The effectiveness of supervised learning models in detection of pump and dump activity in Dogecoin

Sisi Shao

doi:10.1117/12.2622877

1 December 2021 The effectiveness of supervised learning models in detection of pump and dump activity in Dogecoin

Sisi Shao

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120791I (2021) https://doi.org/10.1117/12.2622877
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

B Investment into hazardous assets should always be made with caution, if not avoided completely by risk-averse groups, such as the older workforce. However, as society and technology advance, it becomes almost impossible for regulators to make effective enough laws to mitigate the risk of newly invented financial instruments, such as cryptocurrency. This paper analyzed how effective are modern data science techniques: supervised learning models, such as random forest, K Nearest Neighbors, decision tree, combined with bagging and stacking techniques, could be used to catch the notorious "pump and dump" activities in the Dogecoin market, which is the cryptocurrency that had a close to positive infinity return in May 2021 during the COVID-19 pandemic. This paper concluded that random forest algorithm, when trained with a five-folded cross-validation technique, could reach an out-of-sample testing accuracy of 100%. Furthermore, the F1 score of 0.84101, precision score of 0.94402, and recall score of 0.77700 could alleviate one's concern about overfitting. In conclusion, the model results suggest modern supervised learning techniques are quite effective in catching suspicious activities in modern financial instruments

Citation Download Citation

Sisi Shao "The effectiveness of supervised learning models in detection of pump and dump activity in Dogecoin", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120791I (1 December 2021); https://doi.org/10.1117/12.2622877

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Machine learning

Performance modeling

Web 2.0 technologies

Signal detection

Analytical research

Data conversion

Show All Keywords

Keywords/Phrases

Search In:

Publication Years