Improved Z-ScoreStandard Z-Score scripts lack customization of parameters that I personally desire when doing quantitative analysis. This is an improved Z-Score Indicator to add to your charts that lets you customize various inputs.
Below are the current features:
1) Ticker Type - which data would you like to use for the ticker input - Open, High, Low, Close, OHLC4
2) Ticker Smoothing? - sometimes if you have noisy data, it could be useful to smooth the ticker with a very fast EMA. If this is set to true, the ticker data will be smoothed with an EMA with period that you specify.
3) Ticker Smoothing Period - if Ticker Smoothing? is set to true, this will allow you to specify the smoothing period of the fast EMA - I usually use a 3-period for all of my quantitative analysis, if I am using smoothing.
4) MA Type - Z-Scores are normalized by subtracting a moving average. This allows you to select either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) - the standard is to use SMA.
5) MA Period - the previous X number of bars that you would like to use for normalization. The default is set to 21 (this is roughly 1 month of trading days data for a daily chart).
5) Standard Deviation Period - Z-Scores are normalized by dividing by the standard deviation over X previous periods. This allows you the chance to customize. Default is 252 (this is roughly 1 year of trading days data for a daily chart).
I can add more features if folks are interested, let me know! I hope you like the script.
Best regards,
-Jim Bosse-
Statistics
Yasir Hameed Advance RSI IndicatorRELATIVE STRENGTH INDEX ( RSI )
This is a tool that is widely used
Especially for Overbought and Oversold systems, but I have made some changes in this indicator,
How to use it...!
I have set it as the default setting
- RSI Length: 7
- Overbought: 70
- Oversold: 30
What is unique about this tool?
we can see 3 conditions:
1) RSI Overbought / Oversold with Bullish Engulfing / Bearish Engulfing
2) RSI Overbought / Oversold with Hammer and Shooting Star
3) RSI Overbought / Oversold with 2 Bullish Bars / 2 Bearish Bars
4) RSI Overbought / Oversold with All Patterns at the same time
When the RSI reaches its Oversold line, the code will wait for Bullish Engulfing pattren, when oversold and Bullish engulfing matched, This indicator will generate a buy signal when the condition is met,
and same as for Bear market, When the RSI reaches its Overbought line, the code will wait for Bearish Engulfing pattren, This indicator will generate a sell/exit signal when the condition is met,
2nd condition is that a Hammer candle will be waited for when RSI touches the Overbought line, for Bullish Move
and Shooting Star candle will be waited for when RSI touches the Overbought line, for Bullish Move, for Bearish Move
3rd Condition is also the same as Condition 1 and Condition 2,
When the RSI reaches its Oversold line, the code will wait for 2 Bullish Bars, when oversold and 2 Bullish Bars matched then this indicator will generate a buy signal, and same as for Bear market,
When the RSI reaches its Overbought line, the code will wait for 2 Bearish Bars, when overbought and 2 Bearish Bars matched then this indicator will generate a Sell signal,
4th Condition is that we can use All Conditions at the same time,
- Bullish Engulfing / Bearish Engulfing
- Hammer and Shooting Star
- 2 Bullish Bars / 2 Bearish Bars
Session backtest toolWith this tool you can easily backtest your trading strategy. You can set the times of a day session and evening session separately. The days of the week were indicated at the bottom of the chart.
For me personally, this saves me a lot of time with back testing. Hopefully I can help you with this too
Fed Funds Rate ProjectionsThis script makes projections via drawing boxes based upon changes in the fed funds rate (FRED:EFFR).
It works by turning the change in the fed funds rate into a user defined percentage (using a multiplier, by default a 1% rate of change implies a 10% change in the chart) and then drawing a box that distance away depending on the direction of the rate of change.
The size of the multiplier should depend on the duration of the asset which this is being applied to, for example, a long duration asset such as a high beta growth stock should use a larger multiplier.
Move Up/Down in X daysShows up and down moves off Y per cent for X days.
Also shows a bar for days that has a volume over a threshold.
Default configuration is 20% move up or down for 5 days and volume threshold of 9 Million.
52 Weeks Highs-Lows S&P 500 - MugurThe script uses the MAHP and the MALP index and subtracts the second from the first. So you can see how many stocks in the S&P 500 make new highs or new lows on a 52 weeks basis and see the trend of the market.
5 Day Highs-Lows S&P 500 - MugurThe script uses the M5HP and the M5LP index and subtracts the second from the first. So you can see how many stocks in the S&P 500 make new highs or new lows on a 5 days basis and see the trend of the market.
3 Month Highs-Lows S&P 500 - MugurThe script uses the M3HP and the M3LP index and subtracts the second from the first. So you can see how many stocks in the S&P 500 make new highs or new lows on a 3 month basis and see the trend of the market.
1 Month Highs-Lows S&P 500 - MugurThe script uses the M1HP and the M1LP index and subtracts the second from the first. So you can see how many stocks in the S&P 500 make new highs or new lows on a 1 month basis and see the trend of the market.
Range Gap/Open to Close/Close to CloseThis indicator shows the percentage variation of:
gap
close to close (day including gap)
open to close (without gap)
The green bars represent the days when the variation did not reach the selected range. The red bars show the days when the variation was higher than the selected range.
Best timeframe : DAY
Annual Returns % Comparison [By MUQWISHI]Overview
The Annual Returns % Comparison indicator aimed to compare the historical annual percentage change of any two symbols. The indicator output shows a column-plot that was developed by two using a pine script table, so each period has pair columns showing the yearly percentage change for entered symbols.
Features
- Enter date range.
- Fill up with any two symbols.
- Choose the output data whether adjusted or not.
- Change the location of the table plot
- Color columns by a symbol.
- Size the height and width of columns.
- Color background, border, and text.
- The tooltip of the column value appears once the cursor sets above the specific column. As it seen below.
Let me know if you have any questions.
Thanks.
FunctionPatternFrequencyLibrary "FunctionPatternFrequency"
Counts the word or integer number pattern frequency on a array.
reference:
rosettacode.org
count(pattern)
counts the number a pattern is repeated.
Parameters:
pattern : : array : array with patterns to be counted.
Returns:
array : list of unique patterns.
array : list of counters per pattern.
usage:
count(array.from('a','b','c','a','b','a'))
count(pattern)
counts the number a pattern is repeated.
Parameters:
pattern : : array : array with patterns to be counted.
Returns:
array : list of unique patterns.
array : list of counters per pattern.
usage:
count(array.from(1,2,3,1,2,1))
Rolling QuartilesThis script will continuously draw a boxplot to represent quartiles associated with data points in the current rolling window.
Description :
A quartile is a statistical term that refers to the division of a dataset based on percentiles.
Q1 : Quartile 1 - 25th percentile
Q2 : Quartile 2 - 50th percentile, as known as the median
Q3 : Quartile 3 - 75th percentile
Other points to note:
Q0: the minimum
Q4: the maximum
Other properties :
- Q1 to Q3: a range is known as the interquartile range ( IQR ). It describes where 50% of data approximately lie.
- Line segments connecting IQR to min and max (Q0→Q1, and Q3→Q4) are known as whiskers . Data lying outside the whiskers are considered as outliers. However, such extreme values will not be found in a rolling window because whenever new datapoints are introduced to the dataset, the oldest values will get dropped out, leaving Q0 and Q4 to always point to the observable min and max values.
Applications :
This script has a feature that allows moving percentiles (moving values of Q1, Q2, and Q3) to be shown. This can be applied for trading in ways such as:
- Q2: as alternative to a SMA that uses the same lookback period. We know that the Mean (SMA) is highly sensitive to extreme values. On the other hand, Median (Q2) is less affected by skewness. Putting it together, if the SMA is significantly lower than Q2, then price is regarded as negatively skewed; prices of a few candles are likely exceptionally lower. Vice versa when price is positively skewed.
- Q1 and Q3: as lower and upper bands. As mentioned above, the IQR covers approximately 50% of data within the rolling window. If price is normally distributed, then Q1 and Q3 bands will overlap a bollinger band configured with +/- 0.67x standard deviations (modifying default: 2) above and below the mean.
- The boxplot, combined with TradingView's builtin bar replay feature, makes a great tool for studies purposes. This helps visualization of price at a chosen instance of time. Speaking of which, it can also be used in conjunction with a fixed volume profile to compare and contrast the effects (in terms of price range) with and without consideration of weights by volume.
Parameters :
- Lookback: The size of the rolling window.
- Offset: Location of boxplot, right hand side relative to recent bar.
- Source data: Data points for observation, default is closing price
- Other options such as color, and whether to show/hide various lines.
SuperVos Trade calculatorHave all your trade data in one small overview.
- TP amount in USD and %
- RR of the trade
- Cost if stoploss is hit
- Total profit in USD
- Account growth in percentage
- Sets automatic alerts on SL, entry en TP's if enabled
Enjoy!
Candle DifferenceA simple script to show the price different between the previous candle and all the points of the current open candle. (including: high, low, open)
They are color labeled. (You check what each color means in the settings of the script)
Trade HourThis script is just finds the best hour to buy and sell hour in a day by checking chart movements in past
For example if the red line is on the 0.63 on BTC/USDT chart it mean the start of 12AM hour on a day is the best hour to buy (all based on
It's just for 1 hour time-frame but you can test it on other charts.
IMPORTANT: You can change time Zone in strategy settings.to get the real hours as your location timezone
IMPORTANT: Its for now just for BTC/USDT but you can optimize and test for other charts...
IMPORTANT: A green and red background color calculated for show the user the best places of buy and sell (green : positive signal, red: negative signals)
settings :
timezone : We choice a time frame for our indicator as our geo location
source : A source to calculate rate of change for it
Time Period : Time period of ROC indicator
About Calculations:
1- We first get a plot that just showing the present hour as a zigzag plot
2- So we use an indicator ( Rate of change ) to calculate chart movements as positive and negative numbers. I tested ROC is the best indicator but you can test close-open or real indicator or etc as indicator.
3 - for observe effects of all previous data we should indicator_cum that just a full sum of indicator values.
4- now we need to split this effects to hours and find out which hour is the best place to buy and which is the best for sell. Ok we should just calculate multiple of hour*indicator and get complete sum of it so:
5- we will divide this number to indicator_cum : (indicator_mul_hour_cum) / indicator_cum
6- Now we have the best hour to buy! and for best sell we should just reverse the ROC indicator and recalculate the best hour for it!
7- A green and red background color calculated for show the user the best places of buy and sell that dynamically changing with observing green and red plots(green : positive signal, red: negative signals) when green plot on 15 so each day on hour 15 the background of strategy indicator will change to 15 and if its go upper after some days and reached to 16 the background green color will move to 16 dynamically.
Value At Risk Channel [AstrideUnicorn]The Value at Risk Channel (VaR Channel) is a trading indicator designed to help traders control the level of risk exposure in their positions. The user can select a time period and a probability value, and the indicator will plot the upper and lower limits that the price can reach during the selected time period with the given probability.
CONCEPTS
The indicator is based on the Value at Risk (VaR) calculation. VaR is an important metric in risk management that quantifies the degree of potential financial loss within a position, portfolio or company over a specific period of time. It is widely used by financial institutions like banks and investment companies to forecast the extent and likelihood of potential losses in their portfolios.
We use the so-called “historical method” to compute VaR. The algorithm looks at the history of past returns and creates a histogram that represents the statistical distribution of past returns. Assuming that the returns follow a normal distribution, one can assign a probability to each value of return. The probability of a specific return value is determined by the distribution percentile to which it belongs.
HOW TO USE
Let’s assume you want to plot the upper and lower limits that price will reach within 4 hours with 5% probability. To do this, go to the indicator Settings tab and set the Timeframe parameter to "4 hours'' and the Probability parameter to 5.0.
You can use the indicator to set your Stop-Loss at the price level where it will trigger with low probability. And what's more, you can measure and control the probability of triggering.
You can also see how likely it is that the price will reach your Take-Profit within a specific period of time. For example, you expect your target level to be reached within a week. To determine this probability, set the Timeframe parameter to "1 week" and adjust the Probability parameter so that the upper or lower limit of your VaR channel is close to your Take-Profit level. The resulting Probability parameter value will show the probability of reaching your target in the expected time.
The indicator can be a useful tool for measuring and managing risk, as well as for developing and fine-tuning trading strategies. If you find other uses for the indicator, feel free to share them in the comments!
SETTINGS
Timeframe - sets the time period, during which the price can reach the upper or lower bound of the VaR channel with the probability, set by the Probability parameter.
Probability - specifies the probability with which the price can reach the upper or lower bound of the VaR channel during the time period specified by the Timeframe parameter.
Window - specifies the length of history (number of historical bars) used for VaR calculation.
Opening Price ChangeThis script shows the change from the market opening price to the market closing price of the previous day in percent.
With this you can quickly get an overview of historical data for the change of the respective day.
Important: the market closing price is always used for the calculation and not the pre/post market price.
The label with the change value is always placed above the first opens regular market bar. If the change is positive, the label is draw with a green background, is the change is negative you will have a red background.
SPY Volume Weighted CloseHey everyone!
Deciding to make this indicator public and open access.
This is a volume weighted close indicator for SPY. It is a statistics based indicator.
How it works:
It uses volume data mixed with some price action data to prospectively predict where SPY's price will close within a 30 minute interval.
As such, its different from other indicators in the sense that its not reactive, it proactive and actively predicts the price that SPY will see within the next 30 minutes and where SPY will most likely close at.
It has 3 bands. The main centre band (blue, but colour can be changed) is the most likely price that SPY will close at within the next 30 minutes.
The Upper Level Confidence and Lower Level Confidence bands are the expected range that the analysis thinks SPY will remain confined in based on current volume and price action.
How to Use it:
I personally use this in place of VWAP, but the applications are infinite. Take a look at the chart below:
Applications:
This is specifically programmed for SPY but I have used it with other stocks such as QQQ, UPRO and DIA. However, using it with those stocks, the upper and lower confidence bands are not helpful. But YMMV with other stocks. This is specifically designed for SPY.
Let me know your questions and thoughts!
Thanks for reading and checking this out!
deseasonalized_modDescription:
As in the decomposition of time series data, the indicator was modified from the deseasonalized process, to avoid overfitting as in the original format, aiming to exclude seasonal component (shorter time-period in consideration), thus leaving trend and irregularity. The indicator is expected to identify short-term trends, based on the given timeframe.
Notes:
Length set to 10-bar as default, while reducing the length to e.g. 8 increase more responsive of the fitted data, however inline to increase a false trend identification (bias-variance trade-off). To be noted, the indicator wasn't a momentum indicator, thus can only expect the trend identifier instead. If the price is above the fitted line (indicator), and experiencing a retracement, regularly expected to be bounced around the fitted line (support), while if breaks to the downside, expected a trend reversal, and become a (resistance).
Feature:
Buy/Long overlay signal
Sell/Short overlay signal
Alert
DatasetWeatherTokyoMeanAirTemperatureLibrary "DatasetWeatherTokyoMeanAirTemperature"
Provides a data set of the monthly mean air temperature (°C) for the city of Tokyo in Japan.
this was just for fun, no financial implications in this.
reference:
www.data.jma.go.jp
TOKYO WMO Station ID:47662 Lat 35o41.5'N Lon 139o45.0'E
year_()
the years of the data set.
Returns: array : year values.
january()
the january values of the dataset
Returns: array\ : data values for january.
february()
the february values of the dataset
Returns: array\ : data values for february.
march()
the march values of the dataset
Returns: array\ : data values for march.
april()
the april values of the dataset
Returns: array\ : data values for april.
may()
the may values of the dataset
Returns: array\ : data values for may.
june()
the june values of the dataset
Returns: array\ : data values for june.
july()
the july values of the dataset
Returns: array\ : data values for july.
august()
the august values of the dataset
Returns: array\ : data values for august.
september()
the september values of the dataset
Returns: array\ : data values for september.
october()
the october values of the dataset
Returns: array\ : data values for october.
november()
the november values of the dataset
Returns: array\ : data values for november.
december()
the december values of the dataset
Returns: array\ : data values for december.
annual()
the annual values of the dataset
Returns: array\ : data values for annual.
select_month(idx)
get the temperature values for a specific month.
Parameters:
idx : int, month index (1 -> 12 | any other value returns annual average values).
Returns: array\ : data values for selected month.
select_value(year_, month_)
get the temperature value of a specified year and month.
Parameters:
year_ : int, year value.
month_ : int, month index (1 -> 12 | any other value returns annual average values).
Returns: float : value of specified year and month.
diff_to_median(month_)
the difference of the month air temperature (ºC) to the median of the sample.
Parameters:
month_ : int, month index (1 -> 12 | any other value returns annual average values).
Returns: float : difference of current month to median in (Cº)
Gap Stats v2This helpful analysis tool displays a table of days a stock has gapped, how much it gapped by and what percentage of the gap was covered.
It is meant to be used on the daily timeframe and can help you distinguish if gaps are going to be filled or not. I like to use it mainly on medium + cap stocks
that have gapped overnight or pre-market and see what the tendency is with how it behaves after a major gap.
