Equity CurveAn equity curve is a graphical representation of the change in the value of a trading account over a time period. The equity curve is a direct reflection of a trading strategy's effectiveness. A consistently upward-trending equity curve indicates a successful strategy, while a flat or declining curve may signal the need for adjustment.
This indicator takes traders daily account values as a comma separated list, and creates an equity curve and simple moving average of the equity curve. This serves as a mirror reflecting the outcome of past actions and decisions, guiding traders in fine-tuning their strategies, managing risk more effectively, and ultimately striving towards a consistently profitable trading journey.
New equity values should be added to the end of the current list. A space or no space after the comma has no effect.
Importance of the Equity Curve
Strategy Evaluation: The equity curve is a direct reflection of a trading strategy's effectiveness over time. A consistently upward-trending equity curve indicates a successful strategy, while a flat or declining curve may signal the need for adjustment.
Risk Management: Monitoring the equity curve helps traders to see the impact of their risk management practices. Sudden drops in equity could highlight instances of excessive risk-taking or inadequate stop-loss settings.
Performance Benchmarks: Comparing the equity curve against benchmarks or desired performance goals allows traders to assess if they are meeting, exceeding, or falling short of their trading objectives.
Psychology: Trading is as much about psychology as it is about strategy. A visual representation of one's equity curve helps maintain discipline, encouraging adherence to a trading plan during downturns and preventing overconfidence during upswings.
Having this data visually allows traders to see which category of trader they fall into.
Unprofitable
Boom or Bust
Profitable
Statistical Data
The indicator not only plots the equity curve and moving average, but includes the option to display the highest value reached by the equity curve, the percentage difference from the peak, and performance over selected periods (All Time, YTD, QTD, MTD, WTD).
Historical Analysis
The Equity Curve Indicator is not just a tool for real-time monitoring of trading performance; it also serves as a powerful instrument for conducting historical analysis. By analyzing the equity curve in conjunction with historical market conditions, traders can identify patterns or triggers that resulted in significant gains or losses.
For example, the chart below shows the equity curve overlaid on periods of net new highs / lows. The equity curve experienced declines while the market was showing net new lows or choppy periods (represented by a red or white background), while most of the equity gains were made while net new highs were present (green background).
This retrospective analysis helps in understanding how different market conditions impact trading strategies and performance.
Trading the Equity Curve
All trading strategies produce an equity curve that has winning and losing periods. In the example above, the trader could introduce a simple rule to lighten up on long positions or move to cash during periods of net new lows.
Another simple rule could be introduced to stop trading if the equity curve falls below the moving average, until favorable market conditions return again.
This indicator is intended to be used on the daily timeframe.
Portfolio management
Danger Signals from The Trading MindwheelThe " Danger Signals " indicator, a collaborative creation from the minds at Amphibian Trading and MARA Wealth, serves as your vigilant lookout in the volatile world of stock trading. Drawing from the wisdom encapsulated in "The Trading Mindwheel" and the successful methodologies of legends like William O'Neil and Mark Minervini, this tool is engineered to safeguard your trading journey.
Core Features:
Real-Time Alerts: Identify critical danger signals as they emerge in the market. Whether it's a single day of heightened risk or a pattern forming, stay informed with specific danger signals and a tally of signals for comprehensive decision-making support. The indicator looks for over 30 different signals ranging from simple closing ranges to more complex signals like blow off action.
Tailored Insights with Portfolio Heat Integration: Pair with the "Portfolio Heat" indicator to customize danger signals based on your current positions, entry points, and stops. This personalized approach ensures that the insights are directly relevant to your trading strategy. Certain signals can have different meanings based on where your trade is at in its lifecycle. Blow off action at the beginning of a trend can be viewed as strength, while after an extended run could signal an opportunity to lock in profits.
Forward-Looking Analysis: Leverage the 'Potential Danger Signals' feature to assess future risks. Enter hypothetical price levels to understand potential market reactions before they unfold, enabling proactive trade management.
The indicator offers two different modes of 'Potential Danger Signals', Worst Case or Immediate. Worst Case allows the user to input any price and see what signals would fire based on price reaching that level, while the Immediate mode looks for potential Danger Signals that could happen on the next bar.
This is achieved by adding and subtracting the average daily range to the current bars close while also forecasting the next values of moving averages, vwaps, risk multiples and the relative strength line to see if a Danger Signal would trigger.
User Customization: Flexibility is at your fingertips with toggle options for each danger signal. Tailor the indicator to match your unique trading style and risk tolerance. No two traders are the same, that is why each signal is able to be turned on or off to match your trading personality.
Versatile Application: Ideal for growth stock traders, momentum swing traders, and adherents of the CANSLIM methodology. Whether you're a novice or a seasoned investor, this tool aligns with strategies influenced by trading giants.
Validation and Utility:
Inspired by the trade management principles of Michael Lamothe, the " Danger Signals " indicator is more than just a tool; it's a reflection of tested strategies that highlight the importance of risk management. Through rigorous validation, including the insights from "The Trading Mindwheel," this indicator helps traders navigate the complexities of the market with an informed, strategic approach.
Whether you're contemplating a new position or evaluating an existing one, the " Danger Signals " indicator is designed to provide the clarity needed to avoid potential pitfalls and capitalize on opportunities with confidence. Embrace a smarter way to trade, where awareness and preparation open the door to success.
Let's dive into each of the components of this indicator.
Volume: Volume refers to the number of shares or contracts traded in a security or an entire market during a given period. It is a measure of the total trading activity and liquidity, indicating the overall interest in a stock or market.
Price Action: the analysis of historical prices to inform trading decisions, without the use of technical indicators. It focuses on the movement of prices to identify patterns, trends, and potential reversal points in the market.
Relative Strength Line: The RS line is a popular tool used to compare the performance of a stock, typically calculated as the ratio of the stock's price to a benchmark index's price. It helps identify outperformers and underperformers relative to the market or a specific sector. The RS value is calculated by dividing the close price of the chosen stock by the close price of the comparative symbol (SPX by default).
Average True Range (ATR): ATR is a market volatility indicator used to show the average range prices swing over a specified period. It is calculated by taking the moving average of the true ranges of a stock for a specific period. The true range for a period is the greatest of the following three values:
The difference between the current high and the current low.
The absolute value of the current high minus the previous close.
The absolute value of the current low minus the previous close.
Average Daily Range (ADR): ADR is a measure used in trading to capture the average range between the high and low prices of an asset over a specified number of past trading days. Unlike the Average True Range (ATR), which accounts for gaps in the price from one day to the next, the Average Daily Range focuses solely on the trading range within each day and averages it out.
Anchored VWAP: AVWAP gives the average price of an asset, weighted by volume, starting from a specific anchor point. This provides traders with a dynamic average price considering both price and volume from a specific start point, offering insights into the market's direction and potential support or resistance levels.
Moving Averages: Moving Averages smooth out price data by creating a constantly updated average price over a specific period of time. It helps traders identify trends by flattening out the fluctuations in price data.
Stochastic: A stochastic oscillator is a momentum indicator used in technical analysis that compares a particular closing price of an asset to a range of its prices over a certain period of time. The theory behind the stochastic oscillator is that in a market trending upwards, prices will tend to close near their high, and in a market trending downwards, prices close near their low.
While each of these components offer unique insights into market behavior, providing sell signals under specific conditions, the power of combining these different signals lies in their ability to confirm each other's signals. This in turn reduces false positives and provides a more reliable basis for trading decisions
These signals can be recognized at any time, however the indicators power is in it's ability to take into account where a trade is in terms of your entry price and stop.
If a trade just started, it hasn’t earned much leeway. Kind of like a new employee that shows up late on the first day of work. It’s less forgivable than say the person who has been there for a while, has done well, is on time, and then one day comes in late.
Contextual Sensitivity:
For instance, a high volume sell-off coupled with a bearish price action pattern significantly strengthens the sell signal. When the price closes below an Anchored VWAP or a critical moving average in this context, it reaffirms the bearish sentiment, suggesting that the momentum is likely to continue downwards.
By considering the relative strength line (RS) alongside volume and price action, the indicator can differentiate between a normal retracement in a strong uptrend and a when a stock starts to become a laggard.
The integration of ATR and ADR provides a dynamic framework that adjusts to the market's volatility. A sudden increase in ATR or a character change detected through comparing short-term and long-term ADR can alert traders to emerging trends or reversals.
The "Danger Signals" indicator exemplifies the power of integrating diverse technical indicators to create a more sophisticated, responsive, and adaptable trading tool. This approach not only amplifies the individual strengths of each indicator but also mitigates their weaknesses.
Portfolio Heat Indicator can be found by clicking on the image below
Danger Signals Included
Price Closes Near Low - Daily Closing Range of 30% or Less
Price Closes Near Weekly Low - Weekly Closing Range of 30% or Less
Price Closes Near Daily Low on Heavy Volume - Daily Closing Range of 30% or Less on Heaviest Volume of the Last 5 Days
Price Closes Near Weekly Low on Heavy Volume - Weekly Closing Range of 30% or Less on Heaviest Volume of the Last 5 Weeks
Price Closes Below Moving Average - Price Closes Below One of 5 Selected Moving Averages
Price Closes Below Swing Low - Price Closes Below Most Recent Swing Low
Price Closes Below 1.5 ATR - Price Closes Below Trailing ATR Stop Based on Highest High of Last 10 Days
Price Closes Below AVWAP - Price Closes Below Selected Anchored VWAP (Anchors include: High of base, Low of base, Highest volume of base, Custom date)
Price Shows Aggressive Selling - Current Bars High is Greater Than Previous Day's High and Closes Near the Lows on Heaviest Volume of the Last 5 Days
Outside Reversal Bar - Price Makes a New High and Closes Near the Lows, Lower Than the Previous Bar's Low
Price Shows Signs of Stalling - Heavy Volume with a Close of Less than 1%
3 Consecutive Days of Lower Lows - 3 Days of Lower Lows
Close Lower than 3 Previous Lows - Close is Less than 3 Previous Lows
Character Change - ADR of Last Shorter Length is Larger than ADR of Longer Length
Fast Stochastic Crosses Below Slow Stochastic - Fast Stochastic Crosses Below Slow Stochastic
Fast & Slow Stochastic Curved Down - Both Stochastic Lines Close Lower than Previous Day for 2 Consecutive Days
Lower Lows & Lower Highs Intraday - Lower High and Lower Low on 30 Minute Timeframe
Moving Average Crossunder - Selected MA Crosses Below Other Selected MA
RS Starts Curving Down - Relative Strength Line Closes Lower than Previous Day for 2 Consecutive Days
RS Turns Negative Short Term - RS Closes Below RS of 7 Days Ago
RS Underperforms Price - Relative Strength Line Not at Highs, While Price Is
Moving Average Begins to Flatten Out - First Day MA Doesn't Close Higher
Price Moves Higher on Lighter Volume - Price Makes a New High on Light Volume and 15 Day Average Volume is Less than 50 Day Average
Price Hits % Target - Price Moves Set % Higher from Entry Price
Price Hits R Multiple - Price hits (Entry - Stop Multiplied by Setting) and Added to Entry
Price Hits Overhead Resistance - Price Crosses a Swing High from a Monthly Timeframe Chart from at Least 1 Year Ago
Price Hits Fib Level - Price Crosses a Fib Extension Drawn From Base High to Low
Price Hits a Psychological Level - Price Crosses a Multiple of 0 or 5
Heavy Volume After Significant Move - Above Average and Heaviest Volume of the Last 5 Days 35 Bars or More from Breakout
Moving Averages Begin to Slope Downward - Moving Averages Fall for 2 Consecutive Days
Blow Off Action - Highest Volume, Largest Spread, Multiple Gaps in a Row 35 Bars or More Post Breakout
Late Buying Frenzy - ANTS 35 Bars or More Post Breakout
Exhaustion Gap - Gap Up 5% or Higher with Price 125% or More Above 200sma
Simple Position SizerSimple Position Sizer is designed to calculate optimal position sizes based on a defined risk percentage and stop-loss level. It offers two modes for determining position size: using the current close price or a specified entry price. The script provides key trade details such as entry price, stop-loss level, quantity to trade, total cost, and risk amount in monetary terms, alongside visual indications of these parameters through colored lines and labels on the chart. Users can customize account size, risk per trade percentage, and entry and stop-loss levels directly within the settings.
Usage Scenario:
A trader looking to enter a position would first decide whether the entry is based on the current closing price or a predetermined level. After setting the stop-loss level and specifying the risk per trade as a percentage of the account size, the script calculates the number of shares or contracts to purchase. It also computes the total cost of the position and displays the potential loss if the stop-loss is triggered, allowing the trader to understand the risk involved before entering the trade.
Visual Indicators:
Green indicators suggest a long setup where the entry level is above the stop-loss, indicating bullish entry.
Red indicators signal a short setup where the entry level is below the stop-loss, reflecting bearish entry
Blue lines represent the entry level when specified by the trader, providing a visual cue for planned entries.
Temporal Value Tracker: Inception-to-Present Inflation Lens!What we're looking at here is a chart that does more than just display the price of gold. It offers us a time-traveling perspective on value. The blue line, that's our nominal price—it's the straightforward market price of gold over time. But it's the red line that takes us on a deeper journey. This line adjusts the nominal price for inflation, showing us the real purchasing power of gold.
Now, when we talk about 'real value,' we're not just philosophizing. We're anchoring our prices to a point in time when the journey began—let's say when gold trading started on the markets, or any inception point we choose. By 'shadowing' certain years—say, from the 1970s when the gold standard was abandoned—we can adjust this chart to reflect what the inflation-adjusted price means since that key moment in history.
By doing so, we're effectively isolating our view to start from that pivotal year, giving us insight into how gold, or indeed any asset, has held up against the backdrop of economic changes, policy shifts, and the inevitable rise in the cost of living. If you're analyzing a stock index like the S&P 500, you might begin your inflation-adjusted view from the index's inception date, which allows you to measure the true growth of the market basket from the moment it started.
This adjustment isn't just academic. It influences how we perceive value and growth. Consider a period where the nominal price skyrockets. We might toast to our brilliance in investment! But if the inflation-adjusted line lags, what we're seeing is nominal growth without real gains. On the other hand, if our red line outpaces the blue even during stagnant market periods, we're witnessing real growth—our asset is outperforming the eroding effects of inflation.
Every asset class can be evaluated this way. Stocks, bonds, real estate—they all have their historical narratives, and inflation adjustment tells us if these stories are tales of genuine growth or illusions masked by inflation.
So, as informed traders and investors, we need to keep our eyes on this inflation-adjusted line. It's our measure against the silent thief that is inflation. It ensures we're not just keeping up with the Joneses of the market, but actually outpacing them, building real wealth over time
[S1B] Leverage Take-Profit-LinesShort Description:
The Leverage Take-Profit-Lines indicator assists traders in setting take-profit and stop-loss levels based on leverage, entry price, and risk percentage. It draws horizontal lines representing various take-profit levels and the stop-loss level on the chart, aiding traders in visually identifying potential exit points and managing risk.
Detailed Description:
The Leverage Take-Profit-Lines indicator is designed to provide traders with a visual representation of take-profit and stop-loss levels tailored to their leverage, entry price, and risk preferences.
Key Features:
Customizable Parameters: Traders can adjust parameters such as leverage, entry price, risk percentage, and whether to extend lines to suit their trading strategy.
Take-Profit Levels: The indicator calculates and draws horizontal lines representing different take-profit levels based on the specified percentage of leverage-adjusted entry price.
Stop-Loss Level: It calculates and displays the stop-loss level based on the specified risk percentage and leverage, helping traders manage risk effectively.
Visual Representation: The indicator visually highlights take-profit and stop-loss levels on the chart, facilitating quick decision-making for traders.
Usage Guide:
Setting Parameters: Adjust the input parameters including leverage, entry price, risk percentage, and other settings according to your trading strategy.
Interpreting Lines: Horizontal lines are drawn on the chart representing take-profit levels (TP1, TP2, TP3, TP4) and the stop-loss level. These lines indicate potential exit points and risk management levels.
As an example the TP1 can be used to sell 10% of position size, TP2 20%, TP3 20% and TP4 20-40%.
The Leverage Take-Profit-Lines indicator empowers traders with valuable insights into setting profit targets and managing risk effectively, contributing to more informed trading decisions.
Historical Correlation [LuxAlgo]The Historical Correlation tool aims to provide the historical correlation coefficients of up to 10 pairs of user-defined tickers starting from a user-defined point in time.
Users can choose to display the historical values as lines or the most recent correlation values as a heat map.
🔶 USAGE
This tool provides historical correlation coefficients, the correlation coefficient between two assets highlight their linear relationship and is always within the range (-1, 1).
It is a simple and easy to use statistical tool, with the following interpretation:
Positive correlation (values close to +1.0): the two assets move in sync, they rise and fall at the same time.
Negative correlation (values close to -1.0): the two assets move in opposite directions: when one goes up, the other goes down and vice versa.
No correlation (values close to 0): the two assets move independently.
The user must confirm the selection of the anchor point in order for the tool to be executed; this can be done directly on the chart by clicking on any bar, or via the date field in the settings panel.
For the parameter Anchor period , the user can choose between the following values NONE, HOURLY, DAILY, WEEKLY, MONTHLY, QUARTERLY and YEARLY. If NONE is selected, there will be no resetting of the calculations, otherwise the calculations will start from the first bar of the new period.
There is a wide range of trading strategies that make use of correlation coefficients between assets, some examples are:
Pair Trading: Traders may wish to take advantage of divergences in the price movements of highly positively correlated assets; even highly positively correlated assets do not always move in the same direction; when assets with a correlation close to +1.0 diverge in their behavior, traders may see this as an opportunity to buy one and sell the other in the expectation that the assets will return to the likely same price behavior.
Sector rotation: Traders may want to favor some sectors that are expected to perform in the next cycle, tracking the correlation between different sectors and between the sector and the overall market.
Diversification: Traders can aim to have a diversified portfolio of uncorrelated assets. From a risk management perspective, it is useful to know the correlation between the assets in your portfolio, if you hold equal positions in positively correlated assets, your risk is tilted in the same direction, so if the assets move against you, your risk is doubled. You can avoid this increased risk by choosing uncorrelated assets so that they move independently.
Hedging: Traders may want to hedge positions with correlated assets, from a hedging perspective, if you are long an asset, you can hedge going long a negative correlated asset or going short a positive correlated asset.
Traders generally need to develop awareness, a key point is to be aware of the relationships between the assets we hold or trade, the historical correlation is an invaluable tool in our arsenal which allows us to make better informed decisions.
On this chart we have an example of historical correlations for several futures markets.
We can clearly see how positively correlated the Nasdaq100 and Dow30 are with the SP500 over the whole period, or how the correlation between the Euro and the SP500 falls from almost +85% to almost -4% since 2021.
As we can see, correlations, like everything else in the market, are not static and vary over time depending on many factors, from macro to technical and everything in between.
🔹 Heatmap
The chart above shows the tool with the default settings and the Drawing Mode set to 'HEATMAP'.
We can see the current correlation between the assets, in this case the FX pairs.
The highest positive correlation is +90% (+0.90) between EURUSD and GBPUSD.
The highest negative correlation is -78% (-0.78) between EURUSD and USDJPY.
The pair with no correlation is AUDUSD and EURCAD with 1% (0.01)
On the above chart we can see the current correlations for the futures markets.
Currently, the assets that are less correlated to the SP500 are NaturalGas and the Euro, the more positive correlations are Nasdaq100 and Dow20, and the more negative correlations are the Yen, Treasury Bonds and 10-Year Notes.
🔶 DETAILS
🔹 Anchor Period
This chart shows the standard FX correlations with the Anchor Period set to `MONTHLY`.
We can clearly see how the calculations restart with the new month, in this case we can clearly see the differences between the correlations from month to month.
Let us look at the correlation coefficient between GBPUSD and USDJPY
In January, their correlation started at close to -100%, rose to close to +50%, only to fall to close to 0% and remain there for the second half of the month.
In February it was -90% in the first few days of the month and is now around -57%.
And between AUDUSD and EURCAD
Last month their correlation was negative for most of the month, reaching -70% and ending around -14%.
This month their correlation has never gone below +21% and at the time of writing is close to +53%.
🔶 SETTINGS
Anchor point: Starting point from which the tool is executed
Anchor period: At the beginning of each new period, the tool will reset the calculations
Pairs from 1 to 10: For each pair of tickers, you can: enable/disable the pair, select the color and specify the two tickers from which you wish to obtain the correlation
🔹 Style
Drawing Mode: Output style, `LINES` will show the historical correlations as lines, `HEATMAP` will show the current correlations with a color gradient from green for correlations near 1 to red for correlations near -1.
Power OutageThe Power Outage indicator serves as the antithesis to the Power Trend, highlighting periods of extreme weakness or downtrends. Drawing inspiration from the Power Trend, the Power Outage framework was conceived by reversing the logic to highlight periods where being in cash or net short could be beneficial.
What Initiates a Power Outage?
The high is below the 21-day EMA for at least 10 consecutive days.
The 21-day EMA is below the 50-day SMA for a minimum of five days.
The 50-day SMA is on a downward trajectory.
The closing price is lower than the previous day's close.
A Power Outage can be a caution sign for traders to tighten up risk management and encourage defensive strategies or the consideration of short positions. Not only does this indicator clearly identify a Power Outage by a shaded background or shape plotted on the chart, but it also records metrics for each previous Power Outage.
The number of Power Outages that have occurred, their average length, and average depth (from the first day's close when the Power Outage activates to the low of the Power Outage) are all displayed to help assess the condition of the current Power Outage.
What Ends a Power Outage?
A Power Outage ends when the 21-day EMA crosses above the 50-day SMA, or when the price closes 10% above the recent low and above the 50-day SMA.
This indicator is designed to be viewed on a daily time frame.
Index investingThe Index Investing indicator simplifies decision-making for adding to Index ETF's Long-term investments. By utilizing a percentage discount methodology, it highlights potential opportunities to enhance portfolios. This straightforward tool aids in identifying favorable moments to invest based on calculated price discounts from selected reference points, making the process more systematic and less subjective.
🔶 SETTINGS
Reference Price: Choose between 'All-Time-High' or 'Start of the Year' as the basis for calculating discount levels. This allows for flexibility in strategy depending on market conditions or investment philosophy.
Discount 1 %, Discount 2 %, Discount 3 %: These inputs define the percentage below the reference price at which buy signals are generated. They represent strategic entry points at discounted prices.
🔶 Default Parameters
The default parameters of 4.13%, 8.26%, and 12.39% for the discount levels are chosen based on the average 5-year return of the NSE:NIFTY Index, which stands at approximately 12.39%. By dividing this return into three parts, we obtain a structured approach to capturing potential upside at varying levels of market retracement, providing a logical basis for the selected default values.
Users have the flexibility to modify these parameters, tailoring the indicator to fit their unique approach and market outlook.
🔶 How Levels Are Calculated
Discount levels are calculated using the formula: Discount Price = Reference Price * (1 - Discount %) . This succinct approach establishes specific entry points below the chosen reference, such as an all-time high or the year's start price.
🔶 How Are the Buy Labels Generated
Buy signals are generated when the market price(Low of the candle) crosses under any of the defined discount levels. Each level has a corresponding buy label ('Buy 1', 'Buy 2', 'Buy 3'), which is activated upon the price crossing below the specified discount level and is only reset at the beginning of a new year or upon reaching a new reference high, ensuring signals are not repetitive for the same price level.
🔶 Other Features
Alerts: The indicator provides alerts for each buy signal, notifying potential entry points at their defined discount levels. The alert triggers only once per candle.
Year Marker: A vertical line with an accompanying label marks the start of each trading year on the chart. This feature aids in visualizing the temporal context of buy signals and reference price adjustments.
Position Size CalculatorThe provided Pine Script is a custom indicator titled "Position Size Calculator" designed to assist traders in calculating the appropriate size of a trading position based on predefined risk parameters. This script is intended to be overlaid on a trading chart, as indicated by `overlay=true`, allowing traders to visualize and adjust their risk and position size directly within the context of their trading strategy.
What It Does:
The core functionality of this script revolves around calculating the position size a trader should take based on three input parameters:
**Risk in USD (`Risk`)**: This represents the amount of money the trader is willing to risk on a single trade.
**Entry Price (`EntryPrice`)**: The price at which the trader plans to enter the market.
**Stop Loss (`StopLoss`)**: The price at which the trader plans to exit the market should the trade move against them, effectively limiting their loss.
The script calculates the position size using a function named `calculatePositionSize`, which performs the following steps:
It first calculates the `expectedLoss` by taking 90% (`0.9`) of the input risk. This implies that the script factors in a safety margin, assuming traders are willing to risk up to 90% of their stated risk amount per trade.
It then calculates the position size based on the distance between the Entry Price and the Stop Loss. This calculation adjusts based on whether the Entry Price is higher or lower than the Stop Loss, ensuring that the position size fits the risk profile regardless of trade direction.
The function returns several values: `risk`, `entryPrice`, `stopLoss`, `expectedLoss`, and `size`, which are then plotted on the chart.
How It Does It:
**Expected Loss Calculation**: By reducing the risk by 10% before calculating position size, the script provides a buffer to account for slippage or to ensure the trader does not fully utilize their risk budget on a single trade.
**Position Size Calculation**: The script calculates position size by dividing the adjusted risk (`expectedLoss`) by the price difference between the Entry Price and Stop Loss. This gives a quantitative measure of how many units of the asset can be bought or sold while staying within the risk parameters.
What Traders Can Use It For:
Traders can use this Position Size Calculator for several purposes:
- **Risk Management**: By determining the appropriate position size, traders can ensure that they do not overexpose themselves to market risk on a single trade.
- **Trade Planning**: Before entering a trade, the script allows traders to visualize their risk, entry, and exit points, helping them to make more informed decisions.
- **Consistency**: Using a standardized method for calculating position size helps traders maintain consistency in their trading approach, a key aspect of successful trading strategies.
- **Efficiency**: Automating the calculation of position size saves time and reduces the likelihood of manual calculation errors.
Overall, this Pine Script indicator is a practical tool for traders looking to implement strict risk management rules within their trading strategies, ensuring that each trade is sized appropriately according to their risk tolerance and market conditions.
ABC System [KFB Qaunt]ABC System
The ABC System provides insights into asset performance relative to a benchmark, incorporating metrics such as Alpha, Beta, and Correlation.
Functionality:
The script calculates
Alpha: Indicates an asset's risk-adjusted return compared to a benchmark.
Beta: Measures an asset's volatility compared to a benchmark.
Correlation: Determines the relationship between an asset and a benchmark.
Coloring & Criteria
Based on these metrics and criteria, the script generates signals indicating potential trading opportunities.
Input Setup
Inside the indicators settings you can configure parameters such as the
Benchmark Symbol
Risk-Free Rate
Lengths for Alpha, Beta & Correlation
Visualization Options
Criteria for Beta & Correlation.
The information created and published by me on TradingView is not prohibited, doesn't constitute investment advice, and isn't created solely for qualified investors
Risk Management Chart█ OVERVIEW
Risk Management Chart allows you to calculate and visualize equity and risk depend on your risk-reward statistics which you can set at the settings.
This script generates random trades and variants of each trade based on your settings of win/loss percent and shows it on the chart as different polyline and also shows thick line which is average of all trades.
It allows you to visualize and possible to analyze probability of your risk management. Be using different settings you can adjust and change your risk management for better profit in future.
It uses compound interest for each trade.
Each variant of trade is shown as a polyline with color from gradient depended on it last profit.
Also I made blurred lines for better visualization with function :
poly(_arr, _col, _t, _tr) =>
for t = 1 to _t
polyline.new(_arr, false, false, xloc.bar_index, color.new(_col, 0 + t * _tr), line_width = t)
█ HOW TO USE
Just add it to the cart and expand the window.
█ SETTINGS
Start Equity $ - Amount of money to start with (your equity for trades)
Win Probability % - Percent of your win / loss trades
Risk/Reward Ratio - How many profit you will get for each risk(depends on risk per trade %)
Number of Trades - How many trades will be generated for each variant of random trading
Number of variants(lines) - How many variants will be generated for each trade
Risk per Trade % -risk % of current equity for each trade
If you have any ask it at comments.
Hope it will be useful.
Show PositionBasic script that represents your position on the chart as a line along with your position size, price, change in price, and P&L.
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!
US Yield Curve ComparisonIn finance, the yield curve is a graph which depicts how the yields on debt instruments – such as bonds – vary as a function of their years remaining to maturity. The graph's horizontal or x-axis is a time line of months and years remaining to maturity, with the shortest maturity on the left and progressively longer time periods on the right. The vertical or y-axis depicts the annualized yield to maturity.
To see changes of a definded timeframe, use this indicator to compare the current US yield curve with one in the past.
Rate of Change MachineRate of Change Machine
Author: RWCS_LTD
Disclaimer: This script is provided for informational purposes only and should not be considered financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct your own research and consult with a qualified financial advisor before making any investment decisions.
Introduction:
The Rate of Change Machine is a script designed to assist traders in analyzing multiple cryptocurrency trading pairs simultaneously. This comprehensive indicator offers a holistic view of the rate of change and related metrics, aiding traders in making informed decisions.
Asset Selection:
The script enables users to select up to nine different cryptocurrency trading pairs for in-depth analysis.
Volume Calculation:
Volume plays a crucial role in the analysis, with customizable parameters for volume weighting and length.
Relative Strength Calculation:
Relative Strength is determined through two Exponential Moving Averages (EMA) with user-defined lengths.
Timeframe Weightings:
Different timeframes (1D, AVG 3D, AVG 5D, AVG 7D, AVG 14D, AVG 30D) are assigned weightings to calculate a comprehensive trend score.
Weighted Average and Individual Rate of Change (RoC) Calculation:
The getWeightedAvgAndIndividualROC function calculates the RoC for each selected trading pair based on the given timeframes and weights.
Table Setup:
A table is created to display the results for each trading pair, including relative strength, volume trend, RoC for different timeframes, and a weighted trend score.
Table Formatting:
The table is formatted with different colors indicating positive or negative values for easier interpretation.
Table Position and Size:
Users can customize the position and size of the table on the chart.
Data Retrieval:
The script retrieves the calculated values for each trading pair using the request.security function.
Output:
The final output is a table on the chart, showing relevant information for the selected trading pairs, aiding traders in making informed decisions based on the rate of change and other factors. This indicator provides a comprehensive view of the rate of change and related metrics for multiple trading pairs, assisting traders in identifying potential trends and making informed trading decisions.
BetaBeta , also known as the Beta coefficient, is a measure that compares the volatility of an individual underlying or portfolio to the volatility of the entire market, typically represented by a market index like the S&P 500 or an investible product such as the SPY ETF (SPDR S&P 500 ETF Trust). A Beta value provides insight into how an asset's returns are expected to respond to market swings.
Interpretation of Beta Values
Beta = 1: The asset's volatility is in line with the market. If the market rises or falls, the asset is expected to move correspondingly.
Beta > 1: The asset is more volatile than the market. If the market rises or falls, the asset's price is expected to rise or fall more significantly.
Beta < 1 but > 0: The asset is less volatile than the market. It still moves in the same direction as the market but with less magnitude.
Beta = 0: The asset's returns are not correlated with the market's returns.
Beta < 0: The asset moves in the opposite direction to the market.
Example
A beta of 1.20 relative to the S&P 500 Index or SPY implies that if the S&P's return increases by 1%, the portfolio is expected to increase by 12.0%.
A beta of -0.10 relative to the S&P 500 Index or SPY implies that if the S&P's return increases by 1%, the portfolio is expected to decrease by 0.1%. In practical terms, this implies that the portfolio is expected to be predominantly 'market neutral' .
Calculation & Default Values
The Beta of an asset is calculated by dividing the covariance of the asset's returns with the market's returns by the variance of the market's returns over a certain period (standard period: 1 years, 250 trading days). Hint: It's noteworthy to mention that Beta can also be derived through linear regression analysis, although this technique is not employed in this Beta Indicator.
Formula: Beta = Covariance(Asset Returns, Market Returns) / Variance(Market Returns)
Reference Market: Essentially any reference market index or product can be used. The default reference is the SPY (SPDR S&P 500 ETF Trust), primarily due to its investable nature and broad representation of the market. However, it's crucial to note that Beta can also be calculated by comparing specific underlyings, such as two different stocks or commodities, instead of comparing an asset to the broader market. This flexibility allows for a more tailored analysis of volatility and correlation, depending on the user's specific trading or investment focus.
Look-back Period: The standard look-back period is typically 1-5 years (250-1250 trading days), but this can be adjusted based on the user's preference and the specifics of the trading strategy. For robust estimations, use at least 250 trading days.
Option Delta: An optional feature in the Beta Indicator is the ability to select a specific Delta value if options are written on the underlying asset with Deltas less than 1, providing an estimation of the beta-weighted delta of the position. It involves multiplying the beta of the underlying asset by the delta of the option. This addition allows for a more precise assessment of the underlying asset's correspondence with the overall market in case you are an options trader. The default Delta value is set to 1, representing scenarios where no options on the underlying asset are being analyzed. This default setting aligns with analyzing the direct relationship between the asset itself and the market, without the layer of complexity introduced by options.
Calculation: Simple or Log Returns: In the calculation of Beta, users have the option to choose between using simple returns or log returns for both the asset and the market. The default setting is 'Simple Returns'.
Advantages of Using Beta
Risk Management: Beta provides a clear metric for understanding and managing the risk of a portfolio in relation to market movements.
Portfolio Diversification: By knowing the beta of various assets, investors can create a balanced portfolio that aligns with their risk tolerance and investment goals.
Performance Benchmarking: Beta allows investors to compare an asset's risk-adjusted performance against the market or other benchmarks.
Beta-Weighted Deltas for Options Traders
For options traders, understanding the beta-weighted delta is crucial. It involves multiplying the beta of the underlying asset by the delta of the option. This provides a more nuanced view of the option's risk relative to the overall market. However, it's important to note that the delta of an option is dynamic, changing with the asset's price, time to expiration, and other factors.
Portfolio Management [TrendX_]Portfolio Management is a powerful tool that helps you create and manage your own portfolio of stocks, based on your risk and return preferences.
*** Note: You should select the appropriate index for each stock as the benchmark to compare your portfolio’s performance.
*** Note: You should apply the indicator to the same chart as the benchmark, so that it can capture the historical trends of all the 10 stocks in your portfolio.
USAGE
Analyze your portfolio’s return factor, which shows the compound annual growth rate (CAGR) of each stock and the portfolio as a whole, as well as the weight of each stock in the portfolio.
The Weighting approach contains 2 options, Equal and Growth-based method:
Customize your portfolio by selecting up to 10 stocks from a wide range of markets and sectors:
Compare your portfolio’s performance with a benchmark of your choice, which is the S&P500 by default setting.
Evaluate your portfolio’s risk factor, which includes the capital asset pricing model (CAPM), the portfolio beta, and the Sharpe ratio of both the portfolio and the benchmark:
- CAPM is a model that calculates the expected return of the portfolio based on its risk and the risk-free rate of return.
- Portfolio beta is a measure of how sensitive the portfolio is to the movements of the benchmark. A beta of 1 means the portfolio moves in sync with the benchmark, a beta of less than 1 means the portfolio is less volatile than the benchmark, and a beta of more than 1 means the portfolio is more volatile than the benchmark.
- Sharpe ratio measures how much excess return the portfolio generates per unit of risk. It is calculated by subtracting the risk-free rate of return from the portfolio’s return, and dividing by the portfolio’s standard deviation. A higher Sharpe ratio means the portfolio has a better risk-adjusted return. A Sharpe ratio of more than 1 is considered good, a Sharpe ratio of more than 2 is considered very good, and a Sharpe ratio of more than 3 is considered excellent .
Adjust your portfolio’s rebalancing strategy, which determines when and how to change the weight of each stock in the portfolio to optimize your return and risk objectives. The tool also suggests a default hedging-stock asset, which is the US dollar interpreted through the dollar index (DXY):
- The dollar index is a measure of the value of the US dollar relative to a basket of other major currencies. It is often used as a proxy for the global economic sentiment and the demand for safe-haven assets. A rising dollar index means the US dollar is strengthening, which may indicate a bearish outlook for the stock market. A falling dollar index means the US dollar is weakening, which may indicate a bullish outlook for the stock market.
- The rebalancing strategy suggest increasing the weight of the hedging-stock asset when the dollar index is under positive supertrend condition, and decreasing the weight of the hedging-stock asset when the dollar index is in the downward supertrend. This way, you can hedge against the adverse effects of the stock market fluctuations on your portfolio, simply you can just cash out at the suggested hedging weight.
CONCLUSION
Investors can gain a deeper insight into their portfolio’s performance, risk, and potential, and make informed decisions to achieve their financial goals with confidence and ease.
DISCLAIMER
The results achieved in the past are not all reliable sources of what will happen in the future. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
Therefore, you should always exercise caution and judgment when making decisions based on past performance.
Kaufman Efficiency Ratio-Based Risk PercentageOVERVIEW
The Kaufman Efficiency Ratio-Based Exposure Management indicator uses the Kaufman Efficiency Ratio (KER) to calculate how much you should risk per trade.
If KER is high, then the indicator will tell you to risk more per trade.
A high KER value indicates a trending market, so if you are a trend trader, it makes sense to risk more during these times.
If KER is low, then the indicator will tell you to risk less per trade.
A low KER value indicates a trending market, so if you are a trend trader, it makes sense to risk less during these times.
CONCEPTS
The Kaufman Efficiency Ratio (also known as the Efficiency Ratio, KER, or ER) is a separate indicator developed by Perry J. Kaufman and first published in Kaufman's book, "New Trading Systems and Methods" in 1987.
The KER used to measure the efficiency of a financial instrument's price movement. It is calculated as follows:
KER = (change in price over x bars) / (sum of absolute price changes over x bars)
The first part of the formula, "change in price over x bars" measures the difference between the current close price and the close price x bars ago. The second part of the formula "sum of absolute price changes over x bars" measures the sum of the |open-close| range of each bar between now and x bars ago.
If there is a high change in price over x bars relative to the sum of absolute price changes over x bars, a trending/volatile market is likely in place.
If there is a low change in price over x bars relative to the sum of absolute price changes over x bars, a ranging/choppy market is likely in place.
If you are a trend trader, you can assume that entries taken during high KER periods are more likely to lead to a trend. This indicator helps capitalize on that assumption by increasing risk % per trade during high KER periods, and decreasing risk % per trade during low KER periods.
It uses the following formulas to calculate a KER-adjusted risk % per trade:
Linearly-increasing risk % = min risk + (KER * (max risk - min risk))
Exponentially-increasing risk % = min risk + ((KER^n) * (max risk - min risk))
min risk = the smallest amount you'd be willing to risk on a trade
max risk = the largest amount you'd be willing to risk on a trade
KER = the current Kaufman Efficiency Ratio value
n = an exponent factor used to control the rate of increase of the risk %
Here is an example of how these formulas work:
Assuming that min risk is 0.5%, max risk is 2%, and KER is 0.8 (indicating a trending market), we can calculate the following risk per trade amounts:
Linearly-increasing risk % = 0.5 + (0.8 * (2 - 0.5)) = 1.7%
Exponentially-increasing risk % = 0.5 + ((0.8^3) * (2 - 0.5)) = 1.27%
Now, lets do the same calculations with a lower KER of 0.2 , which indicates a choppy market:
Linearly-increasing risk % = 0.5 + (0.2 * (2 - 0.5)) = 0.8%
Exponentially-increasing risk % = 0.5 + ((0.2^3) * (2 - 0.5)) = 0.51%
With a high KER, we risk more per trade to capitalize on the higher chance of a trending market. With a lower KER, we risk less per trade to protect ourselves from the higher chance of a choppy market.
Normalized Global Net Liquidity + HMA Smoothed RoCThis script calculates "Global Net Liquidity" using various financial data sources, and integrates Rate of Change (RoC) visualization alongside an Equity Hull Moving Average (HMA) plot. It also features an additional "Global Liquidity" metric that is subsequently scaled and plotted.
First, several financial indicators are requested and combined to form the "Global Net Liquidity Indicator." A Rate of Change (RoC) is then calculated, and this RoC, alongside the Equity Hull Moving Average (HMA), is plotted. Next, a "Global Liquidity" measure is formed by combining various financial data.
In summary, this script involves achieving a comprehensive visualization of liquidity-related indicators and measures, providing an inclusive outlook into the nature of global liquidity trends.
The main plot is the 3 liquidity metrics averaged together and normalized then scaled between -1 and 1 for TPI scoring.
You can customize the weighting for each metric, as well as the lookback period for all 3 metrics.
-1 = Negative Trend
1 = Positive Trend
Yellow = Global Net Liquidity
Blue = RoC
Red = Equity HMA
This is insight into global liquidity, and not to be taken in anyway as trading signals. This is an analysis tool to be combined with further research.
Hodl Calculation v1.0I have developed an indicator that calculates the value of our currency if we had periodically bought any stock or cryptocurrency on any exchange. I believe many individuals would be interested in computing such values.
You can customize the start and end times, choose the amount of currency to be used for each deal, and select from two frequency options.
The first option involves specific intervals, such as hourly, every three days, or bi-weekly.
The second option allows purchases at specific dates or times, like every 15th of the month at 12:00 PM, every Monday at 11:00 AM, or every day at 6:00 AM.
After selecting the frequency, the indicator performs calculations and presents statistical information in a table.
The summarized data includes frequency value, total selected period duration, number of deals, total quantity, total cost, current value, and profit/loss status.
Buy and hold visualiserThis indicator shows the historical performance of a buy and hold portfolio. The purpose of the indicator is to show
1. the effect of the hold time (time between buying and selling a number of instruments) and
2. the effect of investing all capital at once (lump sum) versus dividing the investment over a number of months or years (cost averaging).
The indicator shows four lines:
- a dotted line at 0 (dollar or any other currency),
- a dotted line at the level of initial investment,
- a blue line that shows the amount of capital after selling at the end of the investment period after a lump sum investment,
- a green line that shows the amount of capital after selling at the end of the investment period after an investment that was done in chunks (cost averaging)
When 'chunks' is set to 1, the green line will match the blue line.
When 'investment' is set to 1, the blue and green lines will show the factor by which the initial investment was multiplied at the end of the investment period.
The effect of the hold time can be easily seen in the following example: Choose SPX (CBOE) as the active instrument, set 'chunks' to 1 and 'months' to 12. Depending on when you bought your portfolio, selling it a year later is like tossing a coin. Set 'months' to 360 and it becomes clear that it doesn't matter when you buy, the value of your portfolio will likely multiply considerably in 30 years, even if you bought everything all at once just before a bear market. It shows that with a long time horizon, you don't have to worry about timing the market.
Continue the example above and set 'chunks' to 12, thus spreading the initial investment over 12 months. The green line shows the cost averaging performance. The blue lump sum line is above the green line most of the time. Increase the chunks to 60 and the difference increases.
Modern Portfolio TheoryModern Portfolio Theory
The indicator is designed to apply the principles of Modern Portfolio Theory, a financial theory developed by Harry Markowitz. MPT aims to maximize portfolio returns for a given level of risk by diversifying investments.
User Inputs:
Users can customize various parameters, including the bar scale, risk-free rate, and the start year for the portfolio. Additionally, users can assign weights to different assets (symbols) in the portfolio.
Asset Selection:
Users can choose up to 10 different symbols (assets) for the portfolio. The script supports a variety of symbols, including cryptocurrencies such as BTCUSD and ETHUSD.
Weights and Allocation:
Users can assign weights to each selected asset, determining its percentage allocation in the portfolio. The script calculates the total portfolio weight to ensure it equals 100%. If total portfolio weight is lower then 100% you will see orange color with additional cash % bellow
If total portfolio weight is bigger then 100% you will see red big % warning.
Warning: (Total Weight must be 100%)
Cash Mode:
Risk and Return Calculation:
The script calculates the daily returns and standard deviation for each selected asset. These metrics are essential for assessing the risk and return of each asset, as well as the overall portfolio.
Scatter Plot Visualization:
The indicator includes a scatter plot that visualizes the risk-return profile of each asset. Each point on the plot represents an asset, and its position is determined by its risk (X-axis) and return (Y-axis).
Portfolio Optimization:
The script calculates the risk and return of the overall portfolio based on the selected assets and their weights. Based on the selected assets and their weights user can create optimal portfolio with preferable risk and return.
It then plots the portfolio point on the scatter plot, indicating its risk-return profile.
Additional Information:
The indicator provides a table displaying information about each selected asset, including its symbol, weight, and total portfolio weight. The table also shows the total portfolio weight and, if applicable, the percentage allocated to cash.
Visualization and Legend:
The script includes visual elements such as a legend, capital allocation line (CAL), and labels for risk-free rate and key information. This enhances the overall understanding of the portfolio's risk and return characteristics.
User Guidance:
The script provides informative labels and comments to guide users through the interpretation of the scatter plot, risk-return axes, and other key elements.
Interactivity:
Users can interact with the indicator on the TradingView platform, exploring different asset combinations and weightings to observe the resulting changes in the portfolio's risk and return.
In summary, this Pine Script serves as a comprehensive tool for traders and investors interested in applying Modern Portfolio Theory principles to optimize their portfolio allocations based on individual asset characteristics, risk preferences, and return
Annualized ReturnThis is a straightforward tool for investors, offering the capability to select a specific start date and visualize the annualized return of the currently displayed asset.
Annualized return is a crucial metric for investors, as it provides a standardized measure of an investment's performance, making it easier to compare different investments. By annualizing returns, investors can gain insights into the average yearly growth rate of their investments, enabling more informed decision-making and portfolio management .
Selecting various start dates enables users to understand how market timing can influence the success of their investments.
The annualized return is calculated using the following formula :
AnnualizedReturn = (Ending price / Beginning price) ^ (1 / Number of Years) − 1
