Multi-indicador MACD/RSI/volumen en ventanaComplemento para el otro indicador que ya publiqué.
En esta caso añado las gráficas de MACD, RSI y volumen en una sola ventana.
El problema para esto es el escalado de las gráficas del MACD y el volumen para que entren en una escala de 1 a 100 para lo que tomo los máximos y mínimos de 500 velas (este valor se puede cambiar).
Adicionalmente, coloreo el macd de verde cuando sobrepasa a la señal o de rojo cuando va por debajo y lo mismo con el rsi.
Añado el volumen a todo esto, también escalado.
Tìm kiếm tập lệnh với "标普500+指数+构成"
TICK gapUsed with the "Cumulative TICK", highlights a gap up candle in yellow and a gap down candle in white, then plots a line 500 points away, signalling a counter trend entry.
Stochastic & MACD Strategy Ver 1.0This strategy is inspired by ChartArt and jasonluk28.
The following input changes from the initial ChartArt version to achieve higher stability and profit:
Fast MA Len:11
Slow MA len: 24
Stoch Len: 20
No difference is found in minor changes (+-10) lv. of overbought/oversold
It works above 40% winning rate in Heng Heng Index, Shanghai Composite, Dow Jones Industrial Averge, S&P 500 NASDAQ, VT (World Total Market) and in 15 mins chart
Profit: above ~10 to 30% in less than 1year backtest for most major indice of China and US and ~62% in Heng Seng Index (Hong Kong) & 40.5% in SZSE Composite (Shen Zhen)
P.S. Profit: 700 (Tencent) +150.5%, 939 (CCB) +66.5%, 1299 (AIA) +45%, 2628 (CLIC) +41%, 1 (CK Hutchison) +31%
NFLX +82.5%, BABA +55.5%, AMZN +44%, GOOG +38%, MCD +24.5%
However, Loss in FB -19% , AMD -38.5%
Not suitable for stocks with great influences in News or Events ???
Fibonacci Guppy EMAGuppy EMA that uses fibonacci numbers instead of standard guppy numbers.
EMA's used: 1, 2, 3, 5, 8, 13, 15, 21, 34, (50), 55, 89, (100), 144, (200), (500), (1000)
IV/HV ratio 1.0 [dime]This script compares the implied volatility to the historic volatility as a ratio.
The plot indicates how high the current implied volatility for the next 30 days is relative to the actual volatility realized over the set period. This is most useful for options traders as it may show when the premiums paid on options are over valued relative to the historic risk.
The default is set to one year (252 bars) however any number of bars can be set for the lookback period for HV.
The default is set to VIX for the IV on SPX or SPY but other CBOE implied volatility indexes may be used. For /CL you have OVX/HV and for /GC you have GVX/HV.
Note that the CBOE data for these indexes may be delayed and updated EOD
and may not be suitable for intraday information. (Future versions of this script may be developed to provide a realtime intraday study. )
There is a list of many volatility indexes from CBOE listed at:
www.cboe.com
(Some may not yet be available on Tradingview)
RVX Russell 2000
VXN NASDAQ
VXO S&P 100
VXD DJIA
GVX Gold
OVX OIL
VIX3M 3-Month
VIX6M S&P 500 6-Month
VIX1Y 1-Year
VXEFA Cboe EFA ETF
VXEEM Cboe Emerging Markets ETF
VXFXI Cboe China ETF
VXEWZ Cboe Brazil ETF
VXSLV Cboe Silver ETF
VXGDX Cboe Gold Miners ETF
VXXLE Cboe Energy Sector ETF
EUVIX FX Euro
JYVIX FX Yen
BPVIX FX British Pound
EVZ Cboe EuroCurrency ETF Volatility Index
Amazon VXAZN
Apple VXAPL
Goldman Sachs VXGS
Google VXGOG
IBM VXIBM
Quadratic RegressionA quadratic regression is the process of finding the equation that best fits a set of data.This form of regression is mainly used for smoothing data shaped like a parabola.
Because we can use short/midterm/longterm periods we can say that we use a Quadratic Least Squares Moving Average or a Moving Quadratic Regression.
Like the Linear Regression (LSMA) a Quadratic regression attempt to minimize the sum of squares (sum of the squared difference between a set of data and an estimator), this is why
those kinds of filters have low lag .
Here the difference between a Least Squared Moving Average ( green ) and a Quadratic Regression ( red ) of both period 500
Here it look like the Quadratic Regression have a best fit than the LSMA
basic fixed fraction strategyOne of the most common trading strategy is to invest a certain percentage in an asset, and keep the percentage fixed. For example you invest 2% in a stock, and as the value goes up you sell. And as the value goes down you buy. Always trying to keep the value of how much you have invested in that asset at 2%.
This works very well with assets that are stable. If you have something that fluctuates around a value, you will find yourself that each time it has gone back to the value in which you entered, you have actually gained something. With an asset that grows it also works. But in general you might find that more aggressive investments are more profitable. On the other side if there is a bubble, and you invest from the beginning using this strategy you will find yourself at the end of the bubble having gained something. Not as much as having bought all at the beginning and having sold all at the end, but still you will have sold going up, and bought going down. Plus you will have gained in the fluctuation.
Where is instead very dangerous is in stock and assets that go to zero. This because you might invest just 2% in an investment. But then as the strategy works you keep investing more as you are trying to keep 2%. You basically can lose all your money in this way (like if you were invested 100% in an asset). Very dangerous. This is why you should only use this with assets that you are sure cannot go to zero (an ETF on S & P 500 could be a good example).
So I coded this strategy on TradingView. basically it will ask you what percentage you want to invest. Then starts with entering with an order of that amount, and will then keep sitself at the same percentage. The system is discrete, as it can only buy a discrete number of contract.
Note that if you use this for cryptocurrency (where you can buy a fraction of a coin, like 0.01 btc) then you should multiply the money that you have by 10, 100, 1000 ... depending on how many digits after the comma your exchange permit you to trade.
If you are using this for forex or crypto it is quite easy that the number of order will explode. As such I added the date range taken from Allanster great script
One way to use Fixed Fractioning is to calculate the Kelly Index of an asset (which will give you a percentage), and then invest half or a quarter of the kelly in that coin, and then keep this fixed.
Another way (which goes well beyond what this script can do alone) to use the Fixed Fractioning is, if you have two assets that are anticorrelated (has a negative correlation), then investing a certain percentage of your capital in one and another percentage in another. And then each time one goes up (and the other goes down) you sell the one that is going up, and buy the one that is going down to keep the percentages fixed.
Something else, it is pretty common for people to invest around 80% of their money in an ETF that follows tha S&P500. This is why here we use 80%. Generally I have seen a more common investment strategy to be around 2%.
As everybody says: I am not responsible for your money. Study before investing.
Smart Money Index (SMI) Backtest Attention:
If you would to use this indicator on the ES, you should have intraday data 60min in your account.
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
You can change long to short in the Input Settings
WARNING:
- For purpose educate only
- This script to change bars colors.
Smart Money Index (SMI) Strategy Attention:
If you would to use this indicator on the ES, you should have intraday data 60min in your account.
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
WARNING:
- This script to change bars colors.
Retrospective Candlestick ChartWhen i was in Japan with some traders colleagues we talked about traditional charting tools from this country and how they changed the way we look at our charts today. Then suddenly one of the japanese traders i have met earlier said "Why not making another charting tool ? Smoother than Heikin-Ashi and including all the information a trader may need but easier to interpret".
So i had the idea of averaging the input and the output of the respective close / open / high and low price using a recursive exponential window functions, each values will be closer to their true value if they are volatile, if they are not then those values will look smoother, the length input represents the reactivity of the candles, high values represents smoother results but less reactive.The goal of those candles is to make all the information easier to interpret by a trader.
500 input length , the price look smoother, supports and resistances are easier to make.
The interpretation of highs and lows are important, the Retrospective Candlestick Chart save you time by showing only huge movements.
USDJPY Assumption v1Based on the "logical trading" post of Charles Cornley (thanks!).
Indicator States:
Very Bullish (Lime) = USD trend rising and JPY trend falling and Gold trend falling and US 10Y Bond trend falling and
Dow Jones trend rising and Nasdaq trend rising and Russell 2000 trend rising and
S&P 500 trend rising and Nikkei 225 trend rising
Bullish (Green) = USD trend rising and JPY trend falling
Bearish (Red) = USD trend falling and JPY trend rising
Fibonacci ClustersI was reading about Fibonacci Clusters on investopedia (www.investopedia.com) and couldn't find a script for it on tradingveiw. Apparently some people use it successfully but I found it a little chaotic. This script will mark the retracements in a window's length, and you can set this for six windows. This script isn't very pretty because it doesn't seem obviously useful and pinescript has far too many deficiencies to fully flesh this idea out. I was able to make more sense out of larger windowing times (500-4000 periods), than shorter ones (25-333). Try it out, see what it shows you. Happy trading
ATR%A useful measure of recent volatility. I use 50 day or 50 week periods, but you can experiment with other values too. Because it measures ranges as a % of current close it can be used to make good comparisons with other historic periods of low (or high) volatility. This measure reached a new 23 year low for daily S&P 500 in July 2017.
Uses and historic examples: lunatictrader.com
Hersheys CoCo VolumeCoCo Volume shows you volume movement of your symbol after subtracting the movement from another symbol, preferrably the sector or market the stock belongs to.
My latest update to my CoCoVolume Indicator. It calculates today's volume percent over the 60 period average for both your symbol and index, and displays that difference. If the percent is over the max it highlights the color, showing BIG action for that stock.
The last version was calculating the percent volume difference from yesterday to today for the stock and index and displaying the difference. The prior method had large swings on low volume stocks... this one shows the independent volume action much better. The default values will suit most stocks.
You can set three variables...
- the index symbol, default is SPY
- the period for averaging, default is 60
- the max volume percent, default is 500
Good trading!
Brian Hershey
Auto Flag Distribution DaysThis script automatically flags distribution days. Distribution days are defined as any day that is down -0.2% or greater on heavier volume than the previous day. Distribution days are counted on the major indexes (S&P 500, NASDAQ, NYSE, etc...) within the CANSLIM methodology.
Golden Cross, SMA 200 Moving Average Strategy (by ChartArt)This famous moving average strategy is very easy to follow to decide when to buy (go long) and when to take profit.
The strategy goes long when the faster SMA 50 (the simple moving average of the last 50 bars) crosses above the slower SMA 200. Orders are closed when the SMA 50 crosses below the SMA 200. This simple strategy does not have any other stop loss or take profit money management logic. The strategy does not short and goes long only!
Here is an article explaining the "golden cross" strategy in more detail:
www.stockopedia.com
On the S&P 500 index (symbol "SPX") this strategy worked on the daily chart 81% since price data is available since 1982. And on the DOW Jones Industrial Average (symbol "DOWI") this strategy worked on the daily chart 55% since price data is available since 1916. The low number of trades is in both cases not statistically significant though.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
MACD + SMA 200 Strategy (by ChartArt)Here is a combination of the classic MACD (moving average convergence divergence indicator) with the classic slow moving average SMA with period 200 together as a strategy.
This strategy goes long if the MACD histogram and the MACD momentum are both above zero and the fast MACD moving average is above the slow MACD moving average. As additional long filter the recent price has to be above the SMA 200. If the inverse logic is true, the strategy goes short. For the worst case there is a max intraday equity loss of 50% filter.
Save another $999 bucks with my free strategy.
This strategy works in the backtest on the daily chart of Bitcoin, as well as on the S&P 500 and the Dow Jones Industrial Average daily charts. Current performance as of November 30, 2015 on the SPX500 CFD daily is percent profitable: 68% since the year 1970 with a profit factor of 6.4. Current performance as of November 30, 2015 on the DOWI index daily is percent profitable: 51% since the year 1915 with a profit factor of 10.8.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
Stochastic + RSI, Double Strategy (by ChartArt)This strategy combines the classic RSI strategy to sell when the RSI increases over 70 (or to buy when it falls below 30), with the classic Stochastic Slow strategy to sell when the Stochastic oscillator exceeds the value of 80 (and to buy when this value is below 20).
This simple strategy only triggers when both the RSI and the Stochastic are together in a overbought or oversold condition. The one hour chart of the S&P 500 worked quite well recently with this double strategy.
By the way this strategy should not be confused with the 'Stochastic RSI', which measures the RSI only.
All trading involves high risk; past performance is not necessarily indicative of future results.
