Statistical and Financial MetricsGood morning traders!
This time I want to share with you a little script that, thanks to the use of arrays, allows you to have interesting statistical and financial insights taken from the symbol on chart and compared to those of another symbol you desire (in this case the metrics taken from the perpetual future ETHUSDT are compared to those taken from the perpetual future BTCUSDT, used as a proxy for the direction of cryptocurrency market)
By enabling "prevent repainting", the data retrieved from the compared symbol won't be on real time but they will static since they will belong to the previous closed candle
Here are the metrics you can have by storing data from a variable period of candles (by default 51):
✓ Variance (of the symbol on chart in GREEN; of the compared symbol in WHITE)
✓ Standard Deviation (of the symbol on chart in OLIVE; of the compared symbol in SILVER)
✓ Yelds (of the symbol on chart in LIME; of the compared symbol in GRAY) → yelds are referred to the previous close, so they would be calculated as the the difference between the current close and the previous one all divided by the previous close
✓ Covariance of the two datasets (in BLUE)
✓ Correlation coefficient of the two datasets (in AQUA)
✓ β (in RED) → this insight is calculated in three alternative ways for educational purpose (don't worry, the output would be the same).
WHAT IS BETA (β)?
The BETA of an asset can be interpretated as the representation (in relative terms) of the systematic risk of an asset: in other terms, it allows you to understand how big is the risk (not eliminable with portfolio diversification) of an asset based on the volatilty of its yelds.
We say that this representation is made in relative terms since it is expressed according to the market portfolio: this portfolio is hypothetically the portfolio which maximizes the diversification effects in order to kill all the specific risk of that portfolio; in this way the standard deviation calculated from the yelds of this portfolio will represent just the not-eliminable risk (the systematic risk), without including the eliminable risk (the specific risk).
The BETA of an asset is calculated as the volatilty of this asset around the volatilty of the market portfolio: being more precise, it is the covariance between the yelds of the current asset and those of the market portfolio all divided by the variance of the yelds of market portfolio.
Covariance is calculated as the product between correlation coefficient, standard deviation of the first dataset and standard deviation of the second asset.
So, as the correlation coefficient and the standard deviation of the yelds of our asset increase (it means that the yelds of our asset are very similiar to those of th market portfolio in terms of sign and intensity and that the volatility of these yelds is quite high), the value of BETA increases as well
According to the Capital Asset Pricing Model (CAPM) promoted by William Sharpe (the guy of the "Sharpe Ratio") and Harry Markowitz, in efficient markets the yeld of an asset can be calculated as the sum between the risk-free interest rate and the risk premium. The risk premium of the specific asset would be the risk premium of the market portfolio multiplied with the value of beta. It is simple: if the volatility of the yelds of an asset around the yelds of market protfolio are particularly high, investors would ask for a higher risk premium that would be translated in a higher yeld.
In this way the expected yeld of an asset would be calculated from the linear expression of the "Security Market Line": r_i = r_f + β*(r_m-r_f)
where:
r_i = expected yeld of the asset
r_f = risk free interest rate
β = beta
r_m = yeld of market portfolio
I know that considering Bitcoin as a proxy of the market portfolio involved in the calculation of Beta would be an inaccuracy since it doesn't have the property of maximum diversification (since it is a single asset), but there's no doubt that it's tying the prices of altcoins (upward and downward) thanks to the relevance of its dominance in the capitalization of cryptocurrency market. So, in the lack of a good index of cryptocurrencies (as the FTSE MIB for the italian stock market), and as long the dominance of Bitcoin will persist with this intensity, we can use Bitcoin as a proxy of the market portfolio
Sejarah Ketidakstabilan
low and high X Bars//This script finds High and Low X bars back. Simple pine script, can customize lookback period.
Turkey Yield Curve SpreadYield spreads are used to see investors' perception of future risk and predict a recession. The spread is the value obtained by subtracting the near term bond from the distant one. This indicator plots this value historically. I used 3-year and 10-year Turkey treasury bond yields instead of 2-year and 10-year Turkey treasury bond yields due to lack of historical data on Tradingview.
Realized Volatility (annualized for any time frame)Plots standard deviation of returns (realized volatility), and annualizes it for the selected timeframe. Suitable for forex/cryptocurrencies which trade 24/7.
Indices Sector SigmaSpikes█ OVERVIEW
“The benchmark Dow Jones Industrial Average is off nearly 300 points as of midday today...”
“So what? Is that a lot or a little? Should we care?”
-Adam H Grimes-
This screener aims to provide Bird-Eye view across sector indices, to find which sector is having significant or 'out-of-norm' move in either direction.
The significance of the move is measured based on Sigma Spikes, a method proposed by Adam H. Grimes, where Standard Deviation of returns used as a baseline.
*You can google his blog or read his book, got some gold in there, especially on how he use indicators for trading
█ Understanding Sigma Spikes
As described by Grimes, moves in markets are only meaningful when we consider what “normal” is for that market.
Without that baseline, the daily change number, and even the percent change on the day doesn’t really mean much.
To overcome that problem, Sigma Spikes, as a measure of volatility, attempt to put todays change in price (aka return) in context of the standard deviation of 20 days daily's return.
Refer chart below:
1. The blue bars refer to each days return
2. The orange line is 1 time standard deviation of past 20days daily's return (today not included)
3. The red line is 2 time standard deviation of past 20days daily's return (today not included)
Using the ratio of today's return over the Std Deviation, determining your threshold (1,2,3,etc) will be the key that tells if today's move is significant or not.
*Threshold referring to times standard deviation, and different market may require different threshold.
*20 Days period are based on the Lookback Period, adjustable from user input window.
█ Features
- Scan up to 13 symbols at a time (Bursa (MYX) indices are defaulted, but you may change to any symbols/index from the user input setting)
█ Limitation
- Due to multiple use of security() function required to call other symbols, expect the screener to be slow at certain times
- Custom Timeframe currently accept only Daily and Weekly. I'll try to include lower timeframe in the next update
█ Disclaimer
Past performance is not an indicator of future results.
My opinions and research are my own and do not constitute financial advice in any way whatsoever.
Nothing published by me constitutes an investment recommendation, nor should any data or Content published by me be relied upon for any investment/trading activities.
I strongly recommends that you perform your own independent research and/or speak with a qualified investment professional before making any financial decisions.
Any ideas to further improve this indicator are welcome :)
Candle Height in Percentage - ColumnsThis indicator calculates the difference in percentage between lows and highs of a candle. The orange bars show the height of the candle body (open/close) and the red/green on top show the percentage of the wicks (high/low). This assists in understanding the volatility of an asset. Showing this in percentages is more helpful in crypto. It also shows the Simple Moving Average of this data with the blue line.
Average Low/High Percentage DifferenceThis indicator calculates the Simple Moving Average of the difference in percentage between lows and highs of a candle. This assists in understanding the volatility of an asset. Showing this in percentages is more helpful in crypto.
ADR% - Average Daily Range % by MikeC (AKA TheScrutiniser)This applies a 'corrected' formula to the version created by alpine_trader (which is slightly off). It calculates the Average Daily Range (in percent) over the previous 20 periods and plots it in a chart.
I am grateful to GlinckEastwoot for the 'corrected' formula.
OnTheMoveWith this plot one is able to compare the different % change in the given time frame. It calculates the sma of a given period (defval = 7) for the close/open.
Strategy would be to choose (trade) from one to other asset in order to get higher rates when pumping or lower when dumping.
The Symbol & exchange has to be specified.
defSymbols = BTC, ETH and LINK
defExchange = BINANCE
GBTC Fomo Panic PremiumIt is rumored that GBTC price action leads the Bitcoin market. This indicator compares GBTC fomo/panic levels to the (Binance) BTC spot market. Fomo is measured as large percentage moves of the high price from the min over a look-back period. Panic is measured as large percentage moves of the low price from the max over a look-back period. A prime example of this indicator's usage would be as a sell signal confirmation during the 2020 pre-Thanksgiving panic exhibited on the 1-hour chart while the 20 EMA was still above the 99 SMA.
You can customize the leading and lagging markets and the length of the lookback period. I would love to hear what parameters, markets and timeframes work for you. Maybe there is a way to leave comments, or hit me up on Twitter: @thirdreplicator
May you profit and enjoy.
Volatility Prism [Nic]What is this
The volatility rainbow tracks divergences in a security and its volatility index. This can be used to identify periods of heightened implied (future) risk.
About Volatility
The volatility is calculated by looking at put / call ratios. When VIX goes up it means that puts are outpacing calls. This is a bearish signal.
About Correlation
When the security goes up while the VIX goes up, the divergence on the plot will increase and turn a color. This should be a warning.
Volatility Rainbow
This is a similar indicator, but this one merges all signals into a single line.
IV/HV Ratio's [Nic]IV is implied volatility
HV is historic realized volatility
Seneca teaches that we often suffer more in our minds than in reality, and the same is true with the stock market. This indicator can help identify when people are over paying for implied volatility relative to real volatility . This means that short sellers are over paying for puts and can be squeezed into covering their positions, resulting in a massive rally.
The indicator can track this spread over many time frames, when the short time frame is much higher than the lower time frames, consider it a signal-of-interest.
Divergence Indicator [Nic]This divergence indicator can track the correlation between one or more symbols. I use it to track the divergences between the VIX volatility index, gold, bonds, as well as other market leading indicators.
When using with Vix, lower coefficients can lead to false signals. When in a high vix bear market signals, there is more noise and more false (or missing) signals can occur. Please use with other technical tools.
True Range in %I like to look at volatility in percentage and not in numbers. This is exactly what this script provides. It calculates the true range of a candle in percentage to the current price (for finished candles it uses it's close price).
The script also allows you to compare open and close prices.
2HLA very simple, almost naive strategy, in which you buy on the lowest of the two previous candles and sell at the highest of the two previous candles. You can configure these highest and lowest lenght, in some assets two is too small of a number to make profit. You can also configure to exit the position after X, and I found that 7 (which is a week of working days) is a good number for that.
This is strategy is intended to be used as a swing trade. Your capital needs to be high enough so that it can pay the operaitonal costs, and reach it's target with a reasonable profit.
Since this is a volatility based strategy, assets that are more liquid won't work properly.
Pisani BandsThis indicator is based on Historical Volatility.
It's plot the simple moving average with a upper and a lower band.
The bands are calculated like this:
UpperBand = 20 Simple moving average + 20% * Historical volatility
LowerBand = 20 Simple moving average - 20% * Historical volatility
But, you can change the paramters. I use the 200SMA with 100% of Historical Volatility either.
How to use:
If the price are negociating out of the bands, it's dangerous to trade this stock.
Hope you like it.
Long/Short Margin Ratio for cryptocurrenciesBTCUSDSHORTS and BTCUSDLONGS are like datasets provided by Bitfinex exchange. They record the number of margined for longs and shorts and they are measured in BTC (in case using BTCUSD ).
Margin is Like any loan, the borrower may pay interest while the loan is outstanding, and must eventually pay the loan back.
Red Area: More short margin than long margin.
Green Area: More long margin than short margin.
Note: Can only be used with cryptocurrencies that have such dataset within Bitfinex exchange like BTCUSD , ETHUSD , XRPUSD and a few more.
3 Leg Short Strangle BandsDraws 3 leg bands along with safe zone(green lines) based on input
1) Input ATR, Week Day, Current Market Close
2) Input ATR - Previous day 1H Max ATR
3) ADX < 25
4) Input Current Market Close
5) Trading Day - Mon/Tue/Wed/Thu/Fri - Bands distance calculated based on day M/Tu/F 2*(Max ATR), W/Th 1.5(ATR)
6) Safe zone green lines - CMPCls +/- (1.5 * Max ATR)
7) Leg 1 Upper Lower Legs - M/Tu/F - CMPCls +/-(2 * Max ATR), W/Th - CMPCls +/-(1.5 * ATR)
8) Leg 2 & 3 Calculates based on Leg 2 = Leg 1 +/- 100 pts distance, Leg 3 = Leg 2 +/- 100 pts distance'
9) All figures rounded to nearest 100's
10) Safe zone broken exit all positions
This is a popular technic used by Profitable traders on sideway markets for Intraday
One can keep 3K as SL per 1 set of 3 legs for better R:R
NIFTY VIX Bands1) The script takes current INDIA VIX as input Daily time frame for NIFTY
2) Used a Formula VIX Value / Square root of Time Period
3) Change Timeframe input accordingly 1 Year = 1, Monthly = 12, Weekly = 52, Daily = 365
4) based point 2 formula with 1 standard deviation it creates upper & lower range bands
5) This is generally used for option selling by big traders they go and sell above the band strikes
Standard Deviation Volatility HelperHere is a simple Standard Deviation Line based on supply and demand that will help you to find expected move easily. 3 Standart Deviation merged line available. Number of days and adjustable length.
Geometric Brownian Motion BandIf you are an option trader, who are constantly searching opportunities to set up inverse iron condor position or other strategies, you must be familiar in estimating the range induced by Geometric Brownian Motion (GBM), or Lognormal distribution someone may call.
The theory behind is adopted in the Black Scholes Option Pricing model, this assumes the asset price follows the GBM, shown below, and estimates the range where the price will fall into on the specific date and probability.
dS = a dt + v dW
Assuming the drift term is zero, this GBM Band applies the same model and helps you to quickly assess the suitable range to set up your option strategies with simple setting:
Length – number of bars covered
Vol Multiple - the z-score of the probability
Default values of the Length and Vol Multiple are set to 20 bars and 2.0 z-score respectively.
You can find an example how the GMB Band work.
You can also applies this GMB Band like how Bollinger's Band does for swing trade or breakaway trade.
If you find this indicator is useful to you, Star it, Follow, Donate, Like and Share.
Your support is a highly motivation for me.
Historical Volatility Percentile: Price and VolumeThis is an expansion of the Historical Volatility scripts to include both price and volume volatility.
As Tradingview states :
Historical Volatility is a measure of how much price (and now volume ) deviates from its average in a specific time period that can be set. The more price (or/and volume ) fluctuates, the higher the indicator value. Please note it does not measure the direction of price (and volume ) changes, just how volatile price/ volume has become. There are several reasons to care about volatility but it's mainly a risk measure. As volatility increases, so does risk and uncertainty and vice versa. Traders can use the indicator to flag instruments with high volatility which could point to a trend change. It is often used in combination with other signals.
Example options
Example formats
Link back to some other great ideas:
@Cheatcountry with his prolific sharing , what a great inspiration.
@Picte and his inspired idea .
@Balipour and his great script
Comparing this to other significant HVP indicators
Realized Volatility IIR Filters with BandsDISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is following TradingView's regulations. Use of indicator and their code are published by Invitation Only for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED AS TESTING. The models included in the indicator have been taken from open sources on the web and some of them has been modified by the author, problems could occur at diverse data sceneries.
WHAT'S THIS...?
Work derived by previous own research for study:
This is mainly an INFINITE IMPULSE RESPONSE FILTERING INDICATOR , it's purpose is to catch trend given by the nature of lag given by a VOLATILITY ESTIMATION ALGORITHM as it's coefficient. It provides as well an INFINITE IMPULSE RESPONSE DEVIATION FILTER that uses the same coefficients of the main filter to plot deviation bands as an auxiliary tool.
The given Filter based indicator provides my own Multi Volatility-Estimators Function with only 3 models:
ELASTIC VOLUME WEIGHTED VOLATILITY : This is a Modified Daigler & Padungsaksawasdi "Volume Weighted Volatility" as on DOI: 10.1504/IJBAAF.2018.089423 but with Elastic Volume Weighted Moving Average instead of VWAP (intraday) for faster (but inaccurate) calculation. A future version is planned on the way using intra-bar inspection for intraday timeframe as described in original paper.
GARMAN & KLASS / YANG-ZANG EXTENSION : As one of the best range based (OHLC) with open gaps inclusion in a single bar.
PETER MARTIN'S ULCER INDEX : This is a better approach to measure realized volatility than standard deviation of log returns given it's proven convex risk metric for DrawDowns as shown in Chekhlov et al. (2005) . Regarding this particular model, I take a different approach to use it as coefficient feed: Given that the UI only takes in consideration DrawDawns, I code myself the inverse of this to compute Draw-Ups as well and use both of them to filter minimums volatility levels in order to create a SLOW version of the IIR filter, and maximums of both to calculate as FAST variation. This approach can be used as a better proxy instead of any other common moving average given that with NO COMPOUND IN TIME AT ALL (N=1) or only using as long as N=3 bars of compund, the filter can catch a trend easily, making the indicator nearly a NON PARAMETRIC FILTER.
NOTES:
This version DO NOT INCLUDE ALERTS.
This version DO NOT INCLUDE STRATEGY: ALL Feedback welcome.
DERIVED WORK:
Incremental calculation of weighted mean and variance by Tony Finch (fanf2@cam. ac .uk) (dot@dotat.at), 2009.
Volume weighted volatility: empirical evidence for a new realised volatility measure by Chaiyuth Padungsaksawasdi & Robert T. Daigler, 2018.
Basic DSP Tips & Trics by TradingView user @alexgrover
CHEERS!
@XeL_Arjona 2020.
