Statistics for the Cup-and-Handle (Bullish) Pattern
Using sophisticated AI algorithms to find patterns in the securities markets used to be something only hedge funds and large financial institutions did.
Not anymore.
Today, retail investors of all levels can access Artificial Intelligence (A.I.) investment tools with just a few clicks. On Tickeron’s platform, investors can use A.I. to generate investment allocation ideas, to see how well a portfolio is diversified, and even to generate trade ideas based on patterns and trends the A.I. discovers.
One such pattern is the “Cup-and-Handle Bullish” formation. Here’s what it looks like on a stock chart:
Once the security’s price hits the “breakout”, an investor would make a trade in anticipation of the price rising further to the “target price”. The question is: how can investor possibly spot this pattern when there are literally thousands upon thousands of securities being traded?
The answer: Artificial Intelligence! Tickeron’s A.I. has discovered more than 13,000 Cup-and-Handle Bullish patterns, and more than half of them reached the target price as predicted by the A.I. Here are some statistics for the Cup-and-Handle Bullish pattern:
As you can see, for the patterns where the A.I. was correct, the average gain for the trader was +14.75% -- which is much higher than the loss incurred if the A.I. was wrong (which was less than half the time). The average return from all 13,398 discovered patterns was 4.25%.
In short, the Artificial Intelligence is right more often that it’s wrong, which is arguably a noteworthy accomplishment in the trading and investment world.
Here is a real-world example of Tickeron’s Artificial Intelligence in action, and it’s for a company everyone knows: Alphabet (Google).
This pattern emerged late last year, on December 20, 2017. Take a look at the chart closely. You can see how the A.I. monitored Google’s price movements through early January, and how Google’s share price traced a cup (points 1 to 3) and a holder (points 3 to 4). As soon as the A.I. noticed that Google hit it’s “breakout price”, the A.I. made a prediction that the stock would rise to $1,145. The A.I. was right:
For retail investors reading this, who want to learn more about how this tool works and perhaps even give it a try, it is called the Pattern Search Engine and you can try it free for 45 days. The A.I. will deliver trade ideas right to your inbox.
Here is another opportunity that the A.I. discovered recently. Tickeron pattern subscribers would have seen this pattern in their inboxes sometime just before November of last year. The A.I. started tracing a cup formation from early October through the middle of the month, and the holder formed quickly as you can see on the chart below. Once Twitter hit its breakout price, the A.I. predicted it would bump higher to $19.87. The A.I. was correct in this case as well:
For investors who enjoy trading the markets and looking for unique opportunities, it could make sense to add a new, Artificial Intelligence-powered tool to your investment toolbox. Humans do not have the time or the ability to scan the markets day-in and day-out looking for patterns in stocks, ETFs, mutual funds, and cryptocurrencies. It is simply not possible -- unless you get help from algorithms and A.I. Give Tickeron’s new platform a try to enhance your trading by using hard data to trade patterns and make investment decisions. A 45-day trial is free, and you might be surprised at just how effective Artificial Intelligence can be when applied to trading.
The 10-day moving average for GOOGL crossed bullishly above the 50-day moving average on March 22, 2024. This indicates that the trend has shifted higher and could be considered a buy signal. In of 17 past instances when the 10-day crossed above the 50-day, the stock continued to move higher over the following month. The odds of a continued upward trend are .
Following a 3-day Advance, the price is estimated to grow further. Considering data from situations where GOOGL advanced for three days, in of 350 cases, the price rose further within the following month. The odds of a continued upward trend are .
The Aroon Indicator entered an Uptrend today. In of 323 cases where GOOGL Aroon's Indicator entered an Uptrend, the price rose further within the following month. The odds of a continued Uptrend are .
The 10-day RSI Indicator for GOOGL moved out of overbought territory on April 12, 2024. This could be a bearish sign for the stock. Traders may want to consider selling the stock or buying put options. Tickeron's A.I.dvisor looked at 45 similar instances where the indicator moved out of overbought territory. In of the 45 cases, the stock moved lower in the following days. This puts the odds of a move lower at .
The Stochastic Oscillator has been in the overbought zone for 1 day. Expect a price pull-back in the near future.
The Momentum Indicator moved below the 0 level on April 25, 2024. You may want to consider selling the stock, shorting the stock, or exploring put options on GOOGL as a result. In of 92 cases where the Momentum Indicator fell below 0, the stock fell further within the subsequent month. The odds of a continued downward trend are .
The Moving Average Convergence Divergence Histogram (MACD) for GOOGL turned negative on April 16, 2024. This could be a sign that the stock is set to turn lower in the coming weeks. Traders may want to sell the stock or buy put options. Tickeron's A.I.dvisor looked at 49 similar instances when the indicator turned negative. In of the 49 cases the stock turned lower in the days that followed. This puts the odds of success at .
Following a 3-day decline, the stock is projected to fall further. Considering past instances where GOOGL declined for three days, the price rose further in of 62 cases within the following month. The odds of a continued downward trend are .
GOOGL broke above its upper Bollinger Band on April 11, 2024. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options.
The Tickeron Price Growth Rating for this company is (best 1 - 100 worst), indicating outstanding price growth. GOOGL’s price grows at a higher rate over the last 12 months as compared to S&P 500 index constituents.
The Tickeron Profit vs. Risk Rating rating for this company is (best 1 - 100 worst), indicating low risk on high returns. The average Profit vs. Risk Rating rating for the industry is 93, placing this stock better than average.
The Tickeron SMR rating for this company is (best 1 - 100 worst), indicating strong sales and a profitable business model. SMR (Sales, Margin, Return on Equity) rating is based on comparative analysis of weighted Sales, Income Margin and Return on Equity values compared against S&P 500 index constituents. The weighted SMR value is a proprietary formula developed by Tickeron and represents an overall profitability measure for a stock.
The Tickeron PE Growth Rating for this company is (best 1 - 100 worst), pointing to consistent earnings growth. The PE Growth rating is based on a comparative analysis of stock PE ratio increase over the last 12 months compared against S&P 500 index constituents.
The Tickeron Valuation Rating of (best 1 - 100 worst) indicates that the company is slightly overvalued in the industry. This rating compares market capitalization estimated by our proprietary formula with the current market capitalization. This rating is based on the following metrics, as compared to industry averages: P/B Ratio (6.821) is normal, around the industry mean (19.638). P/E Ratio (26.802) is within average values for comparable stocks, (49.308). Projected Growth (PEG Ratio) (1.626) is also within normal values, averaging (3.441). Dividend Yield (0.000) settles around the average of (0.026) among similar stocks. P/S Ratio (6.435) is also within normal values, averaging (110.312).
The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
a holding company with interests in software, health care, transportation and other technologies
Industry InternetSoftwareServices