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2019

3/2 Stochastic Volatility ProxyThis indicator, "3/2 Stochastic Volatility Proxy", implements a realized volatility model that incorporates advanced digital signal processing techniques, such as Butterworth filtering, super smoothing, RMS normalization, and optionally Z-Score transformation, to capture and visualize shifts in market volatility. 🔍 Indicator Overview: "3/2 Stochastic Volatility Proxy" 🎯 Purpose To act as a momentum-based volatility proxy, estimating realized volatility and applying a 3/2 power transformation—a known mathematical volatility model—to better detect volatility regimes and potential price explosions or contractions. 📐 Core Mathematical Model: The 3/2 Stochastic Volatility Model The 3/2 stochastic volatility model is defined in continuous time as: 🔑 Key Idea: The variance follows a mean-reverting process, but the diffusion term has scaling. This makes the volatility more reactive to spikes, creating more realistic behavior for modeling risk, especially under high-volatility periods (tail events). 🧠 Indicator Components Explained 1. 🧮 Realized Variance Estimation pinescript Copy Edit ret = math.log(close / close ) // Log returns vari = ta.sma(ret * ret, length) // Realized variance volatility_proxy = math.pow(vari, 1.5) // Raise to 3/2 power This transforms log returns into variance using a simple moving average. The variance is then raised to the 3/2 power, per the 3/2 volatility model. 2. 🧹 Smoothing Options Two smoothing techniques are available: ✅ Option 1: Z-Score Smoothing (Ehlers Loop logic) pinescript Copy Edit f_zscore(volatility_proxy, smoothing) Normalizes the series to its statistical deviation from the mean. Useful for spotting regime changes (e.g., +2σ or -2σ extremes). ✅ Option 2: RMS Scaled Filtering pinescript Copy Edit scaledFilt(volatility_proxy, ..., ..., ...) This applies three steps: Butterworth Highpass Filter → Removes slow drift, isolates cycles. Super Smoother Filter → Reduces aliasing and short-term noise. Fast RMS Normalization → Stabilizes the scale across varying regimes. 🛠 Filters and Utilities (Detailed) 🔸 butterworthHP() A 2-pole high-pass filter that removes low-frequency trends to highlight cyclic components of volatility. 🔸 superSmoother() Ehlers’ 2-pole smoother that attenuates high-frequency noise more effectively than EMA or SMA. 🔸 fastRMS() An efficient way to estimate root mean square, normalizing the filtered signal to control amplitude. 📈 Plot and Alerts 🔸 plot(smoothed_vol) Plots the smoothed, normalized volatility proxy: Above 0 → Rising volatility. Below 0 → Falling volatility. Above +2σ / Below -2σ → Extreme volatility alerts. 🔸 Alert Conditions: 🔔 Cross Above 0 → Bullish volatility expansion. 🔔 Cross Below 0 → Bearish contraction or mean reversion. 🔔 Crossing ±2σ → Overheated or overcooled volatility zones. 🧪 Practical Use Cases Volatility Momentum Proxy Use this as a signal that volatility is accelerating (breakout environment). Risk-on / Risk-off Filter High values may warn of regime shifts; low values indicate calm markets. Pair with Trend or Mean-Reverting Strategies Helps determine if the current volatility favors breakouts or reversions.
Pine Script®指標
由GabrielAmadeusLau提供
COVID19 New Cases & Threshold per 100k inhabitantsGoal is to be able to keep track of new COVID cases and see when the relative threshold is passed. The default threshold is set to 10 new cases per 100.000 inhabitants per 14-days, please change the available inputs to change this metric Out of curiosity I've added the population density. Because people generally live and socially interact on land I've used the land-area for population density calculation. When comparing metrics between countries there are many more factors to be considered. Create your own symbol list for the CONFIRMED tickers: Create a new list Paste the following text where you would add a symbol: COVID19:CONFIRMED_AT,COVID19:CONFIRMED_BE,COVID19:CONFIRMED_DK,COVID19:CONFIRMED_FI,COVID19:CONFIRMED_FR,COVID19:CONFIRMED_DE,COVID19:CONFIRMED_IS,COVID19:CONFIRMED_IE,COVID19:CONFIRMED_IT,COVID19:CONFIRMED_LV,COVID19:CONFIRMED_LI,COVID19:CONFIRMED_LT,COVID19:CONFIRMED_LU,COVID19:CONFIRMED_MT,COVID19:CONFIRMED_MD,COVID19:CONFIRMED_MC,COVID19:CONFIRMED_NO,COVID19:CONFIRMED_PL,COVID19:CONFIRMED_PT,COVID19:CONFIRMED_RO,COVID19:CONFIRMED_RU,COVID19:CONFIRMED_SK,COVID19:CONFIRMED_SI,COVID19:CONFIRMED_ES,COVID19:CONFIRMED_SE,COVID19:CONFIRMED_CH,COVID19:CONFIRMED_TR,COVID19:CONFIRMED_UA,COVID19:CONFIRMED_AE,COVID19:CONFIRMED_AR,COVID19:CONFIRMED_AU,COVID19:CONFIRMED_BR,COVID19:CONFIRMED_CA,COVID19:CONFIRMED_CL,COVID19:CONFIRMED_CN,COVID19:CONFIRMED_CO,COVID19:CONFIRMED_HR,COVID19:CONFIRMED_ID,COVID19:CONFIRMED_IL,COVID19:CONFIRMED_IN,COVID19:CONFIRMED_IR,COVID19:CONFIRMED_JP,COVID19:CONFIRMED_KR,COVID19:CONFIRMED_KW,COVID19:CONFIRMED_MX,COVID19:CONFIRMED_MY,COVID19:CONFIRMED_NZ,COVID19:CONFIRMED_PE,COVID19:CONFIRMED_PH,COVID19:CONFIRMED_SG,COVID19:CONFIRMED_TH,COVID19:CONFIRMED_US,COVID19:CONFIRMED_US_AZ,COVID19:CONFIRMED_US_CA,COVID19:CONFIRMED_US_FL,COVID19:CONFIRMED_US_IL,COVID19:CONFIRMED_US_MA,COVID19:CONFIRMED_US_NC,COVID19:CONFIRMED_US_NJ,COVID19:CONFIRMED_US_NY,COVID19:CONFIRMED_US_TX,COVID19:CONFIRMED_UZ,COVID19:CONFIRMED_VE,COVID19:CONFIRMED_ZA
Pine Script®指標
由finn提供
Major Event Price Indicators (Coronavirus Lows)This very simple script adds a corridor for two low price ranges, where Corona started to hit. Useful to visualize where a stock currently trades at, relative to the Corona / Covid-19 crisis. Can easily be adjusted for different dates regarding any major events, crashes. Useful when you run out of Alarms and just want to see "is that still below or above where it was before ?". Add as many dates as you want, just alter the names of each indicator. Built upon the script of vitvlkv.
Pine Script®指標
由UnknownUnicorn7544112提供
COVID-19 Case ComparisonDuring this global pandemic, there is limited information available on the COVID-19 disease itself. However one thing we do have is data; and we get more of this every day. Use this indicator to track the live number of new cases each day, along with the current mortality, recovery, and transmission rates. Easily switch data output between multiple countries. If you don't see your country available, please comment below and I will gladly add it.
Pine Script®指標
由oh92提供
COVID-19: Daily change per capita (EU only)New confirmed cases per day (daily change) is one thing, just an absolute value but when we put this number in context of population (per million people) of each country the situation is a bit different. We can easily see that, at the moment (Apr 2nd, 2020), the most affected country is Spain (~150 new cases per million people per day) and surprisingly the second one is Switzerland (CH). We can also see Spain or Belgium's steep curve relative to other countries. I know that some countries run more tests than the others and the outcome might not be reflect the reality but this is the official data that is available.
Pine Script®指標
由icostan提供
COVID-19: Daily momentumThis indicator shows 14-days moving average of daily rate of change (momentum, acceleration), in other words: - up trends means that virus accelerates at the rate displayed on the right scale - consolidation/horizontal movement - virus spreads at constant rate - down trend - virus looses momentum IMPORTANT: the virus STILL accelerates but at a lower rate By default the graphic displays World vs. EU vs. US vs. Asia while individual countries are available in Settings. - EU includes the following countries (DE, FR, IT, ES, CH), all with more than 10k confirmed cases and more than 1k new daily infections. - Asia includes CH and KR To use the indicator it is important to disconnect main chart from the right scale, on main chart click on More (the 3 dots) -> Pin to scale -> Select "No Scale".
Pine Script®指標
由icostan提供
Covid-19 CFR, Difference Indicator [Bitduke]Simple indicator to track case fatality rate and difference in deaths | recovered cases for novel coronavirus. It could help to trace the impact on the stock market and cryptocurrencies. Case fatality rate (CFR) - an indicator equal to the ratio of the number of deaths from a disease to the number of patients with this disease for a certain period of time. That is, if CFR = 30% it means one died, two cured out of 3 infected. The percentage change between recovered cases The percentage change between deaths Assumption It can be assumed that if we consider bitcoin as a store of value, then when the situation getting worse (CFR + deaths difference increase and recovery difference decreases) bitcoin price tends to rise and vice versa. But this is only an assumption that requires additional tests; there is still little data for a robust statistical analysis.
Pine Script®指標
由Bitduke提供