Volatility spillover in crypto-currency markets: Some evidences from GARCH and wavelet analysis

2019 ◽  
Vol 524 ◽  
pp. 448-458 ◽  
Author(s):  
Anoop S. Kumar ◽  
S. Anandarao
Keyword(s):  
Wavelet Analysis ◽  
Volatility Spillover ◽  
Currency Markets ◽  
Crypto Currency

HERDING IN CRYPTO-CURRENCY MARKETS

2018 ◽  
Vol 13 (02) ◽  
pp. 1850006 ◽  
Author(s):  
TAUFEEQ AJAZ ◽  
ANOOP S. KUMAR
Keyword(s):  
Market Volatility ◽  
Currency Markets ◽  
Herding Behavior ◽  
Market Activity ◽  
Reaction Market ◽  
Market Index ◽  
Crypto Currency ◽  
Daily Returns

We test for herding in crypto-currency markets using the CSAD method of Chang et al. (2000). Daily returns of 6 major crypto-currencies and market index CCI30 for the period 07-08-2015 t0 18-01-2018 is used. Possibility of herding under up and down market and high and low volatility is tested. Herding is found under up and down market activity, indicating over-enthusiasm and over-reaction. Market volatility is found not to have any significant impact on herding behavior. Herding is found to be dependent upon the market activity rather than market volatility.

Classification of Acceleration Waveforms during Walking by Wavelet Transform

1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Center Of Gravity ◽  
Dynamic Responses ◽  
Sequential Data ◽  
Acceleration Signal ◽  
Continuous Dynamic

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.

Study of Identification Method of Drunk Driving Based on Wavelet Analysis

ICCTP 2011 ◽  
2011 ◽  
Author(s):  
Xing-jian Zhang ◽  
Xiao-hua Zhao ◽  
Jian Rong ◽  
Shi-li Xu
Keyword(s):  
Wavelet Analysis ◽  
Drunk Driving ◽  
Identification Method

Efficiency of application of the phase-chronometric method and neurodiagnostics for monitoring the degradation of rolling bearings during operation

2020 ◽  
pp. 43-50
Author(s):  
A.S. Komshin ◽  
K.G. Potapov ◽  
V.I. Pronyakin ◽  
A.B. Syritskii
Keyword(s):  
Life Cycle ◽  
Wavelet Analysis ◽  
Metrological Support ◽  
Rolling Bearing ◽  
Technical Condition ◽  
Measurement Information ◽  
Rolling Bearings ◽  
Vibration Diagnostics ◽  
Bearing Life ◽  
Alternative Approach

The paper presents an alternative approach to metrological support and assessment of the technical condition of rolling bearings in operation. The analysis of existing approaches, including methods of vibration diagnostics, envelope analysis, wavelet analysis, etc. Considers the possibility of applying a phase-chronometric method for support on the basis of neurodiagnostics bearing life cycle on the basis of the unified format of measurement information. The possibility of diagnosing a rolling bearing when analyzing measurement information from the shaft and separator was evaluated.

Sign in / Sign up

Export Citation Format

Share Document