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TNYA Biotechology Penny NASDAQ LONGTNYA has been in consolidation the past two days being in the flag of a bull flag pattern on the 1H chart. Earnings about six weeks ago were solid especially for a biotechnology stock which are generally priced based on future potential and not current performance. ( Fundamentally TNYA is in the gene splicing /slicing place which is perhaps the most lucrative and therapeutic of all of the various areas in the biotechnology realm. Seemingly, its potential is expodentially high. ) The zero lag MACD lines have crossed under the histogram which in general can be considered as a buy signal. The histogram has flipped to positive. Upside to the overhead resistance zone by the Luxalgo indicator is from an entry of about 5 to 6 or about 20%. Very recent high relative volume as compared with the 50 day moving average further supports a long trade at this time. The stop loss would be $.02 below the POC line of the volume profile. I will play this with options to further leverage the price action. Both options and stock are inexpensive for a small account.
NASDAQ:TNYALong
by AwesomeAvani
Evolution of MACDMoving Average Convergence Divergence – MACD The most popular indicator used in technical analysis, the moving average convergence divergence (MACD), created by Gerald Appel. MACD is a trend-following momentum indicator, designed to reveal changes in the strength, direction, momentum, and duration of a trend in a financial instrument’s price Historical evolution of MACD, - Gerald Appel created the MACD line, - Thomas Aspray added the histogram feature to MACD - Giorgos E. Siligardos created a leader of MACD MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum. Mathematically expressed as; macd = ma(source, fast_length) – ma(source, slow_length) signal = ma(macd, signal_length) histogram = macd – signal where exponential moving average (ema) is in common use as a moving average (ma) fast_length = 12 slow_length = 26 signal_length = 9 The MACD indicator is typically good for identifying three types of basic signals; Signal Line Crossovers A Signal Line Crossover is the most common signal produced by the MACD. On the occasions where the MACD Line crosses above or below the Signal Line, that can signify a potentially strong move. The standard interpretation of such an event is a recommendation to buy if the MACD line crosses up through the Signal Line (a "bullish" crossover), or to sell if it crosses down through the Signal Line (a "bearish" crossover). These events are taken as indications that the trend in the financial instrument is about to accelerate in the direction of the crossover. Zero Line Crossovers Zero Line Crossovers occur when the MACD Line crossed the Zero Line and either becomes positive (above 0) or negative (below 0). A change from positive to negative MACD is interpreted as "bearish", and from negative to positive as "bullish". Zero crossovers provide evidence of a change in the direction of a trend but less confirmation of its momentum than a signal line crossover Divergence Divergence is another signal created by the MACD. Simply, divergence occurs when the MACD and actual price are not in agreement. A "positive divergence" or "bullish divergence" occurs when the price makes a new low but the MACD does not confirm with a new low of its own. A "negative divergence" or "bearish divergence" occurs when the price makes a new high but the MACD does not confirm with a new high of its own. A divergence with respect to price may occur on the MACD line and/or the MACD Histogram Moving Average Crossovers , another hidden signal that MACD Indicator identifies Many traders will watch for a short-term moving average to cross above a longer-term moving average and use this to signal increasing upward momentum. This bullish crossover suggests that the price has recently been rising at a faster rate than it has in the past, so it is a common technical buy sign. Conversely, a short-term moving average crossing below a longer-term average is used to illustrate that the asset's price has been moving downward at a faster rate and that it may be a good time to sell. Moving Average Crossovers in reality is Zero Line Crossovers, the value of the MACD indicator is equal to zero each time the two moving averages cross over each other. For easy interpretation by trades, Zero Line Crossovers are simply described as positive or negative MACD False signals Like any forecasting algorithm, the MACD can generate false signals. A false positive, for example, would be a bullish crossover followed by a sudden decline in a financial instrument. A false negative would be a situation where there is bearish crossover, yet the financial instrument accelerated suddenly upwards What is “MACD-X” and Why it is “More Than MACD” In its simples form, MACD-X implements variety of different calculation techniques applied to obtain MACD Line, ability to use of variety of different sources, including Volume related sources, and can be plotted along with MACD in the same window and all those features are available and presented within a single indicator, MACD-X Different calculation techniques lead to different values for MACD Line, as will further discuss below, and as a consequence the signal line and the histogram values will differentiate accordingly. Mathematical calculation of both signal line and the histogram remain the same. Main features of MACD-X ; 1- Introduces different proven techniques applied on MACD calculation, such as MACD-Histogram, MACD-Leader and MACD-Source, besides the traditional MACD (MACD-TRADITIONAL) • MACD-Traditional, by Gerald Appel It is the MACD that we know, stated as traditional just to avoid confusion with other techniques used with this study • MACD-Histogram, by Thomas Aspray The MACD-Histogram measures the distance between MACD and its signal line (the 9-day EMA of MACD). Aspray developed the MACD-Histogram to anticipate signal line crossovers in MACD. Because MACD uses moving averages and moving averages lag price, signal line crossovers can come late and affect the reward-to-risk ratio of a trade. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD The MACD-Histogram represents the difference between MACD and its 9-day EMA, the signal line. Mathematically, macdx = macd - ma(macd, signal_length) Aspray's contribution served as a way to anticipate (and therefore cut down on lag) possible MACD crossovers which are a fundamental part of the indicator. Here come a question, what if repeat the same calculations once more (macdh2 = macdh - ma(macdh, signal_length), will it be even better, this question will remain to be tested • MACD-Leader, by Giorgos E. Siligardos, PhD MACD Leader has the ability to lead MACD at critical situations. Almost all smoothing methods encounter in technical analysis are based on a relative-weighted sum of past prices, and the Leader is no exception. The concealed weights of MACD Leader are such that more relative weight is used in the more recent prices than the respective weights used by the components of MACD. In effect, the Leader expresses more changes in average price dynamics for the recent price movement than MACD, thus eventually leading MACD, especially when significant trend changes are about to take place. Siligardos creates two less-laggard moving averages indicators in its formula using the same periods as follows Indicator1 = ma(source, fast_length) + ma(source - ma(source, fast_length), fast_length) Indicator2 = ma(source, slow_length) + ma(source - ma(source, slow_length), slow_length) and then take the difference: Indicator1 - Indicator2 The result is a new MACD Leader indicator macdx = macd + ma(source - fast_ma, fast_length) - ma(source - slow_ma, slow_length) • MACD-Source, a custom experimental interpretation of mine, MACD Source, presents an application of MACD that evaluates Source/MA Ratio, relatively with less lag, as a basis for MACD Line, also can be expressed as source convergence/divergence to its moving average. Among the various techniques for removing the lag between price and moving average (MA) of the price, one in particular stands out: the addition to the moving average of a portion of the difference between the price and MA. MACD Source, is based on signal length mean of the difference between Source and average value of shot length and long length moving average of the source (Source/MA Ratio), where the source is actual value and hence no lag and relatively less lag with the average value of moving average of the source . Mathematically expressed as, macdx = ma(source - avg( ma(source, fast_length), ma(source, slow_length) ), signal_length) MACD Source provides relatively early crossovers comparing to MACD and better momentum direction indications, assuming the lengths are set to same values For further details, you are invited to check the following two studies, where the first seeds were sown of the MACD-Source idea Price Distance to its Moving Averages study, adapts the idea of “Prices high above the moving average (MA) or low below it are likely to be remedied in the future by a reverse price movement", presented in an article by Denis Alajbeg, Zoran Bubas and Dina Vasic published in International Journal of Economics, Commerce and Management First MACD like interpretation comes with the second study named as “P-MACD”, where P stands for price, P-MACD study attempts to display relationship between Price and its 20 and 200-period moving average. Calculations with P-MACD were based on price distance (convergence/divergence) to its 200-period moving average, and moving average convergence/divergence of 20-period moving average to 200-period moving average of price. Now as explained above, MACD Source is a one adapted with traditional MACD, where Source stands for Price, Volume Indicator etc, any source applicable with MACD concept 2- Allows usage of variety of different sources, including Volume related indicators The most common usage of Source for MACD calculation is close value of the financial instruments price. As an experimental approach, this study will allow source to be selected as one of the following series; • Current Close Price (close) • Average of High, Low, and Close Price (hlc3) • On Balance Volume (obv) • Accumulation Distribution (accdist) • Price Volume Trend (pvt) Where, -Current Close Price and Average of High, Low, and Close Price are price actions of the financial instrument -Accumulation Distribution is a volume based indicator designed to measure underlying supply and demand -On Balance Volume (OBV), is a momentum indicator that measures positive and negative volume flow -Price Volume Trend (PVT) is a momentum based indicator used to measure money flow 3- Can be plotted along with MACD in the same window using the same scaling Default setting of MACD-X will display MACD-Source with Current Close Price as a source and traditional MACD can be plotted eighter as a companion of MACD-X or can be selected to be plotted alone. Applying both will add ability to compare, or use as a confirmation of one other In case, traditional MACD Is plotted along with MACD-X to avoid misinterpreting, the lines plotted, the area between MACD-X Line and Signal-X Line is highlighted automatically, even if the highlight option not selected. Otherwise highlight will be applied only if that option selected 4- 4C Histogram Histogram is plotted with four colors to emphasize the momentum and direction 5- Customizable Additional to ability of selecting Calculation Method, Source, plotting along with MACD, there are few other option that allows users to customize the MACD-X indicator Lengths are configurable, default values are set as 12, 26, 9 respectively for fast, slow and smoothing length. Setting lengths to 8,21,5 respectively Is worth checking, slower length moving averages will lead to less lag and earlier reaction to price actions but yet requires a caution and back testing before applying Highlight the area between MACD-X Line and Signal-X Line, with colors emphasising the direction Label can be added to display Calculation Method, Source and Length settings, the aim of this label is to server only as a reminder to trades to be aware of settings while they are occupied with charts, analysis etc. Here comes another question, which is of more importance having the reminder or having the indicators with multi timeframe feature? Build-in Multi Time Frame features of Pine is not supported when labels and lines introduced in the script, there are other methods but brings complexity. To be studied further, this version will be with labels for time being. EPILOGUE MACD-X is an alternative variant of MACD, the insight/signals provided by MACD are also applicable to MACD-X with early and clear warnings for the changes in the trend. If MACD is essential to your analysis, then it is my guess that after using the MACD-X for a while and familiarizing yourself with its unique character and personality, you will make it an inseparable companion to other indicators in your charts. The various signals generated by MACD/MACD-X are easily interpreted and very few indicators in technical analysis have proved to be more reliable than the MACD, and this relatively simple indicator can quickly be incorporated into any short-term trading strategy
Education
by dgtrd
22
Properties And Spectral Interaction Of Zero-Lag FiltersIntroduction In this post i want to talk about zero-lag filters, how they interact with the price and its frequency components. I'll also talk about the phase-response, and try to clearly explain how it works and what information it can give to the user. I'll finally introduce the concept of forward-backward filtering as well as zero-phase non stable causal smoothing. Filters And Lag Lag is a term used in technical analysis that refer to the phase-shift induced by filters. As you know filters interact with the frequency content of a signal, they can remove certain frequency components or amplify/reduce their amplitude. Lag can be perceived when smoothing market price by using a low-pass/band-pass filter, in short a filter with lag will return past-trends instead of new one, this can be considered a tradeoff where the user can access information easier to interpret at the cost of reactivity. Phase Response One can visualize the phase of filters thanks to the phase-response. The phase-response is a value expressed in degree or radians and is described as the relationship of a sinusoid and the phase, its a bit confusing so let me explain you how it works. Remember that a sine wave have a amplitude and a frequency and a period, she can also have a certain phase expressed in degree, for example in this image www.davidbridgen.com the sine wave in red is shifted by 180 degree, the phase response of a filter will tell you how many degree a frequency component (sinusoid) is shifted after being filtered. Here an image showing a frequency response : i.stack.imgur.com This is because frequency components are shifted that lag can be perceived. Tackling The Lag Problem So technical analyst tackled this problem by making zero-lag filters, of course the term zero-lag must be taken lightly, basically zero-lag will mean a filter who better fit to the data. So how do this work ? Remember that a filter posses a frequency response, the frequency response tell you how the filter interact with the frequency components of the signal. So with most of the zero-lag filters lag will be reduced by amplifying some frequency components of the filter, some zero-lag filters will have the following frequency response : This frequency response amplify certain frequencies before the transition band, this allow the filter to better fit to the signal. Of course this is not the only way to make filter have zero-lag, common zero-lag filter structures include : amplifying certain frequencies in price -> applying filter applying a bandpass filter to the price -> summing the result with a low-pass filter multiply a low-pass filter with cutoff frequency a by 2 -> subtract the result to a low-pass filter of cutoff frequency b with a > b As you can see such filters produces better fit but are less smooth than other filters of the same period, this is logical, you are amplifying certain frequencies, and some of those frequencies can be high ones, basically noise, which explain the reactivity-smoothness tradeoff. The amplification process also creates artifacts such as over/undershoots which are direct effects of amplification. Zero-Phase Smooth Filters - Non Causal Any filter can have literally zero-lag and be smooth by a method called forward-backward filtering, this method consist in filtering the data from the left to the right and then filtering this result from the right to the left, during the last step you basically shift back the filtered result to the right, which compensate the shift produced by the first step filtering. Such filters work by reversing the orders of the signal samples, now they are said to be non-causal because they no longer use only past information, this is why such filters are used offline , their phase response is equal to 0. Those filters are the core of many repainting indicators. Zero-Phase Smooth Filters - Causal Impossible ? In theory yes, at least with FIR filters, however IIR filters can work differently. IIR filters are less stable than FIR filters and posses a non-linear phase , this mean that their phase is not a linear function. IIR filters are filters using past outputs as input, as said they can sometimes produce zero-lag smooth outputs, but those results are not stable and does not occur every time, in facts they are rare events. An example is made by using double exponential smoothing Using low values for beta can produce non-stables results appearing non-causal, and sometimes even great fits. However those effects does not appear constantly. Another way to have causal zero-lag filters is to forecast the data and smooth it, however you then are affected by the accuracy of your forecast model, how unfortunate. Conclusion This post took more time than necessary, but it is interesting to see how zero-lag filters works from a signal-processing point of view. So from now on if you see filters appearing to good to be true, you are certainly dealing with one using forward-backward filtering, either way you can't violate causality, no matter how hard you try...its also socially inappropriate (lame jokes !!!!!) . Thanks for reading !
COINBASE:BTCUSDEducation
by alexgrover
14
Thoth Script - BTC:4H:18.08.28 - Open P/L: 7.05% - NO REPAINT!Position: - Still long from 18.08.16 @6270$ - Divergence starting to form on lower timeframes Script Uses: 1. Ichimoku Cloud 2. John E. Zero Lag EMA 3. Hilbert Sine Wave Support/Resistance 4. Linear Regression Divergence of price vs -- ROC -- RSI -- ZL-MACD Inside -- No Repaint! -- No Lookahead (lookahead_off) -- Date Selectors -- Alarms version Parameters: 1. ROC Triggering Threshold: --- Triggering rate of change value in % ----- Low for lower timeframes, less volatile tokens ----- High for higher timeframes, more volatile tokens 2. Divergence Lookback: -- Number of candles to lookback for oscillators vs price divergence. Access: -- Leave a comment with your username. -- 24h trial access activated. Hints: -- Use Heikin Ashi -- Add slippage -- Refer to backtesting links attached to script post below for example setups. -- Script is not for sale or export outside TV. ------ " In art he, Thoth , was often depicted as a man with the head of an ibis bird " Made with 999ug. ------ Trade History: 18.08.28 18.08.25 18.08.20 18.08.16
BITFINEX:BTCUSDLong
by duot
180