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BTC LONGTERM | HODLERS OUTLOOKHODLERS MUST LOOK We are coming up to the next halving in less that 34 DAYS - Est. 13 May 2020. This event is likely to change the value of BTC as it has over the last 3 halvings. In addition to increasing public awareness and media attention around Bitcoin. If your reading this, you have to remember that not even 10% of the global population are actually knowledgable about Bitcoin. We as early adopters need to re-emphasise to ourselves we are submerged in the Crypto Community and crypto and its philosophies are the norm for us. Whoever we are a minority, in a current niche market. That said, why do halvings have positive long-term effects on Bitcoins price. Well, there are a lot of theories, but a common one goes down to SUPPLY & DEMAND. If fewer bitcoins are being generated, the newly increased scarcity automatically makes them more valuable. But this doesn't happen right away. So how has this played out in the past? History shows us that it ends up being a mixture of 'miners giving up' and 'miners hodling'. Some small number of miners will indeed give up, while majority will continue to keep mining and hold. Nov 2012 1BTC ~ $11 2013 ATH 1BTC ~ $1,100 Jul 2016 1BTC ~ $600 2017 ATH 1BTC ~ $20,000 Predictions May 2020 1BTC ~ $7000 2021 ATH 1BTC ~ +$30,000 2022 ATH 1BTC ~ +$80,000 Especially in our current global economic outlook I can see investors looking for alternative safe heavens. Gold and Bitcoin being chosen. Gold because of its track record and trust as a store of value for thousands of years. Bitcoin because of investors analysis of ROI and business opportunity in the Crypto Ecosphere. Hope my readers are healthy and your families are safe. My wishes go out to everyone. Stay Home! :)
BNC:BLXLong
by H_Woodrow
1
SP500 FORECAST - AGREE?Good Day Traders! Congrats to those who made money following our calls! 💰💰💰 Simply following us and we will get you guys our latest updates FOR FREE! Go to the link below & hit the " FOLLOW " button right now ! 👉 www.tradingview.com 👉 www.tradingview.com 👉 www.tradingview.com Above chart is the forecast we made on SP500. Currently SP500 is forming Wave 5. Breaking level of 2400 will confirm the formation. Please like and comment if you agree with us ! Follow us Rule_no1 and Happy Trading Guys:) "It never was my thinking that made the big money for me. It was always my sitting." - Jesse Livermore DISCLAIMER: There is a very high degree of risk involved in trading. Past results are not indicative of future returns. Trade at your own risk.
FOREXCOM:SPX500Short
by Rule_no1
USD/CHF SELL SIGNALHey tradomaniacs, welcome to another free signal! Important: Wait for the breakout of the current trendchannel and sell the retest after rejection. ----------------------------- Type: Daytrade Market Sell: 0,94500 Stop-Loss: 0,95275 Target 1: 0,93800 Target 2: 0,93240 Target 3: 0,92440 Stop-Loss: 77.5 pips Risk: 1-2% Risk-Reward: 2,5 ----------------------------- LEAVE A LIKE AND A COMMENT - I appreciate every support! =) Peace and good trades Irasor Wanna see more? Don`t forget to follow me. Any questions? PM me. :-)
Short
by Trading2ez
1
BTCUSD Inception day 14-1-2020, not convinced yet...Greetings fellow traders, As time goes by, the markets evolve... If your way of TA is strong, then the path will lead its way... More visible, more probable: Dashed lines; Possible forming patterns Solid lines; Confirmed patterns / Support or Resistance Dotted lines; Possible price-action trajectories / wave trend Lighten colors = Support | Darken colors = Resistance ' I’m trying to free your mind, Neo. But I can only show you the door. You’re the one that has to walk through it. ' ~ Morpheus, The Matrix ~ With that having quoted, this is my way of keeping order in the chaos. I call it, "Pattern Formation Level(PFL)": Alpha > Beta > Delta > Echo > Gamma > Theta Explanation PFL: This is an additional stage of usage of the pattern formations. Some level of experience in pattern formations is required. You can also ignore this part and head straight to 'Today's Note', just read the patterns between the brackets. Alpha; ST / Bullish Pennant pattern formation, a.k.a. "The End Game", a.k.a. "The Big Long". (Daily and higher time-frames) Beta; Most recent relevant and biggest forming pattern within The Alpha forming pattern. FW / DC. (4-24 hour time-frames) Delta; Most recent relevant forming patterns within The Beta pattern. (4-8 hour time-frames) Echo; Most recent relevant forming patterns within The Delta pattern. (1-4 hour time-frames) Gamma; You get the picture... (10-60 min. time-frames) Theta; Do not thread these treacherous waters. At least for master level TA skills or higher. (10 min. and lower time-frames) Eventually the PFL's are all connected. Gamma patterns combines into Echo pattern and Echo patterns combines into Delta patterns etc. Until the Alpha patterns has been formed. I'm not calling it just the Alpha for dominance in size. For as this pattern, is, the Alpha and Omega. Which will end current market cycles and start anew. From time to time, I might thread the secret level when I'm feeling gutsy. Additional advantage of the PFL system is, when you have to determine whether a certain pattern will have its usual breakout direction. By inserting pattern formations in the PFL as parameter. This makes it easier keeping track of which pattern formations are relevant to the current TA and entry or exit strategies. It might be hard to learn, but it is certainly easy to master. As a programmer and I like playing chess, as result to my TA. I like to look ahead as far as possible. This is only doable, if you have reasonable reliable trends to follow. In time, as I gain experience in the markets. My TA skills evolves and in parallel my systems and indicators. ------------------------------------- Current Alpha patterns: The End Game: Symmetrical Triangle 1st confirmations support & resistance establish, still in progress. Current Beta patterns: Descending Channel or Falling Wedge, currently breaking out but not yet confirmed Current Delta patterns: Ascending Broadening Wedge, 1st confirmations of support & resistance established, still in progress. Currently retesting resistance of the Delta(ABW) formation and also the 0.5 fib retrace. But might break through the upside and follow the break out of the greater (Beta) pattern. Current Echo patterns: Rising Wedge still in progress, heading towards 2nd confirmation of resistance. Current Gamma patterns: Symmetrical Triangle, broke out Current Theta patterns: This level is currently too dangerous to trade. Greater patterns might break out or follow its trajectory. Today's Note: Honestly, it's looking bullish. But I'm not convinced yet. Btc still has some obstacles to conquer. The 0.5 retrace. and breaking through the resistance of the Delta(ABW) but also the Echo(RW) patterns. These are lesser patterns, but 3 vs 1. That's quite a challenge. EMI 1 & 2 are becoming quite bearish. I might setup a low risk/reward short position from here. But going to wait for more concrete bear or bullish signs. However it is quite certain that something has to give very soon. To be concluded... Current Targets: Exit short position / Entry long position target: ---- region Tip's/FYI: People = Psychology > Patterns > Indicators > Fundamentals. Nonetheless, all is crucial. Psychology? When you observe a chart. Ask yourself who's the most in pain? Bears or Bulls? Watch & learn from experienced traders and discover your style of TA. Hence develop this, imitating will only get you as far. The most accurate trend indicator when using logarithmic, are the; Relative-, Exponential-, Weighted-, Simple- and regular Moving Averages. At least use Heikin Ashi candles if you don't like MA's and vice versa or using both might be even better. The algorithms of these indicators adepts to logarithmic variables visually. Linear tools and pattern formations obviously do not for that matter. Since it doesn't concern logarithmic variables. The trend is your friend! Pattern Formations is the most accurate method, when it comes to observing the behavior of buyers and sellers. If you don't understand this, don't be lazy and google. Learn this as basics, pattern formations are ideal to combine with other methods. ------------------------------------- Epilogue: Hopefully in time and it would be my honor, when other analyst implement at least some of my systems, methods and techniques into their TA. Henceforth bringing their TA skills & abilities to the next level. I have taken a lot of information from this community. However I believe. When you take, you should also share. After all, knowledge and experience are the most valuable things in life. This is why I share my daily TA. Hopefully other will learn from it, but never use someone else's TA. Always do your own do diligence before even considering trading. If you don't want to miss out on any of my daily technical analysis. Then click or tap on follow and don't forget to smash on that like button ^^, thanks in advance. If you're worthy I'll follow you back! In case you're wondering which indicator I'm using. She's called EMI , short for 'Epic Market Indicator' and she's a collection of diverse indicators. How to use, is in the description. You can use them like any other indicators. Search for 'epic market indicator' then add. I have recently published the latest versions. EMI 1 v3.0 & EMI 2 v2.0. Like any other instrument, practice makes perfect. If you have any input for EMI or questions about my way of TA(*Asian sound-effects*). Please leave a comment or DM me and I'll try to respond a.s.a.p. Be careful and good luck fellow traders, may the trend gods be with you!
COINBASE:BTCUSD
by bonic
Don't miss the great Sell opportunity in USDJPYTrading suggestion: . There is a possibility of temporary retracement to suggested Resistance line (108.87). If so, traders can set orders based on Price Action and expect to reach short-term targets. Technical analysis: .USDJPY is in a range bound and the beginning of Downtrend is expected. .The price is above the 21-Day WEMA which acts as a dynamic support. . The RSI is at 33. Take Profits: TP1= @ 107.83 TP2= @ 106.77 TP3= @ 105.24 SL= Break above R2
by ForecastCity
5
Development Log for Neural Network PrototypeThe idea, at the core: Port a limited RNN/LSTM Neural Network model from Python with a reduced training set and dimension size for layers to demonstrate that a fully functional (even if limited) Neural Net can work in Pine. Limited model + having the python code on hand = Able to test and verify components in Pine at every step, in theory The model/script I'm attempting to implement a limited subset of is detailed here: iamtrask.github.io A dataset in binary is required, but binary does not exist in pinescript, thus: To do this, decimal to binary and binary to decimal functions are required. This didn't exist previously - I've written a script to accomplish just that: Originally, this was going to have a input_dim of 2, hidden_dim of 16, but I've changed the hidden_dim to 8 (binary dimensions from 8 to 5) to reduce the dataset range to max 32 while I figure out to implement working pseudo-arrays and state updates. I've looked at RicardoSantos's scripts for Markov and Pseudoarrays, and will be using them as a reference going forward. I've verified the output of the Sigmoid function and 1st derivative of the Sigmoid function in Python for values of (-1,0,0.5,1 ). I've yet to publish the Sigmoid script pending approval from TV moderators about including python code that is commented out at the bottom to verify the results of that script. What I'm trying to do here with training dataset generation was unsuccessful, for multiple reasons: Lack of formal array constructs in pine Psuedorandom Number generator limitations Manual state weighting and updating as per RicardoSantos's Function Markov Process is required: What's being plotted for are the first three layers, but without the full range of the input_dimensions, hidden_dimensions: syn_0 (blue) syn_1 (green) syn_h (red) While there's more than a few technical hurdles to overcome (i.e. potential pine issues from max variables to runtime/compile limits, no real arrays, functions to do state updates RichardoSantos Markov Function style, etc), I'm fairly confident a limited working model should be possible to create in Pine.
COINBASE:BTCUSDEducation
by auroagwei
4
Indicators Input Window Length - Problems And SolutionsIntroduction Most technical indicators possesses a user defined input window length, this input affect the indicator output and for a long time, have been the cause of many innovations in technical analysis. In this post i want to discuss the effects and particularities of indicators inputs window length, the challenges they introduce in trading and their effect when paired with machine learning forecasting models, i hope this post will be easy to read, let me know if you had difficulties understanding it. Speed And Efficiency Problems An input window length can involve the number of data processed by the indicator, therefore higher window length's will process more data, which result in a slower computation time, therefore in high-frequency/algorithmic trading where response time matter, maximizing the profitability might be made at the cost of the indicator response time, and even if computerized trading has been praised for its speed, small lag times can actually affect your strategy, therefore one might enter a trade at a different value than the targeted price. Note : High frequency trading (hft) is a commonly mistaken term, one might believe that hft require the trader to open and close a large number of trades in a short amount of time, in reality hft is related to the "rate at which data is processed". Solution - Efficient Data Processing Solutions have been proposed in order to make certain tools more efficient. For example the simple moving average is a common tool that is the basis of many other indicators, its calculation involve summing the length last data points and diving this sum by length . In signal processing, such tool require what is called "memory", the data points must be stored in order for them to be processed, this is extremely inefficient and slow, therefore alternatives have been proposed, one of them is still mainly used in technical analysis today and is called the exponential moving average (ema), the process of computing an exponential moving average is called exponential averaging, and has the form of : ema = sc*input+(1-sc)*(past ema value) where sc is called the smoothing constant where 1 > sc > 0 . We only need 2 data values in order to perform this computation, lets denote a moving average of period length sma(input,length) , we can estimate it using exponential averaging with sc = 2/(length+1) . The computation time of the exponential moving average is way lower than the one of the sma . This is the most elegant and efficient estimation of the simple moving average. The exponential moving average is the simplest "IIR Filter", or infinite response filter, those filters are as well extremely efficient since they use recursion. Exponential averaging is also the core of many adaptive indicators. In my experience, recursion will always let you create extremely efficient tools. Window Length And Optimization Problems Optimization is a branch of mathematics that help us find the best parameters in order to maximize/minimize a certain function, and thanks to computers this process can be made faster. Optimizing technical indicators during backtesting involve finding the input window length (set of inputs if there are more than 1 input) that maximize the profit of a strategy. The most common approach is brute forcing, in which we test every indicator inputs window length combination and keep the one that yield the best results. However optimization is still computationally intensive, having 2 indicators already involve a high number of combinations. This is why it is important to select a low number of indicators for your strategy. But then other problems arise, the best input window length (set of inputs) might change in the future. This is due to the fact the market price is non-stationary and one of the reasons technical indicators are looked down. In order to deal with this problem, we can propose the following solutions : Use indicators/Information with no input window length -> Vwap/Volume/True Range/Cumulative Mean...etc. Study the relationship between the optimal input window length and price evolution -> Regression analysis Forecast the optimal input window length -> Forecasting The last two are extremely inefficient, kinda nightmarish, and would be time consuming if one use a serious backtesting procedure. However the first solution is still appealing and might actually provide a efficient result. Machine Learning Forecasting - Performance And Technical indicators Input Window Length Dependency Technical indicators outputs can be used as inputs for machine learning algorithms. We could think that we also need to optimize the input window length of the indicators when using machine learning (which would lead to high computations time, machine learning already involve optimization of a high number of parameters), however a research paper named "Forecasting price movements using technical indicators: Investigating the impact of varying input window length" by Yauheniya Shynkevicha, T.M. McGinnitya, Sonya A. Colemana, Ammar Belatrechec and Yuhua Li highlight an interesting phenomenon, the abstract tell us that : "The highest prediction performance is observed when the input window length is approximately equal to the forecast horizon" In short, if you want to forecast market price 14 step ahead with a machine learning model, you should use indicators with input window length approximately equal to 14 as inputs for the model in order to get the best performance. This would allow to skip a lot of optimizations processes regarding the technical indicators used in the model. They used 3 different type of ML algorithms, support vector machine (svm) , adversarial neural networks (ann) and k nearest neighboring (knn) , which reinforce their conclusion. In the paper, we can see something interesting with the indicators they selected as inputs, they used : A simple moving average, an exponential moving average, the average true range, the Average Directional Movement Index, CCI, ROC, RSI, %R, stochastic oscillator. First thing we can see is that they used the exponential moving average instead of the wilder moving average for certain calculations, which i think is a good choice. We can also see they used many indicators outputting the same kind of information, in this case we often talk about "Multicollinearity", for example : The CCI, ROC, RSI, %R, Stochastic output similar information, all remove the trend in the price, the CCI and ROC are both centered around 0 and the %R, RSI and stochastic oscillator around 50. The SMA and EMA also output similar information. In technical analysis this practice is often discouraged since the indicators will output the same kind of information, this lead to redundancy. However such practice has been seen a lot in machine learning models using technical indicators. Maybe that a higher amount of multicollinearity between indicators allow to strengthen the relationship between the forecast horizon and the indicators input window length. Conclusion We talked (a lot) about indicator inputs window length, what problems they cause us and how we can find solutions to those problems. Also we have seen that the forecasting performance of ML models can be higher when they use indicators outputs with input window length equal to the forecasting horizon. This can make to make the process of forecasting financial market price with ML models using technical indicators more efficient. ML is a recurring subject in financial forecasting, those algorithms offer the hope to make technical indicators more useful, and indeed, technical indicators and ML models can benefits from each others, however it is sad to observe that classical indicators are mainly used instead of newer ones, but its also encouraging in the sense that more research can be done, using newer material/procedures. Thanks for reading !
NASDAQ:INTCEducation
by alexgrover
12