scholarly journals STUDY THE POSSIBILITY OF ADDRESS COMPLEX MODELS IN LINEAR AND NON-LINEAR CAUSAL RELATIONSHIPS BETWEEN OIL PRICE AND GDP IN KSA: USING THE COMBINATION OF TODA-YAMAMOTO, DIKS-PANCHENKO AND VAR APPROACH

2020 ◽  
Vol 10 (6) ◽  
pp. 672-678
Author(s):  
Hassan Tawakol A. Fadol
Keyword(s):  
Oil Price ◽  
Causal Relationships ◽  
Non Linear ◽  
Complex Models

scholarly journals Accurate radial basis functions technique for competitive and efficient solutions of non-linear Black-Scholes equations

2020 ◽  
Vol 20 (4) ◽  
pp. 60-83
Author(s):  
Vinícius Magalhães Pinto Marques ◽  
Gisele Tessari Santos ◽  
Mauri Fortes
Keyword(s):  
Radial Basis Function ◽  
Basis Function ◽  
Efficient Solutions ◽  
Basis Functions ◽  
Adaptive Scheme ◽  
Call Options ◽  
Black Scholes ◽  
Non Linear ◽  
Radial Basis ◽  
Complex Models

ABSTRACTObjective: This article aims to solve the non-linear Black Scholes (BS) equation for European call options using Radial Basis Function (RBF) Multi-Quadratic (MQ) Method.Methodology / Approach: This work uses the MQ RBF method applied to the solution of two complex models of nonlinear BS equation for prices of European call options with modified volatility. Linear BS models are also solved to visualize the effects of modified volatility.  Additionally, an adaptive scheme is implemented in time based on the Runge-Kutta-Fehlberg (RKF) method.

TESTING FOR LINEAR AND NON-LINEAR GRANGER NON-CAUSALITY HYPOTHESIS BETWEEN STOCK AND BOND: THE CASES OF MALAYSIA AND SINGAPORE

2014 ◽  
Vol 59 (05) ◽  
pp. 1450045 ◽  
Author(s):  
SHEUE LI ONG ◽  
CHONG MUN HO
Keyword(s):  
Linear Relationship ◽  
Taylor Expansion ◽  
Empirical Studies ◽  
Causal Relationships ◽  
Test Results ◽  
Causality Test ◽  
Dynamic Relationship ◽  
Non Linear ◽  
Causality Hypothesis ◽  
Actual Relationship

The untested assumption of linear relationship between stocks and bonds in previous empirical studies may lead to an invalid conclusion if the actual relationship is non-linear. The emphasis of this paper is on the effect of non-linearities on causal relationships between stocks and bonds in the cases of Malaysia and Singapore. Results from linearity tests indicate the existence of non-linearities in the dynamic relationship between stocks and bonds. Non-linear causality test results based on Taylor expansion suggest that non-linear causality flows from stocks to bonds and vice versa. The test further confirms that bonds with different maturity dates have different relationships with stocks.

scholarly journals Cosmological Evidence Modelling: a new simulation-based approach to constrain cosmology on non-linear scales

2019 ◽  
Vol 490 (2) ◽  
pp. 1870-1878 ◽  
Author(s):  
Johannes U Lange ◽  
Frank C van den Bosch ◽  
Andrew R Zentner ◽  
Kuan Wang ◽  
Andrew P Hearin ◽  
...  
Keyword(s):  
Parameter Space ◽  
Cosmological Parameters ◽  
Computational Cost ◽  
Simulation Based ◽  
Non Linear ◽  
Bayesian Evidence ◽  
The Galaxy ◽  
Complex Models ◽  
Galaxy Halo ◽  
Galaxy Assembly

ABSTRACT Extracting accurate cosmological information from galaxy–galaxy and galaxy–matter correlation functions on non-linear scales (${\lesssim } 10 \, h^{-1}{\rm {Mpc}}$) requires cosmological simulations. Additionally, one has to marginalize over several nuisance parameters of the galaxy–halo connection. However, the computational cost of such simulations prohibits naive implementations of stochastic posterior sampling methods like Markov chain Monte Carlo (MCMC) that would require of order $\mathcal {O}(10^6)$ samples in cosmological parameter space. Several groups have proposed surrogate models as a solution: a so-called emulator is trained to reproduce observables for a limited number of realizations in parameter space. Afterwards, this emulator is used as a surrogate model in an MCMC analysis. Here, we demonstrate a different method called Cosmological Evidence Modelling (CEM). First, for each simulation, we calculate the Bayesian evidence marginalized over the galaxy–halo connection by repeatedly populating the simulation with galaxies. We show that this Bayesian evidence is directly related to the posterior probability of cosmological parameters. Finally, we build a physically motivated model for how the evidence depends on cosmological parameters as sampled by the simulations. We demonstrate the feasibility of CEM by using simulations from the Aemulus simulation suite and forecasting cosmological constraints from BOSS CMASS measurements of redshift-space distortions. Our analysis includes exploration of how galaxy assembly bias affects cosmological inference. Overall, CEM has several potential advantages over the more common approach of emulating summary statistics, including the ability to easily marginalize over highly complex models of the galaxy–halo connection and greater accuracy, thereby reducing the number of simulations required.

scholarly journals The Causal Nexus between Oil Prices, Interest Rates, and Unemployment in Norway Using Wavelet Methods

2018 ◽  
Vol 10 (8) ◽  
pp. 2792 ◽  
Author(s):  
Hyunjoo Kim Karlsson ◽  
Yushu Li ◽  
Ghazi Shukur
Keyword(s):  
Interest Rate ◽  
Impulse Response ◽  
Time Scales ◽  
Time Scale ◽  
Real Interest Rate ◽  
Oil Prices ◽  
Oil Price ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Causal Relationships

This paper applies wavelet multi-resolution analysis (MRA), combined with two types of causality tests, to investigate causal relationships between three variables: real oil price, real interest rate, and unemployment in Norway. Impulse response functions were also utilised to examine effects of innovation in one variable on the other variables. We found that causal relations between the variables tend to be stronger as the wavelet time scale increases; specifically, there were no causal relationships between the variables at the lowest time scales of one to three months. A causal relationship between unemployment rate and interest rate was observed during the period of two quarters to two years, during which time a feedback mechanism was also detected between unemployment and interest rate. Causal relationships between oil price and both interest rate and unemployment were observed at the longest time scale of eight quarters. In conjunction with Granger causality analysis, impulse response functions showed that unemployment rates in Norway respond negatively to oil price shocks around two years after the shocks occur. As an oil exporting country, increases (or decreases) in oil prices reduce (or increase) unemployment in Norway under a time horizon of about two years; previous studies focused on oil importing economies have generally found the inverse to be true. Unlike most studies in this field, we decomposed the implicit aggregation for all time scales by applying MRA with a focus on the Norwegian economy. Thus, one main contribution of this paper is that we unveil and systematically distinguish the nature of the time-scale dependent relationship between real oil price, real interest rate, and unemployment using wavelet decomposition.

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