Uptrend Sentiment Indicator: A new signal for price tendency in the cryptocurrency

Published in

Coinmonks

4 min readNov 27, 2021

Introduction

Sentiment lies at the heart of many aspects of cryptocurrency investors and it is therefore desirable to understand its price effect as well as possible. One attempt to improve our understanding of sentiment is the computational study of investors’ opinions called in the great area Sentiment Analysis (SA) [1].

In this study, Uptrend Sentiment Indicator (USI) will, therefore, be introduced and discussed its relation with price action conditions.

Uptrend Sentiment Indicator data treatment

The current investigation involved tracking and analyzing Google Trends information using the R statistics platform [2] with the gtrendsR package [3]. The uptrend words frequencies (“Bitcoin pump”, “Bitcoin bull”) were selected and subtracted from the downtrend words frequencies (“Bitcoin dump”, “Bitcoin bear”). Data prices were recruited from Quandl [4], 2021. The script repository is stored on Github [5].

Uptrend Sentiment Indicator (USI) equation of the sentiment model is shown in Eqn (1):

Where the USI signal is the dependent variable and f is the frequency of the words.

Next, the standard deviation of USI was used to normalize the USI as can be observed in Eqn (2):

Finally, a Savitzky–Golay filter was applied to smooth the USI data [6]. Data smoothing is achieved by a local polynomial regression, being one of the most popular smoothing filters and far superior to the moving averages commonly used in the crypto world.

Uptrend Sentiment Indicator

The goal of the USI is to express the investor´s sentiment by approximating this feeling as Google Trends queries. Using Eqn (2), the USI was plotted for the past 12 months (Figure 1).

Figure 2 shows the USI for the last seven days. Even though price action in the basis is affected by the global market, on-chain analysis, and others, it is possible to notice that USI presents a related behavior with the price and, this opens the opportunity to model this behavior.

Figure 2. Uptrend Sentiment Indicator (last week).

As can be observed, the representative graphic in Figure 1 gave an uptrend sentiment in the long term, but Figure 2 shows a downtrend sentiment in the short term.

Conclusion

The indicator developed in this work is versatile, fast, simple, and low-cost. The sentiment information made it possible to obtain an excellent price action tool. Applied to Bitcoin prices this year, an interesting relation was confirmed.

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Acknowledgments

The author is grateful to Satoshi Nakamoto, Hal Finney, Nick Szabo, Changpeng Zhao, Sabrina Moraes, and André Fauth.

References

1. Walaa Medhat, Ahmed Hassan, Hoda Korashy, Sentiment analysis algorithms and applications: A survey, Ain Shams Engineering Journal, 5 (4), 2014, https://doi.org/10.1016/j.asej.2014.04.011.

2. R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/

3. Philippe Massicotte and Dirk Eddelbuettel (2021). gtrendsR: Perform and Display Google Trends Queries. R package version 1.5.0. https://CRAN.R-project.org/package=gtrendsR

4. Raymond McTaggart, Gergely Daroczi and Clement Leung (2021). Quandl: API Wrapper for Quandl.com. R package version 2.11.0. https://CRAN.R-project.org/package=Quandl

5. https://github.com/edgarmoraesufrn

6. signal developers (2013). signal: Signal processing. http://r-forge.r-project.org/projects/signal/

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Uptrend Sentiment Indicator: A new signal for price tendency in the cryptocurrency

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Written by Edgar Moraes