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Rolls Royce Stock Analysis HOLDThe Rolls-Royce (LSE:RR) share price has slumped to 84p. Today’s share price crash is due to over 6bn new shares hitting the market. Since each share now represents a far smaller slice of ownership of Rolls-Royce, they are all worth less today compared to yesterday. If you have 300 existing shares, for example, you have the right to buy 1,000 new shares at 32p. By buying all your rights for a total price of £320, you now have 1,300 shares and own the same percentage of the company as you did before the rights issue. Rolls-Royce’s £2bn cash call has been “overwhelmingly” backed by shareholders, unlocking a rescue package totalling £5bn. Investors supported the 10-for-3 rights issue in which they can buy new shares at 32p - a 41pc discount. Agreeing to the rights issue allows Rolls to access £2bn of bonds it has sold, and the Government has backed a potential £1bn of further debt.
LSE:RR.
by Mauriello
RR - ROLLS ROYCE Technical AnalysisPrices have been moving inside the channel and now that the prices are closer to the top resistance level the following Options canbe possible: (hold before going for one of the below options) Option 1 - 50% Only if the resistance level of 2.40 Pound will be broken Option 2 - 50% Only if the resistance level of 2.40 Pound will NOT be broken A Breakout of a support/resistance line could be considered valid only if the close price of a daily candlestick for at least two consecutive days is below/above the support/resistance level
LSE:RR.
by Mauriello
ROLLS ROYCE WAS AN ABSOLUTE BUY AT 100 PSYCHOLOGICAL AREA Rolls Royce was an absolute buy at 100 psychologycal area last week,and in fact it reacted with an epic bounce. By the way, looks like other juicy targets are still available for long term investors. After a massive collapse in price started on january 2014, the price seems to have found a bottom last week. Actually, we are still at prices seen even 15 years ago in 1996, so for investors who truly believe in the company, this looks like a great oppurtunity to accumulate some positions, without looking too much to the possible turbolences that we could see on next months. In case the world would come close to an end(lol),there is also the support in green, that was the absolute bottom of the whole company history in 2003.
LSE:RR.Long
by themaster5
10
HDFCAMC Fib SupportNSE:HDFCAMC experienced quite a lot of hesitation at higher levels after bouncing up from ~2430. After retracing from higher levels, we can see it attempting a recovery once again. If the support is held, it could be a good swing long as long as the incoming resistances can be breached. As of now, it is just under the 13DMA (not added in the chart). So a positive Monday closing could increase strength. HDFCAMC has typically underperformed vis-a-vis the other HDFC sister companies, but it remains to be a fairly strong pick among the various asset management companies.
NSE:HDFCAMCLong
by MarketsWithKR
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