Search results for: conditional volatility
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 437

Search results for: conditional volatility

347 On Periodic Integer-Valued Moving Average Models

Authors: Aries Nawel, Bentarzi Mohamed

Abstract:

This paper deals with the study of some probabilistic and statistical properties of a Periodic Integer-Valued Moving Average Model (PINMA_{S}(q)). The closed forms of the mean, the second moment and the periodic autocovariance function are obtained. Furthermore, the time reversibility of the model is discussed in details. Moreover, the estimation of the underlying parameters are obtained by the Yule-Walker method, the Conditional Least Square method (CLS) and the Weighted Conditional Least Square method (WCLS). A simulation study is carried out to evaluate the performance of the estimation method. Moreover, an application on real data set is provided.

Keywords: periodic integer-valued moving average, periodically correlated process, time reversibility, count data

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346 Studying the Effects of Conditional Conservatism and Lack of Information Asymmetry on the Cost of Capital of the Accepted Companies in Tehran Stock Exchange

Authors: Fayaz Moosavi, Saeid Moradyfard

Abstract:

One of the methods in avoiding management fraud and increasing the quality of financial information, is the notification of qualitative features of financial information, including conservatism characteristic. Although taking a conservatism approach, while boosting the quality of financial information, is able to reduce the informational risk and the cost of capital stock of commercial department, by presenting an improper image about the situation of the commercial department, raises the risk of failure in returning the main and capital interest, and consequently the cost of capital of the commercial department. In order to know if conservatism finally leads to the increase or decrease of the cost of capital or does not have any influence on it, information regarding accepted companies in Tehran stock exchange is utilized by application of pooling method from 2007 to 2012 and it included 124 companies. The results of the study revealed that there is an opposite and meaningful relationship between conditional conservatism and the cost of capital of the company. In other words, if bad and unsuitable news and signs are reflected sooner than good news in accounting profit, the cost of capital of the company increases. In addition, there is a positive and meaningful relationship between the cost of capital and lack of information asymmetry.

Keywords: conditional conservatism, lack of information asymmetry, the cost of capital, stock exchange

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345 Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data

Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L. Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts as a motivating starting point. In this work, the authors extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zₚ, zₙ]. The zₚ component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zₙ component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach coined Augmented Posterior CDE (AP-CDE) only requires a simple modification of the common normalizing flow framework while significantly improving the interpretation of the latent component since zₚ represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of 𝑥-related variations due to factors such as lighting condition and subject id from the other random variations. Further, the experiments show that an unconditional NF neural network based on an unsupervised model of z, such as a Gaussian mixture, fails to generate interpretable results.

Keywords: conditional density estimation, image generation, normalizing flow, supervised dimension reduction

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344 Trading Volume on the Tunisian Financial Market: An Approach Explaining the Hypothesis of Investors Overconfidence

Authors: Fatma Ismailia, Malek Saihi

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This research provides an explanation of exchange incentives on the Tunis stock market from a behavioural point of view. The elucidation of the anomalies of excessive volume of transactions and that of excessive volatility cannot be done without the recourse to the psychological aspects of investors. The excessive confidence has been given the predominant role for the explanation of these phenomena. Indeed, when investors store increments, they become more confident about the precision of their private information and their exchange activities then become more aggressive on the subsequent periods. These overconfident investors carry out the intensive exchanges leading to an increase of securities volatility. The objective of this research is to identify whether the trading volume and the excessive volatility of securities observed on the Tunisian stock market come from the excessive exchange of overconfident investors. We use a sample of daily observations over the period January 1999 - October 2007 and we relied on various econometric tests including the VAR model. Our results provide evidence on the importance to consider the bias of overconfidence in the analysis of Tunis stock exchange specificities. The results reveal that the excess of confidence has a major impact on the trading volume while using daily temporal intervals.

Keywords: overconfidence, trading volume, efficiency, rationality, anomalies, behavioural finance, cognitive biases

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343 Cuckoo Search Optimization for Black Scholes Option Pricing

Authors: Manas Shah

Abstract:

Black Scholes option pricing model is one of the most important concepts in modern world of computational finance. However, its practical use can be challenging as one of the input parameters must be estimated; implied volatility of the underlying security. The more precisely these values are estimated, the more accurate their corresponding estimates of theoretical option prices would be. Here, we present a novel model based on Cuckoo Search Optimization (CS) which finds more precise estimates of implied volatility than Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).

Keywords: black scholes model, cuckoo search optimization, particle swarm optimization, genetic algorithm

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342 The Response of the Central Bank to the Exchange Rate Movement: A Dynamic Stochastic General Equilibrium-Vector Autoregressive Approach for Tunisian Economy

Authors: Abdelli Soulaima, Belhadj Besma

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The paper examines the choice of the central bank toward the movements of the nominal exchange rate and evaluates its effects on the volatility of the output growth and the inflation. The novel hybrid method of the dynamic stochastic general equilibrium called the DSGE-VAR is proposed for analyzing this policy experiment in a small scale open economy in particular Tunisia. The contribution is provided to the empirical literature as we apply the Tunisian data with this model, which is rarely used in this context. Note additionally that the issue of treating the degree of response of the central bank to the exchange rate in Tunisia is special. To ameliorate the estimation, the Bayesian technique is carried out for the sample 1980:q1 to 2011 q4. Our results reveal that the central bank should not react or softly react to the exchange rate. The variance decomposition displayed that the overall inflation volatility is more pronounced with the fixed exchange rate regime for most of the shocks except for the productivity and the interest rate. The output volatility is also higher with this regime with the majority of the shocks exempting the foreign interest rate and the interest rate shocks.

Keywords: DSGE-VAR modeling, exchange rate, monetary policy, Bayesian estimation

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341 An Information Matrix Goodness-of-Fit Test of the Conditional Logistic Model for Matched Case-Control Studies

Authors: Li-Ching Chen

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The case-control design has been widely applied in clinical and epidemiological studies to investigate the association between risk factors and a given disease. The retrospective design can be easily implemented and is more economical over prospective studies. To adjust effects for confounding factors, methods such as stratification at the design stage and may be adopted. When some major confounding factors are difficult to be quantified, a matching design provides an opportunity for researchers to control the confounding effects. The matching effects can be parameterized by the intercepts of logistic models and the conditional logistic regression analysis is then adopted. This study demonstrates an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model for matched case-control data. The asymptotic null distribution of this proposed test statistic is inferred. It needs neither to employ a simulation to evaluate its critical values nor to partition covariate space. The asymptotic power of this test statistic is also derived. The performance of the proposed method is assessed through simulation studies. An example of the real data set is applied to illustrate the implementation of the proposed method as well.

Keywords: conditional logistic model, goodness-of-fit, information matrix, matched case-control studies

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340 Modelling Volatility of Cryptocurrencies: Evidence from GARCH Family of Models with Skewed Error Innovation Distributions

Authors: Timothy Kayode Samson, Adedoyin Isola Lawal

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The past five years have shown a sharp increase in public interest in the crypto market, with its market capitalization growing from $100 billion in June 2017 to $2158.42 billion on April 5, 2022. Despite the outrageous nature of the volatility of cryptocurrencies, the use of skewed error innovation distributions in modelling the volatility behaviour of these digital currencies has not been given much research attention. Hence, this study models the volatility of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, Binance coin, and USD Coin) using four variants of GARCH models (GJR-GARCH, sGARCH, EGARCH, and APARCH) estimated using three skewed error innovation distributions (skewed normal, skewed student- t and skewed generalized error innovation distributions). Daily closing prices of these currencies were obtained from Yahoo Finance website. Finding reveals that the Binance coin reported higher mean returns compared to other digital currencies, while the skewness indicates that the Binance coin, Tether, and USD coin increased more than they decreased in values within the period of study. For both Bitcoin and Ethereum, negative skewness was obtained, meaning that within the period of study, the returns of these currencies decreased more than they increased in value. Returns from these cryptocurrencies were found to be stationary but not normality distributed with evidence of the ARCH effect. The skewness parameters in all best forecasting models were all significant (p<.05), justifying of use of skewed error innovation distributions with a fatter tail than normal, Student-t, and generalized error innovation distributions. For Binance coin, EGARCH-sstd outperformed other volatility models, while for Bitcoin, Ethereum, Tether, and USD coin, the best forecasting models were EGARCH-sstd, APARCH-sstd, EGARCH-sged, and GJR-GARCH-sstd, respectively. This suggests the superiority of skewed Student t- distribution and skewed generalized error distribution over the skewed normal distribution.

Keywords: skewed generalized error distribution, skewed normal distribution, skewed student t- distribution, APARCH, EGARCH, sGARCH, GJR-GARCH

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339 The Use of Authentic Videos to Change Learners’ Negative Attitudes and Perceptions toward Grammar Learning

Authors: Khaldi Youcef

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This investigation seeks to inquire into the effectiveness of using authentic videos for grammar teaching purposes. In this investigation, an English animated situation, Hercules, was used as a type of authentic multimedia to teach a particular grammatical structure, namely conditional sentences. This study also aims at investigating the EFL learners’ attitudes toward grammar learning after being exposed to such an authentic video. To reach that purpose, 56 EFL learners were required ultimately to respond to a questionnaire with an aim to reveal their attitudes towards grammar as a language entity and as a subject for being learned. Then, as a second stage of the investigation, the EFL learners were divided into a control group and an experimental group with 28 learners in each. The first group was taught grammar -conditional sentences- using a deductive-inductive approach, while the second group was exposed to an authentic video to learn conditional sentences. There was a post-lesson stage that included a questionnaire to be answered by learners of each group. The aim of this stage is to capture any change in learners' attitudes shown in the pre-lesson questionnaire. The findings of the first stage revealed learners' negative attitudes towards grammar learning. And the third stage results showed the effectiveness of authentic videos in entirely turning learners' attitudes toward grammar learning to be significantly positive. Also, the utility of authentic videos in highly motivating EFL learners can be deduced. The findings of this survey asserted the need for incorporation and integration of authentic videos in EFL classrooms as they resulted in rising effectively learners’ awareness of grammar and looking at it from a communicative perspective.

Keywords: multimedia, authentic videos, negative attitudes, grammar learning, EFL learners

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338 Oil-price Volatility and Economic Prosperity in Nigeria: Empirical Evidence

Authors: Yohanna Panshak

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The impact of macroeconomic instability on economic growth and prosperity has been at forefront in many discourses among researchers and policy makers and has generated a lot of controversies over the years. This has generated series of research efforts towards understanding the remote causes of this phenomenon; its nature, determinants and how it can be targeted and mitigated. While others have opined that the root cause of macroeconomic flux in Nigeria is attributed to Oil-Price volatility, others viewed the issue as resulting from some constellation of structural constraints both within and outside the shores of the country. Research works of scholars such as [Akpan (2009), Aliyu (2009), Olomola (2006), etc] argue that oil volatility can determine economic growth or has the potential of doing so. On the contrary, [Darby (1982), Cerralo (2005) etc] share the opinion that it can slow down growth. The earlier argument rest on the understanding that for a net balance of oil exporting economies, price upbeat directly increases real national income through higher export earnings, whereas, the latter allude to the case of net-oil importing countries (which experience price rises, increased input costs, reduced non-oil demand, low investment, fall in tax revenues and ultimately an increase in budget deficit which will further reduce welfare level). Therefore, assessing the precise impact of oil price volatility on virtually any economy is a function of whether it is an oil-exporting or importing nation. Research on oil price volatility and its outcome on the growth of the Nigerian economy are evolving and in a march towards resolving Nigeria’s macroeconomic instability as long as oil revenue still remain the mainstay and driver of socio-economic engineering. Recently, a major importer of Nigeria’s oil- United States made a historic breakthrough in more efficient source of energy for her economy with the capacity of serving significant part of the world. This undoubtedly suggests a threat to the exchange earnings of the country. The need to understand fluctuation in its major export commodity is critical. This paper leans on the Renaissance growth theory with greater focus on theoretical work of Lee (1998); a leading proponent of this school who makes a clear cut of difference between oil price changes and oil price volatility. Based on the above background, the research seeks to empirically examine the impact oil-price volatility on government expenditure using quarterly time series data spanning 1986:1 to 2014:4. Vector Auto Regression (VAR) econometric approach shall be used. The structural properties of the model shall be tested using Augmented Dickey-Fuller and Phillips-Perron. Relevant diagnostics tests of heteroscedasticity, serial correlation and normality shall also be carried out. Policy recommendation shall be offered on the empirical findings and believes it assist policy makers not only in Nigeria but the world-over.

Keywords: oil-price, volatility, prosperity, budget, expenditure

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337 Machine Learning for Targeting of Conditional Cash Transfers: Improving the Effectiveness of Proxy Means Tests to Identify Future School Dropouts and the Poor

Authors: Cristian Crespo

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Conditional cash transfers (CCTs) have been targeted towards the poor. Thus, their targeting assessments check whether these schemes have been allocated to low-income households or individuals. However, CCTs have more than one goal and target group. An additional goal of CCTs is to increase school enrolment. Hence, students at risk of dropping out of school also are a target group. This paper analyses whether one of the most common targeting mechanisms of CCTs, a proxy means test (PMT), is suitable to identify the poor and future school dropouts. The PMT is compared with alternative approaches that use the outputs of a predictive model of school dropout. This model was built using machine learning algorithms and rich administrative datasets from Chile. The paper shows that using machine learning outputs in conjunction with the PMT increases targeting effectiveness by identifying more students who are either poor or future dropouts. This joint targeting approach increases effectiveness in different scenarios except when the social valuation of the two target groups largely differs. In these cases, the most likely optimal approach is to solely adopt the targeting mechanism designed to find the highly valued group.

Keywords: conditional cash transfers, machine learning, poverty, proxy means tests, school dropout prediction, targeting

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336 Loan Supply and Asset Price Volatility: An Experimental Study

Authors: Gabriele Iannotta

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This paper investigates credit cycles by means of an experiment based on a Kiyotaki & Moore (1997) model with heterogeneous expectations. The aim is to examine how a credit squeeze caused by high lender-level risk perceptions affects the real prices of a collateralised asset, with a special focus on the macroeconomic implications of rising price volatility in terms of total welfare and the number of bankruptcies that occur. To do that, a learning-to-forecast experiment (LtFE) has been run where participants are asked to predict the future price of land and then rewarded based on the accuracy of their forecasts. The setting includes one lender and five borrowers in each of the twelve sessions split between six control groups (G1) and six treatment groups (G2). The only difference is that while in G1 the lender always satisfies borrowers’ loan demand (bankruptcies permitting), in G2 he/she closes the entire credit market in case three or more bankruptcies occur in the previous round. Experimental results show that negative risk-driven supply shocks amplify the volatility of collateral prices. This uncertainty worsens the agents’ ability to predict the future value of land and, as a consequence, the number of defaults increases and the total welfare deteriorates.

Keywords: Behavioural Macroeconomics, Credit Cycle, Experimental Economics, Heterogeneous Expectations, Learning-to-Forecast Experiment

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335 The Non-Uniqueness of Partial Differential Equations Options Price Valuation Formula for Heston Stochastic Volatility Model

Authors: H. D. Ibrahim, H. C. Chinwenyi, T. Danjuma

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An option is defined as a financial contract that provides the holder the right but not the obligation to buy or sell a specified quantity of an underlying asset in the future at a fixed price (called a strike price) on or before the expiration date of the option. This paper examined two approaches for derivation of Partial Differential Equation (PDE) options price valuation formula for the Heston stochastic volatility model. We obtained various PDE option price valuation formulas using the riskless portfolio method and the application of Feynman-Kac theorem respectively. From the results obtained, we see that the two derived PDEs for Heston model are distinct and non-unique. This establishes the fact of incompleteness in the model for option price valuation.

Keywords: Black-Scholes partial differential equations, Ito process, option price valuation, partial differential equations

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334 Impact of Digitization and Diversification in Reducing Volatility in Art Markets

Authors: Nishi Malhotra

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Art has developed as a mode of investment and saving. Art and culture of any nation is the source of foreign direct investment (FDI) generation and growth development. Several intermediaries and skill-building organizations thrive on at and culture for their earnings. Indian art market has grown to Rs. 2000 Crores. Art establishment houses access to privileged information is the main reason for arbitrariness and volatility in the market. The commercialization of art and development of the markets with refinement in the taste of the customers have led to the development of art as an investment avenue. Investors keen on investing in these products can do so, and earnings from art are taxable too, like any other capital asset. This research paper is aimed at exploring the role of art and culture as an investment avenue in India and reasons for increasing volatilities in the art market. Based on an extensive literature review and secondary research, a benchmarking study has been conducted to capture the growth of the art as an investment avenue. These studies indicate that during the financial crisis of 2008-10, the art emerged as an alternative investment avenue. The paper aims at discussing the financial engineering of various art funds and instruments. Based on secondary data available from Sotheby’s, Christies, Bonham, there is a positive correlation between strategic diversification and increasing return in the Art market. Similarly, digitization has led to disintermediation in the art markets and also helped to increase the market base. The data clearly enumerates the growing interest of the Indian investor towards art as an investment option. Much like any other broad asset class, art market too thrives on excess returns provided by diversification. Many financial intermediaries and art funds have emerged, to offer valuable investment planning advisory to a genuine investor. This paper clearly highlights the increasing returns of strategic diversification and its impact on reducing volatility in the art markets. Moreover, with coming up of e-auctions and websites, investors are able to analyse art more objectively. Digitization and commercialization of art have definitely helped in reducing volatility in world art markets.

Keywords: art, investment avenue, diversification, digitization

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333 A Multilevel Authentication Protocol: MAP in VANET for Human Safety

Authors: N. Meddeb, A. M. Makhlouf, M. A. Ben Ayed

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Due to the real-time requirement of message in Vehicular Ad hoc NETworks (VANET), it is necessary to authenticate vehicles to achieve security, efficiency, and conditional privacy-preserving. Privacy is of utmost relevance in VANETs. For this reason, we have proposed a new protocol called ‘Multilevel Authentication Protocol’ (MAP) that considers different vehicle categories. The proposed protocol is based on our Multilevel Authentication protocol for Vehicular networks (MAVnet). But the MAP leads to human safety, where the priority is given to the ambulance vehicles. For evaluation, we used the Java language to develop a demo application and deployed it on the Network Security Simulation (Nessi2). Compared with existing authentication protocols, MAP markedly enhance the communication overhead and decreases the delay of exchanging messages while preserving conditional privacy.

Keywords: Vehicular Ad hoc NETworks (VANET), vehicle categories, safety, databases, privacy, authentication, throughput, delay

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332 Modelling High-Frequency Crude Oil Dynamics Using Affine and Non-Affine Jump-Diffusion Models

Authors: Katja Ignatieva, Patrick Wong

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We investigated the dynamics of high frequency energy prices, including crude oil and electricity prices. The returns of underlying quantities are modelled using various parametric models such as stochastic framework with jumps and stochastic volatility (SVCJ) as well as non-parametric alternatives, which are purely data driven and do not require specification of the drift or the diffusion coefficient function. Using different statistical criteria, we investigate the performance of considered parametric and nonparametric models in their ability to forecast price series and volatilities. Our models incorporate possible seasonalities in the underlying dynamics and utilise advanced estimation techniques for the dynamics of energy prices.

Keywords: stochastic volatility, affine jump-diffusion models, high frequency data, model specification, markov chain monte carlo

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331 Forecasting for Financial Stock Returns Using a Quantile Function Model

Authors: Yuzhi Cai

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In this paper, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.

Keywords: DJIA, financial returns, predictive distribution, quantile function model

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330 Modelling Agricultural Commodity Price Volatility with Markov-Switching Regression, Single Regime GARCH and Markov-Switching GARCH Models: Empirical Evidence from South Africa

Authors: Yegnanew A. Shiferaw

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Background: commodity price volatility originating from excessive commodity price fluctuation has been a global problem especially after the recent financial crises. Volatility is a measure of risk or uncertainty in financial analysis. It plays a vital role in risk management, portfolio management, and pricing equity. Objectives: the core objective of this paper is to examine the relationship between the prices of agricultural commodities with oil price, gas price, coal price and exchange rate (USD/Rand). In addition, the paper tries to fit an appropriate model that best describes the log return price volatility and estimate Value-at-Risk and expected shortfall. Data and methods: the data used in this study are the daily returns of agricultural commodity prices from 02 January 2007 to 31st October 2016. The data sets consists of the daily returns of agricultural commodity prices namely: white maize, yellow maize, wheat, sunflower, soya, corn, and sorghum. The paper applies the three-state Markov-switching (MS) regression, the standard single-regime GARCH and the two regime Markov-switching GARCH (MS-GARCH) models. Results: to choose the best fit model, the log-likelihood function, Akaike information criterion (AIC), Bayesian information criterion (BIC) and deviance information criterion (DIC) are employed under three distributions for innovations. The results indicate that: (i) the price of agricultural commodities was found to be significantly associated with the price of coal, price of natural gas, price of oil and exchange rate, (ii) for all agricultural commodities except sunflower, k=3 had higher log-likelihood values and lower AIC and BIC values. Thus, the three-state MS regression model outperformed the two-state MS regression model (iii) MS-GARCH(1,1) with generalized error distribution (ged) innovation performs best for white maize and yellow maize; MS-GARCH(1,1) with student-t distribution (std) innovation performs better for sorghum; MS-gjrGARCH(1,1) with ged innovation performs better for wheat, sunflower and soya and MS-GARCH(1,1) with std innovation performs better for corn. In conclusion, this paper provided a practical guide for modelling agricultural commodity prices by MS regression and MS-GARCH processes. This paper can be good as a reference when facing modelling agricultural commodity price problems.

Keywords: commodity prices, MS-GARCH model, MS regression model, South Africa, volatility

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329 Assessing the Resilience of the Insurance Industry under Solvency II

Authors: Vincenzo Russo, Rosella Giacometti

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The paper aims to assess the insurance industry's resilience under Solvency II against adverse scenarios. Starting from the economic balance sheet available under Solvency II for insurance and reinsurance undertakings, we assume that assets and liabilities follow a bivariate geometric Brownian motion (GBM). Then, using the results available under Margrabe's formula, we establish an analytical solution to calibrate the volatility of the asset-liability ratio. In such a way, we can estimate the probability of default and the probability of breaching the undertaking's Solvency Capital Requirement (SCR). Furthermore, since estimating the volatility of the Solvency Ratio became crucial for insurers in light of the financial crises featured in the last decades, we introduce a novel measure that we call Resiliency Ratio. The Resiliency Ratio can be used, in addition to the Solvency Ratio, to evaluate the insurance industry's resilience in case of adverse scenarios. Finally, we introduce a simplified stress test tool to evaluate the economic balance sheet under stressed conditions. The model we propose is featured by analytical tractability and fast calibration procedure where only the disclosed data available under the Solvency II public reporting are needed for the calibration. Using the data published regularly by the European Insurance and Occupational Pensions Authority (EIOPA) in an aggregated form by country, an empirical analysis has been performed to calibrate the model and provide the related results at the country level.

Keywords: Solvency II, solvency ratio, volatility of the asset-liability ratio, probability of default, probability to breach the SCR, resilience ratio, stress test

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328 Inquiry on the Improvement Teaching Quality in the Classroom with Meta-Teaching Skills

Authors: Shahlan Surat, Saemah Rahman, Saadiah Kummin

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When teachers reflect and evaluate whether their teaching methods actually have an impact on students’ learning, they will adjust their practices accordingly. This inevitably improves their students’ learning and performance. The approach in meta-teaching can invigorate and create a passion for teaching. It thus helps to increase the commitment and love for the teaching profession. This study was conducted to determine the level of metacognitive thinking of teachers in the process of teaching and learning in the classroom. Metacognitive thinking teachers include the use of metacognitive knowledge which consists of different types of knowledge: declarative, procedural and conditional. The ability of the teachers to plan, monitor and evaluate the teaching process can also be determined. This study was conducted on 377 graduate teachers in Klang Valley, Malaysia. The stratified sampling method was selected for the purpose of this study. The metacognitive teaching inventory consisting of 24 items is called InKePMG (Teacher Indicators of Effectiveness Meta-Teaching). The results showed the level of mean is high for two components of metacognitive knowledge; declarative knowledge (mean = 4.16) and conditional (mean = 4.11) whereas, the mean of procedural knowledge is 4.00 (moderately high). Similarly, the level of knowledge in monitoring (mean = 4.11), evaluating (mean = 4.00) which indicate high score and planning (mean = 4.00) are moderately high score among teachers. In conclusion, this study shows that the planning and procedural knowledge is an important element in improving the quality of teachers teaching in the classroom. Thus, the researcher recommended that further studies should focus on training programs for teachers on metacognitive skills and also on developing creative thinking among teachers.

Keywords: metacognitive thinking skills, procedural knowledge, conditional knowledge, meta-teaching and regulation of cognitive

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327 The Effect of Accounting Conservatism on Cost of Capital: A Quantile Regression Approach for MENA Countries

Authors: Maha Zouaoui Khalifa, Hakim Ben Othman, Hussaney Khaled

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

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326 Hybrid Equity Warrants Pricing Formulation under Stochastic Dynamics

Authors: Teh Raihana Nazirah Roslan, Siti Zulaiha Ibrahim, Sharmila Karim

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A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Keywords: Cox-Ingersoll-Ross model, equity warrants, Heston model, hybrid models, stochastic

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325 The Properties of Risk-based Approaches to Asset Allocation Using Combined Metrics of Portfolio Volatility and Kurtosis: Theoretical and Empirical Analysis

Authors: Maria Debora Braga, Luigi Riso, Maria Grazia Zoia

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Risk-based approaches to asset allocation are portfolio construction methods that do not rely on the input of expected returns for the asset classes in the investment universe and only use risk information. They include the Minimum Variance Strategy (MV strategy), the traditional (volatility-based) Risk Parity Strategy (SRP strategy), the Most Diversified Portfolio Strategy (MDP strategy) and, for many, the Equally Weighted Strategy (EW strategy). All the mentioned approaches were based on portfolio volatility as a reference risk measure but in 2023, the Kurtosis-based Risk Parity strategy (KRP strategy) and the Minimum Kurtosis strategy (MK strategy) were introduced. Understandably, they used the fourth root of the portfolio-fourth moment as a proxy for portfolio kurtosis to work with a homogeneous function of degree one. This paper contributes mainly theoretically and methodologically to the framework of risk-based asset allocation approaches with two steps forward. First, a new and more flexible objective function considering a linear combination (with positive coefficients that sum to one) of portfolio volatility and portfolio kurtosis is used to alternatively serve a risk minimization goal or a homogeneous risk distribution goal. Hence, the new basic idea consists in extending the achievement of typical risk-based approaches’ goals to a combined risk measure. To give the rationale behind operating with such a risk measure, it is worth remembering that volatility and kurtosis are expressions of uncertainty, to be read as dispersion of returns around the mean and that both preserve adherence to a symmetric framework and consideration for the entire returns distribution as well, but also that they differ from each other in that the former captures the “normal” / “ordinary” dispersion of returns, while the latter is able to catch the huge dispersion. Therefore, the combined risk metric that uses two individual metrics focused on the same phenomena but differently sensitive to its intensity allows the asset manager to express, in the context of an objective function by varying the “relevance coefficient” associated with the individual metrics, alternatively, a wide set of plausible investment goals for the portfolio construction process while serving investors differently concerned with tail risk and traditional risk. Since this is the first study that also implements risk-based approaches using a combined risk measure, it becomes of fundamental importance to investigate the portfolio effects triggered by this innovation. The paper also offers a second contribution. Until the recent advent of the MK strategy and the KRP strategy, efforts to highlight interesting properties of risk-based approaches were inevitably directed towards the traditional MV strategy and SRP strategy. Previous literature established an increasing order in terms of portfolio volatility, starting from the MV strategy, through the SRP strategy, arriving at the EQ strategy and provided the mathematical proof for the “equalization effect” concerning marginal risks when the MV strategy is considered, and concerning risk contributions when the SRP strategy is considered. Regarding the validity of similar conclusions when referring to the MK strategy and KRP strategy, the development of a theoretical demonstration is still pending. This paper fills this gap.

Keywords: risk parity, portfolio kurtosis, risk diversification, asset allocation

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324 The Log S-fbm Nested Factor Model

Authors: Othmane Zarhali, Cécilia Aubrun, Emmanuel Bacry, Jean-Philippe Bouchaud, Jean-François Muzy

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The Nested factor model was introduced by Bouchaud and al., where the asset return fluctuations are explained by common factors representing the market economic sectors and residuals (noises) sharing with the factors a common dominant volatility mode in addition to the idiosyncratic mode proper to each residual. This construction infers that the factors-residuals log volatilities are correlated. Here, we consider the case of a single factor where the only dominant common mode is a S-fbm process (introduced by Peng, Bacry and Muzy) with Hurst exponent H around 0.11 and the residuals having in addition to the previous common mode idiosyncratic components with Hurst exponents H around 0. The reason for considering this configuration is twofold: preserve the Nested factor model’s characteristics introduced by Bouchaud and al. and propose a framework through which the stylized fact reported by Peng and al. is reproduced, where it has been observed that the Hurst exponents of stock indices are large as compared to those of individual stocks. In this work, we show that the Log S-fbm Nested factor model’s construction leads to a Hurst exponent of single stocks being the ones of the idiosyncratic volatility modes and the Hurst exponent of the index being the one of the common volatility modes. Furthermore, we propose a statistical procedure to estimate the Hurst factor exponent from the stock returns dynamics together with theoretical guarantees, with good results in the limit where the number of stocks N goes to infinity. Last but not least, we show that the factor can be seen as an index constructed from the single stocks weighted by specific coefficients.

Keywords: hurst exponent, log S-fbm model, nested factor model, small intermittency approximation

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323 The Potential of Dinar (Gold) Currency as the Main Object Transaction in Indonesia

Authors: Muhammad Ilham Agus Salim, Mohammad Ali

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In this article, we have elaborated a study over the nature of Islamic financial transaction by comparing between Dinar and IDR currency in Indonesia. We have found the interesting issue among scholars and practitioners in which Dinar would be a single currency ASEAN Economic Community (AEC), then becoming motivation and added value research. The assessment among dinar volatility analysis for three years ago and IDR fluctuation as well as outlook qualitative test regarding dinar are components of analysis that weak Indonesian currency should be altered to be better coinage. The value of dinar more stable than IDR and also eligible as a currency e.g. limited quantities, easy to carry, durable, easy to saved, and has the same quality. On the other hand, the existing of IDR has defeated by inflation. The EViews program explained that Dinar at current level still fluctuate, but in the first different have fixed variant. The result of analysis describing that dinar has potential as the medium exchange, because the material of dinar is relevant and feasible since 14 century until present. Therefore, dinar should be considered to solve Indonesia crisis today.

Keywords: medium of exchange, dinar & IDR currency, volatility analysis, EViews program

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322 World Agricultural Commodities Prices Dynamics and Volatilities Impacts on Commodities Importation and Food Security in West African Economic and Monetary Union Countries

Authors: Baoubadi Atozou, Koffi Akakpo

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Since the decade 2000, the use of foodstuffs such as corn, wheat, and soybeans in biofuel production has been growing sharply in the United States, Canada, and Europe. Thus, prices for these agricultural products are rising in the world market. These cereals are the most important source of calorific energy for West African Economic and Monetary Union (WAEMU) countries members’ population. These countries are highly dependent on imports of most of these products. Thereby, rising prices can have an important impact on import levels and consequently on food security in these countries. This study aims to analyze the interrelationship between the prices of these commodities and their volatilities, and their effects on imports of these agricultural products by each WAEMU ’country member. The Autoregressive Distributed Lag (ARDL) model, the GARCH Multivariate model, and the Granger Causality Test are used in this investigation. The results show that import levels are highly and significantly sensitive to price changes as well as their volatility. In the short term as well as in the long term, there is a significant relationship between the prices of these products. There is a positive relationship in general between price volatility. And these volatilities have negative effects on the level of imports. The market characteristics affect food security in these countries, especially access to food for vulnerable and low-income populations. The policies makers must adopt viable strategies to increase agricultural production and limit their dependence on imports.

Keywords: price volatility, import of agricultural products, food safety, WAEMU

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321 Derivation of Fractional Black-Scholes Equations Driven by Fractional G-Brownian Motion and Their Application in European Option Pricing

Authors: Changhong Guo, Shaomei Fang, Yong He

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In this paper, fractional Black-Scholes models for the European option pricing were established based on the fractional G-Brownian motion (fGBm), which generalizes the concepts of the classical Brownian motion, fractional Brownian motion and the G-Brownian motion, and that can be used to be a tool for considering the long range dependence and uncertain volatility for the financial markets simultaneously. A generalized fractional Black-Scholes equation (FBSE) was derived by using the Taylor’s series of fractional order and the theory of absence of arbitrage. Finally, some explicit option pricing formulas for the European call option and put option under the FBSE were also solved, which extended the classical option pricing formulas given by F. Black and M. Scholes.

Keywords: European option pricing, fractional Black-Scholes equations, fractional g-Brownian motion, Taylor's series of fractional order, uncertain volatility

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320 Recent Volatility in Islamic Banking Sector of Bangladesh: Nexus Between Economy, Religion and Politics

Authors: Abdul Kader

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This paper attempts to investigate several contributory factors to recent volatility in the Islamic Banking sector of Bangladesh. In particular, the study explores corporate governance, credit management, credit regulations, inept board of directors, using religious sentiment as a means to deceive general people, and the degree of political interference as potential contributory factors. To find the correlation among different variables, semi-structured questionnaires were distributed among the clients, bank managers, some Banking scholars and ex-members of the board of directors of three Islamic Banks in Bangladesh. Later, ten interviews were collected from key informants to gain in-depth information about the present mismanagement of Islamic Banks in Bangladesh. After then, data were analyzed using statistical software and substantiated by secondary sources like newspapers, reports and investigative reports aired in screen media. The paper found a correlation between almost all contributory factors and recent unstable conditions in the Islamic banking sector. After performing regression analysis, this paper found a more significant relationship between some of the contributory factors with Banking volatility than others. For instance, credit management, inept board of directors, depriving customers of proving no profit in the name of business—no interest-- and political interference have a strong significant positive correlation with the present poor condition of Islamic Banking. This paper concludes that while internal management is important in recovering the losses, the government needs to ensure framing better policy for the Islamic Banking system, Central Bank needs to supervise and monitor all Islamic banks meticulously and loan receivers must go through the impartial evaluation and approved by the representatives of the Central Shariah Board. This paper also recommends that there is a need to strengthen the auditing system and improve regulatory oversight of the Islamic Banks in Bangladesh. Policy recommendations that this paper put forward could provide an outline for dealing with the existing challenging condition of Islamic Banks and these could be applied to similar problems in other countries where the Islamic Banking model exists.

Keywords: Islamic bank, volatility in banking sector, shariah law, credit management, political interference

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319 A Low Power and High-Speed Conditional-Precharge Sense Amplifier Based Flip-Flop Using Single Ended Latch

Authors: Guo-Ming Sung, Ramavath Naga Raju Naik

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This paper presents a low power, high speed, sense-amplifier based flip-flop (SAFF). The flip-flop’s power con-sumption and delay are greatly reduced by employing a new conditionally precharge sense-amplifier stage and a single-ended latch stage. Glitch-free and contention-free latch operation is achieved by using a conditional cut-off strategy. The design uses fewer transistors, has a lower clock load, and has a simple structure, all of which contribute to a near-zero setup time. When compared to previous flip-flop structures proposed for similar input/output conditions, this design’s performance and overall PDP have improved. The post layout simulation of the circuit uses 2.91µW of power and has a delay of 65.82 ps. Overall, the power-delay product has seen some enhancements. Cadence Virtuoso Designing tool with CMOS 90nm technology are used for all designs.

Keywords: high-speed, low-power, flip-flop, sense-amplifier

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318 Modelling the Dynamics of Corporate Bonds Spreads with Asymmetric GARCH Models

Authors: Sélima Baccar, Ephraim Clark

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This paper can be considered as a new perspective to analyse credit spreads. A comprehensive empirical analysis of conditional variance of credit spreads indices is performed using various GARCH models. Based on a comparison between traditional and asymmetric GARCH models with alternative functional forms of the conditional density, we intend to identify what macroeconomic and financial factors have driven daily changes in the US Dollar credit spreads in the period from January 2011 through January 2013. The results provide a strong interdependence between credit spreads and the explanatory factors related to the conditions of interest rates, the state of the stock market, the bond market liquidity and the exchange risk. The empirical findings support the use of asymmetric GARCH models. The AGARCH and GJR models outperform the traditional GARCH in credit spreads modelling. We show, also, that the leptokurtic Student-t assumption is better than the Gaussian distribution and improves the quality of the estimates, whatever the rating or maturity.

Keywords: corporate bonds, default risk, credit spreads, asymmetric garch models, student-t distribution

Procedia PDF Downloads 444