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Twitter Time to Short and Hold Crash Ahead ?Company Details Full Name Twitter, Inc. Country United States Employees 5,200 CEO Jack Dorsey Stock Information Ticker Symbol TWTR Stock Exchange New York Stock Exchange Sector Communication Services Industry Internet Content & Information Unique Identifier NYSE: TWTR IPO Date November 7, 2013 Description Twitter operates as a platform for public self-expression and conversation in real time United States and internationally. The company offers various products and services, including Twitter, a platform that allows users to consume, create, distribute, and discover content; and Periscope, a mobile application that enables user to broadcast and watch video live with others. It also provides promoted products and services, such as promoted tweets, promoted accounts, and promoted trends, which enable its advertisers to promote their brands, products, and services. In addition, the company offers a set of tools and public application programming interfaces for developers to contribute their content to its platform, syndicate and distribute Twitter content across their properties, and enhance their Websites and applications with Twitter content. Further, it provides subscription access to its public data feed for data partners. Twitter, Inc. was founded in 2006 and is headquartered in San Francisco, California. The IPO opening print also marks the 50% retracement of the downtrend into 2016, highlighting the need for skeptical buyers to come off the sidelines here and lift the stock into the $50s. The uptick has just eased into a trading range that acknowledges resistance, so a positive catalyst may be needed to trigger a breakout. That could be a tall order in the fourth quarter, given the extraordinary challenges. As a result, there isn't much to do except to wait and watch price action in coming weeks. The Bottom Line Twitter stock has returned to seven-year resistance and still give no clear break out above the IPO 50% Retrace Level, Ahead elections Covid-19 $ Crash may lead s&p500 and major stock market to down side, we can expect a twitter crash or Correction to down side soon! Best Regards: RideTheMacro
NYSE:TWTRShort
by Ridethemacro
1
EURUSD Intraday Sell Sept 17EURUSD has rejected resistance multiple times. We entered at 9:45am when price was under the 14EMA. The analysis is still valid and is providing an opportunity to get in for a sell at a higher price with a tighter SL. Risk at this moment around 8 pips. Reward still 30+ pips. This trade is risker than we usually take however with the SL being so tight this is a good risk to reward. As always, will keep you updated in the comments. *Keep in mind we captured 60 pips between Tuesday and Wednesday. It is normal for the markets to consolidate and not bust out any major moves the next day.*
Short
by csohrab
3
RISK TO REWARD 📚 An Educational Write-up on How to Find ThisIntroduction: This illustration explains the minimum Risk-To-Reward ratio needed based on your average win-rate while using a fixed % risk amount. "Risk-To-Reward ratio": The ratio of what you stand to lose compared to win. "Fixed % Risk": A static % amount of your total account balance at risk per trade. "Fixed Dollar Risk": A static $ amount at risk per trade. Regardless of account size fluctuations. "Win-rate": The % out of all trades that are winners. Steps: 1. Before being able to determine what Risk-To-Reward is acceptable to use, you will need to create a baseline measurement of your strategy's performance. 2. To create this baseline, you will need to backtest your strategy and obtain its current average win-rate. 3. This can be done using your pre-determined entry logic with a fixed stop-loss/take-profit offset amount. (Adjusting your entry logic prior to finishing a round of backtesting may produce skewed results. Do not "cherry-pick" trades as that will lead to false results.) 4. Based on the resulting average win-rate you can then find the minimum Risk-To-Reward ratio you should be using. 5. Backtest again using the more optimal Risk-To-Reward ratio and repeat this step until the most optimal backtest results are obtained. Here is the formula for determining your Average win-rate after you have tallied the wins/losses of your backtest: #W = Number of winning trades #L = Number of losing trades (#W / (#W + #L)) * 100 = your average win rate % ----- Introduction to Fixed Dollar Risk: We have found it common for people to use the logic of fixed dollar risk amounts when calculating win-rates needed to break even, but then to use a fixed % risk in practice. This simple-to-make mistake can lead to account erosion over time due to the way compounding works. The fixed dollar approach uses relatively simple math for breaking even as shown below. Example: 3 losing trades followed by 1 winning trade using 1:3 risk-to-reward achieves breakeven (ignoring trading fees and slippage) This risk-to-reward ratio itself implies the win-rate needed (lose $100 three times, win $300 once, you break even). The fixed dollar amount risk doesn't deal with compounding. As such, its logic cannot be used for fixed %. ----- Using Fixed Percentage Risk: Fixed % uses a more complicated and less apparent method for calculating how to break even. As shown in our illustration, if you take three losses in a row you won’t break even after your next win. Fixed % is always dealing with the same % of your current balance. So as your balance decreases, the total dollar amount risked is less, and the total dollar amount gained with each win is reduced. Thus, strings of losses require additional wins compared to the fixed dollar approach. The fixed % method ensures against account erosion by showing the minimum win-rate needed to use each risk-to-reward ratio. MATH NOTE: We used a simplified method for finding the minimum win-rate to make this useful and generally applicable. Our method is based on a given risk-to-reward ratio and assumes the max number of losses in a row to produce a minimum win-rate, it does not factor in all different possible loss strings and their probability. ----- WHY USE FIXED % !?: The question one will have at this point is, "Why to use fixed % if it is so F'ing complicated!?" The answer to that is simple. Despite being more complicated, fixed % is actually objectively better by almost every other measure. With fixed % you generally perform better than fixed dollar during strings of losses and wins. As with fixed %, you lose less as you go down (because you only ever lose 1% of your balance), and you gain more as you go up (because of your winnings compounding). Not only that, but you also perform better even when losses and wins are more scattered, as you can see on the chart below. ----- Conclusion: Fixed % is more complicated than fixed dollar... to say the least. However , it is none-the-less superior in most instances. Use the logic above while using fixed % risk, since if you use fixed dollar logic but use fixed % in practice you will underperform your theoretical results. If there are any major flaws in our logic/approach please let us know in the comments as of course, we are looking to provide as accurate instructional writeups as possible!
BITSTAMP:BTCUSDEducation
by AlphaBotSystem
65
WHY CAN´T I BE PROFITABLE??!!Every trader has got himself into a loosing trade. This is simply the part of this game. You will never be able to predict every move correctly. The biggest thing that separates a profitable trader from an unprofitable trader is actually not better technical analysis or more experience. The biggest factors in my opinion are trade management and risk management. These two components will have immense effect on your profitability. With good risk management you can be profitable even if you are right on less than 50% of your trades. Good risk management means you know where you should get into a trade so you can set a stop loss (which upon hitting it should invalidate your entry) relatively close to your entry. This makes your losing trades much smaller than your winning ones. And the result of this ratio will be seen in your profitability through time. On the picture above you can see how one of my last trades went. I got in on the close of the candle marked with a green arrow. The trade then quickly went against me. But with my risk management i minimized the loss by closing the position when it closed below the red support line. I also put a stop(white support line) at a level that would upon breaking very likely invalidate my my long entry. Even though i took a loss i do not regret taking that trade since taking losses here and there is a part of my strategy and it can not be otherwise. Yesterday i also posted about another trade i was playing on the s&p 500. That trade turned out perfect. And with 50% winning rate for that day i made some really nice profit simply thanks to my risk management. Here you can check out how it went You can also go check out my posts from yesterday on why i was taking those trades.
Education
by Mathsio