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Lag

UPST ready to run higherUPST on the daily chart is 65% below its highs of March 22 . It rose above the long term POC line of the volume profile two months ago after a favorable earnings report. Another earnings will report in a month. There has been very little trading above the current price in the visible range. This means there is little volume resistance to price rise. Price is presently at the longterm mean VWAP anchored 16 months in the past and got there by rising from the support of the line one standard deviation below the mean aVWAP. On the zero-lag MACD, the lines have first crossed under the histogram and then ascended in parallel above the zero line in yet another sign of bullish momentum. Lastly, the three in one indicator including money flow is all green. I readily conclude that UPST is set up well for a long swing trade targetting just below the mentioned swing highs and so $160 or so. This would be about 200% while setting a stop loss at $50. I believe the trade offers a great potential reward to risk and so will open this position while identifying an entry on the 15-30 minute chart looking for a pivot low.
NASDAQ:UPSTLong
by AwesomeAvani
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
ETH LEAD to CROSSOVER LAGMy first post of hopefully more to come! Please note, I have no formal TA training and the lines are just a rough guide to get my main SMA crossover point across. Please also forgive me for my vague phrasing. A friend and I have been researching and testing a few different neural network models, LSTM and reinforcement. We are now getting deeper into the LSTM model to predict near term price changes, later incorporating market sentiment (positivity) that we will hopefully use to construct a portfolio of non correlated instruments that will be automatically readjusted frequently to push fund allocation towards positive predictions and away from negative ones. Now to this chart, while we were looking at different models and backtesting strategies we came across a simple program where you can search for the optimal (most successful) lead/lag SMA periods for crossover trading. While this doesn't mean that the crossover periods will continue to perform as well or at all compared to the backtest, it has worked the best so far. I'm going to be making a small entry if the lead crosses above the lag by 2.5%, with selling to be done when it falls below it by 2.5% Let's see what happens!
BITFINEX:ETHUSDLong
by sammc
[NM]Bull and Bear Power trade signal - thanks to [RS]The base code for this indicator was created by RicardoSantos and can be found here : What I added is a signal line that indicates when to buy and when to sell. Advised use : Combine with a zero-lag indicator like ZeroLagEMA_LB by LazyBear (suggested period = 34) Then use the following Rules of engagement : Current price > ZLEMA & Signal line of BBP_NM is green : BUY Current price < ZLEMA & Signal line of BBP_NM is red : SELL Please click the like button if you dig this indicator !
by Nico.Muselle
40