Introduction
Are you fascinated by the world of Algo Trading but the complex programming languages make you think it’s above your pay grade?
What if you had access to such a system without writing a single line of code? A trading strategy that works for you 24/7, executing trades with precision, discipline, and zero emotional bias. In this blog, we’ll walk you through the key steps of designing a fully automated trading with sharpely. Ready to show off in front of your coder friends?
The Power of Rule-Based Investing
Before we explore automated strategies in detail, let’s understand, ‘What is Rule-Based Investing?’
You see, traditional investing often falls prey to emotional decision-making. Traders panic-sell in downturns and chase overhyped stocks during bull runs. It’s easy to get caught up in the moment, leading to overtrading or abandoning well-researched positions at the wrong time. This often results in the frustrating cycle of buying high and selling low.
Rules-based investing, on the other hand, is a systematic approach where all investment decisions – when to buy, when to sell, and how to manage risk – are determined by a set of pre-defined rules.
By establishing these rules in advance, you create a framework that guides your trading activity, eliminating impulsive actions driven by emotions. This disciplined approach can significantly improve your long-term investment outcomes.
Platforms like sharpely allow you to:
- Build a proven framework without emotional interference.
- Backtest strategies to see how they perform historically.
- Execute paper trades consistently with high efficiency and build a strategy without risking a penny.
Let’s now explore what’s special about such platforms.
Using No-Code Platforms for Trading
You don’t need to know Python or write scripts to automate your strategy. Several no-code trading platforms allow you to set up and execute strategies effortlessly.
Some popular ones include:
- sharpely– Lets you build a fully automated strategy in 7 simple steps
- QuantConnect – Drag-and-drop interface for building algorithmic strategies.
- Tradetron – An Algo Strategy marketplace for people to create algo strategies with their strategy builder
These platforms allow you to define your trading logic using dropdowns, checkboxes, and formula builders—without touching a single line of code.
Now, let’s explore how you can build an automated trading system on sharpely in simple steps.
Part 1: Define Your Trading Strategy
A trading strategy is a set of predefined rules that determine:
- Stock Selection – Which stocks to buy or short?
- Entry & Exit Rules – When to enter and exit trades.
- Position Sizing – How much capital should be allocated per trade?
- Risk Management – How to protect against major losses.
Without a solid trading strategy on paper, having tools like sharpely is like having a Ferrari but no fuel in the tank! Once you have these things ready, you can begin creating your entry conditions. Let’s explore an example
Example: High-Quality Growth and Momentum Stocks
To create this rules-based strategy, we’ll use these conditions in our screener. It is not purely value-based. Instead, we focus on a mix of quality earnings, operational efficiency, and momentum.s. Here’s a simple approach:
- Stock Selection: Focus on companies where Operating Cash Flow (TTM) / Profit After Tax (TTM) > 1.5, ensuring strong earnings quality.
- Momentum Filter: Pick stocks with a Price Momentum Score > 70 to favor those already in a strong uptrend.
- Profitability Filter: Select stocks with an EBITDA Margin (TTM) > 20% for solid profitability and ROE (TTM) > 15% for efficient capital allocation.
(Disclaimer: This is for educational purposes only.)
Once this is done, we then need to work on position sizing. Here’s how we’ve kept things for this example:
Once the weights are assigned you need to set the rebalancing frequency. This is a crucial step in automated strategies as this defines how often you want to rebalance your portfolio.
Part 2: Setting Exit Parameters
Now in automated strategies, there’s a very important step that can make or break your portfolio, the exit conditions. On sharpely you can set up an exit signal [Eg; Sell when the stock’s price closes below a key EMA (like 20-day or 50-day EMA)] as well as have a risk management strategy in place. We have 3 different types of risk management conditions– trailing stop loss-based, fixed stop and drawdown protection-based, and fixed stop and profit booking-based.
Part 3: Backtest Your Strategy
Before deploying your strategy in the real market, you need to test its historical performance. Backtesting involves applying your rules to past market data to evaluate:
- Profitability (CAGR%) – The compound annual growth rate of your strategy.
- Maximum Drawdown – The worst peak-to-trough decline in portfolio value.
- Win Rate & Risk-Reward Ratio – Percentage of winning trades and average gain vs. loss.
A solid strategy should outperform market benchmarks (e.g., Nifty 50 or Nifty 500) while keeping risk under control. Here’s a quick look into how our above strategy performs:
Part 4: Automate Execution & Monitoring
Once you’re satisfied with your backtesting results, you can set your strategy to run live. Running it on a paper trade for a few months is always better than directly jumping into real trades. With sharpely you can:
- Automatically place buy/sell orders based on predefined rules.
- Monitor real-time market conditions and adjust positions dynamically.
- Get alerts and notifications when trades are executed.
This offers you better control over your strategy.
Part 5: Optimize & Scale Your Strategy
Even a profitable strategy requires continuous improvement. Constantly:
- Identify weak points (e.g., high drawdowns, excessive transaction costs).
- Tweak parameters (e.g., adjusting stop-loss levels, and entry conditions).
- Diversify strategies (e.g., combining momentum with value investing).
We’ve covered these steps in detail in our recent masterclass. P.S. It also covers a strategy that has delivered 30%+ CAGR returns on the backtest!
Watch this exciting FREE masterclass now!
A Proven, Fully-Automated Strategy for Smarter, Global Equity Investing
Let’s now look at a real-world example of what’s possible with sharpely’s strategy builder.
We’ll take reference of a strategy that’s actively on paper trade on sharpely right now. Here’s a sneak peek into its performance.
This strategy is built for aggressive, long-term investors (5+ years horizon), offering a balanced exposure across 5 proven factors in India — Market, Momentum, Low Volatility, Value, and Quality — through ETFs.
20% of the portfolio is allocated to US Equity ETFs (S&P 500 Top 50 and NASDAQ 100), adding global diversification.
By combining factor investing with international exposure, the strategy aims to deliver better risk-adjusted returns than the traditional Nifty 50 — without active management, emotions, or guesswork.
Here’s a quick snapshot of the backtested performance of this strategy
Want to explore more? Get your hands on this ready-to-invest strategy on sharpely here.
(Disclaimer: This is for informational purposes only. Always do your due diligence before investing.)
Conclusion
Building a fully automated trading strategy has never been easier. Thanks to no-code platforms like sharpely, anyone can implement a rule-based investing approach without programming expertise. By following these steps—defining a strategy, using automation tools, backtesting, and optimizing—you can create a trading system that runs on autopilot, minimizing emotional biases and maximizing long-term returns.
Are you ready to take the next step in automated trading?