Easy To Trade indicatorAbstract
This script evaluates how easy for traders to trade.
This script computes the level that the gains were distributed in many trading days.
We can use this indicator to decide the instruments and the time we trade.
Introduction
Why we think the trading markets are boring?
It is because most of the gains were concentrated in a few trading days.
We look for instruments we can buy at support and sell at resistance frequently and repeatedly.
However, it does not happen usually because it is difficult to find sellers sell at support and buyers buy at resistance.
This script is a method to measure if an instrument is difficult to trade.
If most of the gains were concentrated in a few trading days, this script says it is difficult to trade.
If gains were distributed in many trading days and we can buy low and sell high repeatedly, this script says it is easy to trade.
Therefore, this script measure how difficult for us to trade by the ratio between the area of value and the total gain.
How it works
1. Determine the instruments and time frames we are interested in.
2. Determine how many days this script evaluate the result. This number may depend on how many days from you buy in to you sell out.
3. If the instrument you choose is easy to trade, this script reports higher values.
4. If the instrument is long term bullish, the number "easy to invest" is usually higher than the number "easy to short" .
5. We can consider trade instruments which are easier to trade than others.
6. We can consider wait until the period that it is difficult to trade has past or keep believing that some instruments are easier to trade than others.
Parameters
x_src = The price for each trading day this script use. It may be open , high , low , close or their combination.
x_is_exp = Whether this script evaluate the price movement in exponential or logarithm. You are advised to answer yes if the price changes drastically.
x_period = How many days this script evaluate the result.
Conclusion
With this indicator , we have data to explain how easy or difficult an instrument is for traders . In other words , if we hear some people say the trading markets are boring or difficult for traders , we can use this indicator to verify how accurate their comments are.
With this explainable analysis , we have more knowledge about which instruments and which sessions are relative easy for us to buy low and sell high repeatedly and frequently , we can have better proceeding than buy and hold simply.
볼래틸리티
Liquidity Price Depth Chart [LuxAlgo]The Liquidity Price Depth Chart is a unique indicator inspired by the visual representation of order book depth charts, highlighting sorted prices from bullish and bearish candles located on the chart's visible range, as well as their degree of liquidity.
Note that changing the chart's visible range will recalculate the indicator.
🔶 USAGE
The indicator can be used to visualize sorted bullish/bearish prices (in descending order), with bullish prices being highlighted on the left side of the chart, and bearish prices on the right. Prices are highlighted by dots, and connected by a line.
The displacement of a line relative to the x-axis is an indicator of liquidity, with a higher displacement highlighting prices with more volume.
These can also be easily identified by only keeping the dots, visible voids can be indicative of a price associated with significant volume or of a large price movement if the displacement is more visible for the price axis. These areas could play a key role in future trends.
Additionally, the location of the bullish/bearish prices with the highest volume is highlighted with dotted lines, with the returned horizontal lines being useful as potential support/resistances.
🔹 Liquidity Clusters
Clusters of liquidity can be spotted when the Liquidity Price Depth Chart exhibits more rectangular shapes rather than "V" shapes.
The steepest segments of the shape represent periods of non-stationarity/high volatility, while zones with clustered prices highlight zones of potential liquidity clusters, that is zones where traders accumulate positions.
🔹 Liquidity Sentiment
At the bottom of each area, a percentage can be visible. This percentage aims to indicate if the traded volume is more often associated with bullish or bearish price variations.
In the chart above we can see that bullish price variations make 63.89% of the total volume in the range visible range.
🔶 SETTINGS
🔹 Bullish Elements
Bullish Price Highest Volume Location: Shows the location of the bullish price variation with the highest associated volume using one horizontal and one vertical line.
Bullish Volume %: Displays the bullish volume percentage at the bottom of the depth chart.
🔹 Bearish Elements
Bearish Price Highest Volume Location: Shows the location of the bearish price variation with the highest associated volume using one horizontal and one vertical line.
Bearish Volume %: Displays the bearish volume percentage at the bottom of the depth chart.
🔹 Misc
Volume % Box Padding: Width of the volume % boxes at the bottom of the Liquidity Price Depth Chart as a percentage of the chart visible range
Bollinger Bands StrategyBollinger Bands Strategy :
INTRODUCTION :
This strategy is based on the famous Bollinger Bands. These are constructed using a standard moving average (SMA) and the standard deviation of past prices. The theory goes that 90% of the time, the price is contained between these two bands. If it were to break out, this would mean either a reversal or a continuation. However, when a reversal occurs, the movement is weak, whereas when a continuation occurs, the movement is substantial and profits can be interesting. We're going to use BB to take advantage of this strong upcoming movement, while managing our risks reasonably. There's also a money management method for reinvesting part of the profits or reducing the size of orders in the event of substantial losses.
BOLLINGER BANDS :
The construction of Bollinger bands is straightforward. First, plot the SMA of the price, with a length specified by the user. Then calculate the standard deviation to measure price dispersion in relation to the mean, using this formula :
stdv = (((P1 - avg)^2 + (P2 - avg)^2 + ... + (Pn - avg)^2) / n)^1/2
To plot the two Bollinger bands, we then add a user-defined number of standard deviations to the initial SMA. The default is to add 2. The result is :
Upper_band = SMA + 2*stdv
Lower_band = SMA - 2*stdv
When the price leaves this channel defined by the bands, we obtain buy and sell signals.
PARAMETERS :
BB Length : This is the length of the Bollinger Bands, i.e. the length of the SMA used to plot the bands, and the length of the price series used to calculate the standard deviation. The default is 120.
Standard Deviation Multipler : adds or subtracts this number of times the standard deviation from the initial SMA. Default is 2.
SMA Exit Signal Length : Exit signals for winning and losing trades are triggered by another SMA. This parameter defines the length of this SMA. The default is 110.
Max Risk per trade (in %) : It's the maximum percentage the user can lose in one trade. The default is 6%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:BTCUSD in 8h timeframe with the following parameters :
BB Length = 120
Standard Deviation Multipler = 2
SMA Exit Signal Length = 110
Max Risk per trade (in %) = 6%
ENTER RULES :
The entry rules are simple:
If close > Upper_band it's a LONG signal
If close < Lower_band it's a SHORT signal
EXIT RULES :
If we are LONG and close < SMA_EXIT, position is closed
If we are SHORT and close > SMA_EXIT, the position is closed
Positions close automatically if they lose more than 6% to limit risk
RISK MANAGEMENT :
This strategy is subject to losses. We manage our risk using the exit SMA or using a SL sets to 6%. This SMA gives us exit signals when the price closes below or above, thus limiting losses. If the signal arrives too late, the position is closed after a loss of 6%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the fixed ratio value, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
NOTE :
Please note that the strategy is backtested from 2017-01-01. As the timeframe is 8h, this strategy is a medium/long-term strategy. That's why only 51 trades were closed. Be careful, as the test sample is small and performance may not necessarily reflect what may happen in the future.
Enjoy the strategy and don't forget to take the trade :)
Rate of Change StrategyRate of Change Strategy :
INTRODUCTION :
This strategy is based on the Rate of Change indicator. It compares the current price with that of a user-defined period of time ago. This makes it easy to spot trends and even speculative bubbles. The strategy is long term and very risky, which is why we've added a Stop Loss. There's also a money management method that allows you to reinvest part of your profits or reduce the size of your orders in the event of substantial losses.
RATE OF CHANGE (ROC) :
As explained above, the ROC is used to situate the current price compared to that of a certain period of time ago. The formula for calculating ROC in relation to the previous year is as follows :
ROC (365) = (close/close (365) - 1) * 100
With this formula we can find out how many percent the change in the current price is compared with 365 days ago, and thus assess the trend.
PARAMETERS :
ROC Length : Length of the ROC to be calculated. The current price is compared with that of the selected length ago.
ROC Bubble Signal : ROC value indicating that we are in a bubble. This value varies enormously depending on the financial product. For example, in the equity market, a bubble exists when ROC = 40, whereas in cryptocurrencies, a bubble exists when ROC = 150.
Stop Loss (in %) : Stop Loss value in percentage. This is the maximum trade value percentage that can be lost in a single trade.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by an amount chosen by the user.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:BTCUSD in 1D timeframe with the following parameters :
ROC Length = 365
ROC Bubble Signal = 180
Stop Loss (in %) = 6
LONG CONDITION :
We are in a LONG position if ROC (365) > 0 for at least two days. This allows us to limit noise and irrelevant signals to ensure that the ROC remains positive.
SHORT CONDITION :
We are in a SHORT position if ROC (365) < 0 for at least two days. We also open a SHORT position when the speculative bubble is about to burst. If ROC (365) > 180, we're in a bubble. If the bubble has been in existence for at least a week and the ROC falls back below this threshold, we can expect the asset to return to reasonable prices, and thus a downward trend. So we're opening a SHORT position to take advantage of this upcoming decline.
EXIT RULES FOR WINNING TRADE :
The strategy is self-regulating. We don't exit a LONG trade until a SHORT signal has arrived, and vice versa. So, to exit a winning position, you have to wait for the entry signal of the opposite position.
RISK MANAGEMENT :
This strategy is very risky, and we can easily end up on the wrong side of the trade. That's why we're going to manage our risk with a Stop Loss, limiting our losses as a percentage of the trade's value. By default, this percentage is set at 6%. Each trade will therefore take a maximum loss of 6%.
If the SL has been triggered, it probably means we were on the wrong side. This is why we change the direction of the trade when a SL is triggered. For example, if we were SHORT and lost 6% of the trade value, the strategy will close this losing trade and open a long position without taking into account the ROC value. This allows us to be in position all the time and not miss the best opportunities.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
NOTE :
Please note that the strategy is backtested from 2017-01-01. As the timeframe is 1D, this strategy is a medium/long-term strategy. That's why only 34 trades were closed. Be careful, as the test sample is small and performance may not necessarily reflect what may happen in the future.
Enjoy the strategy and don't forget to take the trade :)
BUY/SELL RSI FLIUX v1.0The "BUY/SELL RSI FLUX v1.0" indicator is designed to provide buy and sell signals based on the RSI (Relative Strength Index) and price action in relation to support and resistance levels. It overlays directly on the price chart and includes the following components:
- Support and Resistance Levels: Determined over a specified number of bars (lengthSR), these levels represent potential barriers where price action may stall or reverse.
- ATR (Average True Range): Used to measure market volatility. While it's calculated in the script, it's not visualized on the chart as per the latest modification.
- RSI: The RSI is calculated over a defined period (lengthRSI) and is used to identify overbought or oversold conditions. Buy signals are generated when the RSI is below the oversold threshold (rsiOversold) and the price is above the support level. Conversely, sell signals occur when the RSI is above the overbought threshold (rsiOverbought), the price is below the resistance level, and additionally, the price is below a long-term moving average, which acts as a trend filter.
- Long-Term Moving Average: This moving average is plotted to help identify the prevailing market trend. Sell signals are filtered based on the price's position in relation to this moving average.
- Buy/Sell Signals: Visual representations in the form of shapes are plotted below (for buy) or above (for sell) the price bars to indicate potential entry points.
By combining these elements, the indicator aims to provide high-probability trading signals that align with both the market's momentum and trend.
RSI & Backed-Weighted MA StrategyRSI & MA Strategy :
INTRODUCTION :
This strategy is based on two well-known indicators that work best together: the Relative Strength Index (RSI) and the Moving Average (MA). We're going to use the RSI as a trend-follower indicator, rather than a reversal indicator as most are used to. To the signals sent by the RSI, we'll add a condition on the chart's MA, filtering out irrelevant signals and considerably increasing our winning rate. This is a medium/long-term strategy. There's also a money management method enabling us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RSI :
The RSI is one of the best-known and most widely used indicators in trading. Its purpose is to warn traders when an asset is overbought or oversold. It was designed to send reversal signals, but we're going to use it as a trend indicator by increasing its length to 20. The RSI formula is as follows :
RSI (n) = 100 - (100 / (1 + (H (n)/L (n))))
With n the length of the RSI, H(n) the average of days closing above the open and L(n) the average of days closing below the open.
MA :
The Moving Average is also widely used in technical analysis, to smooth out variations in an asset. The SMA formula is as follows :
SMA (n) = (P1 + P2 + ... + Pn) / n
where n is the length of the MA.
However, an SMA does not weight any of its terms, which means that the price 10 days ago has the same importance as the price 2 days ago or today's price... That's why in this strategy we use a RWMA, i.e. a back-weighted moving average. It weights old prices more heavily than new ones. This will enable us to limit the impact of short-term variations and focus on the trend that was dominating. The RWMA used weights :
The 4 most recent terms by : 100 / (4+(n-4)*1.30)
The other oldest terms by : weight_4_first_term*1.30
So the older terms are weighted 1.30 more than the more recent ones. The moving average thus traces a trend that accentuates past values and limits the noise of short-term variations.
PARAMETERS :
RSI Length : Lenght of RSI. Default is 20.
MA Type : Choice between a SMA or a RWMA which permits to minimize the impact of short term reversal. Default is RWMA.
MA Length : Length of the selected MA. Default is 19.
RSI Long Signal : Minimum value of RSI to send a LONG signal. Default is 60.
RSI Short signal : Maximum value of RSI to send a SHORT signal. Default is 40.
ROC MA Long Signal : Maximum value of Rate of Change MA to send a LONG signal. Default is 0.
ROC MA Short signal : Minimum value of Rate of Change MA to send a SHORT signal. Default is 0.
TP activation in multiple of ATR : Threshold value to trigger trailing stop Take Profit. This threshold is calculated as multiple of the ATR (Average True Range). Default value is 5 meaning that to trigger the trailing TP the price need to move 5*ATR in the right direction.
Trailing TP in percentage : Percentage value of trailing Take Profit. This Trailing TP follows the profit if it increases, remaining selected percentage below it, but stops if the profit decreases. Default is 3%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. Default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:ETHUSD with a timeframe set to 6h. Parameters are set as follows :
MA type: RWMA
MA Length: 19
RSI Long Signal: >60
RSI Short Signal : <40
ROC MA Long Signal : <0
ROC MA Short Signal : >0
TP Activation in multiple ATR : 5
Trailing TP in percentage : 3
ENTER RULES :
The principle is very simple:
If the asset is overbought after a bear market, we are LONG.
If the asset is oversold after a bull market, we are SHORT.
We have defined a bear market as follows : Rate of Change (20) RWMA < 0
We have defined a bull market as follows : Rate of Change (20) RWMA > 0
The Rate of Change is calculated using this formula : (RWMA/RWMA(20) - 1)*100
Overbought is defined as follows : RSI > 60
Oversold is defined as follows : RSI < 40
LONG CONDITION :
RSI > 60 and (RWMA/RWMA(20) - 1)*100 < -1
SHORT CONDITION :
RSI < 40 and (RWMA/RWMA(20) - 1)*100 > 1
EXIT RULES FOR WINNING TRADE :
We have a trailing TP allowing us to exit once the price has reached the "TP Activation in multiple ATR" parameter, i.e. 5*ATR by default in the profit direction. TP trailing is triggered at this point, not limiting our gains, and securing our profits at 3% below this trigger threshold.
Remember that the True Range is : maximum(H-L, H-C(1), C-L(1))
with C : Close, H : High, L : Low
The Average True Range is therefore the average of these TRs over a length defined by default in the strategy, i.e. 20.
RISK MANAGEMENT :
This strategy may incur losses. The method for limiting losses is to set a Stop Loss equal to 3*ATR. This means that if the price moves against our position and reaches three times the ATR, we exit with a loss.
Sometimes the ATR can result in a SL set below 10% of the trade value, which is not acceptable. In this case, we set the SL at 10%, limiting losses to a maximum of 10%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
Enjoy the strategy and don't forget to take the trade :)
Narrow Range StrategyNarrow Range Strategy :
INTRODUCTION :
This strategy is based on the Narrow Range Day concept, implying that low volatility will generate higher volatility in the days ahead. The strategy sends us buy and sell signals with well-defined profit targets. It's a medium/long-term strategy. There's also a money management method that allows us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
NARROW RANGE (NR) DAY :
A Narrow Range Day is a day in which price variations are included in those of a specific day some time before. The high and low of this specific day form the "reference range". In general, we compare these variations with those of 4 or 7 days ago. The mathematical formula for finding an NR4 is :
If low > low(4) and high < high(4) :
nr = true
This implies that the current low is greater than the low of 4 days ago, and the current high is smaller than the high of 4 days ago. So today's volatility is lower than that of 4 days ago, and may be a sign of high volatility to come.
PARAMETERS :
Narrow Range Length : Corresponds to the number of candles back to compare current volatility. The default is 4, allowing comparison of current volatility with that of 4 candles ago.
Stop Loss : Percentage of the reference range on which to set an exit order to limit losses. The minimum value is 0.001, while the maximum is 1. The default value is 0.35.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by an amount chosen by the user.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot was used to test NR4 and NR7 with all possible Stop Losses in order to find out which combination generates the highest return on BITSTAMP:ETHUSD while limiting the drawdown. This strategy is the most optimal with an NR4 and a SL of 35% of the reference range size in 5D timeframe.
BUY AND SHORT SIGNALS :
When an NR is spotted, we create two stop orders on the high and low of the reference range. As soon as there's a breakout from this reference range (shown in blue on the chart), we open a position. We're LONG if there's a breakout on the high and SHORT if there's a breakout on the low. Executing a stop order cancels the second stop order.
RISK MANAGEMENT :
This strategy is subject to losses. We manage our risk with Stop Losses. The user is free to enter a SL as a percentage of the reference range. The maximum amount risked per trade therefore depends on the size of the range. The larger the range, the greater the risk. That's why we have set a maximum Stop Loss to 10% to limiting risks per trade.
The special feature of this strategy is that it targets a precise profit objective. This corresponds to the size of the reference range at the top of the high if you're LONG, or at the bottom of the low if you're short. In the same way, the larger the reference range, the greater the potential profits.
The risk reward remains the same for all trades and amounts to : 100/35 = 2.86. If the reference range is too high, we have set a SL to 10% of the trade value to limit losses. In that case, the risk reward is less than 2.86.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
NOTE :
Please note that the strategy is backtested from 2017-01-01. As the timeframe is 5D, this strategy is a medium/long-term strategy. That's why only 37 trades were closed. Be careful, as the test sample is small and performance may not necessarily reflect what may happen in the future.
Enjoy the strategy and don't forget to take the trade :)
Session Fibonacci Levels [QuantVue]The "Session Fibonacci Levels" indicator is a powerful tool designed for traders who aim to use Fibonacci retracement and extension levels in their trading strategy.
The indicator combines Fibonacci levels with customized trading sessions, allowing traders to observe and utilize Fibonacci levels that are automatically calculated for each defined session.
This approach offers a dynamic and session-relevant perspective on potential support and resistance levels, which can be crucial for intraday trading strategies.
🔹The indicator calculates Fibonacci retracement and extension levels based on the high and low prices of a specified trading session, dynamically adjusting to the location of the high and low bar.
If the low of the session occurs before the high, the fib levels are measured from low to high.
If the low of the session occurs after the high, the fib levels are measured from high to low.
🔹Users can set their time zone and define trading sessions, allowing for flexibility and applicability across global markets. This is particularly beneficial for traders who focus on specific market hours like the London or New York sessions.
Important sessions:
New York (8:00am - 5:00pm EST)
London (3:00am - 12:00pm EST)
Asia (7:00pm - 4:00am EST)
Custom session (user defined session in indicator settings)
🔹The indicator dynamically updates Fibonacci levels as new highs and lows are made within the session, keeping the analysis current. Additionally, it provides alerts when prices hit key Fibonacci levels, aiding in timely decision-making.
How to Use:
Configure the time zone and session time
Once the session begins, the indicator will begin highlighting the session range
When the session ends, Fibonacci levels based on the high and low of the session will be drawn
Use these levels to identify potential support and resistance areas
Standardized SuperTrend Oscillator
The Standardized SuperTrend Oscillator (SSO) is a versatile tool that transforms the SuperTrend indicator into an oscillator, offering both trend-following and mean reversion capabilities. It provides deeper insights into trends by standardizing the SuperTrend with respect to its upper and lower bounds, allowing traders to identify potential reversals and contrarian signals.
Methodology:
Lets begin with describing the SuperTrend indicator, which is the fundamental tool this script is based on.
SuperTrend:
The SuperTrend is calculated based on the average true range (ATR) and multiplier. It identifies the trend direction by placing a line above or below the price. In an uptrend, the line is below the price; in a downtrend, it's above the price.
pine_st(float src = hl2, float factor = 3., simple int len = 10) =>
float atr = ta.atr(len)
float up = src + factor * atr
up := up < nz(up ) or close > nz(up ) ? up : nz(up )
float lo = src - factor * atr
lo := lo > nz(lo ) or close < nz(lo ) ? lo : nz(lo )
int dir = na
float st = na
if na(atr )
dir := 1
else if st == nz(up )
dir := close > up ? -1 : 1
else
dir := close < lo ? 1 : -1
st := dir == -1 ? lo : up
SSO Oscillator:
The SSO is derived from the SuperTrend and the source price. It calculates the standardized difference between the SuperTrend and the source price. The standardization is achieved by dividing this difference by the distance between the upper and lower bounds of the SuperTrend.
float sso = (src - st) / (up - lo)
Components and Features:
SuperTrend of Oscillator - An additional SuperTrend based on the direction and volatility of the oscillator, behaving as the SuperTrend OF the SuperTrend. This provides further trend analysis of the underlying broad trend regime.
Reversion Tracer - The RSI of the direction of the original SuperTrend, providing a dynamic threshold for premium and discount price areas.
float rvt = ta.rsi(dir, len)
Heikin Ashi Transform - An option to apply the Heikin Ashi transform to the source price of the oscillator, providing a smoother visual representation of trends.
Display Modes - Choose between Line mode for a standard oscillator view or Candle mode, displaying the oscillator as Heikin Ashi candles for more in-depth trend analysis.
Contrarian and Reversion Signals:
Contrarian Signals - Based on the SuperTrend of the oscillator, these signals can act as potential buy or sell indications, highlighting potential trend exhaustion or premature reversals.
Reversion Signals - Generated when the oscillator crosses above or below the Reversion Tracer, signaling potential mean reversion opportunities or trend breakouts.
Utility and Use Cases:
Trend Analysis - Utilize the SSO as a trend-following tool with the added benefits of the oscillator's SuperTrend and Heikin Ashi transform.
Valuation Analysis - Leverage the oscillator's reversion signals for identifying potential mean reversion opportunities in the market.
The Standardized SuperTrend Oscillator enhances the capabilities of the SuperTrend indicator, offering a balanced approach to both trend-following and mean reversion strategies. Its customizable options and contrarian signals make it a valuable instrument for traders seeking comprehensive trend analysis and potential reversal signals.
Ranges With Targets [ChartPrime]The Ranges With Targets indicator is a tool designed to assist traders in identifying potential trading opportunities on a chart derived from breakout trading. It dynamically outlines ranges with boxes in real-time, providing a visual representation of price movements. When a breakout occurs from a range, the indicator will begin coloring the candles. A green candle signals a long breakout, suggesting a potential upward movement, while a red candle indicates a short breakout, suggesting a potential downward movement. Grey candles indicate periods with no active trade. Ranges are derived from daily changes in price action.
This indicator builds upon the common breakout theory in trading whereby when price breaks out of a range; it may indicate continuation in a trend.
Additionally, users have the ability to customize their risk-reward settings through a multiplier referred to as the Target input. This allows traders to set their Take Profit (TP) and Stop Loss (SL) levels according to their specific risk tolerance and trading strategy.
Furthermore, the indicator offers an optional stop loss setting that can automatically exit losing trades, providing an additional layer of risk management for users who choose to utilize this feature.
A dashboard is provided in the top right showing the statistics and performance of the indicator; winning trades; losing trades, gross profit and loss and PNL. This can be useful when analyzing the success of breakout trading on a particular asset or timeframe.
What RSI? Weighted Heiken Ashi Triple RSIWhat You're Looking At:
The indicator presents a few key elements on its pane which is separate from the price chart:
Smoothed RSI Average Line: This line represents an average of three different RSI calculations, each weighted differently. It's been smoothed out to reduce noise and help you see the trend more clearly.
Moving Average Line: This is a line that smooths out the average RSI line even further and helps you identify the overall trend.
Bollinger Bands: These are two lines that create a channel around the RSI average line. The upper band typically represents an overbought condition, and the lower band represents an oversold condition.
Background Color: The background of the indicator pane will change colors to indicate buy (green) or sell (red) signals.
Horizontal Lines: There are horizontal lines drawn at levels 70, 50, and 30. These represent overbought, midpoint, and oversold levels, respectively.
How to Operate and Interpret:
Trend Identification: Look at the moving average line. If it's trending upwards, the overall momentum may be considered bullish. If it's trending downwards, the momentum may be bearish.
Buy Signals: You may consider a buy signal when:
The smoothed RSI average crosses above the moving average line.
The smoothed RSI average is below 30 and starts to rise, crossing the oversold line.
The background color turns green, signifying favorable conditions to buy according to the indicator's logic.
Sell Signals: You may consider a sell signal when:
The smoothed RSI average crosses below the moving average line.
The smoothed RSI average is above 70 and starts to fall, crossing the overbought line.
The background color turns red, signifying favorable conditions to sell according to the indicator's logic.
Overbought/Oversold Conditions: When the smoothed RSI line touches or crosses the Bollinger Bands, it could be indicating that the asset is overbought (upper band) or oversold (lower band). Some traders use these conditions to look for potential reversals.
Cautions for Trading:
If the smoothed RSI average is between the bands and near the middle line (50), the market might be considered neutral, and some traders may choose to wait for clearer signals.
Just because the indicator gives a buy or sell signal, it doesn't mean the price will immediately move in that direction. It's important to consider other factors in your trading strategy.
Final Notes:
Always use this indicator in conjunction with other analysis methods. No indicator is perfect, and they should be used to supplement your trading strategy, not replace it.
It's important to set stop losses according to your risk tolerance when entering any trades based on these signals.
Practice with the indicator in a demo account to become familiar with its behavior before using it with real money.
By following the movements and signals of this indicator, you can get a sense of the momentum and potential entry or exit points in the markets you are trading.
Bollinger Bands (Nadaraya Smoothed) | Flux ChartsTicker: AMEX:SPY , Timeframe: 1m, Indicator settings: default
General Purpose
This script is an upgrade to the classic Bollinger Bands. The idea behind Bollinger bands is the detection of price movements outside of a stock's typical fluctuations. Bollinger Bands use a moving average over period n plus/minus the standard deviation over period n times a multiplier. When price closes above or below either band this can be considered an abnormal movement. This script allows for the classic Bollinger Band interpretation while de-noising or "smoothing" the bands.
Efficacy
Ticker: AMEX:SPY , Timeframe: 1m, Indicator settings: Standard Dev: 2; Level 1 : off; Level 2: off; labels: off
Upper Band Key:
Blue: Bollinger No smoothing
Orange: Bollinger SMA smoothing period of 10
Purple: Bollinger EMA smoothing period of 10
Red: Nadaraya Smoothed Bollinger bandwidth of 6
Here we chose periods so that each would have a similar offset from the original Bollinger's. Notice that the Red Band has a much smoother result while on average having a similar fit to the other smoothing techniques. Increasing the EMA's or SMA's period would result in them being smoother however the offset would increase making them less accurate to the original data.
Ticker: AMEX:SPY , Timeframe: 1m, Indicator settings: Standard Dev: 2; Level 1: off; Level 2: off; labels: off
Upper Band Key:
Blue: Bollinger No smoothing
Orange: Bollinger SMA smoothing period of 20
Purple: Bollinger EMA smoothing period of 20
Red: Nadaraya Smoothed Bollinger bandwidth of 6
This makes the Nadaraya estimator a particularly efficacious technique in this use case as it achieves a superior smoothness to fit ratio.
How to Use
This indicator is not intended to be used on its own. Its use case is to identify outlier movements and periods of consolidation. The Smoothing Factor when lowered results in a more reactive but noisy graph. This setting is also known as the "bandwidth" ; it essentially raises the amplitude of the kernel function causing a greater weighting to recent data similar to lowering the period of a SMA or EMA. The repaint smoothing simply draws on the Bollinger's each chart update. Typically repaint would be used for processing and displaying discrete data however currently it's simply another way to display the Bollinger Bands.
What makes this script unique.
Since Bollinger bands use standard deviation they have excess noise. By noise we mean minute fluctuations which most traders will not find useful in their strategies. The Nadaraya-Watson estimator, as used, is essentially a weighted average akin to an ema. A gaussian kernel is placed at the candlestick of interest. That candlestick's value will have the highest weight. From that point the other candlesticks' values effect on the average will decrease with the slope of the kernel function. This creates a localized mean of the Bollinger Bands allowing for reduced noise with minimal distortion of the original Bollinger data.
Crypto Market OverviewCrypto Market Overview
The Crypto Market Overview (CMO) indicator is your one-stop tool for keeping tabs on the cryptocurrency market. It provides a comprehensive snapshot of key data and trends, helping you make informed decisions in the fast-paced world of crypto trading. Here's what this indicator offers:
1. Lookback Period Control:
You can customize the lookback period for percentage change calculations, tailoring it to your specific analysis needs.
2. Currency Selection:
Choose your preferred currency to view market data in your desired denomination.
3. Major Market Cap Data:
Real-time information on Bitcoin (BTC) and Ethereum (ETH) market caps.
Total market capitalization data for the entire crypto market.
4. Stablecoin Market Cap Data:
Keep track of stablecoin market caps, including USDT, USDC, DAI, TUSD, and BUSD.
Get a clear picture of the stablecoin segment of the market.
5. Shitcoin Market Cap Data:
An interesting category that represents the market cap of all cryptocurrencies not classified as major or stable.
6. Dominance Data:
Dominance percentages for BTC, ETH, stablecoins and shitcoins.
Total market dominance, allowing you to gauge the influence of major cryptocurrencies.
7. Rate of Change (RoC) Metrics:
Monitor the RoC for market caps and dominance percentages.
Positive or negative trends are clearly highlighted with color-coded indicators.
8. Intuitive Table Layout:
A user-friendly table layout displays all the data.
Key assets such as Bitcoin and Ethereum are listed along with their market caps and dominance.
9. Color Coding:
Upward and downward trends are easily identifiable with color-coded cells.
A white background with bold text ensures readability.
The Crypto Market Overview indicator is an invaluable tool for cryptocurrency traders and enthusiasts, offering a quick and convenient way to stay updated on market dynamics. It's perfect for making data-driven decisions in the ever-changing world of digital assets.
[MAD] Harmonic Wave Fourier AnalysisThis script uses Fourier Analysis with additional postcalculations to draw a plot which displays the Amplitude-Change of the Fouriers
Parameter Settings:
You can set the number of data points to analyze
the period to check for extremes.
Fourier Transform: The script breaks down the time series data into its frequency components using cosine and sine calculations.
Harmonic Analysis: It calculates the strength and phase of each frequency component, producing harmonic waves.
Amplitude Change: It determines the change in amplitude between peaks and troughs for each harmonic.
Latest Value Extraction: The script selects the middle amplitude change as the latest data point.
High/Low Points: Finds the maximum and minimum amplitude changes over a specified period.
Visualization: It plots the latest amplitude change with a color that indicates its value relative to the identified extremes.
splitted by 3 Blue plots (1/3 1/2 2/3 from min to max)
How to trade?
May go for retests to the blue lines after big moves.
See this script as braindump of an idea, so its just a concept :-)
Expected Move by Option's Implied Volatility High Liquidity
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols with high option liquidity.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options.There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry. This script will display Expected Move data for Symbols within the range of JBL-NOTE in alphabetical order.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Ultimate RSIThis indicator is a customized version of the RSI indicator that by default utilizes Bollinger Bands. It have included two layers of bands, with separate standard deviations. The indicator is fully customizable.
The indicator displays bullish and bearish divergence from price.
You are able to change the moving average that is used to calculate both the RSI itself, as well as the moving average used for the Bollinger Bands.
I have included fills that color the background to indicate various zones of RSI values.
Price tends to either reject or move quickly at these levels.
I have a yellow RSI zone that indicates a sideways market with little to no momentum with default values of 45 to 55. These are areas where trading is stagnant and you should likely avoid placing trades.
There is now an ATR feature to adjust the Bollinger Bands with ATR (Average True Range).
In order to trade with this indicator, you should watch for the white line (RSI) to cross into the Bollinger Bands, then cross over the yellow moving average (Basis line), where you would enter a BUY or SELL.
Watch this indicator in action and look for patterns. Draw vertical lines on the chart where you would have wanted to buy or sell and study this to understand how to make better trading decisions.
NOTE:
While not required in order to use this indicator, it was designed to visually work with another indicator of mine called The Ultimate Buy and Sell Indicator. I recommend using both together as they are a strong pair of indicators that share the same settings. This indicator while it can be used independently can also help you visualize the settings changes made to the other one which are unable to be displayed on the main chart by that indicator.
Monthly beta (5Y monthly) with multi-timeframe supportThe PROPER way to calculate beta for a stock using monthly price returns . None of this nonsense using daily returns and sliding windows as done by other scripts...
Works on any timeframe.
This script has been checked against 100s of stocks on Yahoo finance and Zacks research data and matches 100% (some rounding error as this script is kept updated live on unconfirmed monthly bars).
You can check for yourself:
Zacks fundamentals - beta
The script calculates beta using the Variance-Covariance Method as described on Investopedia
How to calculate Beta
Anticipated Profit Targets (APT)Anticipated Profit Targets (APT)
Purpose:
The Anticipated Profit Targets script is a specialized tool designed to assist traders in visualizing potential exit points for their trades. This is achieved by leveraging the Average True Range (ATR), a renowned measure of market volatility.
How It Works:
ATR Computations: At its core, the script calculates the ATR based on a user-defined number of periods. The ATR captures the range between the high and low prices of an asset over a specific duration, providing a snapshot of its volatility.
Multiplier Application: To fine-tune the profit targets, the ATR is multiplied by a user-defined multiplier. This step adjusts the ATR value, setting the profit targets at a distance from the current price, thus accounting for potential price movements.
Adaptable Timeframes: One of the standout features of this script is its adaptability. Users can select their desired timeframe for the profit target calculations. This flexibility means that a trader can be on a 15-minute chart but visualize profit targets based on the volatility of a 1-hour chart.
Visual Representation: The calculated profit targets are then overlaid onto the current chart. This visual aid provides traders with a clear perspective of potential exit points in relation to ongoing price movements.
Originality and Usefulness:
While the concept of using ATR for setting profit targets isn't new, this script's adaptability across timeframes and its user-centric customization options make it a unique offering. The combination of ATR with dynamic multipliers and timeframe adaptability ensures that traders get a tool tailored to their specific needs, rather than a one-size-fits-all solution.
Usage Guidelines:
After adding the script to the chart, traders can adjust the input parameters to their preferences. The anticipated profit targets will then be displayed, offering potential exit points. It's recommended to use these targets in conjunction with other technical indicators and chart patterns for a holistic trading strategy.
Features:
ATR Periods: The ATR is calculated using a user-defined number of periods. By default, it's set to 14 periods, a standard setting. The ATR gauges the asset's volatility, and adjusting the periods can increase or decrease its sensitivity to recent price fluctuations.
ATR Multiplier: The ATR is multiplied by a user-defined factor to determine the profit targets. With a default multiplier of 1.5, the profit target will be positioned 1.5 times the ATR above (for bullish trades) or below (for bearish trades) the current price.
Target Timeframe: Traders can choose the timeframe for which the profit targets are calculated. This feature enables viewing of profit targets from higher timeframes on the current chart. For instance, while observing a 15-minute chart, one can see the 1-hour profit targets.
Visual Indicators:
1. Two lines are plotted: the bullish target (in green) and the bearish target (in red).
2. At the onset of each new candle in the selected higher timeframe, labels indicating the precise profit target values are displayed.
3. Price scale labels also showcase the profit targets, offering a quick reference for potential exit points.
Customization:
Traders can modify the following parameters:
1. ATR Periods: Adjusting the number of periods can refine the ATR's sensitivity to price changes.
2. Multiplier for ATR: Tweaking this value alters the distance between the profit targets and the current price.
3. Timeframe for Profit Targets: A variety of timeframes are available, granting flexibility in viewing profit targets.
How to Use:
After integrating the script into their chart, traders can modify the input parameters as desired. The anticipated profit targets will then be overlaid on the chart, offering potential exit points. When used alongside other technical indicators and chart patterns, this tool can enhance trading decision-making.
Note: This script is designed for educational purposes and should not be considered as financial advice. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Z-ScoreThe "Z-Score" indicator is a unique and powerful tool designed to help traders identify overbought and oversold conditions in the market. Below is an explanation of its features, usefulness, and what makes it special:
Features:
Z-Score Calculation: The indicator calculates the Z-Score, a statistical measure that represents how far the current price is from the moving average (MA) in terms of standard deviations. It helps identify extreme price movements.
Customizable Parameters: Traders can adjust key parameters such as the Z-Score threshold, the type of MA (e.g., SMA, EMA), and the length of the moving average to suit their trading preferences.
Signal Options: The indicator offers flexibility in terms of signaling. Traders can choose whether to trigger signals when the Z-Score crosses the specified threshold or when it moves away from the threshold.
Visual Signals : Z-Score conditions are represented visually on the chart with color-coded background highlights. Overbought conditions are marked with a red background, while oversold conditions are indicated with a green background.
Information Table: A dynamic information table displays essential details, including the MA type, MA length, MA value, standard deviation, current price, and Z-Score. This information table helps traders make informed decisions.
Usefulness:
Overbought and Oversold Signals: Z-Score is particularly valuable for identifying overbought and oversold market conditions. Traders can use this information to potentially enter or exit positions.
Statistical Analysis: The Z-Score provides a statistical measure of price deviation, offering a data-driven approach to market analysis.
Customization: Traders can customize the indicator to match their trading strategies and preferences, enhancing its adaptability to different trading styles.
Visual Clarity: The visual signals make it easy for traders to quickly spot potential trade opportunities on the price chart.
In summary, the Z-Score indicator is a valuable tool for traders looking to incorporate statistical analysis into their trading strategies. Its customizability, visual signals, and unique statistical approach make it an exceptional choice for identifying overbought and oversold market conditions and potential trading opportunities.
Expected Move by Option's Implied Volatility Symbols: EAT - GBDC
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of EAT-GDBC in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
Expected Move by Option's Implied Volatility Symbols: CLFD-EARN This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of CLFD - EARN in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
ATR SpikeALWAYS TRADE THE DIRECTION OF THE TREND
This indicator is useful for 5-minute Bank Nifty intraday trading.
It compares the Open-Close value for a 5-minute bar with the current ATR value.
When a bar has higher than the ATR value then it means that the current bar has a higher Open-Close than the ATR.
This means that after a period of dull action, some action has taken place.
And more action will follow in the direction of the immediate trend.
It signals the start of momentum which I look for as a intraday trader.
Feel free to experiment and change values as it suits you.
I use it on Bank Nifty only on 5 minute timeframe with 14 period ATR.
Expected Move by Option's Implied Volatility Symbols: A - AZZ
This script plots boxes to reflect weekly, monthly and yearly expected moves based on "At The Money" put and call option's implied volatility.
Symbols in range: This script will display Expected Move data for Symbols within the range of A - AZZ in alphabetical order.
Weekly Updates: Each weekend, the script is updated with fresh expected move data, a job that takes place every Saturday following the close of the markets on Friday.
In the provided script, several boxes are created and plotted on a price chart to represent the expected price moves for various timeframes.
These boxes serve as visual indicators to help traders and analysts understand the expected price volatility.
Definition of Expected Move: Expected Move refers to the anticipated range within which the price of an underlying asset is expected to move over a specific time frame, based on the current implied volatility of its options. Calculation: Expected Move is typically calculated by taking the current stock price and applying a multiple of the implied volatility. The most commonly used multiple is the one-standard-deviation move, which encompasses approximately 68% of potential price outcomes.
Example: Suppose a stock is trading at $100, and the implied volatility of its options is 20%. The one-standard-deviation expected move would be $100 * 0.20 = $20.
This suggests that there is a 68% probability that the stock's price will stay within a range of $80 to $120 over the specified time frame. Usage: Traders and investors use the expected move as a guideline for setting trading strategies and managing risk. It helps them gauge the potential price swings and make informed decisions about buying or selling options. There is a 68% chance that the underlying asset stock or ETF price will be within the boxed area at option expiry. The data on this script is updating weekly at the close of Friday, calculating the implied volatility for the week/month/year based on the "at the money" put and call options with the relevant expiry.
In summary, implied volatility reflects market expectations about future price volatility, especially in the context of options. Expected Move is a practical application of implied volatility, helping traders estimate the likely price range for an asset over a given period. Both concepts play a vital role in assessing risk and devising trading strategies in the options and stock markets.
