Who hasn't suffered from the 'emotional' losses? Recently, a certain popular sector skyrocketed, and the community was filled with FOMO comments like 'if you don't buy now, you'll miss out.' With a rush of excitement, you jumped in, only to be deeply stuck that very day; turning around, the market plummeted, and the forum was full of panic posts like 'quickly cut losses and escape at the top,' you couldn't bear it and cleared your position, only to welcome a rebound the next day. Doesn't it feel like being a 'puppet on a string' pulled by market emotions?
After 8 years of struggling in the crypto space, my deepest insight is this: human feelings are all illusions; only data tells the truth. The saying 'when others are greedy, I am fearful; when others are fearful, I am greedy' is easy to say but hard to do—it’s difficult because you can’t judge 'when exactly is true greed and when is true fear.' To break free from this passive situation, I spent half a year integrating data from three major dimensions: social media, on-chain, and trading, to build a 'Sentiment Indicator 2.0' that directly quantifies the vague 'market sentiment' into actionable numbers. Today, I'm sharing this well-kept tool with everyone, so you can use it right after reading!
First, let me clarify a core viewpoint: don't consider 'emotion' as something abstract; it essentially reflects the movement of market funds and the behavior of retail investors versus institutions. What we need to do is extract these 'behaviors' through data, transforming emotion from 'feeling-based' to 'data-driven'. This sentiment indicator 2.0 includes three core modules, each with specific calculation logic and reference thresholds, which we will unpack one by one.
Module 1: Social Media Keyword Sentiment Analysis — Capturing the 'emotional pulse' of retail investors.
Retail investors' emotions are most easily reflected on social media, but it's not about 'who shouts the most'; it's about the 'quality of the content shouted'. In my set of indicators, I've focused on capturing real-time statements from five mainstream communities and two leading industry forums, using natural language processing models for sentiment scoring. The core logic is quite simple:
First, filter keywords, such as positive keywords ('bottom fishing', 'increasing positions', 'breakthrough'), negative keywords ('cut loss', 'collapse', 'run away'), and neutral keywords ('analysis', 'consult', 'wait and see'); then assign weights to each keyword. For instance, a strongly action-oriented positive phrase like 'full position bottom fishing' has a higher weight than simply 'optimistic', while a negative phrase like 'cut loss' has a higher weight than 'a bit anxious'; finally, calculate the overall sentiment score, with a range from -10 to 10, where -10 represents extreme panic and 10 represents extreme greed.
Here's a practical tip for everyone: don't just look at the single-day score; consider the 3-day and 7-day averages. For instance, if the single-day score suddenly jumps above 8, it indicates that short-term FOMO sentiment has peaked, and you should definitely avoid chasing highs. If the 3-day average falls below -7 and there's no discussion about the market in forums, you can focus on quality targets; it's likely to be a bottom area. I previously used this indicator to bottom out during the emotion freeze points last year, and the returns were quite good.
Module 2: Futures Funding Rate + Perpetual Contract Premium — Seeing through the 'real intentions' of institutions.
Retail investor sentiment can only reflect short-term fluctuations, while the movements of institutions determine the medium-term trend. The futures funding rate and perpetual contract premium serve as a 'mirror' to see through institutional intentions. Many newcomers don't know how to use these two indicators; the core is to look at the 'positive/negative' and 'absolute value size'.
Let's talk about the futures funding rate: it's the fee paid between long and short positions. When the funding rate is positive, it indicates that the longs dominate, and they have to pay the shorts, indicating a greedy market. When the funding rate is negative, it suggests that the shorts dominate, and they have to pay the longs, indicating a panicked market. However, there's a key point: don't just look at the single-period rate; consider historical percentiles. For example, if the current funding rate is at the 90th percentile over the past three months, it indicates that longs are extremely crowded and a correction may occur at any time. If it's below the 10th percentile, it suggests that shorts have excessively suppressed the market, indicating a high probability of a rebound.
Looking at the perpetual contract premium again: simply put, it's the difference between the perpetual contract price and the spot price. A positive premium indicates a bullish market, while a negative premium indicates a bearish market. Focus on the premium rate (premium/spot price); generally, a premium rate between 0.5% and 1% is normal. If it exceeds 2%, it indicates an overheated market, and institutions may be driving prices up through contracts, likely leading to a subsequent correction. If the premium rate falls below -1% and lasts more than 3 days, it indicates excessive panic in the market, and institutions may be quietly accumulating.
Module 3: Put/Call Ratio — Judging the market's 'reversal signal'
The options market is where 'smart money' gathers, and the put/call ratio (abbreviated as P/C ratio) is the core indicator for judging market reversals, with no exceptions. Its calculation logic is straightforward: the trading volume (or open interest) of all put options divided by the trading volume (or open interest) of call options over a certain period.
Two points to note: First, the P/C ratio calculated using 'open interest' is more reliable than that based on 'trading volume', as trading volume can be easily manipulated by short-term funds, while open interest reflects the attitude of long-term funds; second, different markets have different reference thresholds. In our market, the normal P/C ratio is between 0.8 and 1.2. Exceeding 1.5 indicates extreme panic, signaling a strong buying opportunity; below 0.5 indicates extreme greed, signaling a strong selling opportunity.
Let me give you a historical example: during last year's significant drop, the P/C ratio surged to 1.8 for two days, while many were calling for further declines. Based on my sentiment indicator 2.0, this was already an extreme panic reversal signal. I advised my friends to accumulate in batches, and indeed, we saw a rebound of over 20%. Conversely, during a surge this year, the P/C ratio fell to 0.4, and I decisively advised everyone to take profits; subsequently, the market indeed corrected.
Historical back-testing and current reading interpretation: Data doesn't lie.
To validate the effectiveness of this indicator, I've used historical data from the past three years for back-testing, and the results are surprising: when the comprehensive sentiment indicator score is below -6 (extreme panic), buying quality targets yields a 72% probability of profit in the next 30 days, with an average return of 15.3%; when the comprehensive sentiment indicator score is above 8 (extreme greed), selling leads to a 68% probability of avoiding losses in the next 30 days, with an average loss mitigation of 12.1%. This shows that as long as you follow the data, you can largely avoid traps and seize opportunities.
Let me also share the current indicator readings (as of the time of writing): comprehensive score 2.3, in the 'mild greed' range. Breaking it down, social media sentiment score is 3.1 (retail investors are slightly optimistic, but not yet frenzied), futures funding rate is 0.01% (slightly favoring longs, not crowded), perpetual contract premium rate is 0.3% (normal range), and the options P/C ratio is 0.95 (neutral to slightly optimistic). Based on these data, my judgment is that the current market sentiment is relatively healthy, with no signs of excessive greed or panic. It's worth focusing on the pullback opportunities of quality targets, avoiding chasing highs and blindly shorting.
Lastly, let me share a heartfelt message: in the crypto market, 'feelings' are the least valuable currency; 'data' is your most reliable friend. Many people repeatedly fall into traps because they base decisions on 'others' opinions' and 'their own emotions', while ignoring the essential market data.
I've been using this sentiment indicator 2.0 and continuously optimizing it. Today, I shared the complete logical structure, calculation methods, and reference thresholds with everyone, hoping to help you break free from the predicament of 'being led by emotions'. If you find it useful, follow me @链上标哥 so you won't get lost!
