The article talks about how the writer and his team missed a good opportunity to make money by trading stocks of IBM, which is a big company that makes computers and other technology stuff. They didn't believe their own system that gives them a score on how likely IBM's stock will go up or down after they report their earnings (how much money they made in a period). Because they ignored their system, they missed a chance to make more than 100% profit from trading stock options. The writer says he learned his lesson and won't repeat the same mistake again. Read from source...

1. The author admits that they did not believe their own composite score for IBM, which was very bullish based on social data. This shows a lack of confidence in their methodology and an unwillingness to follow the data-driven insights provided by their approach.
2. The author states that they missed out on what might have been a >100% return on an options trade because of their skepticism. This implies that they did not execute the trade, or they sold the option before it expired, resulting in a loss of potential profit. This demonstrates poor decision-making and risk management skills, as well as a failure to recognize the value of their own analysis.
3. The author does not explain why they were skeptical of their composite score for IBM, or provide any evidence or reasoning behind their doubt. This leaves the reader wondering if there was any valid justification for their reluctance, or if it was simply based on personal bias or emotional factors.
4. The author does not acknowledge any possible flaws or limitations in their approach to analyzing earnings trades, nor do they provide any examples of when it has worked well or failed miserably. This makes the article seem like a one-sided promotion of their methodology, without any critical evaluation or self-reflection.
5. The author does not offer any concrete advice or guidance on how to avoid making the same mistake in the future, other than stating that they won't make it again. This is an unsatisfying and unhelpful conclusion for the reader, who may be looking for actionable steps or tips on how to improve their own trading performance.
6. The author does not provide any context or background information about IBM, its industry, its competitors, or its recent performance. This makes the article seem like it is focused solely on the author's personal experience and feelings, rather than offering any valuable insights or analysis of the company or its stock.
7. The author does not address any potential conflicts of interest or biases that may have influenced their decision-making or reporting. This could include financial incentives, professional relationships, or personal opinions that may have swayed their judgment or objectivity.
8. The author uses vague and ambiguous language throughout the article, such as "very bullish", "might have been", "we'll avoid this mistake next time", etc. This makes it difficult for the reader to understand exactly what the author is trying to communicate, or how they are measuring their performance or results.
9. The author does not cite any sources or evidence to support their claims or arguments, such as data, statistics, studies, or expert opinions. This leaves the article lacking in credibility and authority, as well as making it difficult for the

- The article is written with a bullish sentiment towards IBM, as it highlights the missed opportunity to make a profit from an options trade due to skepticism of the composite score. However, it also serves as a learning experience and suggests that they will not make the same mistake again in the future.

1. Based on the article, it seems that IBM is a good candidate for an earnings trade, as the composite score was very bullish and there was potential for >100% return on an options trade. However, the authors missed out on this opportunity due to their skepticism of the score, which they later regretted.
2. The main risk in trading IBM is that the company faces significant competition from cloud computing providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform, which could erode its market share and revenues in the long run. Additionally, IBM's transition to a hybrid cloud provider may not be smooth or profitable, as it requires heavy investments in research and development, infrastructure, and partnerships.
3. To mitigate these risks, an investor could consider a covered call strategy, where they buy the stock and sell a corresponding number of call options with a strike price close to the current market price. This way, the investor would receive income from the option premium while also participating in any upside potential of the stock. However, this strategy also exposes the investor to the risk of losing their dividend if the stock price declines significantly before the expiration date of the options. Alternatively, an investor could consider a bull call spread, where they sell a higher strike call option and buy a lower strike call option, collecting a premium for the difference. This way, the investor would limit their upside potential to the difference between the two strikes, but also reduce their risk of losing their dividend if the stock price drops. However, this strategy requires a larger upfront capital outlay and exposes the investor to the risk of the stock price moving sideways or slightly higher.