Volatility Clustering, Fat Tails and Bitcoin Exchange Rate Returns

2017 ◽  
Author(s):  
Ruiping Liu ◽  
Zhichao Shao ◽  
Guodong Wei
Keyword(s):  
Exchange Rate ◽  
Fat Tails ◽  
Volatility Clustering

scholarly journals Modeling the Co-Movement of Inflation and Exchange Rate

2020 ◽  
Author(s):  
Nelson Christopher Dzupire
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Policy Design ◽  
Great Influence ◽  
Causality Test ◽  
Bivariate Model ◽  
Volatility Clustering ◽  
Hedging Strategies ◽  
Consumer Prices ◽  
Inflation Rates

Inflation and exchange rates have great influence on consumer prices especially on imports and exports. Exchange rate fluctuations create inefficiency and distort world prices whereas changes in inflation rates have a direct impact on consumer goods prices which incidentally include exchange rates. There is a direct interdependence between inflation and exchange rates and this paper is aimed at investigating this relationship in dynamic context. It tries to find out how changes in inflation and exchange rates impact on another by adopting the econometric and copula approaches. Both inflation and exchange rates data are susceptible to volatility clustering, possess fat tails and are skewed coupled with conditional heteroskedasticity. Hence we model the univariate distributions by using ARMA$(p,q)$-GARCH$(x,y)$ so as to capture the most important stylized features of inflation and exchange rates. A bivariate model is then constructed by coupling the marginal distributions of inflation and exchange rates using the survival Clayton copula. Empirical results from monthly inflation and exchange rates data show positive correlation between the two based on Kendall $\tau$ test which confirms that a change in inflation results in change of exchange rates an vice versa hence there is co-movement. Furthermore, by the Granger causality test, exchange rates spikes cause changes in inflation rates. The results of the study have implications on economic policy design and hedging strategies for traders on imports and exports.

scholarly journals Modeling Exchange Rate and Nigerian Deposit Money Market Dynamics Using Trivariate form of Multivariate GARCH Model

2019 ◽  
pp. 1-18
Author(s):  
Deebom, Zorle Dum ◽  
Tuaneh, Godwin Lebari
Keyword(s):  
Exchange Rate ◽  
Garch Model ◽  
Money Market ◽  
Multivariate Garch ◽  
Market Dynamics ◽  
Volatility Clustering ◽  
Volatility Spillovers ◽  
Multivariate Garch Model ◽  
The Difference ◽  
Student’S T

The risks associated with exchange rate and money market indicators have drawn the attentions of econometricians, researchers, statisticians, and even investors in deposit money banks in Nigeria. The study targeted at modeling exchange rate and Nigerian deposit banks money market dynamics using trivariate form of multivariate GARCH model. Data for the period spanning from 1991 to 2017 on exchange rate (Naira/Dollar) and money market indicators (Maximum and prime lending rate) were sourced for from the central bank of Nigeria (CBN) online statistical database. The study specifically investigated; the dynamics of the variance and covariance of volatility returns between exchange rate and money market indicators in Nigeria were examine whether there exist a linkage in terms of returns and volatility transmission between exchange rate and money market indicators in Nigeria and compared the difference in Multivariate BEKK GARCH considering restrictive indefinite under the assumption of normality and that of student’s –t error distribution.  Preliminary time series checks were done on the data and the results revealed the present of volatility clustering. Results reveal the estimate of the maximum lag for exchange rate and money market indicators were 4 respectively. Also, the results confirmed that there were two co-integrating equations in the relationship between the returns on exchange rate and money market indicators.  The results of the diagonal MGARCH –BEKK estimation  confirmed  that diagonal MGARCH –BEKK in students’-t was  the best fitted and an appropriate model for modeling exchange rate and Nigerian deposit money market dynamics using trivariate form of multivariate GARCH model. Also, the study confirmed presence of two directional volatility spillovers between the two sets of variables.

scholarly journals ASYMMETRIES, CORRELATIONS AND FAT TAILS IN PERCOLATION MARKET MODEL

2002 ◽  
Vol 05 (06) ◽  
pp. 585-597 ◽  
Author(s):  
IKSOO CHANG ◽  
DIETRICH STAUFFER ◽  
RAS B. PANDEY
Keyword(s):  
Power Law ◽  
Cumulative Distribution Function ◽  
Percolation Model ◽  
Cumulative Distribution ◽  
Market Model ◽  
Fat Tails ◽  
Nonlinear Feedback ◽  
Volatility Clustering ◽  
Correlated Percolation ◽  
Random Fluctuations

Modifications of the Cont-Bouchaud percolation model for price fluctuations give an asymmetry for time-reversal, an asymmetry between high and low prices, volatility clustering, effective multifractality, correlations between volatility and traded volume, and a power law tail with exponent near 3 for the cumulative distribution function of price changes. Combining them together still gives the same power law. Using Ising-correlated percolation does not change these results. Different modifications give log-periodic oscillations before a crash, arising from nonlinear feedback between random fluctuations.

scholarly journals RESPON ASIMETRI DALAM SPILLOVER VOLATILITAS : SUATU STUDI EMPIRIS TERHADAP PASAR MODAL JEPANG DAN INDONESIA

2017 ◽  
Vol 12 (2) ◽  
Author(s):  
Petra Minurvia Yudha
Keyword(s):  
Volatility Spillover ◽  
Fat Tails ◽  
Volatility Clustering ◽  
Bear Market ◽  
Asymmetric Volatility ◽  
Arch Effect ◽  
Phase Asymmetry

Penelitian ini bertujuan mengkaji asymmetric volatility spillover phenomenon dalam mekanisme transmisi spillover volatilitas return dari pasar saham Jepang kepada pasar saham Indonesia. Studi ini menyatakan bahwa semakin meningkatnya integrasi pasar keuangan, korelasi return dan volatilitas antara kedua pasar menjadi lebih kuat serta proses transmisi shock dalam spillover volatilitas tersebut memiliki karakteristik asimetris. Pengamatan ke arah respon asimetris menjadi penting karena spillover yang asimetris merupakan sumber penularan keuangan serta berimplikasi penting ke arah kebijakan makro bagi pengambil keputusan keuangan, termasuk alokasi aset optimal maupun konstruksi portfolio global. Pengujian yang Rasi TGARCH model dengan menggunakan dua variabel dummyZ, yakni sign asymmetry dan phase asymmetry. Uji normalitas data menunjukkan adanya fenomena fat tails dan volatility clustering dalam data. Uji ARCH effect menunjukkan adanya efek ARCH dalam residual data. Estimasi model TGARCH dengan spesifikasi ARMA (3,3) menghasilkan: (1) transmisi shock/volatilitas return dari Bursa Efek Jepang ke Bursa Efek Indonesia akan menjadi lebih kuat ketika Bursa Efek Jepang mengalami return negatif (sign asymmetry) dibandingkan dengan ketika Bursa Efek Jepang mengalami return positif; dan (2) transmisi shock juga menjadi lebih kuat ketika Bursa Efek Jepang berada dalam fase downward (bear market), dan ini disebut phase asymmetry.

scholarly journals TECHNICAL ANALYSIS BASED ON PRICE-VOLUME SIGNALS AND THE POWER OF TRADING BREAKS

2006 ◽  
Vol 09 (02) ◽  
pp. 227-244 ◽  
Author(s):  
FRANK H. WESTERHOFF
Keyword(s):  
Stock Market ◽  
Nonlinear Model ◽  
Stock Markets ◽  
Trading Volume ◽  
Market Model ◽  
Fat Tails ◽  
Stylized Facts ◽  
Volatility Clustering ◽  
Intrinsic Values ◽  
Artificial Stock Market

We propose a novel stock market model and investigate the effectiveness of trading breaks. Our nonlinear model consists of two types of traders: while fundamentalists expect prices to return towards their intrinsic values, chartists extrapolate past price movements into the future. Moreover, chartists condition their orders on past trading volume. The model is able to replicate several stylized facts of stock markets such as fat tails and volatility clustering. Using the model as an artificial stock market laboratory we find that trading breaks have the power to reduce volatility and — if fundamentals do not move too strongly — also mispricing.

scholarly journals Market Liberalization and Trading in Korea

2010 ◽  
Author(s):  
Lloyd P. Blenman ◽  
Dar-Hsin Chen ◽  
Chun-Da Chen
Keyword(s):  
Exchange Rate ◽  
South Korea ◽  
Trading Volume ◽  
Trading Behavior ◽  
Currency Markets ◽  
Foreign Investments ◽  
Volatility Clustering ◽  
Market Participants ◽  
Investment Trust ◽  
Market Instability

This paper reports on the trading behavior of major participants, investment trust companies, banks, and foreigners in South Korea in the period after the currency markets were liberalized and the limits on foreign investments were lifted. It was found that trading in the spot currency market was impacted by volatility in the daily Won/USD rates. As the daily unexpected range expanded (narrowed), daily spot trading volume and volatility increased (decreased). This is evidence of asymmetric trading behavior on the part of market participants. It was found that only investment trust companies adjusted their spot positions by trading USD futures as a response to unexpected volatility changes of the exchange rate. There is evidence of volatility clustering of the trading volatilities across Korean markets and trader types and no signs of market instability was found.  

scholarly journals Stock Market Volatility under Sanctions

2014 ◽  
Vol 3 (4) ◽  
pp. 234-249
Author(s):  
Hojatallah Goudarzi
Keyword(s):  
Stock Market ◽  
Nuclear Energy ◽  
Market Volatility ◽  
Stock Market Volatility ◽  
Fat Tails ◽  
Arch Models ◽  
Volatility Clustering ◽  
Market Growth ◽  
Congressional Research ◽  
The U.S

Since 1979, Iran has faced with unilateral and multilateral harsh sanctions due to its nuclear energy program. These sanctions have resulted in significant problem to both sanctioned and sanctioning parties. Given the fact that sanctions have had significant impacts on Iran’s economy and since Iran stock market is the barometer of its economy, it is assumed that sanctions affect the Iranian stock market as well. To test this hypothesis, this study studied the Iranian stock market volatility during harsh sanctions using ARCH models. The study found that, despite all sanctions, not only Iran’s stock market shows major stylized facts of any stock market’s volatility i.e. volatility clustering, fat tails and mean reversion but also it shows no irregularity which could be attributed to effect of sanctions. This finding was consistent with Iranian stock market regulators claiming Iranian stock market growth and the U.S. Congressional Research Service report 2013. Therefore, based on findings, this study concluded that Iranian stock market has not affected by sanctions.

A STOCHASTIC MODEL FOR MULTIFRACTAL BEHAVIOR OF STOCK PRICES

2004 ◽  
Vol 18 (04n05) ◽  
pp. 681-689 ◽  
Author(s):  
UMBERTO L. FULCO ◽  
MARCELO L. LYRA ◽  
FILIPPO PETRONI ◽  
MAURIZIO SERVA ◽  
GANDHI M. VISWANATHAN
Keyword(s):  
Time Series ◽  
Stock Prices ◽  
Financial Time Series ◽  
Probability Density Functions ◽  
Density Functions ◽  
Fat Tails ◽  
Volatility Clustering ◽  
Financial Time ◽  
Time Scaling ◽  
Multifractal Behavior

We investigate the general problem of how to model the kinematics of stock prices without considering the dynamical causes of motion. We propose a Markovian stochastic process which is able to reproduce the experimentally observed volatility clustering and fat tails in the probability density functions (PDF) of financial time series. More importantly, the process also reproduces the PDF time scaling, the power law memory of volatility and the apparent multifractality of the time series up to the time scale which is experimentally observable.

Sign in / Sign up

Export Citation Format

Share Document