How to Use Second-Level Thinking in Trading
Trading capital markets is a classic zero-sum game. The better you understand your opponents, the more success you will have. How can we apply this understanding to expand our way of thinking in trading?
First, let’s explore the nature of the game. What is a zero-sum game? Laura Porter of Investopedia summarizes it well:
Zero-sum is a situation, often cited in game theory, in which one person’s gain is equivalent to another’s loss, so the net change in wealth or benefit is zero.
Like players in a chess match, traders must understand that where there is a winner, there is consequently a loser. Traders who have made money in a trade are a result of other traders who have lost money in their own different trades. As a market participant, this is fundamental to understand because it eliminates the illusion that money earned from trading comes from thin air.
How can we use this principle to gain an edge?
Trading is like a game of war, a player versus another in a tennis match, or an elaborate game of chess. Nobody likes to lose, especially when it comes to money, so there is an underlying incentive for market participants to gain a competitive edge to make money. So what is the trading equivalent of having a competitive edge, like understanding nine moves ahead in chess? An edge can come in many forms, but typically in the form of inefficiency. For example, timing an entry/exit to the second of a new announcement is a potential strategy for reacting more quickly than other participants. Another example would be a thorough analysis of the rumored acquisition of a company and its likelihood and positioning for a trade before other participants fully account for that possibility.
The point is that trading is, at its very core, people-based. It is deeply psychological, extending from an internal and individual to an external and consensus perspective. Leveraging this idea is crucial in reducing the noise and staying more focused on specific metrics like market sentiment, which have been very useful for some of my best trades. So how might we get an edge in market sentiment over other traders?
Second-level thinking
A trader must identify how people’s perceptions (like other traders) move the markets. In Howard Marks’ “The Most Important Thing,” a well-regarded book for investing, he highlights that there are two levels of thinking for market participants. The first-level is often obvious and trivial (i.e., coronavirus is not good for the stock market), so it has limited potential to be used as an accessory to achieve consistently profitable trades. On the other hand, the second-level of thinking analyzes the market sentiment more deeply and critically. After all, many variables must be considered for a potentially profitable trade idea. Second-level thinkers often ask themselves some of the following:
- What do most market participants think of the coronavirus omicron variant (2021)?
- How does my expectation differ from theirs?
- How does the S&P’s (broad market equity index) current price behave compared to the consensus view of the future?
- How does the Nasdaq’s (broad tech-heavy equity index) current price differ from the S&P’s price, if at all?
- Is the consensus psychology incorporated in the markets too bullish or bearish? Is there a potential opportunity?
To become a good trader, you must utilize the second-level of thinking because the majority of money in the market is held by people who only use the first level of thinking. Think of your family or friends, people who have invested in their 401k (broad market), or even newly active traders who have yet to discover the second-level thinking that is often convoluted and complex. Most importantly, because other seasoned traders already use this second-level of thinking, it is critical to understand how to utilize it for yourself to beat them in the game of chess. This method is now sometimes referred to as contrarian investing/trading. Marks summarizes this idea well in the book:
“You must do things not just because they’re the opposite of what the crowd is doing, but because you know why the crowd is wrong. Only then will you be able to hold firmly to your views and perhaps buy more as your positions take on the appearance of mistakes and as losses accrue rather than gains” (pg. 111).
Example application (conceptual):
An application of this idea for equity trading in particular — now that we better understand the nature of trading and the financial markets — is through observing institutional influence. It should raise your eyebrow when market participants with influence release their opinions of the market or specific assets. For example, when an analyst changes their target price for a stock, and the institution they’re representing has a position in that same stock…we may suspect a potential underlying bias or motive. Suppose the target price of a stock is raised, and the institution is bullish. In that case, the majority use their first level of thinking to deduce the following: “This financial institution specializing in stock valuation and financial assets certainly knows more than I do. Therefore, I will buy the stock.”
However, finding out who benefits from this type of strategy under the surface and playing on their side can be very beneficial. Using the second-level of thinking, an experienced trader may theorize that an institution issuing a higher target price for a stock may intend to sell that same stock at a higher price after the announcement. Perhaps the institution has an underlying belief that the market cycle has come to the top or that the forward-looking fundamentals of the company are lacking compared to its valuation in the long run. In any case, it is up to you to perform the analysis and utilize second-level thinking to understand why the crowd might be wrong. Peter Lynch details an example of this idea in his equity investing classic “One Up On Wall Street”:
“If forty Wall Street analysts are giving the stock their highest recommendation, 60 percent of the shares are held by institutions, and three national magazines have fawned over the CEO, then it’s definitely time to think about selling.”
This is not to say that these recommendations are always intentionally misleading or unethical. Remember, many financial institutions serve to aid their clients and the masses achieve their financial goals. Still, as a trader, it is your job to understand the layered consequences when an institution with influence takes a stance. It serves a trader best to view all types of information without personal bias because external emotional influence can easily cloud one’s judgment.
Below is an example that will give you an idea of how to utilize the concepts above to expand your way of thinking when trading. This is a look into how I approach a trade idea. This portion is much more technical than the above. Feel free to skip down to the takeaways at any point.
Example Application (technical): Tesla and the Put/Call Ratio
It’s time to put our newfound knowledge of understanding others into action to form a basic hypothesis for Tesla. Sentiment analysis can prove very valuable once you know the nature of the game. One of my favorite sentiment indicators is the put/call ratio. The put/call ratio is calculated by dividing the number of put options by the number of call options for a given time. For simplicity’s sake, a put option is a bet that the price will go down, and a call option is a bet that the price will go up. Let’s begin.
As shown above, Tesla has been trending significantly downward for the last six months. Tesla is down over 20% on the 1M charts. Using my first level of thinking, I conclude that Tesla has been going down because the rest of the stock market is going down, mainly because of the increased rate hikes from the Federal Reserve due to inflation. Perhaps I can also conclude that tech stocks are falling at a higher rate than non-tech stocks (higher beta), so Tesla’s stock price suffers because of that phenomenon. There is undoubtedly more information to analyze, like Elon Musk’s recent behavior and how his Twitter acquisition ties into Tesla’s current stock valuation, but let’s keep it simple for the exercise. What sort of information can we extract from the put/call ratio?
How do we analyze the put/call ratio?
- Using historical data, a rising put/call ratio of 0.7 or exceeding 1 suggests a bearish sentiment.
- Conversely, a falling put/call ratio below 0.7 would indicate bullish sentiment as more calls are being purchased than puts.
To give context for exhibit A, Tesla stock fell a whopping 8.05% today, as shown in exhibit B. In exhibit A, we can see that the put/call ratio was 0.84, which is above 0.7 but has yet to exceed the 1.0 threshold. The historical analysis above suggests that the data is in line with the market (the market is bearish, and the indication is bearish). Looking at the future expiration dates on the left, my goal is to analyze the short-term market sentiment using the 12/23 expiration.
My Analysis:
For the 12/23 expiration, we can see that the put/call ratio sits at 0.7 for the rest of the week. Using my second-level of thinking, I recognize that this ratio is lower than expected. Why? My initial expectation of the reading is a bearish consensus (0.7–1.0+), given the significant price decrease on 12/20 and the sustained bearish trend in recent weeks. However, the data suggests that the market sentiment for the remainder of the week is neutral to slightly bullish, given the context. Maintaining the contrarian mindset of going against the crowd, I lean somewhat towards favoring a bearish continuation.
Outside of this exercise, my personal strategy factors in that this ratio is in what I consider neutral territory (.6 to .8). Therefore, I would not be as interested in taking a position based on this data alone. Due to my risk tolerance, I had set my parameters only to enter a trade when I considered an outcome highly probable which I measure by an exceedingly bearish consensus (over 1–1.1), in which case I would buy calls or an exceptionally bullish consensus (under .5) in which case I would buy puts. Remember, everybody’s strategy can be different. Using other people’s strategies as a baseline can be a good place to start. Had the reading been >1 for the rest of this week instead of 0.7, I would proceed by analyzing other data to build more support for a long (bullish) position. This additional data could include current events affecting the broader markets for the rest of the week, Tesla-specific news, technical analysis, etc.
Further analysis using analyst ratings:
Inspired by Peter Lynch’s quote and the conceptual application illustrated earlier, I looked at Tesla’s most recent price target and rating changes from analyst institutions. The results support Peter Lynch’s second-level thinking example very closely, in an inverse fashion. To reiterate, we have seen Tesla’s stock price decline sharply for the past six months, as previously illustrated. However, the analyst ratings suggest that the price is significantly undervalued (targeting over 100% upside in some instances) and has been suggesting price upside for the last two months.
If a new trader had seen this data and applied the first level of thinking, they might have thought that the institutions with far more expertise and prowess in analyzing stock prices would be right. This would have led them to buy into Tesla’s upside and suffer losses. However, we have learned that by applying the second-level of knowledge, a more experienced trader could have become profitable using this data as an indicator to position in the opposite direction. They could speculate that institutions may be taking significant hedges or even short positions in preparation for worsening general market conditions, which could be taken at a lower price if the short-term price is elevated after an announcement. In any case, this shows a real-world example of Lynch’s theory at work.
Takeaways
My goal is to help break down the nature of trading to get aspiring and new traders to think differently. This is not to say that the examples used above will work in the future - as we know, there is never a guarantee - but the concepts should inspire you to challenge what you think you know and join other traders in constantly thinking outside the box. Utilize the second-level of thinking, remember the nature of the game, and never grow tired of learning. It is a complex and convoluted web of information to sift and work through constantly, but when you finally find an edge, I can assure you there is nothing quite as rewarding.
It is important to note that the two data sets analyzed would not be sufficient for me to make an executable trade. More data is necessary to solidify a strong trade idea, especially since the put/call ratio was particularly neutral. As mentioned earlier, if the put/call ratio had been more extreme, I could use that data point as a base to build around for a trade setup. It is up to the individual trader to figure out how much weight to put on each piece of information and if the information is sufficient to take a stance. This ultimately results in the formation of a strategy that will beat or lose to another trader in this zero-sum game.
Note from the example: Tesla is not identical to the general market, so using the same metrics to analyze the two could present inaccuracies. I have linked a tool I use to find moving averages of the put/call ratio volume to find more specific data for a specific asset. The example aims to establish a structure for a potential trading approach using the concepts discussed throughout the post.
Thank you for reading!
12/22/22 Update for the Tesla example:
Tesla’s stock price continued down before the 12/23 expiration, analyzed using the put/call data from earlier. The application of our contrarian second-level of thinking in our analysis pointed in the right direction. In summary, we observed that the put/call ratio at 0.7 (which suggested market confidence leaning in favor of bounce, or long, from Tesla by the end of 12/23 from 12/20, given the context of the drop) was lower than the ratio we expected. So, we were inclined to exercise thinking against the crowd, understanding why we were doing so and taking on a neutral or bearish stance. If we had spent the time to build a stronger case around this exercise, a short term short trade at the time could have worked remarkably well, as shown today.
