Table of Contents
Smart Stop Set is a trading platform that enables users to design algorithms easily using a drag-and-drop system called blueprint that can perform thousands of complex calculations in seconds.
Speed is the most critical key to success in the trading world. These days, many are employing bots to make the most accurate decisions in the least possible time. No one can monitor the market continuously all the time; In addition, it takes time to analyze all the conditions and make a correct decision. Sometimes only some milliseconds are enough to turn you from a winner into a loser.
Yeah, we all know that writing bots need high-level coding skills. Wait a minute, who said you need coding to can run a bot? As we present the blueprint environment, you can design complex algorithms without coding in just a few minutes. Our system creates bots that will run your algorithms continuously until you decide to stop them.
We strictly follow a set of rules to ensure your data's security, and no one, including us, has absolutely no access to your assets. All we do is send signals to your brokers, and they do the rest; we have no more access, and thus you don't need to trust us at any step of the process.
blueprintenvironment, you can design complex algorithms with no lines of code in just a couple of minutes. Learning how to work with this system is super easy and doesn't need much time; In addition, we prepared many guides in various places to help you as fast as possible when you need them.
Accountssection, click on the
Add Accountbutton and select one exchange from the dropdown list. Some fields will appear right after choosing the exchange; fill them in with the required data and then push the
Add Scenariobutton on either the
Scenariospage, fill in the fields of the
Scenario Informationpage with the required data as explained below, and then click on the
Createbutton routing you to the scenario editor environment.
Scenario name: Choose a name for your scenario. (required)
Scenario description: Explain your scenario's cons and pros, how it would be most efficacious, and - if you wish - how it works. (required)
Owner fee: The profit percentage you will earn by sharing the scenario on the market. This value is needed when you've checked the
Share in marketplacecheckbox. (default value is zero)
Share in marketplace: Determines whether you want to share your scenario in the marketplace.
Show your scenario as an open source: Appoints whether you let other users see your algorithm.
Go to the
page. There are buttons nested in the
column; let's review them.
Deep Dive into the Blueprint>
Datawatchers) get signals periodically and push them into the subsequent blocks. They process the caught signals, and if all the conditions are satisfied, would trigger the
SELLblocks to send requests to the user exchanges.
New Backtestbutton at the bottom right corner of the modal. When you press the button, another modal will get shown that asks you to specify a date range and enter your asset in BTC and USDT. Press the
Run the backtestbutton; It will get added to the list, and you can check its status. Initially, your backtest may get put in a queue and take some time to get started; Since then, you can review its real-time status via a chart, a list of signals, and an information box.
EditOpens the scenario editor environment containing the scenario content.
DeleteShows an alert modal; Confirm the deletion by pressing the
OKbutton, and the scenario will get removed.
CopyOpens a modal; Fill in the name field, and after pressing the
Clonebutton, you will get redirected to the scenario editor containing the newly cloned scenario content.
SettingAllows you to edit fields on the
Scenario Informationpage. (look at the
Vector Absolute Value
calculates the absolute value of each element in an array. [
calculates the Trigonometric arccosine of each element in an array. [
Accumulation Distribution Line
determines the trend of a stock, using the relation between the volume flow and the stock’s price.
adds two arrays together.
Accumulation Distribution Oscillator
is calculated by taking an exponential moving average of short periods of accumulation distribution line subtracted from an exponential moving average of long periods of accumulation distribution line.
Average Directional Movement Index
shows the strength of a trend through a value in a range of 0 to 100.
Average Directional Movement Index Rating
is the same as the average directional movement index but is smoother. This indicator gets less affected than
from the fast short-term market oscillations.
measures the momentum of the market.
Absolute Price Oscillator
is the difference between the short-period exponential moving average and the long-period exponential moving average.
comprises two indicators:
. Aroon can identify the beginning of a trend, its strength, and any changes.
is the difference between
indicators, and the output would be a value between 0 and 100.
calculates the trigonometric arcsine of each element in an array.
calculates the trigonometric arctangent of each element in an array.
Average True Range
measures market volatility over a stock’s price range for a specified period.
shows the mean of open, high, low, and close prices of a stock.
contains the upper, middle, and lower bands. The middle one is a moving average indicator, and the upper and lower bands are on the sides of the middle one. The value of the standard deviations determines the distance between the middle band and the upper and lower ones.
Balance of Power
evaluates the strength of buyers and sellers in the market.
Commodity Channel Index
would be high when prices are far above the average and would be low when prices are far below it. So cci can identify overbought and oversold areas of price action. Besides that, it gets used to discover reversals and divergences.
shows the smallest integer from the elements of an array.
Chande Momentum Oscillator
calculates the price of momentum on bullish or/and bearish days. In other words, it computes the difference between the sum of higher closes and the sum of lower closes, dividing by the sum of all price movements.
calculates the trigonometric cosine of each element in an array.
Vector Hyperbolic Cosine
calculates the trigonometric hyperbolic cosine of each element in an array.
continuously detects whether the inputs are crossing each other.
continuously detects whether the first input is crossing over the other one. It means, against the crossany indicator, the only situation that matters is when the first input would place above the other one.
calculates the difference between the high and low prices for each period.
saves an array of recent signals. It is a useful indicator, especially in machine learning algorithms.
Double Exponential Moving Average
is the same as the exponential moving average, but due to allocating more weight to recent data points, delivers fewer lag data.
positive directional indicator
negative directional indicator
lines that show the price trend movement. Crossing these two lines propagates the buy and sell signals; If the positive line crosses up through the negative one, it is a Buy signal, and vice versa.
divides the provided inputs.
positive directional movement
negative directional movement
lines. They get calculated using the prior high and low prices.
Detrended Price Oscillator
removes price trends to make it easier to identify peaks and troughs. Thus, estimating the cycle lengths using the indicator is much simpler.
Directional Movement Index
, which is also referred to as
, contains two directional movement lines and the average directional movement index indicator.
is almost the same as decay but faster for the same period.
Exponential Moving Average
shows the direction of the price changes over a period. EMA is like a
Simple Moving Average
, but where the SMA directly calculates the average price values, EMA applies more weight to the recent prices.
Ease of Movement
investigates the relationship between price fluctuations and trading volume.
raised to the power of each input element.
is an unpopular indicator that, collaborating with other indicators, can identify price reversals.
of a value is the largest integer less than or equal to it.
predicts the upcoming stock's price by monitoring the difference between the current stock's price and a linear regression price resulting from the
Time Series Forecast
Hull Moving Average
is an improved moving average that removes the lags (and thus is super fast) and is smoother than the other traditional moving average indicators.
Kaufman Adaptive Moving Average
reduces false signals by eliminating short-term price fluctuations. In other words, kama removes the market noises, so if the market volatility is low, it will heel the current market price.
Klinger Volume Oscillator
forecasts market reversals by comparing the volume to the price.
indicator produces lag to its input.
plots the ending values of linear regression lines for a specific number of bars.
Linear Regression Intercept
returns the height of the linear regression line for the first input bar in the moving period.
Linear Regression Slope
determines the direction of trend strength. The indicator determines the slope for each bar using the current bar and the n-1 previous bars where
is the period specified by the trader.
Vector Natural Log
calculates the natural logarithm for each element in an input array.
Vector Base-10 Log
calculates the base-10 logarithm for each element in an input array.
Moving Average Convergence Divergence
determines the direction of the stock price. Consider not using this indicator for detecting trend reversals since it can detect them only after they happen. It is not usually used to identify overbought or oversold conditions as well.
Market Facilitation Index
measures the trend strength and predicts the starting of a trend when it is about to occur. It calculates the price movement per volume unit.
detects market trend reversals.
Maximum In Period
returns the maximum value in the last
Mean Deviation Over Period
computes the absolute mean deviation over a period.
computes the mean of the high and low prices for a bar.
Money Flow Index
measures the trading pressure by monitoring both the price and volume and returns a value between 0 and 100.
Minimum In Period
returns the minimum value in the last
computes the change between the current price and the price of the
bar from the last.
Mesa Sine Wave
detects whether the market is in a cycle mode or a trend mode.
takes two input arrays and multiplies them.
Normalized Average True Range
is a normalized version of the
average true range
and gets calculated with the following formula: NATR = (ATR / Close) * 100.
Negative Volume Index
is a cumulative indicator and is sensitive to the market volume. It argued that high market volume is because of uninformative traders, so it doesn't care about the high-volume days. On low-volume days, informed traders are more active, and therefore
indicator gets affected by them; the
value will rise on positive price changes and will fall on negative price changes.
On Balance Volume
is a cumulative indicator that calculates buying and selling pressures. It increases on up days and decreases on down days.
Percentage Price Oscillator
calculates the difference between two exponential moving averages with different periods divided by the longer one.
helps to figure out stop points and potential reversals in trends. Indeed
stop and reverse
, which describes its application nicely.
Positive Volume Index
is the same as
- and often gets used in conjunction with it - but is sensitive to high-volume days.
as a momentum indicator applies a simple moving average on the difference between the stock close and open prices.
Rate of Change
computes the percentage change between the current price and the price
periods ago. The formula is:
[current price - price n periods ago]/price n periods ago * 100
Rate of Change Ratio
computes the change between the current price and the price
periods ago. The formula is:
current price/price n periods ago
returns the closest integer for each element in an array.
Relative Strength Index
measures the speed and rate of change in price movements within the market; it oscillates between zero and 100.
computes the Trigonometric sine of each element in an array.
Vector Hyperbolic Sine
computes the Trigonometric hyperbolic sine of each element in an array.
Simple Moving Average
shows the direction of the price changes over a period by calculating the average price value.
Vector Square Root
computes the square root of each element in an array.
Standard Deviation Over Period
measures the difference between the current price and the average price over a period.
Standard Error Over Period
shows how different the population mean is from the sample mean.
compares the last close price to the highest and lowest prices over a period and ranges from zero to 100.
is a combination of two indicators: stoch and rsi. Actually, it's applying a stoch indicator on a rsi indicator, which means it's a measure of rsi relative to its high/low range over a period.
returns the subtraction of the two inputs.
Sum Over Period
returns the sum of the last
calculates the Trigonometric tangent of each element in an array.
Vector Hyperbolic Tangent
calculates the Trigonometric hyperbolic tangent of each element in an array.
Triple Exponential Moving Average
is a high-speed moving average with smoother data. It reduces the lags by placing more weight on the recent data and thus is more appropriate for short-term trading.
Vector Degree Conversion
converts an array of radians into an array of degrees.
Vector Radian Conversion
converts an array of degrees into an array of radians.
is the maximum of the following values: Subtraction of the high and low prices of the same day. The absolute value of the subtraction of a day's high price and the previous day's close price. The absolute value of the subtraction of a day's low price and the previous day's close price.
Triangular Moving Average
is the same as sma, but it's averaged twice; In other words, trima is a sma that applies to another sma. This approach leads to a smoother line that places more weight on the middle bars.
shows the percentage change of a triple-smoothed ema (applying an ema three times).
returns only the integer part of a number for each element in an array.
Time Series Forecast
, as expected from the name, predicts future trends based on past data. It is more sensitive to sudden price changes compared to the moving average indicators.
computes the arithmetic mean of the high, low, and close prices.
measures buying pressure by considering three different time frames. These periods (7, 14, 28) describe short, medium, and long-term market trends.
Variance Over Period
measures the variation by calculating the average of squared deviations from the mean.
Vertical Horizontal Filter
monitors the price movements and indicates the prices phase, that they are in the trading or the congestion phase.
Variable Index Dynamic Average
calculates an ema with a dynamic period depending on the market volatility.
Annualized Historical Volatility
measures the deviation of the annual average stock price over a period.
'Volume Oscillator' calculates the difference between a fast volume moving average and a slow volume moving average. Monitoring volume changes in this manner has more technical importance than monitoring volume itself.
Volume Weighted Moving Average
is just like most moving average indicators but considers the market volume in its calculations. It actually gives more weight to the high-volume prices than the low-volume prices.
is the accumulated sum of accumulation and distribution price changes. Accumulation and distribution describe a market controlled by buyers and sellers, respectively. Indeed, the wad indicator measures the positive and negative market pressures.
Weighted Close Price
is simply the average of high, low, and doubled closing prices.
is the same as ema, but wilder's smoothing uses a different smoothing factor, which leads to a slower response to price changes.
identifies overbought and oversold markets by comparing the position of the most recent closing price to the highest and lowest prices over a period.
Weighted Moving Average
is the same as sma, but puts more weight on the recent data. This way, it responds faster to price changes and will stay closer to the market price.
Zero-Lag Exponential Moving Average
follows the same goal as dema and tema. It eliminates the lags to improve the speed and track the price more closely.