Mastering Trading Strategies with Thinkorswim: Unleashing the Power of Buy and Sell Signal Scripts

In the fast-paced world of trading, having access to advanced tools and platforms can make all the difference. Thinkorswim, a leading trading platform by TD Ameritrade (now owned by Charles Schwab), provides traders with a comprehensive suite of features to analyze, execute, and manage trades effectively. Among its many capabilities, Thinkorswim offers the ability to create and leverage custom scripts, enabling traders to generate powerful buy and sell signals. In this blog post, we will explore how Thinkorswim’s scripting capabilities can enhance your trading strategies and help you make informed decisions.

Understanding thinkScript

At the heart of Thinkorswim’s scripting capabilities lies thinkScript, a proprietary scripting language designed specifically for the platform. thinkScript allows traders to create custom studies, indicators, and strategies to analyze market data and generate personalized trading signals. Just because it’s a proprietary scripting language, however, doesn’t mean you must know how to write code to utilize these powerful tools. More on that later.

Creating Custom Buy and Sell Signals

With thinkScript, traders can develop custom scripts to identify specific market conditions and generate buy and sell signals accordingly. This opens up a world of possibilities, enabling you to tailor your trading strategy to your unique preferences and risk tolerance.

To create a custom signal, you can define the conditions that must be met for a buy or sell signal to trigger. These conditions can include technical indicators, moving averages, trend lines, or any other parameters relevant to your trading strategy. Once the conditions are met, thinkorswim will automatically generate alerts or even execute trades on your behalf.

Backtesting and Optimization

One of the most valuable features of thinkorswim is its ability to backtest and optimize custom scripts. Before deploying a trading strategy in real-time, it is crucial to evaluate its performance using historical data. With thinkScript, you can test your custom buy and sell signals against past market conditions to determine their effectiveness.

By backtesting, you can assess the profitability, risk, and overall performance of your strategy. This process helps you identify potential weaknesses or areas for improvement, allowing you to refine and optimize your trading signals over time.

Leveraging Thinkorswim’s Community

As I stated before, just because it’s a proprietary scripting language doesn’t mean you must know how to write code. In fact, the thinkorswim platform boasts a vibrant community of traders who actively share their scripts and strategies. Leveraging this community can provide you with a wealth of knowledge and ideas for building effective trading signals. By exploring shared scripts and indicators, you can gain insights into different trading approaches and adapt them to suit your trading style.

In addition to the great community of traders, there are many companies that create and sell custom indicators, like us :), that provide installation and usage support, as well as regular updates to the code when necessary. Furthermore, the thinkScript Lounge, an online forum dedicated to thinkScript users, is an excellent resource for troubleshooting, seeking advice, and collaborating with fellow traders. Engaging with the community not only expands your understanding of thinkScript but also opens doors to valuable connections and learning opportunities.


Thinkorswim’s powerful scripting capabilities, combined with its comprehensive suite of tools, make it a go-to platform for traders looking to develop and implement custom buy and sell signals. By harnessing the potential of thinkScript, you can create personalized trading strategies that align with your goals and risk tolerance. Remember to backtest and optimize your signals to ensure their effectiveness, and leverage the Thinkorswim community for inspiration and collaboration. With Thinkorswim, you can take your trading to new heights by unleashing the power of custom scripts and unlocking profitable opportunities in the market.

Just remember not to share our code 🙂

Thinkorswim Paper Trading

Paper trading, also known as virtual trading or simulated trading, is a practice in which individuals or investors simulate the process of trading securities without using real money. Instead, they use a simulated trading platform that replicates the actual market conditions and allows users to execute trades, track performance, and monitor the impact of their investment decisions. Paper trading provides a risk-free environment for individuals to gain experience in trading without incurring any financial losses. It is commonly used by novice traders, investors, and students to learn about the dynamics of the financial markets, test investment strategies, and practice executing trades.

In paper trading, users are typically provided with a virtual account balance, which they can use to buy and sell stocks, bonds, options, or other financial instruments based on the current market prices. The platform records the transactions and keeps track of the user’s portfolio value, giving them a realistic sense of how their trades would have performed if they were using real money. By engaging in paper trading, individuals can develop and refine their trading skills, understand market trends, analyze investment strategies, and assess the potential risks and rewards of different trading approaches. It’s a valuable tool for building confidence, experimenting with new investment techniques, and evaluating the performance of specific trading strategies before committing real capital (read, your hard-earned money!) to the market.

Does Thinkorswim offer paper trading?

Yes, Thinkorswim, a popular trading platform developed by TD Ameritrade (now part of Charles Schwab), does offer paper trading capabilities. Thinkorswim’s paper trading feature allows users to practice trading without risking real money. It provides a simulated trading environment where users can execute trades, monitor their portfolios, and test various trading strategies. With Thinkorswim’s paper trading, users can access a wide range of financial instruments, including stocks, options, futures, and forex. The platform provides real-time market data1 and a suite of advanced trading tools and charting capabilities, allowing users to perform technical analysis and make informed trading decisions.

Thinkorswim’s paper trading feature is particularly popular among both beginner and experienced traders who want to practice and refine their strategies before trading with actual funds. It allows users to gain familiarity with the platform’s features, test different order types, assess risk management techniques, and track the performance of their virtual trades.

The difference between paper trading and on-demand

Thinkorswim offers two distinct features for simulated trading: paper trading and on-demand.

  1. Paper Trading: Thinkorswim’s paper trading feature allows users to practice trading in a simulated environment using virtual funds. It replicates real-time market conditions and provides users with a virtual account balance to execute trades, monitor portfolios, and test various trading strategies. Key features of paper trading include:
    • Simulated trading environment: Users can trade stocks, options, futures, and forex using virtual money, enabling them to practice without risking real capital.
    • Real-time market data: Paper trading reflects live market conditions, providing users with access to real-time prices, quotes, and market depth.
    • Tracking and performance analysis: Users can monitor their paper trading portfolio, track trades, and evaluate the performance of their virtual trades over time.
    • Practice and experimentation: Paper trading allows users to test different trading strategies, explore advanced order types, and gain familiarity with the platform’s features.
  1. On-Demand: On-demand is a unique feature within Thinkorswim that enables users to access historical market data and replay it as if it were happening in real-time. Unlike paper trading, on-demand is not limited to simulated trading with virtual funds. Instead, it allows users to review and analyze past market conditions to refine their strategies or learn from historical price movements. Key features of on-demand include:
    • Historical data replay: Users can select specific dates and times and replay the market activity as if it were occurring in real-time.
    • Advanced charting and analysis: Users can apply technical indicators, draw trend lines, and perform analysis on historical data to study patterns and price movements.
    • Strategy evaluation: Traders can test their strategies on historical data, assess their performance, and make adjustments based on past market conditions.
    • Learning and education: On-demand provides an opportunity for traders to review historical events, study market behavior, and enhance their understanding of the markets.

In short, Thinkorswim’s paper trading feature focuses on simulated trading with virtual funds in real-time market conditions, while the on-demand feature allows users to replay historical market data for analysis, strategy refinement, and educational purposes.


The best part about all of this is that ThinkScript indicators can be used with both Thinkorswim’s paper trading and on-demand features! ThinkScript is a scripting language developed by TD Ameritrade that allows users to create their own custom studies, strategies, and alerts within the Thinkorswim platform.

When using Thinkorswim’s paper trading feature, you can apply your custom ThinkScript indicators to analyze the simulated market data and test your trading strategies. The platform provides a built-in editor where you can write and modify ThinkScript code, and then apply those custom indicators to your paper trading charts.

By utilizing custom ThinkScript indicators while paper trading, you can enhance your analysis, identify potential trade setups, and evaluate the effectiveness of your trading strategies in a simulated environment. This can help you gain confidence in your custom indicators and refine them before using them in live trading with real money.

1. Real-time market data is available only with a funded account, and you must sign the exchange agreements first. Additionally, to remove the delay from your PaperMoney account you’ll need to contact TD Ameritrade support directly either through phone support or by chat.

Double bottom line investing

Double bottom line investing, also referred to as “impact investing” or “socially responsible investing,” refers to a type of investment strategy that seeks both financial returns and social or environmental impact. This approach aims to create a positive impact on society or the environment while also generating profits for investors.

Unlike traditional investment approaches that focus solely on financial returns, double bottom line investors consider social and environmental factors in their investment decisions. This could include investing in companies that are working to solve social or environmental issues, such as those focused on renewable energy or sustainable agriculture. By investing in companies with a strong commitment to social and environmental responsibility, double bottom line investors aim to create a positive impact on society while still generating financial returns.

There are various investment asset classes that can be considered for impact investing, depending on the specific social or environmental goals that an investor wants to achieve. Some examples of asset classes that can be used for impact investing include:

  • Public equities: Investing in publicly traded stocks of companies that have a strong commitment to sustainability and social responsibility.
  • Private equity: Investing in privately held companies that are focused on addressing social or environmental issues, such as renewable energy or clean water.
  • Bonds: Investing in fixed income securities issued by companies or governments that are focused on addressing social or environmental issues.
  • Real estate: Investing in real estate projects that are designed to have a positive impact on the environment or community, such as affordable housing or green buildings.
  • Microfinance: Investing in microfinance institutions or funds that provide financial services to low-income individuals or communities.
  • Impact funds: Investing in mutual funds or exchange-traded funds (ETFs) that are focused on impact investing, and typically invest in a variety of asset classes.

What’s the risk?

Impact investing can involve a higher degree of risk than traditional investing, and investors should carefully evaluate the potential financial and social returns before making any investment decisions. Many impact investments are made in emerging or untested markets, where the regulatory environment and business practices may not be well-established. This can increase the risk of investing in such markets as they may not have a proven track record of success. Some impact investments may not be liquid, meaning they cannot be easily bought or sold on the open market. This can limit an investor’s ability to sell their investment and can increase the risk of not being able to recover their initial investment.

Impact investments are typically made with the goal of achieving social or environmental impact, in addition to financial returns. However, achieving such impact may take time and resources, and there is no guarantee that the desired outcomes will be achieved. This can increase the risk of an investment not meeting its intended impact objectives. Impact investing is a relatively new field, and many impact investment strategies have limited track records of success. This can make it difficult for investors to assess the performance of potential impact investments, and can increase the risk of investing in an unproven strategy.

Aligning personal goals with investment goals

When considering impact investing, you should align your personal goals with your investment goals. Start by identifying personal values and priorities that align with social or environmental impact. For example, you may prioritize sustainability, social justice, or community development. Once personal values and priorities have been identified, set specific impact goals that align with those values. This could include goals such as reducing carbon emissions, supporting fair labor practices, or improving access to education.

Once impact goals have been set, determine investment goals that align with those impacts. For example, you may seek to invest in renewable energy companies, fair trade businesses, or education-focused organizations. Evaluate potential impact investments to determine if they align with your personal and impact goals, and to assess the potential risks and rewards of each investment opportunity. Once impact investments have been made, monitor their performance and impact on an ongoing basis. Adjust investments as needed to ensure they continue to align with your personal and impact goals.

By aligning personal and impact goals with investment goals, you can make meaningful contributions to social and environmental causes while still achieving your financial objectives!

Emotional trading can lead to losses. Tips to greater profitability

The stock market is unpredictable and it’s unpredictable for a variety of reasons. Changes in economic factors such as inflation, interest rates, and gross domestic product (GDP) growth can affect investor sentiment and lead to changes in stock prices. The performance of individual companies can have a significant impact on their stock prices. If a company reports strong earnings or announces a new product, its stock price may rise. Conversely, if a company reports weak earnings or faces legal or regulatory issues, its stock price may fall. Political events such as elections, changes in government policy, or geopolitical tensions can also affect the stock market. These events can create uncertainty among investors and lead to volatility in stock prices. Investor sentiment plays a large role in stock market unpredictability. This, in my opinion, is one of the single most influential factors. If investors are optimistic about the future of the economy and individual companies, stock prices may rise. However, if investors become fearful or uncertain, stock prices may fall.

One truism about making money in any market is that perception overpowers reality. Even during periods of great economic growth, holding on to the stock of fundamentally sound companies may not make you any richer. If investors perceive that better profits can be made elsewhere, that is where the money is going to go.

Stephen Bigalow, Profitable Candlestick Trading (Amazon affiliate link)

I’ve said it before, and I’ll say it again. You need to write a trading plan! In addition, you should attempt to learn the art (or maybe it’s a skill) of trading without emotion. Trading without emotion can help you improve your odds of success in an unpredictable market in several ways. Emotions such as fear, greed, and panic often lead traders to make impulsive decisions that are not based on sound analysis or strategy. By trading without emotion, you can avoid making impulsive decisions and stick to your trading plan. It’s no easy task, and requires discipline and self-control. Traders who are able to control their emotions are more likely to stick to their trading plan and avoid making emotional decisions that can lead to losses. You’ll also be more likely to make more rational decisions based on objective analysis of market data and other factors. This can help you identify trends and patterns in the market and make more informed trading decisions. Emotional trading can also lead to overtrading, which can be costly for traders. By trading without emotion, you can avoid the temptation to make too many trades and focus on making high-quality trades that are more likely to be profitable.

Learning to put emotions aside when trading stocks can be challenging, but here are some tips that can help:

  • Develop a Trading Plan: I know…I said it again, again! Having a well-defined trading plan can help you make more objective trading decisions. This plan should include your trading strategy, risk management guidelines, and criteria for entering and exiting trades. By sticking to your plan, you can avoid making emotional decisions that deviate from your strategy.
  • Use Technical Analysis: Technical analysis involves studying price charts and other market data to identify trends and patterns in the market. By using technical analysis, you can make more objective trading decisions based on market data rather than emotions.
  • Manage Risk: Managing risk is essential for trading without emotion. This involves setting stop-loss orders to limit your potential losses and determining your risk tolerance for each trade. By managing your risk, you can reduce the emotional impact of trading losses.
  • Practice Mindfulness: Mindfulness techniques, such as meditation or deep breathing exercises, can help you stay calm and focused during volatile market conditions. By practicing mindfulness, you can develop a greater awareness of your emotions and learn to manage them more effectively.
  • Learn from Your Mistakes: It’s important to learn from your mistakes and avoid repeating them in the future. Analyzing your past trades and identifying the emotional factors that influenced your decisions can help you improve your trading performance over time.

Trading without emotion takes time, effort, and practice. By developing a trading plan, using technical analysis, managing risk, practicing mindfulness, and learning from your mistakes, you can become a more disciplined and successful trader. As always, I wish you the best and happy trading!

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The two essentials of trading – Trading edge & trading plan

If you’re just beginning your trading journey, there are two essentials that you absolutely must have before you start. Nobody wants to lose money in the market, but the fact is that every trader will lose money. The difference in a successful trader and a failing trader is that the successful trader knows how to plan the trade and trade the plan. Simply put, they know that their trading edge and trading plan are the key factors in being a successful trader.

What is a trading plan?

A trading plan is a written document that outlines a trader’s strategy and approach to trading. The specific details of a trading plan will vary depending on the trader’s individual style and preferences, but here is an example of what a typical trading plan might include:

  • Trading goals: The trader should clearly define their trading goals, such as the desired rate of return, the amount of capital to be invested, and the time frame for achieving their goals.
  • Market analysis: The trader should conduct a thorough analysis of the market, including an assessment of overall market trends, sector performance, and individual stock performance. This analysis should be based on statistical data and technical analysis.
  • Entry and exit criteria: The trader should establish clear criteria for entering and exiting trades, based on their analysis of market trends and statistical advantage. This could include specific price levels, chart patterns, or other technical indicators.
  • Risk management: The trader should define their risk management strategy, including position sizing, stop-loss orders, and maximum loss limits. This is essential for managing risk and avoiding catastrophic losses.
  • Trading journal: The trader should keep a trading journal to record all trades, including entry and exit points, position sizes, and profits or losses. This can help the trader to analyze their performance and identify areas for improvement.
  • Review and evaluation: The trader should regularly review and evaluate their trading plan and performance, making adjustments as necessary based on changes in market conditions or their own experience.

What does statistical advantage mean, and how might it relate to trading stocks?

A statistical advantage is a probability-based advantage that arises from the analysis of historical data. In the context of trading stocks, a statistical advantage could mean identifying patterns and trends in the historical data of a particular stock or the overall market that could be used to make informed trading decisions. For example, a trader might use technical analysis to identify historical price patterns and support and resistance levels in a particular stock.

By analyzing this data, the trader might identify a statistical advantage in predicting the future price movements of that stock. Another way a statistical advantage might relate to trading stocks is through the use of quantitative models and algorithms. These models use statistical analysis to identify market trends and patterns that could be used to make profitable trades.

When people say trading edge they are referring to a statistical advantage. A trading edge is a statistical or strategic advantage that a trader possesses, which increases their chances of making profitable trades in the stock market. This edge can come from a variety of sources, including a deep understanding of market trends and patterns, access to privileged information, advanced technical analysis skills, or proprietary trading algorithms.

Having a trading edge means that a trader has a higher probability of being right in their market predictions than the average market participant. This can lead to consistently profitable trades and long-term success in the stock market. Having a trading edge does not guarantee profits, but rather it increases the probability of success. To maintain a trading edge, you must constantly adapt and refine their strategies based on changing market conditions and evolving market trends.

Remember the saying, you have to survive until you thrive. The key to doing so is keeping your losers small and your winners big, and the only way to achieve those two things is to plan your trade and trade your plan!

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Trading using confluence

Trading using confluence is an important aspect of any good trading system. Confluence refers to the coming together of multiple factors that confirm a trading signal or setup, which increases the probability of a successful trade. In intraday trading, where price movements can be quick and unpredictable, it’s important to have multiple confirmations before entering a trade. Confluence should be used for swing, and long-term trading as well.

Some examples of confluence factors in trading include:

  1. Technical indicators: When multiple technical indicators such as moving averages, RSI, and MACD all point to the same direction, it can provide confluence and increase the likelihood of a successful trade. Thinkorswim indicators are available on our site. If you’re using Trading View you might want to read about the top 3 best Trading View indicators.
  2. Support and resistance levels: When price approaches a key support or resistance level, and it coincides with a trend line or a moving average, it can provide confluence for a trade setup.
  3. Fundamental factors: When news or economic data aligns with technical signals, it can provide additional confirmation for a trade.

One of my favorite strategies is the classic pullback strategy, but attempting to take a trade on just one entry signal can be a mistake. In order to increase the likelihood that an entry will result in a winning trade, we must use confluence by looking at a higher timeframe. This is called multiple timeframe analysis.

Trading using confluence is closely related to multiple timeframe analysis. Multiple timeframe analysis involves analyzing price action and trends across multiple timeframes to gain a better understanding of the overall market context and to identify trading opportunities. When using confluence in trading, traders typically look for multiple factors that confirm a trading signal or setup. These factors can include technical indicators, support and resistance levels, and fundamental factors. When multiple factors align and confirm a trade setup, it provides a higher level of confidence in the trade.

Multiple timeframe analysis is important when looking for confluence in trading because it allows traders to identify trends and potential trading opportunities on different timeframes. For example, a trader might identify a bullish trend on the daily chart and then look for confluence on a lower timeframe, such as the 1-hour chart, to enter a long position. By analyzing multiple timeframes, traders can also gain a better understanding of the overall market context and potential price action that may affect their trades. This can help traders manage risk and avoid entering trades that may go against the overall market trend.

Trading using confluence and multiple timeframe analysis go hand in hand. By analyzing multiple timeframes and looking for confluence in trading signals and setups, traders can increase their confidence in their trades and make more informed trading decisions.

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How is a pullback defined and how do I trade it?

A pullback is a temporary reversal in the direction of an underlying trend. In other words, it is a retracement in price that goes against the current trend. For example, if an asset is in an uptrend and its price starts to fall for a short period before resuming its upward trajectory, that short-term decline is called a pullback. Similarly, if an asset is in a downtrend and its price rises temporarily before resuming its downward trend, that short-term increase is also called a pullback.

Pullbacks can be caused by a variety of factors, such as profit-taking by traders, changes in market sentiment, or unexpected news or events that impact the market. They can be identified by technical analysis tools such as trend lines, moving averages, or chart patterns.

The pullback strategy is a popular one among traders, including day traders. It is a common strategy that is used to take advantage of temporary price retracements within a larger trend. Many traders believe that pullbacks can provide favorable risk-to-reward opportunities because they can offer a chance to enter a trade at a better price than the trend’s current price.

How to trade a pullback

Traders need to identify the direction of the trend to determine whether a pullback is likely to occur. They may use technical analysis tools such as moving averages, trend lines, or chart patterns to identify the trend. Once the trend is identified, traders look for a pullback in price that retraces a portion of the trend’s move. They may use technical indicators such as the Relative Strength Index (RSI) or Moving Average Convergence Divergence (MACD) to confirm the pullback. Day traders look for areas where the price may find support and reverse its direction. They may use previous swing lows, Fibonacci retracement levels, or moving averages as potential support levels.

Traders may wait for confirmation that the pullback is ending and the trend is resuming before entering a trade. They may look for bullish candlestick patterns, a break of a trend line, or a bounce off a support level as confirmation. Once the confirmation is received, traders may enter a long position with a stop loss order just below the support level. They may also set a profit target based on the previous swing high or a Fibonacci extension level.

Traders need to manage their trade by monitoring the price action and adjusting their stop loss and profit target levels as the trade progresses. They may also use trailing stop orders to lock in profits as the price moves in their favor.

What are the Trade For Me rules for trading a pullback?

  1. There must be a sequential series of retracing bars that do not exceed the average range. Our favorite average for intraday trading is 20 periods.
  2. There must be at least two (2) or more lower highs for a long entry, or two (2) or more higher lows for a short entry.
  3. It must be the first or second pullback of a stage 2 uptrend or coming from a double bottom retest.
  4. Long entry: A buy stop limit order is placed with a stop one penny above the high of the lowest pullback bar. The limit is a few pennies higher than the stop. The stop loss is just below the pullback bar. Add padding of a few pennies to the stop loss. The target is your risk (entry price – stop loss) x 2 + entry price.
  5. Short entry: A sell stop limit order is placed with a stop one penny below the low of the highest pullback bar. The limit is a few pennies lower than the stop. The stop loss is just above the pullback bar. Add padding of a few pennies to the stop loss. The target is your risk (entry price – stop loss) x 2 + entry price.

The pullback indicator for thinkorswim (TOS) has an audible alert when the pattern sets up, so you won’t miss an entry. Like everything with trading, there is no perfect system, so it attempts to find only the best patterns so you don’t miss them. It’s important to note, however, that even though a pattern sets up that appears to be just right, if it doesn’t adhere to the rules above, the trade should not be taken. Specifically, we’re talking about rule #3. It’s very difficult, if not impossible, to determine the long term trend programmatically using an indicator. You will have to rely on your ability to assess where the pattern is coming from to be successful.

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What is the simple moving average (SMA) and how to use it

What is the simple moving average?

A simple moving average (SMA) is a technical indicator that calculates the average price of a stock over a certain number of periods (e.g. days, weeks, months). This average is then plotted on a chart to indicate a trend or direction of the stock. For example, if a stock’s SMA over 50 days is increasing, it may indicate an upward trend, whereas if the SMA is decreasing, it may indicate a downward trend. Traders often use moving averages in conjunction with other indicators to confirm or refute signals of a stock’s direction.

Can multiple SMAs be used simultaneously?

It’s common for traders to use multiple simple moving averages (SMAs) simultaneously. By comparing different SMAs with different time periods, traders can get a more comprehensive view of a stock’s trend and potential direction. For example, one trader might use a short-term SMA (e.g. 10 days) to identify short-term fluctuations in the stock’s price, and a long-term SMA (e.g. 200 days) to identify long-term trends. By comparing the short-term SMA to the long-term SMA, the trader can gain insight into whether the short-term fluctuations are consistent with the long-term trend or if they are likely to be temporary. Another example is using 2 moving averages with different periods and when the shorter period SMA crosses over the longer period SMA it can indicate a bullish or bearish direction. This technique is known as the Moving Average Crossover.

What are some other indicators used in conjunction with the simple moving average?

There are many technical indicators that traders use in conjunction with simple moving averages (SMAs) to help identify trends and make investment decisions. Some of the most commonly used indicators include:

  1. Relative Strength Index (RSI): This indicator compares the magnitude of a stock’s recent gains to the magnitude of its recent losses, and is used to identify overbought or oversold conditions.
  2. Bollinger Bands: This indicator consists of a simple moving average and two standard deviation lines that are plotted above and below the average. It is used to identify overbought or oversold conditions and potential breakouts.
  3. Stochastic Oscillator: This indicator compares a stock’s closing price to its price range over a certain period of time and is used to identify overbought or oversold conditions.
  4. Moving Average Convergence Divergence (MACD): This indicator is calculated by subtracting a 26-day exponential moving average from a 12-day exponential moving average. It is used to identify changes in momentum and potential trend reversals.
  5. Fibonacci retracements: This indicator is a way to identify support and resistance levels by plotting horizontal lines at key Fibonacci levels of a price move.

Can simple moving averages be used to automate trading?

Simple moving averages (SMAs) are sometimes used to automate trading. Traders can create algorithms that use SMAs and other technical indicators to generate buy or sell signals. These algorithms can then be programmed into trading software, which can execute trades automatically based on the signals generated by the algorithm.

Please note that automating trading based on SMAs or any other technical indicator is not a guarantee of success. Many factors can influence a stock’s price, and no single indicator can provide a complete picture of a stock’s trend or direction. It’s important to backtest the algorithm and also keep monitoring it, as market conditions change over time which can cause the algorithm to stop working as expected.

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What is the Relative Strength (RSI) indicator?

The Relative Strength Index (RSI) is a popular technical indicator used in the analysis of financial markets. Developed by J. Welles Wilder Jr. in 1978, the RSI is a momentum indicator that measures the strength of a security’s price action. It compares the magnitude of recent gains to recent losses in an attempt to determine overbought and oversold conditions of an asset.

The RSI is calculated using a simple mathematical formula that compares the average gains of an asset to the average losses over a specified period of time. The resulting value is then plotted on a scale of 0 to 100, with values above 70 indicating that the asset is overbought, and values below 30 indicating that the asset is oversold.

One of the key strengths of the RSI indicator is its ability to identify potential trend reversals. If the RSI is above 70, it may indicate that the asset is overbought and that a price correction or reversal is likely to occur. Similarly, if the RSI is below 30, it may indicate that the asset is oversold and that a price rally is likely to occur.

Another important aspect of the RSI indicator is that it is a momentum indicator, meaning that it helps traders to identify the strength of a trend. If the RSI is trending higher, it may indicate that the underlying asset is in an uptrend and that the trend is gaining momentum. Conversely, if the RSI is trending lower, it may indicate that the underlying asset is in a downtrend and that the trend is losing momentum.

It’s also worth noting that RSI is a lagging indicator. It is based on past performance, so it may not always be the best indicator to predict future price movements. Therefore, traders should use RSI in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions.

The RSI is a powerful technical indicator that can be used to determine overbought and oversold conditions, identify potential trend reversals, and measure the strength of a trend. While it is not a perfect indicator, it can be a valuable tool for traders when used in conjunction with other technical indicators and fundamental analysis.

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How to create a thinkorswim (TOS) dollar gainer scan

If you’re just starting out, be sure to visit the thinkorswim Learning Center first. The video on that page describes how to get started with creating your first scan. I’ll keep this simple, and even provide the code for you! In this scan we will meet the following criteria. 1) The stock must have gained at least one dollar from the previous day’s close during the pre-market trading session. The pre-market is defined as the time between 4:00am and 9:29am. 2) The pre-market cumulative volume must exceed 5,000 shares traded. Here are the steps to create a thinkorswim (TOS) dollar gainer scan. Feel free to update the change and preMktVolMin variables to meet your needs.

  1. For the “Scan in:” section, choose All Stocks from the Category list
  2. For the “Exclude:” section, choose All OTC Stocks from the Category list (unless you like to trade OTC stocks, of course)
  3. Add a filter using the “+ Add filter” button. Choose Stock. Under the first drop-down, choose Last and set the min and max price for the stocks you like to trade
  4. Add another filter. This time choose Study. At the bottom of the first drop-down list, choose custom. A window will open. Click the “thinkScript Editor” tab at the top of the window. Also, change the Aggregation (also at the top of the window) to 1 min. Remove the default code from the editor window and copy/paste the code from below. Update the “change” or “preMktVolMin” variable values as needed.
  5. Add another “Stock” filter. Set it to a Market cap min. of 1M. This will filter out some things that are not stocks.
def change = 1.00;
def preMktVolMin = 50000;
def mktClose = 1559;
def preMktStart = 0400;
def preMktEnd = 0929;
rec closePrice = CompoundValue(1, if SecondsTillTime(mktClose) == 0 then close else closePrice[1], close);
def gainers = (close - closePrice) >= change;
def preMkt = SecondsFromTime(preMktStart) >= 0 and SecondsTillTime(preMktEnd) >= 0;
def preMktVol = if preMkt and !preMkt[1] then volume else if preMkt then preMktVol[1] + volume else preMktVol[1];
plot scan = preMkt and gainers and preMktVol > preMktVolMin;
  1. Click OK to exit the window.
  2. Click the menu to the far right of the “Add condition group” button, and click “Save scan query…”
  3. Give your scan a name, and save it.
  4. Click the Scan button and await your results! NOTE: If you’re not scanning during the pre-market, you’ll get no results.

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