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10 strategies and tactics for Technical Analysis

What is Technical Analysis strategy?

Every great achievement starts with a well-thought-out plan. It can be the launch of a new product, expanding into new markets, or just trying to increase efficiency. You'll need a delicate combination of strategies and tactics to ensure that the journey is smooth and effective.

Identifying the optimal Technical Analysis strategy can be challenging, especially when everyday tasks consume your time. To help you, we've assembled a list of examples to ignite your creativity.

You can copy these examples into your preferred app, or alternatively, use Tability to stay accountable.

How to write your own Technical Analysis strategy with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI generator below or our more complete goal-setting system to generate your own strategies.

Technical Analysis strategy examples

You'll find below a list of Technical Analysis tactics. We also included action items for each template to make it more practical and useful.

Strategies and tactics for developing a 15-Second Pocket Option Trading Strategy

  • ⛳️ Strategy 1: Utilise existing technical analysis techniques

    • Research and select established technical analysis indicators suitable for short-term trading such as RSI, MACD, and Moving Averages
    • Identify the best period settings for these indicators that align with 15-second time frames
    • Develop rules for entry and exit points using these indicators
    • Test the chosen indicators and rules on historical data for 15-second windows
    • Evaluate the performance using backtesting and refine settings based on results
    • Integrate successful indicator settings into an algorithm compatible with AI systems
    • Continuously monitor and update the chosen indicators as needed for market changes
    • Create a contingency plan for unusual market movements or volatility spikes
    • Run a trial phase with simulated trading to check for any inconsistencies
    • Gather feedback and make adjustments before full implementation in the AI signal bot

  • ⛳️ Strategy 2: Create a machine learning model

    • Collect historical minute-by-minute price data for training a machine learning model
    • Preprocess the data to remove noise and normalise it for better learning
    • Select a machine learning algorithm suitable for time series prediction, such as LSTM
    • Train the model using the preprocessed data, focusing on 15-second window predictions
    • Evaluate the model's accuracy by comparing predicted vs actual outcomes
    • Optimise the model by tweaking parameters to improve accuracy and speed
    • Integrate the model into a trading bot framework for real-time predictions
    • Conduct pilot testing by executing simulated trades based on the model's signals
    • Assess the model's performance and make necessary adjustments for improvement
    • Deploy the machine learning model in a live trading environment once reliable

  • ⛳️ Strategy 3: Implement a custom algorithm

    • Define clear objectives and parameters for the trading algorithm, focusing on 15-second trades
    • Draft logic for determining buy and sell signals based on identified objectives
    • Choose suitable programming language and tools to build the customised algorithm
    • Develop the algorithm to process real-time market data effectively within the required time frame
    • Incorporate filters and checkpoints to handle unexpected market conditions
    • Test the algorithm with historical data and evaluate its success rate over a predetermined period
    • Iterate on the algorithm, implementing feedback and addressing potential weak spots
    • Ensure the algorithm can seamlessly integrate with pocket option brokers and platforms
    • Create a user-interface for easier monitoring and manipulation of the algorithm
    • Regularly optimise and update the algorithm as market conditions evolve
technical-analysismachine-learningdata-scientistalgorithm-developerai-development-teamtrading-strategy-team
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Strategies and tactics for developing a Profitable Day Trading Strategy

  • ⛳️ Strategy 1: Adopt the EMA Pullback Method

    • Set up 9 EMA and 21 EMA on your trading charts
    • Choose assets that are highly liquid such as major forex pairs or SP500 futures
    • Monitor the 5-minute chart actively during the highest liquidity hours for your chosen market
    • Identify the trend by ensuring the price is above both 9 EMA and 21 EMA for a bullish trend
    • Wait for the price to pull back to the 9 or 21 EMA in the direction of the trend
    • Confirm an entry using volume spikes on breakout candles and bullish candlestick patterns
    • Place a buy stop order above the high of the pullback candle
    • Set a stop loss below the recent swing low or use 1.5x ATR for volatility adjustment
    • Establish initial profit targets at 1:1 risk-reward ratio and adjust as needed
    • Ensure total exposure to risk per trade does not exceed 1% of your account balance

  • ⛳️ Strategy 2: Utilise Effective Risk Management

    • Define your maximum risk tolerance per trade and systematically adhere to it
    • Set a daily maximum loss cap at 2% of your account balance to cease trading if reached
    • Implement position sizing methods to ensure capital preservation
    • Avoid trades during major scheduled news events to manage unexpected volatility
    • Utilise ATR to determine the appropriate market conditions and avoid low volatility trades
    • Confirm that higher timeframe trends align with 5-minute chart setups for consistency
    • Exclude trades in markets deemed to provide choppy or unclear signals
    • Define clear conditions under which you will avoid or limit leveraged trades
    • Backtest risk parameters on historical data and adjust accordingly
    • Evaluate overall performance monthly and recalibrate risk strategies if necessary

  • ⛳️ Strategy 3: Maintain Trading Discipline and Setups

    • Create a predefined trading plan specifying entry, exit, and stop criteria
    • Document every trade in detail for subsequent analysis and learning
    • Restrain from making impulsive decisions and overtrading throughout sessions
    • Monitor psychological aspects such as greed or fear which affect decision making
    • Focus only on high-probability setup opportunities termed as A+ setups
    • Commit to frequent review of strategy effectiveness and adaptability
    • Ingrain a structured routine to aid consistent and disciplined trading practices
    • Use mechanical aids like hotkeys to ensure swift execution during peak moments
    • Engage in strategy optimisation based on observed performance and market shifts
    • Develop coping strategies to manage emotional stress and minimise revenge trading
scalpingtechnical-analysisday-traderrisk-managertrading-teamrisk-management-team
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Strategies and tactics for utilising Football Metaphors to Manage an Investment Portfolio

  • ⛳️ Strategy 1: Balance offensive and defensive plays

    • Identify high-growth stocks like selecting star forwards
    • Include dividend-paying stocks as defenders for stability
    • Diversify investments across sectors like a varied team line-up
    • Mix tech and healthcare stocks to spread risk
    • Research management teams to find strong leaders as team captains
    • Implement a rotational investment strategy similar to player rotations
    • Regularly review portfolio performance with team huddle simulations
    • Apply the Executive-Investment Coach (EIC) top-down approach
    • Conduct macroeconomic analysis like assessing the playing field
    • Stay informed on global economic trends like watching global soccer tournaments

  • ⛳️ Strategy 2: Choose strong economies and companies

    • Select portfolios spread across promising economies like US and India
    • Identify stocks based on their economic growth potential
    • Focus on companies with growing capital per worker
    • Measure steady capital-output ratios over time
    • Evaluate ROE figures, prioritising those above 30%
    • Choose companies based on PE and PB ratios fitting desired criteria
    • Consider monetary policy impacts on sectors like banking and finance
    • Incorporate valuation factors across multiple categories
    • Assess investor sentiment for market timing
    • Monitor geopolitics to exploit industry-specific opportunities

  • ⛳️ Strategy 3: Engage in team-based decision-making

    • Conduct daily team meetings to discuss and deliberate over options
    • Utilise a structured ideation phase for stock selection input
    • Allocate roles within the team for sector-based research
    • Select top competitors of the chosen stocks for analysis
    • Analyse financial statements and ratios for decision making
    • Use technical chart trends for short-term investment forecasts
    • Utilise a custom screener for long-term investment options
    • Discuss and resolve conflicting opinions during team meetings
    • Simulate portfolio testing through various economic scenarios
    • Define a clear process from industry selection to stock segregation
investment-diversificationfootball-metaphorsinvestorfinancial-analystinvestment-management-teameconomic-analysis-team
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Strategies and tactics for developing a Trading Strategy for TradingView Signals

  • ⛳️ Strategy 1: Utilise Technical Indicators

    • Identify currency pairs or cryptocurrencies with high liquidity
    • Select primary technical indicators such as RSI, MACD, and Moving Averages
    • Use RSI to identify overbought and oversold conditions
    • Incorporate MACD crossovers for trend confirmation
    • Apply moving average crossovers for additional entry and exit signals
    • Determine optimum buy and sell points using indicator values
    • Set stop-loss slightly below recent support for buys or above resistance for sells
    • Establish TP1 at recent swing highs or lows
    • Aim TP2 at 1.5x the distance of TP1 for risk reward ratio
    • Test the strategy on historical data and backtest for win rate validation

  • ⛳️ Strategy 2: Implement Price Action Analysis

    • Study candlestick patterns like Doji, Engulfing, and Hammer
    • Identify key support and resistance levels on the chart
    • Draw trendlines to establish overall market direction
    • Look for price breaks or bounces at trendlines for entry signals
    • Set buy signals on breakout above resistance levels
    • Indicate sell signals on failure at support or breakdowns
    • Position stop-loss just beyond the identified pattern
    • Set TP1 at the next major pivot point
    • Place TP2 at twice the distance from entry to TP1 for optimal risk reward
    • Backtest strategy using TradingView’s replay mode for signal quality

  • ⛳️ Strategy 3: Blend Fundamental and Sentiment Analysis

    • Stay updated on major economic events affecting desired currency pair or crypto asset
    • Use an economic calendar to track upcoming announcements
    • Analyse news sentiment around the particular asset
    • Incorporate sentiment indicators like the Fear and Greed Index for cryptocurrencies
    • Combine sentiment analysis with technical indicators to strengthen signal accuracy
    • Use positive sentiment along with technical breakouts for buys
    • Utilise negative sentiment with technical breakdowns for sells
    • Define stop-loss beneath technical and sentiment support levels
    • Place TP1 using anticipated short-term sentiment shift support
    • Calculate TP2 based on macroeconomic expectations and trends
technical-analysissentiment-analysistradermarket-analysttrading-strategy-developmentrisk-management
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Strategies and tactics for setting up an EMA Crossover Alert on TradingView

  • ⛳️ Strategy 1: Configure EMAs on TradingView

    • Log in to your TradingView account
    • Open the chart of the desired financial instrument
    • Navigate to the 'Indicators & Strategies' tab
    • Search and select the 'Moving Average Exponential' indicator
    • Add three EMA indicators to the chart
    • Set the period of the first EMA to 9
    • Set the period of the second EMA to 50
    • Set the period of the third EMA to 100
    • Adjust the colour and style for each EMA for clear visual distinction
    • Save the chart layout for quick access in the future

  • ⛳️ Strategy 2: Create a Crossover Alert on TradingView

    • Ensure all three EMAs are visible on the chart
    • Open the 'Alerts' tab on TradingView
    • Select 'Add Alert' and choose EMA 9 as the first condition
    • Choose the 'Crossing' option
    • Set EMA 50 as the second condition for crossover
    • Add another alert for EMA 9 crossing EMA 100
    • Define alert notifications (pop-up, email, SMS) per your preference
    • Name the alerts clearly for easy identification
    • Set the alert expiration date based on your trading timeline
    • Create the alert and activate it

  • ⛳️ Strategy 3: Test and Monitor the Alerts

    • Simulate market conditions with historical data to test alerts
    • Verify the correct functionality of alerts through visual and audible signals
    • Adjust alert settings if signals are not appearing as expected
    • Monitor the chart regularly for the first few days to ensure reliability
    • Take notes on market conditions when alerts trigger
    • Modify action plan based on market behavior observed post-alert
    • Review historical performance of signals to evaluate effectiveness
    • Check alert logs for missed notifications due to technical issues
    • Communicate with TradingView support for unresolved alert issues
    • Share feedback or improvement suggestions with the TradingView community
tradingtechnical-analysistraderdata-analystmarket-analysistrading-strategy-development
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Strategies and tactics for generating strategies for the MT5 platform

  • ⛳️ Strategy 1: Analyse market trends

    • Study historical market data to identify recurring patterns
    • Utilise technical indicators to assess current market conditions
    • Review economic news and reports to predict market movements
    • Monitor trading volumes to gauge market sentiment
    • Utilise trend lines and chart patterns for analysis
    • Backtest historical data to verify the viability of trends
    • Set alerts for identified trend breaks or continuations
    • Compare multiple timeframes for a comprehensive view
    • Join trading forums to gather insights from experienced traders
    • Regularly update your market analysis with fresh data

  • ⛳️ Strategy 2: Optimise risk management

    • Determine your risk tolerance level based on your capital
    • Set stop-loss and take-profit orders for every trade
    • Diversify your portfolio to spread risks
    • Limit your position size according to your risk tolerance
    • Monitor open positions and adjust accordingly
    • Use trailing stops to lock in profits
    • Avoid overtrading by following a strict trade plan
    • Keep track of key economic events that may impact trades
    • Regularly review and update your risk management plan
    • Utilise risk/reward ratio for every potential trade

  • ⛳️ Strategy 3: Develop and test automated systems

    • Learn to create Expert Advisors (EAs) on the MT5 platform
    • Define clear rules and conditions for your trading system
    • Backtest your automated strategy using historical data
    • Optimise parameters to enhance the strategy's performance
    • Set up a demo account to run your EA in live conditions
    • Monitor the EA's performance and make necessary adjustments
    • Implement fail-safes to handle erratic market conditions
    • Regularly update the EA with new market data and trends
    • Incorporate machine learning for advanced automation
    • Switch to live trading only after successful testing and validation
market-analysisrisk-managementtraderrisk-managertechnical-analysis-teamtrading-system-development-team
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Strategies and tactics for developing a high probability scalping strategy

  • ⛳️ Strategy 1: Utilise technical analysis effectively

    • Identify key technical indicators such as moving averages and stochastic oscillators
    • Conduct backtesting on historical data to validate indicator effectiveness
    • Establish clear entry and exit points based on indicator signals
    • Determine the optimal time frame for scalping based on market volatility
    • Incorporate support and resistance levels in decision-making
    • Use candlestick patterns to anticipate price movements
    • Monitor trading volume as a measure of market strength
    • Set tight stop-loss orders to minimise potential losses
    • Continuously adapt technical indicators to changing market conditions
    • Evaluate technical analysis outcomes regularly to improve strategy

  • ⛳️ Strategy 2: Manage risk efficiently

    • Define maximum acceptable loss per trade to protect capital
    • Use position sizing techniques to control risk exposure
    • Implement a risk-reward ratio of at least 1:2 for trades
    • Limit trading to a well-researched selection of markets
    • Use trailing stops to lock in profits while reducing exposure
    • Adopt a disciplined approach to exiting losing trades quickly
    • Diversify trades across different asset classes to spread risk
    • Keep a trading journal to analyse and improve risk management
    • Avoid over-leveraging positions to prevent significant capital loss
    • Regularly review and adjust risk management strategies

  • ⛳️ Strategy 3: Improve decision-making with analytical tools

    • Utilise algorithmic trading software to identify scalping opportunities
    • Incorporate machine learning to predict short-term price movements
    • Implement real-time data feeds to ensure up-to-date analysis
    • Analyse market sentiment using sentiment analysis tools
    • Backtest strategies using simulated trading environments
    • Use heat maps to identify high volatility and liquidity zones
    • Develop custom indicators incorporating multiple data sources
    • Apply pattern recognition software to identify repeating trade patterns
    • Analyse economic and market news impact through aggregators
    • Maintain a database of trade performance for in-depth analysis
scalpingtechnical-analysistraderrisk-managerquantitative-analysis-teamrisk-management-team
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Strategies and tactics for growing Sales and Market Penetration for IMZ Corporate's IoT Solutions

  • ⛳️ Strategy 1: Enter the state excise departments market

    • Conduct market intelligence in Maharashtra, Jharkhand, Karnataka, and Kerala
    • Develop hyper-localized solution templates based on collected data
    • Map region-specific pain points to showcase immediate value
    • Create a narrative highlighting technological disruption in liquor supply chain management
    • Develop predictive analytics demonstrating cost savings beyond traditional tracking
    • Design cost-effective pilot programs with minimal client investment
    • Implement a 'Zero-Risk Pilot Program' with performance-linked pricing
    • Create transparent, data-driven ROI calculators
    • Offer flexible implementation models allowing modular scaling
    • Provide complimentary initial security and efficiency audits

  • ⛳️ Strategy 2: Target food corporations for market penetration

    • Identify Jharkhand Food Corporation as strategic entry point
    • Evaluate target based on openness to technological innovation and existing challenges
    • Develop a comprehensive digital security ecosystem extending beyond traditional tracking
    • Design modular solutions adaptable to various organisational complexities
    • Integrate machine learning algorithms for predictive loss prevention
    • Create user-friendly dashboards for real-time insights
    • Establish trust through transparent technological demonstrations
    • Offer phased implementation with clear milestone-based achievements
    • Provide continuous support and commit to technology evolution
    • Establish collaborative feedback mechanisms for improvement

  • ⛳️ Strategy 3: Penetrate the railway sector with innovative IoT solutions

    • Identify critical security and operational pain points in railway logistics
    • Develop comprehensive security solutions exceeding traditional tracking
    • Create a technology sandbox for continuous solution refinement
    • Integrate multiple tracking technologies including GPS, RFID, and AI-powered analytics
    • Develop predictive maintenance and security algorithms
    • Create a unified monitoring platform with intuitive interfaces
    • Ensure AIS 140 compliance with additional innovative features
    • Leverage academic and research partnerships to bolster credibility
    • Obtain necessary certifications and security clearances
    • Demonstrate technological superiority through live pilot programs
market-penetrationiot-solutionsmarket-researchertechnology-analystsales-teamtechnology-innovation-team
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Strategies and tactics for developing Nifty 50 Trading Strategies

  • ⛳️ Strategy 1: Utilize technical analysis

    • Learn the basics of technical analysis
    • Study historical price charts of Nifty 50
    • Identify key support and resistance levels
    • Use moving averages to determine market trends
    • Implement relative strength index (RSI) for momentum analysis
    • Apply Bollinger Bands to assess market volatility
    • Test your analysis with backtesting on historical data
    • Stay updated with technical analysis through financial news platforms
    • Join forums or groups to discuss technical strategies
    • Evaluate the effectiveness of your analysis periodically

  • ⛳️ Strategy 2: Implement risk management practices

    • Determine your risk tolerance before trading
    • Set a fixed percentage of capital for each trade
    • Use stop-loss orders to manage potential losses
    • Define profit-taking points along with entry points
    • Ensure diversification across different asset classes
    • Keep track of past trades to understand risk patterns
    • Adjust position sizes based on market volatility
    • Avoid over-leveraging to prevent substantial losses
    • Use trailing stops to protect profits
    • Review and update your risk management strategy periodically

  • ⛳️ Strategy 3: Incorporate fundamental analysis

    • Research the economic indicators affecting Nifty 50
    • Assess company earnings and financial reports
    • Monitor news related to the top 50 companies in the index
    • Understand present economic conditions and forecasts
    • Evaluate the performance of different sectors within the Nifty 50
    • Keep an eye on government policy changes affecting the market
    • Use analyst reports to support your trading decisions
    • Understand global market trends impacting the index
    • Periodically reassess the influence of fundamental factors
    • Blend fundamental insights with technical signals for better trades
technical-analysisrisk-managementtraderrisk-manageranalysis-teamrisk-management-team
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Strategies and tactics for becoming a Profitable Trader

  • ⛳️ Strategy 1: Master Technical Analysis

    • Study chart patterns that are relevant to scalping
    • Learn to interpret key technical indicators such as moving averages and Bollinger Bands
    • Practice identifying support and resistance levels on different timeframes
    • Familiarise yourself with candlestick patterns that signal potential entry or exit points
    • Utilise backtesting software to refine technical analysis skills on historical data
    • Attend webinars and courses focused on technical analysis for scalping
    • Join online forums to discuss and learn from other experienced scalpers
    • Create a checklist of technical factors to consider before entering a trade
    • Review daily and weekly market trends in relation to your analysis
    • Evaluate and adjust your strategies periodically based on your analysis performance

  • ⛳️ Strategy 2: Implement a Risk Management Plan

    • Set a maximum risk percentage per trade and adhere to it strictly
    • Utilise stop-loss orders to limit potential losses on each trade
    • Determine and maintain an acceptable risk-reward ratio for all trades
    • Use position sizing techniques to manage capital effectively
    • Review and adjust your risk management plan as market conditions change
    • Establish a daily trading loss limit to prevent emotional decision-making
    • Keep a trading journal to analyse trades and improve risk management
    • Backtest your risk management strategies on various market conditions
    • Attend workshops focused on risk management for scalpers
    • Regularly assess your psychological readiness to manage trading risks

  • ⛳️ Strategy 3: Enhance Trading Discipline

    • Establish a fixed daily trading routine and stick to it
    • Set specific trading goals and review them regularly
    • Use mental preparation techniques such as visualisation and deep breathing before trading
    • Limit distractions by creating a focused trading environment
    • Use a trading journal to record emotions and thoughts during trades
    • Practice consistency by adhering to your trading plan without deviation
    • Identify triggers that lead to emotional trading and develop coping strategies
    • Evaluate daily trades to ensure adherence to your trading plan
    • Take regular breaks to maintain mental clarity during trading sessions
    • Join a trading accountability group for support and motivation
technical-analysisrisk-managementtraderrisk-managertrading-teamanalysis-team
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How to track your Technical Analysis strategies and tactics

Having a plan is one thing, sticking to it is another.

Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.

A tool like Tability can also help you by combining AI and goal-setting to keep you on track.

More strategies recently published

We have more templates to help you draft your team goals and OKRs.

Planning resources

OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:

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