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Inverted Yield Curve with VIX Fear IndexUS 2 year and US 10 year comparison, inverted yield curve with VIX. I use this on a weekly chart with 2 moving averages, the 40 week (ma200 daily) and the 520 week (10 year median). The bottom histogram is the VIX and the plot is the yield curve. When the VIX is above a certain level (you can set it in settings) and the ýield curve is close to or at inversion the background goes red. The last seven recessions were preceded by an inverted yield curve. Here I combined the two main fear indexes, the VIX and the run for safe US treasuries (Inverted Yield Curve). This is preset to the 2 year and 10 year US bond, weekly, and the normal VIX ticker but you can set it to whatever you like. Published with source code for anyone to modify. Please comment below if you do so! This is the second in a series of indicators I intend to publish as a package of economic recoverty/recession symptom indicators. Follow me for updates, next one up is commodities with dr Copper and oil!
Penunjuk Pine Script™
oleh monotones
2
ka66: Volatility MomentumThis is a 'monitoring' indicator to see if an instrument is viable enough to be traded, by virtue of volatility (or lack of volatility in context may lead to a break out), or may become so. It shows the following information: Price Range (high - low) averaged across a set of bars: Useful gauging potential trading profits. This was its initial goal, to not measure bars manually! ATR : As a comparison point for the price range above. Divergence between true range (TR) and plain price range might signal volatility changes occurring in the instrument. Signal volatility line : a moving average of the larger of the average price range and ATR. This takes inspiration from other indicators like MACD and Stochastic, and is a way of comparing change in recent volatility --- this achieves the momentum part. The larger was chosen to keep things simple, and not have a signal line per range! avgRange = movingAvg(high - low, avgPeriod) atr = movingAvg(trueRange, avgPeriod) signal = movingAvg(max(avgRange, atr), avgPeriod) Configurable periods and averaging mechanism.
Penunjuk Pine Script™
oleh ka66
4
OHLC Volatility Estimators by @Xel_arjonaDISCLAIMER: 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 embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is by Creative-Commons as TradingView's regulations. Any use, copy or re-use of this code should mention it's origin as it's authorship. WARNING NOTICE! THE INCLUDED FUNCTION MUST BE CONSIDERED AS DEBUGING CODE The models included in the function have been taken from openly sources on the web so they could have some errors as in the calculation scheme and/or in it's programatic scheme. Debugging are welcome. WHAT'S THIS? Here's a full collection of candle based (compressed tick) Volatility Estimators given as a function, openly available for free, it can print IMPLIED VOLATILITY by an external symbol ticker like INDEX:VIX. Models included in the volatility calculation function: CLOSE TO CLOSE: This is the classic estimator by rule, sometimes referred as HISTORICAL VOLATILITY and is the must common, accepted and widely used out there. Is based on traditional Standard Deviation method derived from the logarithm return of current close from yesterday's. ELASTIC WEIGHTED MOVING AVERAGE: This estimator has been used by RiskMetriks®. It's calculation is based on an ElasticWeightedMovingAverage Standard Deviation method derived from the logarithm return of current close from yesterday's. It can be viewed or named as an EXPONENTIAL HISTORICAL VOLATILITY model. PARKINSON'S: The Parkinson number, or High Low Range Volatility, developed by the physicist, Michael Parkinson, in 1980 aims to estimate the Volatility of returns for a random walk using the high and low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval. n=10, 20, 30, 60, 90, 120, 150, 180 days. ROGERS-SATCHELL: The Rogers-Satchell function is a volatility estimator that outperforms other estimators when the underlying follows a Geometric Brownian Motion (GBM) with a drift (historical data mean returns different from zero). As a result, it provides a better volatility estimation when the underlying is trending. However, this Rogers-Satchell estimator does not account for jumps in price (Gaps). It assumes no opening jump. The function uses the open, close, high, and low price series in its calculation and it has only one parameter, which is the period to use to estimate the volatility. YANG-ZHANG: Yang and Zhang were the first to derive an historical volatility estimator that has a minimum estimation error, is independent of the drift, and independent of opening gaps. This estimator is maximally 14 times more efficient than the close-to-close estimator. LOGARITHMIC GARMAN-KLASS: The former is a pinescript transcript of the model defined as in iVolatility . The metric used is a combination of the overnight, high/low and open/close range. Such a volatility metric is a more efficient measure of the degree of volatility during a given day. This metric is always positive.
Penunjuk Pine Script™
oleh xel_arjona
14
Historical Volatility Strategy Backtest Strategy buy when HVol above BuyBand and close position when HVol below CloseBand. Markets oscillate from periods of low volatility to high volatility and back. The author`s research indicates that after periods of extremely low volatility, volatility tends to increase and price may move sharply. This increase in volatility tends to correlate with the beginning of short- to intermediate-term moves in price. They have found that we can identify which markets are about to make such a move by measuring the historical volatility and the application of pattern recognition. The indicator is calculating as the standard deviation of day-to-day logarithmic closing price changes expressed as an annualized percentage. Please, use it only for learning or paper trading. Do not for real trading.
Strategi Pine Script™
oleh HPotter
2
Historical Volatility Strategy Strategy buy when HVol above BuyBand and close position when HVol below CloseBand. Markets oscillate from periods of low volatility to high volatility and back. The author`s research indicates that after periods of extremely low volatility, volatility tends to increase and price may move sharply. This increase in volatility tends to correlate with the beginning of short- to intermediate-term moves in price. They have found that we can identify which markets are about to make such a move by measuring the historical volatility and the application of pattern recognition. The indicator is calculating as the standard deviation of day-to-day logarithmic closing price changes expressed as an annualized percentage.
Penunjuk Pine Script™
oleh HPotter
7
We Are Witnessing A Historical Event With A Clear Outcome!!!"Full Disclosure: I came across this information from www.SentimenTrader.com I have no financial affiliation…They provide incredible statistical facts on The General Market, Currencies, and Futures. They offer a two week free trial. I Highly Recommend. The S&P 500 has gone 43 trading days without a 1% daily move, up or down. which is the equivalent of two months and one day in trading days. During this stretch, the S&P has gained more than 4%, and it has notched a 52-week high recently as well. Since 1952, there were nine other precedents. All of these went 42 trading days without a 1% move, all of them saw the S&P gain at least 4% during their streaks, and all of them saw the S&P close at a 52-week highs. ***There was consistent weakness a week later, with only three gainers, and all below +0.5%. ***After that, stocks did better, often continuing an Extraordinary move higher. Charts can sometimes give us a better nuance than numbers from a table, and from the charts we can see a general pattern - ***if stocks held up well in the following weeks, then they tended to do extremely well in the months ahead. ***If stocks started to stumble after this two- month period of calm, however, then the following months tended to show a lot more volatility. We already know we're seeing an exceptional market environment at the moment, going against a large number of precedents that argued for weakness here, instead of the rally we've seen. If we continue to head higher in spite of everything, these precedents would suggest that we're in the midst of something that could be TRULY EXTRAORDINARY.
Penunjuk Pine Script™
oleh ChrisMoody
12