Pagina 32 | Risultati della ricerca di script per “bot”

Gunbot MACDgen Ok this is just some strat based on MACD, checking for a few conditions until giving buy/sell signals to Gunbot via alerts. It is generalized but if you want to go play with the values. I will continue to develop this further and am happy to receive feedback. Notations are coming. Usage notes: -ONLY use this with TV_GAIN: 0.6 because on downtrends it is supposed to double up to pull down the average bought price! -Use "buying condition" and "selling condition" for alerts, trigger on close and I suggest you use 3 min intervals but try what looks good to you -Use this on pairs that are curvy and have atleast 0.6% gain between buy/sell triggers. This is also general advise when you want to take microprofits. -Don't be confused with sell arrows, it will only trigger the bot sell on gain when you've set TV_GAIN

[Autoview] Every Candle Alert Script This script is designed specifically for firing an alert every candle. It can also be used to just fire an alert on a green candle, or a red candle to slow it down a bit. This is a script we use to close all of our orders or positions on any of the integrated exchanges. You can use a fire once alert with greater than on condition and the alert will typically fire within seconds. You can also use this to place orders for you without having to navigate away from TradingView to your exchange/brokerage site. If you would like a better understanding of how to create an alert for automation, please visit the article this strategy is being published for. use.autoview.with.pink

Stealthy7 Technical Analysis Trend Line Study The closing price has broken the upper trend line when the color is green. The closing price has broken the lower trend line when the color goes red. In the event of a mixed trend the color is brown. Support me by purchasing my bots at Cryptotrader.

Price Regression Agreggator Price Estimator with aggregated linear regresion --------------------------------------------------------------------------- How it works: It uses 6 linear regression from time past to get an estimated point in future time, and using transparency, those areas that are move "visited" by those 6 different regressions and maybe more probable to be visited by the price (in fact if you zoom out you will see that price normally is around the lighter zones) have more aggregated painted colors, the transparency is lower and well, the lighter area should be more probable to be visited by the price should we put any faith on linear regression estimations and even more when many of them coincide in several points where the color is more aggregated. If the "I" (the previous regressions increment) is too low, then we will have huge spikes as the only info gathered from the oldest linear regresssion will be within the very same trend we are now, resulting in "predictions" of huge spikes in the trend direction. (all regressions estimating on a line pointing to infinite) If the "I" is high enough (not very or TV won't be able to display it) then you will get somewhat a "vectorial" resultant force of many linear regressions giving a more "real prediction" as it comes from tendencies from higher timeframes. E.g. 12 hours could be going down, 4h could be going sideways, 30m could be going up. contact tradingview -> hecate . The idea and implementation is mine. Note: transparency + 10 * tranparencygradient cannot be > 100 or nothing will be displayed Note2: if the Future increment (how many lines are displayed to the right of the actual price ) are excessive, it will start to do weird things. Note3: two times the standard deviation statistically correponds to a probability of 95%. We are calculating Top and Bot with that amount above and below. So anything inside those limits is more probable and if we are out of those limits it should fall back soon. Increase the number of times the std deviation as desired. There are calculators in the web to translate number of times std dev to their correspondent probability. Note4: As we use backwards in time linear regressions for our "predictions" we lose responsiveness. Those old linear regressions are weighted with less value than more recent ones. Note5: In the code i have included many color combinations (some horrible :-) ) Note6: This was an experiment while i was quite bored although ended enjoying playing with it. Have fun! :-) I leave it here because i am getting dizzy.