Optimal Buy Day (Zeiierman)█ Overview
The Optimal Buy Day (Zeiierman) indicator identifies optimal buying days based on historical price data, starting from a user-defined year. It simulates investing a fixed initial capital and making regular monthly contributions. The unique aspect of this indicator involves comparing systematic investment on specific days of the month against a randomized buying day each month, aiming to analyze which method might yield more shares or a better average price over time. By visualizing the potential outcomes of systematic versus randomized buying, traders can better understand the impact of market timing and how regular investments might accumulate over time.
These statistics are pivotal for traders and investors using the script to analyze historical performance and strategize future investments. By understanding which days offered more shares for their money or lower average prices, investors can tailor their buying strategies to potentially enhance returns.
█ Key Statistics
⚪ Shares
Definition: Represents the total number of shares acquired on a particular day of the month across the entire simulation period.
How It Works: The script calculates how many shares can be bought each day, given the available capital or monthly contribution. This calculation takes into account the day's opening price and accumulates the total shares bought on that day over the simulation period.
Interpretation: A higher number of shares indicates that the day consistently offered better buying opportunities, allowing the investor to acquire more shares for the same amount of money. This metric is crucial for understanding which days historically provided more value.
⚪ AVG Price
Definition: The average price paid per share on a particular day of the month, averaged over the simulation period.
How It Works: Each time shares are bought, the script calculates the average price per share, factoring in the new shares purchased at the current price. This average evolves over time as more shares are bought at varying prices.
Interpretation: The average price gives insight into the cost efficiency of buying shares on specific days. A lower average price suggests that buying on that day has historically led to better pricing, making it a potentially more attractive investment strategy.
⚪ Buys
Definition: The total number of transactions or buys executed on a particular day of the month throughout the simulation.
How It Works: This metric increments each time shares are bought on a specific day, providing a count of all buying actions taken.
Interpretation: The number of buys indicates the frequency of investment opportunities. A higher count could mean more consistent opportunities for investment, but it's important to consider this in conjunction with the average price and the total shares acquired to assess overall strategy effectiveness.
⚪ Most Shares
Definition: Identifies the day of the month on which the highest number of shares were bought, highlighting the specific day and the total shares acquired.
How It Works: After simulating purchases across all days of the month, the script identifies which day resulted in the highest total number of shares bought.
Interpretation: This metric points out the most opportune day for volume buying. It suggests that historically, this day provided conditions that allowed for maximizing the quantity of shares purchased, potentially due to lower prices or other factors.
⚪ Best Price
Definition: Highlights the day of the month that offered the lowest average price per share, indicating both the day and the price.
How It Works: The script calculates the average price per share for each day and identifies the day with the lowest average.
Interpretation: This metric is key for investors looking to minimize costs. The best price day suggests that historically, buying on this day led to acquiring shares at a more favorable average price, potentially maximizing long-term investment returns.
⚪ Randomized Shares
Definition: This metric represents the total number of shares acquired on a randomly selected day of the month, simulated across the entire period.
How It Works: At the beginning of each month within the simulation, the script selects a random day when the market is open and calculates how many shares can be purchased with the available capital or monthly contribution at that day's opening price. This process is repeated each month, and the total number of shares acquired through these random purchases is tallied.
Interpretation: Randomized shares offer a comparison point to systematic buying strategies. By comparing the total shares acquired through random selection against those bought on the best or worst days, investors can gauge the impact of timing and market fluctuations on their investment strategy. A higher total in randomized shares might indicate that over the long term, the specific days chosen for investment might matter less than consistent market participation. Conversely, if systematic strategies yield significantly more shares, it suggests that timing could indeed play a crucial role in maximizing investment returns.
⚪ Randomized Price
Definition: The average price paid per share for the shares acquired on the randomly selected days throughout the simulation period.
How It Works: Each time shares are bought on a randomly chosen day, the script calculates the average price paid for all shares bought through this randomized strategy. This average price is updated as the simulation progresses, reflecting the cost efficiency of random buying decisions.
Interpretation: The randomized price metric helps investors understand the cost implications of a non-systematic, random investment approach. Comparing this average price to those achieved through more deliberate, systematic strategies can reveal whether consistent investment timing strategies outperform random investment actions in terms of cost efficiency. A lower randomized price suggests that random buying might not necessarily result in higher costs, while a higher average price indicates that systematic strategies might provide better control over investment costs.
█ How to Use
Traders can use this tool to analyze historical data and simulate different investment strategies. By inputting their initial capital, regular contribution amount, and start year, they can visually assess which days might have been more advantageous for buying, based on historical price actions. This can inform future investment decisions, especially for those employing dollar-cost averaging strategies or looking to optimize entry points.
█ Settings
StartYear: This setting allows the user to specify the starting year for the investment simulation. Changing this value will either extend or shorten the period over which the simulation is run. If a user increases the value, the simulation begins later and covers a shorter historical period; decreasing the value starts the simulation earlier, encompassing a longer time frame.
Capital: Determines the initial amount of capital with which the simulation begins. Increasing this value simulates starting with more capital, which can affect the number of shares that can be initially bought. Decreasing this value simulates starting with less capital.
Contribution: Sets the monthly financial contribution added to the investment within the simulation. A higher contribution increases the investment each month and could lead to more shares being purchased over time. Lowering the contribution decreases the monthly investment amount.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Daytrading
Day/Week/Month Metrics (Zeiierman)█ Overview
The Day/Week/Month Metrics (Zeiierman) indicator is a powerful tool for traders looking to incorporate historical performance into their trading strategy. It computes statistical metrics related to the performance of a trading instrument on different time scales: daily, weekly, and monthly. Breaking down the performance into daily, weekly, and monthly metrics provides a granular view of the instrument's behavior.
The indicator requires the chart to be set on a daily timeframe.
█ Key Statistics
⚪ Day in month
The performance of financial markets can show variability across different days within a month. This phenomenon, often referred to as the "monthly effect" or "turn-of-the-month effect," suggests that certain days of the month, especially the first and last days, tend to exhibit higher than average returns in many stock markets around the world. This effect is attributed to various factors including payroll contributions, investment of monthly dividends, and psychological factors among traders and investors.
⚪ Edge
The Edge calculation identifies days within a month that consistently outperform the average monthly trading performance. It provides a statistical advantage by quantifying how often trading on these specific days yields better returns than the overall monthly average. This insight helps traders understand not just when returns might be higher, but also how reliable these patterns are over time. By focusing on days with a higher "Edge," traders can potentially increase their chances of success by aligning their strategies with historically more profitable days.
⚪ Month
Historically, the stock market has exhibited seasonal trends, with certain months showing distinct patterns of performance. One of the most well-documented patterns is the "Sell in May and go away" phenomenon, suggesting that the period from November to April has historically brought significantly stronger gains in many major stock indices compared to the period from May to October. This pattern highlights the potential impact of seasonal investor sentiment and activities on market performance.
⚪ Day in week
Various studies have identified the "day-of-the-week effect," where certain days of the week, particularly Monday and Friday, show different average returns compared to other weekdays. Historically, Mondays have been associated with lower or negative average returns in many markets, a phenomenon often linked to the settlement of trades from the previous week and negative news accumulation over the weekend. Fridays, on the other hand, might exhibit positive bias as investors adjust positions ahead of the weekend.
⚪ Week in month
The performance of markets can also vary within different weeks of the month, with some studies suggesting a "week of the month effect." Typically, the first and the last week of the month may show stronger performance compared to the middle weeks. This pattern can be influenced by factors such as the timing of economic reports, monthly investment flows, and options and futures expiration dates which tend to cluster around these periods, affecting investor behavior and market liquidity.
█ How It Works
⚪ Day in Month
For each day of the month (1-31), the script calculates the average percentage change between the opening and closing prices of a trading instrument. This metric helps identify which days have historically been more volatile or profitable.
It uses arrays to store the sum of percentage changes for each day and the total occurrences of each day to calculate the average percentage change.
⚪ Month
The script calculates the overall gain for each month (January-December) by comparing the closing price at the start of a month to the closing price at the end, expressed as a percentage. This metric offers insights into which months might offer better trading opportunities based on historical performance.
Monthly gains are tracked using arrays that store the sum of these gains for each month and the count of occurrences to calculate the average monthly gain.
⚪ Day in Week
Similar to the day in the month analysis, the script evaluates the average percentage change between the opening and closing prices for each day of the week (Monday-Sunday). This information can be used to assess which days of the week are typically more favorable for trading.
The script uses arrays to accumulate percentage changes and occurrences for each weekday, allowing for the calculation of average changes per day of the week.
⚪ Week in Month
The script assesses the performance of each week within a month, identifying the gain from the start to the end of each week, expressed as a percentage. This can help traders understand which weeks within a month may have historically presented better trading conditions.
It employs arrays to track the weekly gains and the number of weeks, using a counter to identify which week of the month it is (1-4), allowing for the calculation of average weekly gains.
█ How to Use
Traders can use this indicator to identify patterns or trends in the instrument's performance. For example, if a particular day of the week consistently shows a higher percentage of bullish closes, a trader might consider this in their strategy. Similarly, if certain months show stronger performance historically, this information could influence trading decisions.
Identifying High-Performance Days and Periods
Day in Month & Day in Week Analysis: By examining the average percentage change for each day of the month and week, traders can identify specific days that historically have shown higher volatility or profitability. This allows for targeted trading strategies, focusing on these high-performance days to maximize potential gains.
Month Analysis: Understanding which months have historically provided better returns enables traders to adjust their trading intensity or capital allocation in anticipation of seasonally stronger or weaker periods.
Week in Month Analysis: Identifying which weeks within a month have historically been more profitable can help traders plan their trades around these periods, potentially increasing their chances of success.
█ Settings
Enable or disable the types of statistics you want to display in the table.
Table Size: Users can select the size of the table displayed on the chart, ranging from "Tiny" to "Auto," which adjusts based on screen size.
Table Position: Users can choose the location of the table on the chart
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
"Daily Range with Filtre [Hunter_Algo]
- The script calculates the high and low ranges based on the specified session time, such as the Asia Liquidity session.
- It uses the timeinrange function to determine if the current bar is within the specified session.
- High and low values are updated based on whether the current high or low surpasses the previous values within the specified session.
- The script includes functions to convert day strings to integers and style strings to enumeration values.
- There are additional inputs related to the start and end of the day range, as well as colors and styles for various elements.
- The script calculates daily high (Dh), daily low (Dl), and other variables based on certain conditions, including the day of the week.
Opening Range & Prior Day High/Low [Gorb]Introduction:
Opening Range & Prior Day High/Low indicator is an easy to use day traders tool. This indicator automatically plots the previous days high and low, as well as drawing a box from the opening range that the user specifies in the settings. These two together can help provide an indication of market sentiment and price trends for the day. They are often used as a trading strategy for day traders.
Overview:
The Opening Range , draws a box from the high to the low of the user defined time period and is extended until the end of the trading session. Most common are the 5/15/30min opening ranges.
Prior Day High/Low , draws lines from the previous days high and low that extend across the current session. These are used as support/resistance and also a marker to see market sentiment by crossing one of these levels.
The indicator is designed for all kinds of traders, offering a simple approach to automatically plot levels for you.
Features:
All skill-level friendly presets, easy to enable with one-click
Opening Range: Allows user to choose what time the range starts and ends to measure the high & low.
Extend Range Lines: allows the user to choose when the box stops extending according to the trading session time.
Enable Opening Range Box: allows the user to choose to plot the opening range or not.
ORB Border Color: allows the user to change the box border color.
ORB Box Shade Color: allows the user to change the background of the opening range box.
ORB Line Width: allows users to chose the width of the opening range box lines.
Enable Previous Day High: allows users to enable the previous days high to be plotted.
Enable Previous Day Low: allows users to enable the previous days high to be plotted.
Previous Day High Color: allows users to choose the color for this line.
Previous Day Low Color: allows users to choose the color for this line.
All colors are changeable for the user to customize to their liking.
Usage Demonstration
In the image below, we can see a basic example of how these 3 features function.
As explained above, the opening range is customizable to meet the users needs and can be disabled with one click. Same goes for the prior day high(green) and low(red) lines. All 3 are plotted each day automatically for the user if enabled.
In the image below, we can see an example of using the opening range break and prior day high together for a trading strategy.
This is a great example of using the prior day high with the opening range to use as a day trading strategy. It provides the trader with levels to watch for price to break out from for possible trade setups.
In this next image, we can see a failed breakdown from the opening range that results in a bullish breakout.
The first move was a fake breakdown with the failed rejection on the retest of the opening range lows. This led to a breakout above the range and a confirmation bounce on the breakout retest. Price did break above the prior day high and confirmed with a retest bounce on that level as well.
In the image below, we can see how previous days levels can act as resistance to use with the opening range.
Price didn't reject the opening range low, but it did reject the prior day high for the second time. This could be used as an entry or once price breaks down out of the opening range again.
Conclusion:
We believe in providing user-friendly tools to help speed up traders technical analysis and implement easy trading strategies. The goal is to provide a user-friendly indicator to automatically draw opening ranges and previous days levels to suit the users needs and trading style.
RISK DISCLAIMER
All content, tools, scripts & education provided by Monstanzer or Gorb Algo LLC are for informational & educational purposes only. Trading is risk and most lose their money, past performance does not guarantee future results.
Swing based support and resistanceThis indicator provided here is for identifying swing-based support and resistance levels. It uses two swing lengths, which can be adjusted by the user, to identify swings in the price data. For each swing length, the script calculates the support level as the low of the swing if the trend is up, or the high of the swing if the trend is down. It then plots the support and resistance levels on the chart, along with buy and sell signals.
The buy and sell signals are generated by comparing the current closing price to the support and resistance levels. If the closing price is above the support level, the script plots a buy signal. If the closing price is below the level, the script plots a sell signal.
To use the script, you would first need to add it to your trading platform. Once it is added, you can configure the swing lengths and other parameters to suit your trading style. You can then apply the script to a chart and begin using the support and resistance levels and buy and sell signals to make trading decisions.
Points to be noted while using the indicator:
# The script is designed to be used on a daily chart. However, you can also use it on other timeframes, such as weekly or monthly charts.
# The swing lengths that you choose will depend on your trading style. If you are a swing trader, you may want to use longer swing lengths. If you are a day trader, you may want to use shorter swing lengths.
# Remember, the support and resistance levels generated by the script are not exact price points. They are rather zones where demand and supply can change. Therefore, you should always use other technical analysis tools and indicators to confirm your trading decisions.
# Overall, the script is a useful tool for identifying swing-based support and resistance levels. It can be used by traders of all experience levels to generate trading ideas and improve their trading performance.
To use the swing-based support and resistance indicator with respect to price, you can follow these steps:
=> Identify the support and resistance levels that have been generated by the indicator.
=> Look for price action that is taking place near these levels.
=> If the price is above the level, look for bullish reversals or continuations.
=> If the price is below the level, look for bearish reversals or continuations.
For Example,
=> Bullish reversal: The price is above the level and forms a bullish candlestick pattern, such as a bullish hammer or engulfing pattern.
=> Bullish continuation: The price is above the level and bounces off of the level.
=> Bearish reversal: The price is below the level and forms a bearish candlestick pattern, such as a bearish hammer or engulfing pattern.
=> Bearish continuation: The price is below the level and rejects the level.
$$ You can also use the indicator to identify potential trading entry and exit points. For example, you could enter a long trade when the price breaks above a resistance level and exit the trade when the price retraces to the resistance level. Or, you could enter a short trade when the price breaks below a support level and exit the trade when the price rallies to the support level.
This swing-based support and resistance indicator is just one tool that you can use to trade. You should always use other technical analysis tools and indicators, such as price action and trend analysis, to confirm your trading decisions.
Additionally:
=> Be aware of the overall trend direction. If the trend is up, you should be looking for bullish reversals or continuations. If the trend is down, you should be looking for bearish reversals or continuations.
=> Use a stop loss order to limit your risk on each trade.
=> Consider using a position sizing strategy to manage your risk.
=> Do your own research and backtest any trading strategy before using it in a live trading environment.
Follow us for timely updates regarding future indicators and give it a like if you appreciate the indicator.
Day Trader's Anchored Moving Averages [wbburgin]For day traders, establishing a trend at the start of the day is critically important for setting targets and entering positions. This can be difficult when traditional moving averages lag from previous days, causing late entry and/or incorrect trend interpretation.
The Day Trader's Anchored MA indicator plots three dynamic moving averages which restart on each new period (session or monthly - more coming soon). This eliminates the lag in traditional moving averages while better identifying the trend, as the moving averages essentially 'build up' their lengths as the day progresses, until they reach your chosen maximum length.
This means that these anchored moving averages are
Quicker to identify the start-of-day trend, as markets tend to establish and then follow one trend throughout the day;
Dynamically increasing throughout the day (to your specifications)
Completely independent from previous days
Quick usage note: make sure that your moving average length is less than the number of bars in the period, or it won't reach the maximum length you specified.
TL;DR: Moving average that resets every day and does not lag. Inspired by the VWAP.
Intraday Volatility BarsThis script produce a volatility histrogram by bar with the current volatility overlayed.
The histogram shows cumulative average volatility over n days.
And the dots are todays cumulative volatility.
In other words, it calculates the True Range of each bar and adds it to todays value.
This script is build for intraday timeframes between one and 1440 minutes only.
I use this to show me when volatility is above/below/equal to the average volatility.
When the dots are above the histogram then it is a more volatile day, and vice versa.
Recognizing a more volatile day as early as possible can be an advantage for daytrader.
Days that start with higher volatility seems to continue to increase relative to the past few days. Or when midday volatility rises it seems to continue as well.
Happy Trading!
LNL Trend SystemLNL Trend System is an ATR based day trading system specifically designed for intra-day traders and scalpers. The System works on any chart time frame & can be applied to any market. The study consist of two components - the Trend Line and the Stop Line. Trend System is based on a special ATR calculation that is achieved by combining the previous values of the 13 EMA in relation to the ATR which creates a line of deviations that visually look similar to the basic moving average but actually produce very different results ESPECIALLY in sideways market.
Trend Line:
Trend Line is a simple line which is basically a fast gauge represented by the 13 EMA that can change the color based on the current trend structure defined by multiple averages (8,13,21,34 EMAs). Trend Line is there to simply add the confluence for the current trend. Colors of the line are pretty much self-explanatory. Whenever the line turns red it states that the current structure is bearish. Vice versa for green line. Gray line represents neutral market structure.
Stop Line:
Stop Line is an ATR deviaton line with special calculation based on the previous bar ATRs and position of the price in relation to the current and previous values of 13 EMA. As already stated, this creates an ATR deviation marker either above or below the price that trails the price up or down until they touch. Whenever the price comes into the Stop Line it means it is making an ATR expansion move up or down .This touch will usually resolve into a reaction (a bounce) which provides trade opportunities.
Trend Bars:
When turned ON, Trend Bars can provide additional confulence of the current trend alongside with the Trend Line color. Trend Bars are based on the DMI and ADX indicators. Whenever the DMI is bearish and ADX is above 20 the candles paint themselfs red. And vice versa applies for the green candles and bullish DMI. Whenever the ADX falls below the 20, candles are netural (Gray) which means there is no real trend in place at the moment.
Trend Mode:
There are total of 5 different trend modes available. Each mode is visualizing different ATR settings which provides either aggressive or more conservative approach. The more tigher the mode, the more closer the distance between the price and the Stop Line. First two modes were designed for slower markets, whereas the "Loose" and "FOMC" modes are more suitable for products with high volatility.
Trend Modes:
1. Tight
Ideal for the slowest markets. Slowest market can be any market with unusually small average true range values or just simply a market that does have a personality of a "sleeper". Tight Mode can be also used for aggresive entries in the most ridiculous trends. Sometimes price will barely pullback to the Trend Line not even the Stop Line.
2. Normal
Normal Mode is the golden mean between the modes. "Normal" provides the ideal ATR lengths for the most used markets such as S&P Futures (ES) or SPY, AAPL and plenty of other highly popular stocks. More often than not, the length of this mode is respected considering there is no breaking news or high impact market event scheduled.
3. Loose
The "Loose" mode is basically a normal mode but a little bit more loose. This mode is useful whenever the ATRs jump higher than usual or during the days of highly anticipated news events. This mode is also better suited for more active markets such as NQ futures.
4. FOMC
The FOMC mode is called FOMC for a reason. This mode provides the maximum amount of wiggle room between the price and the Stop Line. This mode was designed for the extreme volatility, breaking news events or post-FOMC trading. If the market quiets down, this mode will not get the Stop Line touch as frequently as othete modes, thus it is not very useful to run this on markets with the average volatlity. Although never properly tested, perhaps the FOMC mode can find its value in the crypto market?
5. The Net
The net mode is basically a combination of all modes into one stop line system which creates "the net" effect. The Net provides the widest Stop Line zone which can be mainly appreciated by traders that like to use scale-in scale-out methods for their trading. Not to mention the visual side of the indicator which looks pretty great with the net mode on.
HTF (Higher Time Frame) Trend System:
The system also includes additional higher time frame (HTF) trend system. This can be set to any time frame by manual HTF mode. HTF mode set to "auto" will automatically choose the best suitable higher time frame trend system based on how appropriate the aggregation is. For everything below 5min the HTF Trend System will stay on 5min. Anything between 5-15min = 30min. 30min - 120min will turn on the 240min. 180min and higher will result in Daily time frame. Anything above the Daily will result in Weekly HTF aggregation, above W = Monthly, above M = Quarterly.
Background Clouds:
In terms of visualization, each trend system is fully customizable through the inputs settings. There is also an option to turn on/off the background clouds behind the stop lines. These clouds can make the charts more clean & visible.
Tips & Tricks:
1. Different Trend Modes
Try out different modes in different markets. There is no one single mode that will fit to everyone on the same type of market. I myself actually prefer more Loose than the Normal.
2. Stop Line Mirroring
Whenever the Stop Lines start to mirror each other (there is one above the price and one below) this means the price is entering a ranging sideways market. It does not matter which Stop Line will the price touch first. They can both be faded until one of them flips.
3. Signs of the Ranging Market
Watch out for signs of ranging market. Whenever the Trend System looses its colors whether on trend line or trend bars, if everything turns neutral (gray) that is usually a solid indication of a range type action for the following moments. Also as already stated before, the Stop Line mirroring is a good sign of the range market.
4. Trailing Tool, Trend System as an Additional Study?
In case you are not a fan of the colorful green / red charts & candles. You can switch all of them off and just leave the Stop Line on. This way you can use the benefits of the trend system and still use other studies on top of that. Similarly as the Parabolic SAR is often used.
5. The Flip Setup
One of my favorite trades is the Flip Setup on the 5min charts. Whenever the Stop Line is broken , the very first opposing touch after the Trend System flips is a usually a highly participated touch. If there is a strong reaction, this means this is likely a beginning of a new trend. Once I am in the position i like to trail the Stop Line on the 1min charts.
Hope it helps.
Directional Movement Index FLEXA common problem experienced by short term traders using DMI/ADX is that the session breaks results in carry-over effects from the prior session. For example, a large gap up would result in a positive DMI, even though momentum is clearly negative. Note the extremely different results in the morning session, when the gap is reversed.
The DMI-FLEX algoritm resets the +DI and -DI values to the prior session ending midpoint, so that new momentum can be observed from the indicator. (Note for Pinescript coders: rma function does not accept series int, thus the explicit pine_rma function)
DMI-FLEX has the added feature that the ADX value, instead of a separate line, is shown as shading between the +DI and -DI lines, and the color itself is determined by whether +DI is above -DI for a bullish color, or -DI is above +DI for a bearish color.
DMI Flex also gives you the flexibility of inverse colors, in case your chart has inverted scale.
Summary and How to use:
1) Green when +DI is above -DI
2) Red when -DI is above +DI
3) Deeper shading represents a higher ADX value.
High of Day Low of Day hourly timings: Statistics. Time of day %High of Day (HoD) & Low of Day (LoD) hourly timings: Statistics. Time of day % likelihood for high and low.
//Purpose:
To collect stats on the hourly occurrences of HoD and LoD in an asset, to see which times of day price is more likely to form its highest and lowest prices.
//How it works:
Each day, HoD and LoD are calculated and placed in hourly 'buckets' from 0-23. Frequencies and Percentages are then calculated and printed/tabulated based on the full asset history available.
//User Inputs:
-Timezone (default is New York); important to make sure this matches your chart's timezone
-Day start time: (default is Tradingview's standard). Toggle Custom input box to input your own custom day start time.
-Show/hide day-start vertical lines; show/hide previous day's 'HoD hour' label (default toggled on). To be used as visual aid for setting up & verifying timezone settings are correct and table is populating correctly).
-Use historical start date (default toggled off): Use this along with bar-replay to backtest specific periods in price (i.e. consolidated vs trending, dull vs volatile).
-Standard formatting options (text color/size, table position, etc).
-Option to show ONLY on hourly chart (default toggled off): since this indicator is of most use by far on the hourly chart (most history, max precision).
// Notes & Tips:
-Make sure Timezone settings match (input setting & chart timezone).
-Play around with custom input day start time. Choose a 'dead' time (overnight) so as to ensure stats are their most meaningful (if you set a day start time when price is likely to be volatile or trending, you may get a biased / misleadingly high readout for the start-of-day/ end-of-day hour, due to price's tendency for continuation through that time.
-If you find a time of day with significantly higher % and it falls either side of your day start time. Try adjusting day start time to 'isolate' this reading and thereby filter out potential 'continuation bias' from the stats.
-Custom input start hour may not match to your chart at first, but this is not a concern: simply increment/decrement your input until you get the desired start time line on the chart; assuming your timezone settings for chart and indicator are matching, all will then work properly as designed.
-Use the the lines and labels along with bar-replay to verify HoD/LoD hours are printing correctly and table is populating correctly.
-Hour 'buckets' represent the start of said hour. i.e. hour 14 would be populated if HoD or LoD formed between 14:00 and 15:00.
-Combined % is simply the average of HoD % and LoD %. So it is the % likelihood of 'extreme of day' occurring in that hour.
-Best results from using this on Hourly charts (sub-hourly => less history; above hourly => less precision).
-Note that lower tier Tradingview subscriptions will get less data history. Premium acounts get 20k bars history => circa 900 days history on hourly chart for ES1!
-Works nicely on Btc/Usd too: any 24hr assets this will give meaningful data (whereas some commodities, such as Lean Hogs which only trade 5hrs in a day, will yield less meaningful data).
Example usage on S&P (ES1! 1hr chart): manual day start time of 11pm; New York timezone; Visual aid lines and labels toggled on. HoD LoD hour timings with 920 days history:
DJ Soori Trading StrategyThe strategy combines three indicators: Exponential Moving Average (EMA), Weighted Moving Average (WMA), and Average Directional Index (ADX).
The EMA and WMA are used to track the average price over different time periods.
The ADX measures the strength of a trend in the market.
The strategy generates buy signals when the EMA is higher than the WMA and the ADX is above a certain threshold. It suggests a potential uptrend.
It generates sell signals when the EMA is lower than the WMA and the ADX is above the threshold. It suggests a potential downtrend.
The strategy also considers whether the ADX is rising or falling to indicate the strength of the trend.
The EMA, WMA, and ADX values are plotted on the chart.
Buy and sell signals are shown as labels on the chart, indicating "Buy (Strong)" or "Buy (Weak)" for buy signals, and "Sell (Strong)" or "Sell (Weak)" for sell signals.
Typical Sweeps: Pivot high/low boxes. Grade sweeps, Handles/PipsTool to show typical pip-grade/ handle-grade sweep distance above pivot highs and pivot lows
-In consolidation/ranging periods (i.e. most of the time); Highs/Lows may by swept by fairly consistent distances in typical stop raids.
-Idea is from ICT teaching on typical Pip-grade sweeps in FX (10,20,30pips). Designed to work on FX, Indices, Commodities, Bitcoin.
-Above chart shows S&P; sweeping below and then above by 5 handles.
///inputs///
~choose sweep distance handles ($) or pips: will auto-calculate depending on the asset: FX= pips; Indices/stocks/commodities = handles ($)
--(2,5,10,20,30,50,100, 500, 1000)
~choose pivot lookback: larger number for more significant swing highs/lows
~choose number of historical boxes to display
~toggle on/off Pivot high boxes and Pivot low boxes independently
~extend boxes fully to the right (default is not extend)
~toggle on/off text
~text & box formatting options
Bitcoin, hourly chart; Pivot lookback = 15; $100 sweep boxes:
Eur/Usd; 15m chart; Pivot lookback = 30; 10pip sweep boxes; Boxes extended fully to the right:
TMO ScalperTMO - (T)rue (M)omentum (O)scillator) MTF Scalper Version
TMO Scalper is a special custom version of the popular TMO Oscillator. Scalper version was designed specifically for the lower time frames (1-5min intraday scalps). This version prints in the signals directly on top of the oscillator only when the higher aggregations are aligned with the current aggregation (the big wheels must be spinning in order for a small wheel to spin). The scalper consist of three MTF TMO oscillators. First one is the one that plot signals (should be the fastest aggregation), second serves as a short term trend gauge (good rule of thumb is to us 2-5x of the chart time frame or the first aggregation). The third one (optional) is shaded in the background & should only serve as a trend gauge for the day (usually higher time frames 30min+).
Time Frames Preffered by Traders:
1. 1m / 5m / 30m - This one is perfect for catching the fastest moves. However, during choppy days the 1min can produce more false signals..
2. 2m / 10m / 30m - Healthy middle, the 2min aggregation nicely smooths out the 1min mess. Short term gauge is turning slowly (10min for a signal to confirm).
3. 3m / 30m / 60m - This TF is awesome for day traders that prefer to take it slow. Obviously, this combination will produce far less signals during the day.
Hope it helps.
Moving Average Directional IndexMADX is ADX-inspired indicator with moving averages that determines strength of a trend, as well as its direction. Indicator works following:
As the value of MADX increases, so does the strength of a trend
If MADX+ ( green line - bullish MADX ) crosses above MADX- ( red line - bearish MADX ) we consider trend as bullish and vice versa..
There will be situations where MADX- and MADX+ cross multiple times in a short period of time -> that will mean that market indecision is happening and big move will most likely happen after it.
For the calculation of MADX+ and MADX- we need Moving Averages or Exponential Moving Averages with three specific sources ( high, close, low ).
Now, the calculation of each MADX will differ
=> for MADX+: Moving Average (high) / Moving Average (close)
=> for MADX-: Moving Average (close) / Moving Average (low)
Length of Moving Average is editable.
SUPPORT RESISTANCE STRATEGY [5MIN TF]A SUPPORT RESISTANCE BREAKOUT STRATEGY for 5 minute Time-Frame , that has the time condition for Indian Markets
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above Resistance Level ,indicated by Red Line, is a Long condition.
2) Price crosses below Support Level ,indicated by Green Line , is a Short condition.
3) Candle high crosses above ema1, is a part of the Long condition .
4) Candle low crosses below ema1, is a part of the Short condition .
5) Volume Threshold is an added confirmation for long/short positions.
6) Maximum Risk per trade for the intraday trade can be changed .
7) Default qty size is set to 50 contracts , which can be changed under settings → properties → order size.
8) ATR is used for trailing after entry, as mentioned in the inputs below.
// ═════════════════════════//
// ————————> INPUTS <————————— //
// ═════════════════════════//
→ L_Bars ———————————> Length of Resistance / Support Levels.
→ R_Bars ———————————> Length of Resistance / Support Levels.
→ Volume Break ———————> Volume Breakout from range to confirm Long/Short position.
→ Price Cross Ema —————> Added condition as explained above (3) and (4).
→ ATR LONG —————————> ATR stoploss trail for Long positions.
→ ATR SHORT ————————> ATR stoploss trail for Short positions.
→ RISK ————————————> Maximum Risk per trade intraday.
The strategy was back-tested on TCS ,the input values and the results are mentioned under "BACKTEST RESULTS" below.
// ═════════════════════════ //
// ————————> PROPERTIES<——————— //
// ═════════════════════════ //
Default_qty_size ————> 50 contracts , which can be changed under
Settings
↓
Properties
↓
Order size
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the script , Add it → click on ' { } ' → Pine editor→ making it a copy [right top corner} → Edit the line 27.
The Indian Markets open at 9:15am and closes at 3:30pm.
The 'time_cond' specifies the time at which Entries should happen .
"Close All" function closes all the trades at 3pm , at the open of the next candle.
To change the time to close all trades , Go to Pine Editor → Edit the line 92 .
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 100 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better Back-Test results.
The strategy applied to NSE:TCS ( 5 min Time-Frame and contract size 50) gives us 60% profitability , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.8 ,net Profit of 30,000 Rs profit .
Sharpe Ratio : 0.49
Sortino Ratio : 1.4
The graph has a Linear Curve with Consistent Profits.
The INPUTS are as follows,
1) L_Bars —————————> 4
2) R_Bars —————————> 4
3) Volume Break ————> 5
4) Price Cross Ema ——> 100
5) ATR LONG ——————> 2.4
6) ATR SHORT —————> 2.6
7) RISK —————————> 2000
8) Default qty size ——> 50
NSE:TCS
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Thank You ☺ NSE:TCS
PIVOT STRATEGY [INDIAN MARKET TIMING]
A Back-tested Profitable Strategy for Free!!
A PIVOT INTRADAY STRATEGY for 5 minute Time-Frame , that also explains the time condition for Indian Markets
The Timing can be changed to fit other markets, scroll down to "TIME CONDITION" to know more.
The commission is also included in the strategy .
The basic idea is when ,
1) Price crosses above ema1 ,indicated by pivot highest line in green color .
2) Price crosses below ema1 ,indicated by pivot lowest line in red color .
3) Candle high crosses above pivot highest , is the Long condition .
4) Candle low crosses below pivot lowest , is the Short condition .
5) Maximum Risk per trade for the intraday trade can be changed .
6) Default_qty_size is set to 60 contracts , which can be changed under settings → properties → order size .
7) ATR is used for trailing after entry, as mentioned in the inputs below.
// ═════════════════════════//
// ————————> INPUTS <————————— //
// ═════════════════════════//
Leftbars —————> Length of pivot highs and lows
Rightbars —————> Length of pivot highs and lows
Price Cross Ema —————> Added condition
ATR LONG —————> ATR stoploss trail for Long positions
ATR SHORT —————> ATR stoploss trail for Short positions
RISK —————> Maximum Risk per trade for the day
The strategy was back-tested on RELIANCE ,the input values and the results are mentioned under "BACKTEST RESULTS" below .
// ═════════════════════════ //
// ————————> PROPERTIES<——————— //
// ═════════════════════════ //
Default_qty_size ————> 60 contracts , which can be changed under settings
↓
properties
↓
order size
// ═══════════════════════════════//
// ————————> TIME CONDITION <————————— //
// ═══════════════════════════════//
The time can be changed in the script , Add it → click on ' { } ' → Pine editor→ making it a copy [right top corner} → Edit the line 25 .
The Indian Markets open at 9:15am and closes at 3:30pm .
The 'time_cond' specifies the time at which Entries should happen .
"Close All" function closes all the trades at 3pm, at the open of the next candle.
To change the time to close all trades , Go to Pine Editor → Edit the line 103 .
All open trades get closed at 3pm , because some brokers don't allow you to place fresh intraday orders after 3pm .
NSE:RELIANCE
// ═══════════════════════════════════════════════ //
// ————————> BACKTEST RESULTS ( 128 CLOSED TRADES )<————————— //
// ═══════════════════════════════════════════════ //
INPUTS can be changed for better back-test results.
The strategy applied to NIFTY ( 5 min Time-Frame and contract size 60 ) gives us 60% profitability y , as shown below
It was tested for a period a 6 months with a Profit Factor of 1.45 ,net Profit of 21,500Rs profit .
Sharpe Ratio : 0.311
Sortino Ratio : 0.727
The graph has a Linear Curve with consistent profits .
The INPUTS are as follows,
1) Leftbars ————————> 3
2) Rightbars ————————> 5
3) Price Cross Ema ——————> 150
4) ATR LONG ————————> 2.7
5) ATR SHORT ———————> 2.9
6) RISK —————————> 2500
7) Default qty size ——————> 60
NSE:RELIANCE
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Trade HourThis script is just finds the best hour to buy and sell hour in a day by checking chart movements in past
For example if the red line is on the 0.63 on BTC/USDT chart it mean the start of 12AM hour on a day is the best hour to buy (all based on
It's just for 1 hour time-frame but you can test it on other charts.
IMPORTANT: You can change time Zone in strategy settings.to get the real hours as your location timezone
IMPORTANT: Its for now just for BTC/USDT but you can optimize and test for other charts...
IMPORTANT: A green and red background color calculated for show the user the best places of buy and sell (green : positive signal, red: negative signals)
settings :
timezone : We choice a time frame for our indicator as our geo location
source : A source to calculate rate of change for it
Time Period : Time period of ROC indicator
About Calculations:
1- We first get a plot that just showing the present hour as a zigzag plot
2- So we use an indicator ( Rate of change ) to calculate chart movements as positive and negative numbers. I tested ROC is the best indicator but you can test close-open or real indicator or etc as indicator.
3 - for observe effects of all previous data we should indicator_cum that just a full sum of indicator values.
4- now we need to split this effects to hours and find out which hour is the best place to buy and which is the best for sell. Ok we should just calculate multiple of hour*indicator and get complete sum of it so:
5- we will divide this number to indicator_cum : (indicator_mul_hour_cum) / indicator_cum
6- Now we have the best hour to buy! and for best sell we should just reverse the ROC indicator and recalculate the best hour for it!
7- A green and red background color calculated for show the user the best places of buy and sell that dynamically changing with observing green and red plots(green : positive signal, red: negative signals) when green plot on 15 so each day on hour 15 the background of strategy indicator will change to 15 and if its go upper after some days and reached to 16 the background green color will move to 16 dynamically.
Days and Session
This indicator optionally displays 2 informations:
- The Day of the week
- The New session's Candle
You can turn off/on the displayed information
Disclaimer: Scripts that I post publicly are experimental. They are not financial advices. Always backtest your ideas using your own methodologies.
3C QFL Mean reversalWhat is QFL trading strategy?
QFL stands for Quickfingersluc, and sometimes it is referred to as the Base Strategy or Mean Reversals. Its main idea is about identifying the moment of panic selling and buying below the base level and utilizing Safety orders.
What is Base level or Support Level?
Base level or Support Level refers to the lowest price level that was reached before the moment the price started increasing again. At that level, you can notice that buyers of some cryptocurrencies make a strong reaction.
In this strategy we can also reverse the strategy and go short. But i must warn you that that is alot riskier.
QFL is meant to be used on higher TF's like 1hr, 2hr and 4hr. But this strategy also work well on lower Timeframes.
The script also simulates DCA strategy with parameters used in 3commas DCA bots for futures trading.
Experiment with parameters to find your trading setup.
Beware how large your total leveraged position is and how far can market go before you get liquidated!
Do that with the help of futures liquidation calculators you can find online!
Included:
An internal average price and profit calculating, instead of TV`s native one, which is subject to severe slippage.
A graphic interface, so levels are clearly visible and back-test analyzing made easier.
Long & Short direction of the strategy.
Table display a summary of past trades
Vertical colored lines appear when the new maximum deviation from the original price has
been reached
All the trading happens with total account capital, and all order sizes inputs are expressed in percent.
God Number Channel V1 (GNC V1)Channel, made of 5 MAs, which a made this way: High of N-period SMA - Low of N-period SMA + X-period SMA (check the code), where N and X are defined by your input.
Main purpose: helps you understand in what range price can move.
WARNING!
HAS TO BE USED WITH OTHER INDICATORS TO HAVE MORE ACCURATE ENTRIES!!!
If the price is above or below the channel, it means that the movement is very strong and you count it as a trend, but be careful then the price returns to the channel, as correction will follow very soon. Use fib correction tool to understand the approximate depth of correction, works pretty good.
Recommendation: consider using the Vortex Indicator( len 21 and 14 are fine; for trend) and "Vumanchu Divergencies + B"(for anything, but calibrate for accuracy, otherwise there will be too much false signals). If you want to see more options where the price might go, just add new MA and add/substract to/from its value avg1*(any of fibonacci correction levels, I personally use 1.618 and 2.618 and for me it is ok): plot(show_ma1 ? ma1+( [ [ ]]]*avg1) : na, color = ma1_color, title="MA №1")
Recommendations and feedback are welcome(!)
Take your wins
Current Trend [KPM] - Buy / SellYou can filter the trend with this indicator. Green Lines indicate a short-term up trend and Red lines indicate a short-term downtrend. and black lines indicate short-term consultation.
I'm not regarding anything with this indicator. All risk is yours
Thank you
ATR and IV Volatility TableThis is a volatility tool designed to get the daily bottom and top values calculated using a daily ATR and IV values.
ATR values can be calculated directly, however for IV I recommend to take the values from external sources for the asset that you want to trade.
Regarding of the usage, I always recommend to go at the end of the previous close day of the candle(with replay function) or beginning of the daily open candle and get the expected values for movements.
For example for 26April for SPX, we have an ATR of 77 points and the close of the candle was 4296.
So based on ATR for 27 April our TOP is going to be 4296 + 77 , while our BOT is going to be 4296-77
At the same time lets assume the IV for today is going to be around 25% -> this is translated to 25 / (sqrt (252)) = 1.57 aprox
So based on IV our TOP is going to be 4296 + 4296 * 0.0157 , while our BOT is going to be 4296 - 4296 * 0.0157
I found out from my calculations that 80-85% of the times these bot and top points act as an amazing support and resistence points for day trading, so I fully recommend you to start including them into your analysis.
If you have any questions let me know !
Hulk Strategy x35 Leverage 5m chart w/Alerts This strategy is a pullback strategy that utilizes 2 EMAs as a way of identifying trend, MACD as an entry signal, and RSI and ADX to filter bad trades. By using the confirmation of all of these indicators the strategy attempts to catch pullbacks, and it is optimized to wait for high probability setups. Take not that the strategy is optimized for use on BTCUSDT along with 35 times leverage(Using leverage is risky). The Hulk Strategy waits for strong trend confirmation and then attempts to identify pullbacks using MACD and RSI. By using these it identifies strong short term movement against the trend(hence the name Hulk). To use the strategy wait for the strategy to make an entry, and then enter with a stop loss of 1.1% and a take profit of 1.35% with respect to if it is a long or short position. The trade frequency of this strategy is high as it is made for use on the 5m timeframe. But this does not mean you will have to be staring at your computer constantly as an average of 1 trade takes place each day. This will vary a lot though, somedays the strategy enters up to 4 times. I wish you good trading and hope that you like this strategy!
P.S. The indicators on my chart are visualizations of the indicators used in the strategy, they are not necessary for the strategy to work though. Also the colored in cloud on the price chart is an EMA cloud and it comes with the strategy when you add it to your chart. This EMA cloud consists of two EMAs a 50 and a 200 EMA.
