scholarly journals Modelling the Efficiency of TGARCH Model in Nigeria Inflation Rate

2021 ◽  
Vol 3 (2) ◽  
pp. 20-35
Author(s):  
Michael Sunday Olayemi ◽  
Adenike Oluwafunmilola Olubiyi ◽  
Oluwamayowa Opeyimika Olajide ◽  
Omolola Felicia Ajayi
Keyword(s):  
Inflation Rate ◽  
Random Variable ◽  
Mean Value ◽  
Volatility Models ◽  
Downward Spiral ◽  
The Garch Model ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Best Fit ◽  
Lower Production ◽  
Better Than

In general, volatility is known and referred to as variance and it is a degree of spread of a random variable from its mean value. Two volatility models were considered in this paperwork. Nigeria's inflation rate was modeled by applying the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Threshold GARCH models. Symmetric and asymmetric models captured the most commonly stylized facts about the rate of inflation in Nigeria like leverage effects and irregularities in clustering and were studied. These models are GARCH (1,1) and TGARCH (1,1). This work estimated the comparison of volatility models in term of best fit and forecasting. The result showed that TGARCH (1,1) model outperformed GARCH (1,1) models in term of best fit, because it has the least AIC of 2.590438. We forecasted to see the level of volatility using Theils Inequality Coefficient and the result shows that TGARCH has the highest Theils Inequality Coefficient of 0.065075 which makes the TGARCH model better than the GARCH model in this research. From the initial and modified sample static forecast, it was discovered that the return on inflation is stable and shows that volatility slows towards the end of the month, we can see a downward spiral, which means price reaction to economic crisis led to lower production, lower wages, decreased demand, and still lower prices.

scholarly journals Do We Need Stochastic Volatility and Generalised Autoregressive Conditional Heteroscedasticity? Comparing Squared End-Of-Day Returns on FTSE

Risks ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 12 ◽  
Author(s):  
David E. Allen ◽  
Michael McAleer
Keyword(s):  
Stochastic Volatility ◽  
Ordinary Least Squares ◽  
Conditional Heteroscedasticity ◽  
Daily Data ◽  
Volatility Models ◽  
Tail Behaviour ◽  
Comparable Performance ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Daily Returns ◽  
Better Than

The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV) of FTSE sampled at 5 min intervals taken from the Oxford Man Realised Library. Both models demonstrated comparable performance and were correlated to a similar extent with RV estimates when measured by ordinary least squares (OLS). However, a crude variant of Corsi’s (2009) Heterogeneous Autoregressive (HAR) model, applied to squared demeaned daily returns on FTSE, appeared to predict the daily RV of FTSE better than either of the two models. Quantile regressions suggest that all three methods capture tail behaviour similarly and adequately. This leads to the question of whether we need either of the two standard volatility models if the simple expedient of using lagged squared demeaned daily returns provides a better RV predictor, at least in the context of the sample.

scholarly journals Contactless Video-Based Heart Rate Monitoring of a Resting and an Anesthetized Pig

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 442
Author(s):  
Meiqing Wang ◽  
Ali Youssef ◽  
Mona Larsen ◽  
Jean-Loup Rault ◽  
Daniel Berckmans ◽  
...  
Keyword(s):  
Heart Rate ◽  
Estimation Error ◽  
Well Being ◽  
Absolute Error ◽  
Mean Value ◽  
Video Data ◽  
Window Functions ◽  
The Face ◽  
Short Time ◽  
Better Than

Heart rate (HR) is a vital bio-signal that is relatively easy to monitor with contact sensors and is related to a living organism’s state of health, stress and well-being. The objective of this study was to develop an algorithm to extract HR (in beats per minute) of an anesthetized and a resting pig from raw video data as a first step towards continuous monitoring of health and welfare of pigs. Data were obtained from two experiments, wherein the pigs were video recorded whilst wearing an electrocardiography (ECG) monitoring system as gold standard (GS). In order to develop the algorithm, this study used a bandpass filter to remove noise. Then, a short-time Fourier transform (STFT) method was tested by evaluating different window sizes and window functions to accurately identify the HR. The resulting algorithm was first tested on videos of an anesthetized pig that maintained a relatively constant HR. The GS HR measurements for the anesthetized pig had a mean value of 71.76 bpm and standard deviation (SD) of 3.57 bpm. The developed algorithm had 2.33 bpm in mean absolute error (MAE), 3.09 bpm in root mean square error (RMSE) and 67% in HR estimation error below 3.5 bpm (PE3.5). The sensitivity of the algorithm was then tested on the video of a non-anaesthetized resting pig, as an animal in this state has more fluctuations in HR than an anaesthetized pig, while motion artefacts are still minimized due to resting. The GS HR measurements for the resting pig had a mean value of 161.43 bpm and SD of 10.11 bpm. The video-extracted HR showed a performance of 4.69 bpm in MAE, 6.43 bpm in RMSE and 57% in PE3.5. The results showed that HR monitoring using only the green channel of the video signal was better than using three color channels, which reduces computing complexity. By comparing different regions of interest (ROI), the region around the abdomen was found physiologically better than the face and front leg parts. In summary, the developed algorithm based on video data has potential to be used for contactless HR measurement and may be applied on resting pigs for real-time monitoring of their health and welfare status, which is of significant interest for veterinarians and farmers.

To the problem of uncertainty in interpolation of annual runoff

2012 ◽  
Vol 43 (6) ◽  
pp. 833-850 ◽  
Author(s):  
Ziqi Yan ◽  
Lars Gottschalk ◽  
Irina Krasovskaia ◽  
Jun Xia
Keyword(s):  
Cross Validation ◽  
Drainage Basin ◽  
Annual Runoff ◽  
Mean Value ◽  
Regular Grid ◽  
Main River ◽  
Average Annual Runoff ◽  
The One ◽  
Better Than

The long-term mean value of runoff is the basic descriptor of available water resources. This paper focuses on the accuracy that can be achieved when mapping this variable across space and along main rivers for a given stream gauging network. Three stochastic interpolation schemes for estimating average annual runoff across space are evaluated and compared. Two of the schemes firstly interpolate runoff to a regular grid net and then integrate the grid values along rivers. One of these schemes includes a constraint to account for the lateral water balance along the rivers. The third scheme interpolates runoff directly to points along rivers. A drainage basin in China with 20 gauging sites is used as a test area. In general, all three approaches reproduce the sample discharges along rivers with postdiction errors along main river branches around 10%. Using more objective cross-validation results, it was found that the two schemes based on basin integration, and especially the one with a constraint, performed significantly better than the one with direct interpolation to points along rivers. The analysis did not allow identification of possible influence of surface water use.

Numerical integration by systematic sampling

1950 ◽  
Vol 46 (1) ◽  
pp. 111-115 ◽  
Author(s):  
P. A. P. Moran
Keyword(s):  
Numerical Integration ◽  
Bounded Variation ◽  
Mathematical Problem ◽  
Random Variable ◽  
Mean Value ◽  
Lattice Points ◽  
Systematic Sampling ◽  
Image Position ◽  
Infinite Sum

Recent investigations by F. Yates (1) in agricultural statistics suggest a mathematical problem which may be formulated as follows. A function f(x) is known to be of bounded variation and Lebesgue integrable on the range −∞ < x < ∞, and its integral over this range is to be determined. In default of any knowledge of the position of the non-negligible values of the function the best that can be done is to calculate the infinite sumfor some suitable δ and an arbitrary origin t, where s ranges over all possible positive and negative integers including zero. S is evidently of period δ in t and ranges over all its values as t varies from 0 to δ. Previous writers (Aitken (2), p. 45, and Kendall (3)) have examined the resulting errors for fixed t. (They considered only symmetrical functions, and supposed one of the lattice points to be located at the centre.) Here we do not restrict ourselves to symmetrical functions and consider the likely departure of S(t) from J (the required integral) when t is a random variable uniformly distributed in (0, δ). It will be shown that S(t) is distributed about J as mean value, with a variance which will be evaluated as a function of δ, the scale of subdivision.

scholarly journals Constructing Semantic Models From Words, Images, and Emojis

2020 ◽  
Author(s):  
Armand Stefan Rotaru ◽  
Gabriella Vigliocco
Keyword(s):  
Visual Information ◽  
Semantic Processing ◽  
Empirical Work ◽  
Abstract Concepts ◽  
Visual Model ◽  
Semantic Data ◽  
Text Corpora ◽  
Abstract Words ◽  
Best Fit ◽  
Better Than

A number of recent models of semantics combine linguistic information, derived from text corpora, and visual information, derived from image collections, demonstrating that the resulting multimodal models are better than either of their unimodal counterparts, in accounting for behavioural data. Empirical work on semantic processing has shown that emotion also plays an important role especially for abstract concepts, however, models integrating emotion along with linguistic and visual information are lacking. Here, we first improve on visual and affective representations, derived from state-of-the-art existing models, by choosing models that best fit available human semantic data and extending the number of concepts they cover. Crucially then, we assess whether adding affective representations (obtained from a neural network model designed to predict emojis from co-occurring text) improves the model’s ability to fit semantic similarity/relatedness judgements from a purely linguistic and linguistic-visual model. We find that, given specific weights assigned to the models, adding both visual and affective representations improve performance, with visual representations providing an improvement especially for more concrete words, and affective representations improving especially the fit for more abstract words.

scholarly journals Pemodelan Deteksi Krisis Keuangan di Indonesia Berdasarkan Indikator M2/Cadangan Devisa

2019 ◽  
Vol 16 (2) ◽  
pp. 98-103
Author(s):  
Aisyah Zahrotul Hidayah ◽  
Sugiyanto Sugiyanto ◽  
Isnandar Slamet
Keyword(s):  
Financial Crisis ◽  
Regime Switching ◽  
Structural Changes ◽  
Detection System ◽  
International Reserves ◽  
Markov Regime Switching ◽  
Volatility Models ◽  
Macroeconomic Indicators ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Very High

The banking crisis reflects the liquidity crisis and bankruptcy of banks in the financial system. The financial crisis that occurred in mid-1997 resulted in a financial crisis that had a severe impact on the Indonesian economy. This made it aware of the importance of building a financial crisis early detection system to prepare for a crisis. The crisis occurs due to several macroeconomic indicators undergoing structural changes (regimes) and contain very high fluctuations. Combined volatility models and Markov regime switching are very suitable for explaining crises. The M2/international reserves indicator from 1990 to 2018 was used to build a crisis model. The results showed that the Markov regime switching autoregressive conditional heteroscedasticity model MRS-ARCH(2,1) could explain the crisis that occurred in mid-1997. Based on this model, in the future the crisis might occur if the M2/international reserves indicator decreased minimum of 13%

How Accurate is Qcbed ? -- the Case of Rutile (TiO2)

2001 ◽  
Vol 7 (S2) ◽  
pp. 368-369
Author(s):  
B. Jiang ◽  
J. Friis ◽  
J.C.H. Spence
Keyword(s):  
Systematic Errors ◽  
Mean Value ◽  
Order Structure ◽  
Data Sets ◽  
X Ray ◽  
Silicon Crystals ◽  
Structure Factors ◽  
The Mean ◽  
Mott Formula ◽  
Better Than

An accuracy of better than 1% is needed to measure the changes in charge density due to bonding. Here we report an accuracy up to 0.025% (random error) obtained in rutile crystal structure factors measurement by QCBED. This error is the standard deviation in the mean value obtained from ten data sets. Systematic errors may be present. Figure 1 gives an example of the (200) refinement results. Table 1 lists several low order structure factor refinement results. The accuracy of the measured electron structure factors was 0.1-0.2% but after conversion to x-ray structure factors, the accuracy for low orders improved due to the Mott formula [1] For (110) and (101) reflections, the accuracy in x-ray structure factors became 0.025% and 0.048% respectively. This accuracy is equivalent to that of the X-ray single crystal Pendellosung method on silicon crystals [2].The experiments were done on a Leo 912 Omega TEM.

Weak and Strong Compatibility in Data Fitting Problems Under Interval Uncertainty

2020 ◽  
Vol 12 (01) ◽  
pp. 2050002
Author(s):  
Sergey P. Shary
Keyword(s):  
Computational Complexity ◽  
Interval Data ◽  
Data Fitting ◽  
Interval Uncertainty ◽  
Systems Of Equations ◽  
Interval Systems ◽  
Best Fit ◽  
Computational Technology ◽  
Fitting Problem ◽  
Better Than

For the data fitting problem under interval uncertainty, we introduce the concept of strong compatibility between data and parameters. It is shown that the new strengthened formulation of the problem reduces to computing and estimating the so-called tolerable solution set for interval systems of equations constructed from the data being processed. We propose a computational technology for constructing a “best-fit” linear function from interval data, taking into account the strong compatibility requirement. The properties of the new data fitting approach are much better than those of its predecessors: strong compatibility estimates have polynomial computational complexity, the variance of the strong compatibility estimates is almost always finite, and these estimates are rubust. An example considered in the concluding part of the paper illustrates some of these features.

Fluorine and chlorine in peralkaline liquids and the need for magma generation in an open system

1975 ◽  
Vol 40 (312) ◽  
pp. 405-414 ◽  
Author(s):  
D. K. Bailey ◽  
R. Macdonald
Keyword(s):  
Trace Element ◽  
Evolutionary Process ◽  
Correlation Coefficients ◽  
Fluid Phase ◽  
Alkali Feldspar ◽  
Magma Evolution ◽  
Kenya Rift ◽  
Best Fit ◽  
Very High ◽  
Better Than

SummaryFluorine, chlorine, zinc, niobium, zirconium, yttrium, and rubidium have been deter-mined on fifteen obsidians from Eburru volcano (Kenya Rift Valley), spanning the range from pantel-leritic trachyte to pantellerite. All pairs of elements show positive correlation coefficients, ranging between 0·769 and 0·998, but with most values better than 0·900. In spite of some very high correlations, only two of the twenty-one best-fit lines pass near the origin of the Cartesian coordinates. Linear distributions are found within two separate groups of elements: F, Zr, Rb; and Cl, Nb, Yt. Zn behaves in general as a member of the second group but seems to be subject to an additional variation. When an element from the fluorine group is plotted against one from the chlorine group the resulting pattern is non-linear. Therefore, although the elements in both groups would generally be considered ‘residual’ (partition coefficients between crystals and liquid approaching zero) there are clearly detectable differences in their variation, and hence their behaviour.Major-element variations in the obsidians are such that a vapour (fluid) phase would be needed to account for any magma evolution. The trace-element patterns are also impossible by closed-system crystal fractionation and suggest that this fluid may have been rich in halogens, with the metallic elements forming preferred ‘complexes’ with either F or Cl. The F-Zr-Rb ‘complex’ also varies quite independently of the important major oxides (e.g. A12O3) in the rocks. In the case of Rb this is but one aspect of a more significant anomaly, in which there is no sign of any influence of alkali feldspar (which partitions Rb) in the variation. This is remarkable because trachytes and rhyolites have normative ab+or > 50 %, and any evolutionary process controlled by crystal ⇋ liquid interactions must be dominated by the melting or crystallization of alkali feldspar. The results on the Eburru obsidians show that if they are an evolutionary series then either, the process was not crystal ⇋ liquid controlled, or that any such process has been overriden (or buffered) by other processes that have superimposed the observed trace-element patterns. In the latter event, the buffering phase may have been a halogen-bearing vapour.The same considerations must apply to other pantellerite provinces where Rb appears to have behaved as a ‘residual’ element.

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