scholarly journals The Non-Linear Trade-Off between Return and Risk: A Regime-Switching Multi-Factor Framework

2014 ◽  
Author(s):  
John Cotter ◽  
Enrique Salvador
Keyword(s):  
Regime Switching ◽  
Trade Off ◽  
Non Linear

scholarly journals Linear and Non-Linear Modelling of Nigerian Crude Oil Prices

2021 ◽  
pp. 52-63
Author(s):  
Wiri Leneenadogo ◽  
Sibeate Pius U
Keyword(s):  
Crude Oil ◽  
Linear Model ◽  
Regime Switching ◽  
Linear Models ◽  
Nonlinear Models ◽  
Oil Prices ◽  
Information Criterion ◽  
Ar Model ◽  
Crude Oil Prices ◽  
Non Linear

To model Nigeria crude oil prices, this analysis compared univariate linear models to univariate nonlinear models. The data for this analysis was gathered from the Central Bank of Nigeria (CBN) Monthly Statistical Bulletin. The upward and downward movement in the series revealed by the time plot suggests that the series exhibit a regime-switching pattern: the cycle of expansion and contraction. At lag one, the Augmented Dickey-Fuller test was used to test for stationarity. For univariate linear ARIMA (p, d, q)) and univariate non-linear MS-AR, seven models were estimated for the linear model and two for the non-linear model. The best model was chosen based on the criterion of least information criterion,  AIC (2.006612), SC (2.156581), and the maximum log-likelihood of   (-150.5480) for the crude oil prices were used to pick MS-AR (1) for the series. In analysing crude oil prices data, the MS-AR model proposed by Hamilton outperforms the linear autoregressive models proposed by Box- Jenkins. The model was used to predict the series' values over a one-year cycle (12 months).

scholarly journals Bitcoin and Fiat Currency Interactions: Surprising Results from Asian Giants

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1395
Author(s):  
Samet Gunay ◽  
Kerem Kaskaloglu ◽  
Shahnawaz Muhammed
Keyword(s):  
Regime Switching ◽  
Market Timing ◽  
Harmful Effect ◽  
Downward Trend ◽  
Switching Regression ◽  
Indian Rupee ◽  
Non Linear ◽  
Causality Tests ◽  
Causal Nexus ◽  
Chinese Yuan

This study examines the interaction of Bitcoin with fiat currencies of three developed (euro, pound sterling and yen) and three emerging (yuan, rupee and ruble) market economies. Empirical investigations are executed through symmetric, asymmetric and non-linear causality tests, and Markov regime-switching regression (MRSR) analysis. Results show that Bitcoin has a causal nexus with Chinese yuan and Indian rupee for price and various return components. The MRSR analysis justifies these findings by demonstrating the presence of interaction in contractionary regimes. Accordingly, it can be stated that when markets display a downward trend, appreciation of the Chinese yuan and Indian rupee positively and strongly affects the value of Bitcoin, possibly due to the market timing. The MRSR analysis also exhibits a transition from a tranquil to a crisis regime in March 2020 because of the pandemic. However, a shorter duration spent in the crisis regime in 2020 indicates the limited and relatively less harmful effect of the pandemic on the cryptocurrency market when compared to the turmoil that occurred in 2018.

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