[blackcat] L3 Xerxes ChannelsLevel 3
Background
The stock price channel theory is a widely used and mature theory in western securities analysis. In the 1970s, American Xerxes first established this theory.
Function
In fact, it is contained by the short-term small channel and runs up and down in the long-term large channel. The basic trading strategy is that when the short-term small channel approaches the long-term large channel, it indicates a recent reversal of the trend. The trend reverses downwards as the upper edge approaches, capturing short-term selling points. The trend reverses upward as the lower edge approaches, capturing short-term buying points. Studying this method can successfully escape from the top and catch the bottom in every wave of the market and seek the maximum profit.
The long-term major channel reflects the long-term trend state of the stock, the trend has a certain inertia, and the extension time is long, reflecting the large cycle of the stock, which can grasp the overall trend of the stock, and is suitable for medium and long-term investment;
The short-term small channel reflects the short-term trend status of the stock, accommodates the ups and downs of the stock, effectively filters out the frequent vibrations in the stock trend, but retains the up and down fluctuations of the stock price in the large channel, reflecting the small cycle of the stock, suitable for medium short-term speculation;
The long-term large channel is upward, that is, the general trend is upward. At this time, when the short-term small channel touches or is close to the bottom of the long-term large channel, it indicates that the stock price is oversold and there is a possibility of a rebound. The short-term small channel has touched the top of the long-term large channel, indicating that the stock price has been overbought, and there will be a correction or consolidation in the form, and there is a trend of approaching the long-term large channel. It is more effective if the K-line trend and the short-term small channel trend also match well;
The long-term big channel goes up, and the short-term small channel touches the top of the long-term big channel. At this time, the stock is in the stage of strong elongation. It can be appropriate to wait and see. When it turns flat in the short-term or turns its head down, it is a good delivery point, but it will penetrate If the area is a risk area, you should pay close attention to the reversal signal and ship at any time;
The long-term large channel is downward, that is, the general trend is downward. At this time, the short-term small channel or the stock price peaks and the selling pressure increases, and there is a downward trend again. The bottoming pattern means that the buying pressure is increasing, and there is a requirement for slow decline adjustment or stop decline, and the price movement will tend to be close to the upper edge of the long-term large channel. Callbacks should be treated with caution, and buy only after confirming the reversal signal;
The long-term large channel is down, while the short-term small channel penetrates the bottom line of the long-term large channel downward. At this time, it is mostly a slump process, and there is a rebound requirement, but the decline process will continue. It is not appropriate to open a position immediately. There is an upward trend, and when the short-term small channel turns back up and crosses back, it is a better opportunity to open a position at a low level;
When the long-term large channel is flat horizontally for a long time, it is to consolidate the market, and the price fluctuates up and down along the channel. At this time, it is the stage of adjustment, opening and washing, indicating the emergence of the next round of market. Short-term speculators can sell on highs and buy on lows. If the short-term small channel strongly crosses the long-term large channel, and the long-term large channel turns upward, it indicates that a strong upward trend has begun. If the short-term small channel penetrates down the long-term large channel, and the long-term large channel turns downward, it indicates that the decline will continue.
In a large balanced market, buy when the stock price hits the lower rail of the large channel at the bottom of the swing, and sell when the stock price hits the upper rail of the large channel at the peak of the swing.
Remarks
Feedbacks are appreciated.
Blackcat1402
[blackcat] L1 Vitali Apirine Exponential Deviation BandsLevel 1
Background
Vitali Apirine’s articles in the July issues on 2019,“Exponential Deviation Bands”
Function
In “Exponential Deviation Bands” in this issue, author Vitali Apirine introduces a price band indicator based on exponential deviation rather than the more traditional standard deviation, such as is used in the well-known Bollinger Bands. As compared to standard deviation bands, the author’s exponential deviation bands apply more weight to recent data and generate fewer breakouts. Apirine describes using the bands as a tool to assist in identifying trends.
Remarks
Feedbacks are appreciated.
[blackcat] L2 Ehlers Pairs RotationLevel 2
Background
John Ehlers’ articles in the July issues on 2022,“Pairs Rotation With Ehlers Loops, Part 2”
Function
In part 1 of his article in the June 2022 issue (“Ehlers Loops”), John Ehlers uses a relationship of price and volume to determine if any predictive value can be obtained. His technique, called Ehlers Loops, aid in visualizing the performance of one datastream against another. In part 2 appearing in this issue (“Pairs Rotation With Ehlers Loops”), the author demonstrates Ehlers Loops in action with a pairs trading example. This pairs rotation strategy is aimed at minimizing drawdown while simultaneously maximizing return on capital.
Remarks
Feedbacks are appreciated.
[blackcat] L1 Python Friendly Lucid SARLevel 1
Background
LUCID SAR is an interesting technical indicator. I'm having trouble converting this to Python code. So a "Python friendly" version was rewritten literally. Because some basic functions and structures have been replaced. The performance can be 100% consistent with LUCID SAR.
Function
Mr. Bowman wrote this script after having listened to Hyperwave with Sawcruhteez and Tyler Jenks of Lucid Mr. Bowmannvestments Strategies LLC on July 3, 2019. They felt that the existing built-in Parabolic SAR indicator was not doing its calculations properly, and they hoped that someone might help them correct this. So Mr. Bowman tried his hand at it,adding the rule regarding the SAR not advancing beyond the high (low) of the prior two candles during an uptrend (downtrend), but the core script is as it was.
I use large sized cross with red color for downtrend, with green color for uptrend, so that when I overlapped original work from Mr. Bowman, they can be 100% matched, which provided a validation process for this re-writing work. Enjoy!
Remarks
Feedbacks are appreciated.
Python version Lucid SAR performance discussion is desired.
[blackcat] L1 OBV-MFI ComboLevel 1
Background
As requested, this is a combo of OBV and MFI indicators
Function
On-balance volume (OBV) is a technical trading momentum indicator that uses volume flow to predict changes in stock price. Joseph Granville first developed the OBV metric in the 1963 book Granville's New Key to Stock Market Profits.
The Money Flow Index (MFI) is a technical oscillator that uses price and volume data for identifying overbought or oversold signals in an asset. It can also be used to spot divergences which warn of a trend change in price. The oscillator moves between 0 and 100.
The combo of them is still an oscillator.
Remarks
Feedbacks are appreciated.
[blackcat] L1 Simplest Sentiment ModelLevel 1
Background
My market sentiment indicator system mainly includes collecting various statistical data and drawing. Again, it was fitted using the OHLC data. This belongs to the latter.
Function
Through a simple calculation, the ratio of high and low breakouts to the price range, we know the sentiment of funds. At the same time, a delay line is used as a trigger signal to judge the inflection point of emotions through the golden fork and the dead fork. Mood thresholds can be defined, such as 20 and 80. This is an oscillator model, but also the simplest indicator of sentiment.
Remarks
Feedbacks are appreciated.
[blackcat] L1 Pawel Kosinski BB with CandlesLevel 1
Background
In Traders’ Tips of October 2019, the focus is Pawel Kosinski’s article : “Combining Bollinger Bands With Candlesticks”
Function
In “Combining Bollinger Bands With Candlesticks” in this issue, author Pawel Kosinski introduces us to a trading indicator that combines standard Bollinger Bands with the bullish engulfing candlestick pattern. Along the way we get a glimpse into the author’s process for trading strategy design and testing.
Remarks
Feedbacks are appreciated.
[blackcat] L3 Market Sentiment IndicatorLevel 3
Background
I've been thinking about trying out some technical indicators of market sentiment recently. Of course, this may not be limited to OHLC data, but requires more statistical data for analysis. However, I still wanted to try making a market sentiment indicator with OHLC. In this way, the difference between the two indicators can be compared later.
Function
This market sentiment indicator is functionally divided into two categories: the first is the sentiment line, which is a total of 3 lines. The first line is the yellow aggressive trader sentiment line, usually expressed as a 5-period moving average; the second line is the purple conservative trader interest line, which I used a slightly more complicated algorithm. The third line is the market sentiment line that takes the average of the first two. It is yellow when the market price is rising and purple when the price is falling.
The second type is the pressure line and the support line, a total of four, when they are support lines, the color is green; once they become resistance lines, the color will change from green to red, and show the current price of pressure or support.
Remarks
Feedbacks are appreciated.
[blackcat] L3 Financial Minesweeper: Altman Z ScoreLevel: 3
Background
The Altman Z-score is the output of a credit-strength test that gauges a publicly traded manufacturing company's likelihood of bankruptcy. The Altman Z-score is a formula for determining whether a company, notably in the manufacturing space, is headed for bankruptcy.
Function
The possibility of financial failure or bankruptcy of the enterprise is analyzed and predicted through the comprehensive score. The lower the Z value, the more likely the enterprise will go bankrupt. By calculating the Z value of an enterprise for several consecutive years, we can find out whether the enterprise has signs of financial crisis. Generally speaking, when the Z value is greater than 2.675, it indicates that the financial situation of the enterprise is good, and the possibility of bankruptcy is small; When the value is less than 1.81, it indicates that the enterprise is in a potential bankruptcy crisis; when the Z value is between 1.81 and 2.675, it is called a "gray area, indicating that the financial situation of the enterprise is extremely unstable.
Remarks
STOCKs ONLY which require financial data.
X1~X5 coefficients can be customized for different stock markets.
Compared to TradingView official Altman Z-Score Indicator.
Feedbacks are appreciated.
[blackcat] L1 Vitali Apirine OBVMLevel 1
Background
Traders’ Tips of April 2020, the focus is Vitali Apirine’s article in the April issue, “On-Balance Volume Modified (OBVM)”.
Function
In “On-Balance Volume Modified (OBVM)” in this issue, author Vitali Apirine presents a new indicator called OBVM that is based on the classic on-balance volume indicator originally developed by Joe Granville. The author has smoothed the OBV calculation and has added a signal line to help the trader identify entry and exit points. Apirine also notes that the OBVM indicator is useful in helping to identify divergences.
Remarks
Feedbacks are appreciated.
[blackcat] L1 Vitali Apirine Compare Price Momentum OscillatorLevel 1
Background
Traders’ Tips of August 2020, the focus is Vitali Apirine’s article in the August issue, “The Compare Price Momentum Oscillator (CPMO)”.
Function
In his article in this issue, “The Compare Price Momentum Oscillator (CPMO),” author Vitali Apirine reintroduces us to the DecisionPoint PMO originally developed by Carl Swenlin and presents a new way to use it to compare the relative momentum of two different securities. Trading signals can be derived in a number of ways including momentum, signal line, and zero-line crossovers.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L2 James Garofallou RSI In 4 DimLevel 2
Background
Traders’ Tips of September 2020, the focus is James Garofallou’s article in the September issue, “Tracking Relative Strength In Four Dimensions”.
Function
In “Tracking Relative Strength In Four Dimensions” in this issue, author James Garofallou introduces us to a new method of measuring the relative strength of a security. This new technique creates a much broader reference than would be obtained by using a single security or index and combines several dimensions, as the author calls them, into a single rank value. This study compares a security to another in four dimensions, as explained in the article. James Garofallou presents a metric for a security’s strength relative to 11 major market sectors and over several time periods. All this is squeezed into a single value. The first step is the RS2. It normalizes the security to a market index, then calculates four moving averages and encodes their relations in a returned number. I just modified it by using most BTC-correlated instruments to reflect how BTC response to their performance.
Remarks
This is a Level 2 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L2 FArden Thomas Voting With Multiple TimeframesLevel 2
Background
For Traders’ Tips of November 2020, the focus is F. Arden Thomas’ article in the August 2020 issue, “Voting With Multiple Timeframes”.
Function
F. Arden Thomas sums up the returns by a stochastic indicator in a voting process over seven different timeframes, and uses the resulting votes for trade signals. He shows us a new way of using the classic stochastic oscillator by combining many timeframes into a single value by voting. By using this voting process, buy and sell signals derived from many intervals become clearly visible on the chart. This is an interesting concept that can be applied to many common indicators such as the RSI or ADX, not just the stochastic.
Although the author creates a voting system by counting the number of times the indicator is in overbought/oversold range, I thought it would be interesting to create a composite indicator by averaging the stochastic value over multiple timeframes into a single indicator that moves along the standard scale.
Remarks
Maroon~ Red color bars for bullish market.
Teal~ Green color bars for bearish market.
This is a Level 2 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L2 Vitali Apirine Stochastic MACD OscillatorLevel 2
Background
Traders’ Tips of November 2019, the focus is Vitali Apirine’s article in the November issue, “The Stochastic MACD Oscillator”.
Function
In “The Stochastic MACD Oscillator” in this issue, author Vitali Apirine introduces a new indicator created by combining the stochastic oscillator and the MACD. He describes the new indicator as a momentum oscillator and explains that it allows the trader to define overbought and oversold levels similar to the classic stochastic but based on the MACD. The STMACD reflects the convergence and divergence of two moving averages relative to the high–low range over a set number of periods.
Remarks
This is a Level 2 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L1 Richard Poster Trend PersistenceLevel 1
Background
In Traders’ Tips of February 2021, the focus is Richard Poster’s article in the February 2021 issue, “Trend Strength: Measuring The Duration Of A Trend”.
Function
In his article in this issue, Richard Poster outlines several common ways to evaluate the strength and duration of trends. Then he evaluates their sensitivity to volatility. Next, he steps up our game a bit by proposing an indicator that seeks to measure a trend’s persistence rate, or TPR for short. TPR turns out to be relatively insensitive to the influence of volatility.
Financial markets are not stationary; price curves can swing all the time between trending, mean-reverting, or entire randomness. Without a filter for detecting trend regime, any trend-following strategy will bite the dust sooner or later. In his article in this issue, Richard Poster offers a trend persistence indicator (TPR) for helping to avoid unprofitable market periods.The TPR indicator measures the steepness of a SMA (simple moving average) slope and counts the bars where the slope exceeds a threshold. The more steep bars, the more trending the market. Threshold, TPR period, and SMA period are the parameters of the TPR indicator.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L1 Vitali Apirine MABWLevel 1
Background
Vitali Apirine’s articles in the July & August issues on 2021, “Moving Average Band Width”
Function
In “Moving Average Bands” (part 1, July 2021 issue) and “Moving Average Band Width” (part 2, August 2021 issue), author Vitali Apirine explains how moving average bands (MAB) can be used as a trend-following indicator by displaying the movement of a shorter-term moving average in relation to the movement of a longer-term moving average. The distance between the bands will widen as volatility increases and will narrow as volatility decreases. In part 2, the moving average band width (MABW) measures the percentage difference between the bands. Changes in this difference may indicate a forthcoming move or change in the trend.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L1 Vitali Apirine MABLevel 1
Background
Vitali Apirine’s articles in the July & August issues on 2021, “Moving Average Bands”
Function
In “Moving Average Bands” (part 1, July 2021 issue) and “Moving Average Band Width” (part 2, August 2021 issue), author Vitali Apirine explains how moving average bands (MAB) can be used as a trend-following indicator by displaying the movement of a shorter-term moving average in relation to the movement of a longer-term moving average. The distance between the bands will widen as volatility increases and will narrow as volatility decreases.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L1 RSMKLevel 1
Background
This is a modified version of indicator from Markos Katsanos’ article in the March issue, “Using Relative Strength To Outperform The Market”.
Function
In “Using Relative Strength To Outperform The Market” in this issue, author Markos Katsanos presents a trading system based on a new relative strength indicator he calls RSMK. The indicator improves on the traditional relative strength indicator by separating periods of strong or weak relative strength.
I found it helpful for divergence identification.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L2 Eyman OscillatorLevel 2
Background
Eyman Oscillator
Function
The Eyman oscillator is also an analytical indicator derived from the moving average principle, which reflects the deviation between the current price and the average price over a period of time. According to the principle of moving average, the price trend can be inferred from the value of OSC. If it is far from the average, it is likely to return to the average. OSC calculation formula: Take 10-day OSC as an example: OSC = closing price of the day - 10-day average price Parameter setting: The period of the OSC indicator is generally 10 days; the average number of days of the OSC indicator can be set, and the average line of the OSC indicator can also be displayed. OSC judgment method: Take the ten-day OSC as an example: 1. The oscillator takes 0 as the center line, the OSC is above the zero line, and the market is in a strong position; if the OSC is below the zero line, the market is in a weak position. 2. OSC crosses the zero line. When the line is up, the market is strengthening, which can be regarded as a buy signal. On the contrary, if OSC falls below the zero line and continues to go down, the market is weak, and you should pay attention to selling. The degree to which the OSC value is far away should be judged based on experience.
Remarks
This is a Level 2 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L3 Faster MACDLevel 3
Background
I am seeking a way to make MACD faster
Function
By using stoch, but with MACD method, a faster MACD is made. short term faster kd is used for macd lines. long term kd is used for histogram, which can counteract the histogram grade gap caused by tradtional MACD.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L1 Markos Katsanos Volume Flow IndicatorLevel 1
Background
Markos Katsanos’ volume flow indicator (VFI) calculation uses a default period of 130 days for daily charts. As a result, when applying the strategy, you will need to set the maximum number of bars the study will reference in the general tab of properties for all to at least 130. In order to compare the system objectively with the buy & hold results, he specified a trade size as a percent of equity.
Function
For more information see Markos Katsanos's articles in the June 2004 and July 2004 issues of Technical Analysis of Stocks & Commodities magazine. Period=days for VFI calculation. Default values are 130 for daily and 26 for weekly charts.Coef=coefficient for minimal price cut-of (use 0.2 for daily and 0.1 for intraday 5-15 min data) Vcoef=coefficient for volume cut-off (use 2.5 for daily and 3.5 for intraday charts)
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L1 Vitali Apirine RS EMALevel 1
Background
For Traders’ Tips for 2022.05, the focus is Vitali Apirine’s article in the January 2022 issue, “Relative Strength Moving Averages, Part 1: The Relative Strength Exponential Moving Average (RS EMA)”.
Function
Author Vitali Apirine introduces the relative strength exponential moving average (RS EMA). The study is designed to account for relative strength of price and is considered a trend-following indicator that can be used in combination with an EMA of the same length to identify the overall trend. RS EMAs with different lengths can define turning points and filter price movements.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
[blackcat] L3 Chip TrendsLevel 3 (Stock ONLY)
Background
Chip theory is an intersting TA for trading. The profit and loss (pnl) ratio represents the ratio of profit-making or loss-making orders in the current market. The larger the profit ratio, the more investors are in a profitable state. Stock chip analysis is a kind of stock technical analysis. Investors can analyze it in combination with other indicators and data.
Function
This is a chip distribution and trend indicator I developed that consists of three different colored histograms. Yellow represents the percentage of floating chips, green represents the percentage of hold-ups, and red represents the percentage of profit. Among them, the more red columns, the more profitable chips, the more green columns, the more trapped chips. At the same time, I used three colored moving averages to represent the trends of these three types of chips for reference. At the same time, a table will appear in the middle of the indicator, indicating the chip ratio value of the latest bar in the form of a percentage.
Key Signal
profit chip percentage and trend--> red color
floating chip percentage and trend --> yellow color
loss chip percentage and trend --> green color
Remarks
This is a Level 3 free and closed source indicator.
NOT applicable for instruments except stocks.
Feedbacks are appreciated.
