best chance of success.
A quality Backtesting Developer will have an in depth understanding of modern quantitative trading strategies and techniques. This includes understanding scripting languages such as Python and R, as well as TradingView strategies. Backtesting also requires an understanding of finance markets, so including financial forecasting topics such as Kalman Filters or Multi-factor Models is essential for successful analysis.
By creating simulations based on specific criteria and inputs, our expert Backtesting Developers can create accurate models to assess profitability and accurate predictions of future price movements.
Here’s some projects that our expert Backtesting Developer made real:
As you can see, Backtesting Developers often have highly technical abilities in order to accurately assess algorithmic trading scenarios. Their expertise in scripting languages allow them to quickly set up simulations that can provide valuable insights into the profitability of a specific trading system. At Freelancer.com, you can employ exceptional Backtesting Developers to help take your quantitative trading strategies to the next level! So don't hesitate and post your own project now! Hire an expert Backtesting Developer on Freelancer.com today for assistance with refining your algorithms or creating new ones from scratch!
From 4,916 reviews, clients rate our Backtesting Developers 4.92 out of 5 stars.Backtesting is a crucial part of a software development process that allows developers to simulate a trading strategy through specific historical data sets. By looking at the past results of the simulation, a Backtesting Developer can further refine and polish a trading system to ensure maximum efficiency and accuracy. This allows clients to optimize the entire process and give their strategies the best chance of success.
A quality Backtesting Developer will have an in depth understanding of modern quantitative trading strategies and techniques. This includes understanding scripting languages such as Python and R, as well as TradingView strategies. Backtesting also requires an understanding of finance markets, so including financial forecasting topics such as Kalman Filters or Multi-factor Models is essential for successful analysis.
By creating simulations based on specific criteria and inputs, our expert Backtesting Developers can create accurate models to assess profitability and accurate predictions of future price movements.
Here’s some projects that our expert Backtesting Developer made real:
As you can see, Backtesting Developers often have highly technical abilities in order to accurately assess algorithmic trading scenarios. Their expertise in scripting languages allow them to quickly set up simulations that can provide valuable insights into the profitability of a specific trading system. At Freelancer.com, you can employ exceptional Backtesting Developers to help take your quantitative trading strategies to the next level! So don't hesitate and post your own project now! Hire an expert Backtesting Developer on Freelancer.com today for assistance with refining your algorithms or creating new ones from scratch!
From 4,916 reviews, clients rate our Backtesting Developers 4.92 out of 5 stars.I'm looking for an expert to identify, backtest, and forward test profitable trading strategies in the interest rate futures goal is to pass and beat prop firms and result in payouts. Key Tasks: - Develop strategies in trend following, mean reversion, and arbitrage. - Backtest and forward test the strategies. - Provide comprehensive performance reports. Ideal Skills and Experience: - Strong background in futures trading, especially interest rate futures. - Proven track record in developing and testing trading strategies. - Proficient in trading platforms and backtesting software. - Ability to analyze and interpret market data effectively.
I need my intraday iron condor converted into a fully automated Tradetron strategy that I can activate straight away. The rules are already defined and I do not intend to add extra risk filters beyond what is listed below, so the job is mostly about translating logic into Tradetron blocks, testing, and handing over a working template I can clone in my own account. Core logic to be coded • Entry time 09:45 AM. • Select 0- or 1-DTE weekly index options (NIFTY on Monday–Tuesday, SENSEX on Wednesday–Thursday; if a holiday shifts expiries, always give 0-DTE priority). • Sell the nearest 21-delta Call, buy a hedge worth 10 % of its premium first, then place the short Call. • Mirror the above on the Put side: sell the Put closest in price to the short Call...
$10 project max. This can be finished in a few hours max. I need someone to work fast. Title: Speed Optimization and Completion of Forex Non-Print Quant Research Program I have an existing Windows-based, three-part quantitative research program designed to discover and validate trading strategies for OANDA forex markets. The program is functional, but its historical tick-data backfill is too slow and produces excessive timeout and service-error messages. I need an experienced Python, market-data, and quantitative-research developer to optimize and complete the existing program. I am not requesting a rebuild from scratch. The program uses historical BID and ASK tick data to derive Non-Print events and Line Break market structures. I want it to collect as much legitimate historical data ...
Create a TradingView Pine Script automated Supply & Demand trading bot using existing indicator on Trading View. Entry: * Detect newly created Supply/Demand zones from the indicator. * Place a Limit Order at the zone. * Demand Zone = BUY; Supply Zone = SELL. * Only one entry per zone. Trade Management: * Option for 1 or 2 trades per setup. * Adjustable TP/SL for each trade (e.g. Trade 1 = 1:3 RR, Trade 2 = 1:10 RR). * SL below Demand Zone / above Supply Zone. * Adjustable SL buffer. Risk: * Fixed lot size OR percentage risk. * Adjustable risk for each trade. Sessions: * Selectable ON/OFF: Asia, London, New York. Trend Filter: * Optional 200 EMA filter. * Above 200 EMA = BUY only. * Below 200 EMA = SELL only. Backtesting: Include full TradingView backtesting with net profit,...
Options Trading Bot — Real-Data Validation & Fix. Why this bot is currently shut down — stated plainly This is a real-money automated options trading bot (Schwab broker). It is currently fully halted by two independent safety locks (a hard kill switch and a max-drawdown gate), both enforced in code and verified directly against live server logs. It stays off until someone proves — with real data, not guesses — that it can make money without blowing up the account. The real trading record, from the account’s own ledger: • 25 real trades: 6 wins, 19 losses • Realized P&L: -$1,527.85 on a $1,885.57 starting account (81% drawdown) • The losing streak that did the real damage: six straight losing trades in August with zero wins in between, c...
Project Requirements: Multi-Sniper Spot Bot Automated Spot Trading Bot on Binance — Full Project Scope Overview: Looking for an experienced Python developer to build an automated Spot-only trading bot (no leverage) on Binance, using multi-indicator technical analysis, an independent risk-management layer, and full control via Telegram. Verifiable prior experience building real trading bots that handled live WebSockets and real funds is required — not demo scripts. Core Technical Requirements: - Python 3.11+, modular OOP architecture — each functional module in its own file/folder - Docstrings for every function and file - Unit tests covering at least 80% of profit/cooling calculation logic - Instant market-price entry via live Binance WebSockets - Limit IOC order execut...
I need my NZPack-powered NinjaTrader environment configured from scratch so I can reliably backtest and refine a metals strategy (gold and silver). Your task begins with a clean install: connect to my machine through the temporary remote credentials I will supply, load NZPack, adjust any dependencies, and verify that every component compiles without errors. Because I don’t yet have the historical data, please locate a high-quality tick or one-minute feed that covers at least the past five years of COMEX gold and silver futures, import it, and build the necessary databases so the platform can run fast, repeated simulations. Once the data is in place, run representative backtests that highlight the performance of my current template. I am interested in performance optimisation rather...
I’m ready to turn an existing idea into a fully-functional TradingView bot written entirely in Pine Script and linked to my IC Markets account. The bot must operate hands-free once deployed, yet still give me the control and transparency I need to monitor and refine performance. Core requirements • Automated trading – the script must fire real orders on IC Markets without manual confirmation, handling position sizing, stop-loss and take-profit automatically. • Backtesting strategies – I need clean, reliable backtest output inside TradingView so I can validate and fine-tune before going live. • Alert notifications – every executed trade, entry signal, and error should generate an alert to my phone/email through TradingView’s native alert s...
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