Financial Econometrics

A large literature studies the predictability of stock returns by other lagged financial variables in a predictive regression setting. A common feature of widely used testing procedures is a failing robustness, which may lead to misleading conclusions determined by the particular features of a small subfraction of the data. We propose a new general method to deal with this problem based on the robust subsampling approach. The method implies robust confidence intervals and inference results. It is applicable both in the multipredictor context and in settings with nearly integrated regressors. Simulation evidence confirms the higher accuracy and efficiency of our robust testing approach for typical applications in which the data may follow only approximately a predictive regression model. We apply our approach to US equity data from 1961 to 2008 and find that it yields a stronger evidence in favor of predictability than a number of other (nonrobust) tests in the literature.

We use the database leak of Mt. Gox exchange to analyze the dynamics of the price of bitcoin from June 2011 to November 2013. This gives us a rare opportunity to study an emerging retail-focused, highly speculative and unregulated market with trader identifiers at a tick transaction level. Jumps are frequent events and they cluster in time. The order flow imbalance and the preponderance of aggressive traders, as well as a widening of the bid-ask spread predict them. Jumps have short-term positive impact on market activity and illiquidity and induce a persistent change in the price.

We test for the presence of low-dimensional chaotic structure in the Stock Exchanges of Indonesia and Malaysia. While we find strong evidence of nonlinear dependencies, the evidence is not consistent with chaos. Our test results indicate that ARCH-type processes generally explain the nonlinearities in the data. We also show that employing seasonally adjusted index series contributes to obtaining robust results via some of the existing tests for chaotic structures.

Розглянуто проблему ідентифікації параметрів математичних моделей динамічних процесів, які можуть бути описані звичайними диференціальними рівняннями та системами рівнянь. На прикладі математичних моделей динамічного формування ринкової вартості однієї акції та портфеля цінних паперів розроблено алгоритми побудови оптимальних значень параметрів таких моделей. Алгоритми параметричної ідентифікації та оптимізації ґрунтуються на ітераційних процедурах, які дозволяють на кожному кроці формувати «кращі» з точки зору вибраних критеріїв якості значення параметрів моделі. Гарантовані оцінки параметрів будуються у класі еліпсоїдальних множин, які, на прикладі математичних задач фінансового аналізу, дозволяють отримати гарантовані фінансові показники інвестиційної діяльності.The problem of identification of parameters of mathematical models of dynamic processes is considered that can be described by ordinary differential equations and systems of such equations. Using an example of mathematica...

In recent years, there have been attempts to test the theory of market efficiency, using more efficient and accurate models to predict changes in the prices of various financial instruments. Actually there are two ways to predict such variations: parametric and nonparametric models. In the first group there are various statistical-econometric models, while in the second there are artificial intelligence techniques as neural networks and genetic algorithms. The use of neural networks for predicting the behaviour of economic variables has increased greatly in recent years. This paper describes the design of solutions to forecast the share price of Telecom Argentina SA, which is listed on the Stock Exchange of Buenos Aires, in the period 2005-2012 from the use of a technique called Principal Component Analysis. The results are presented based on traditional models Arch-Garch and backpropagation networks. Additionally, a comparison between the methodologies is presented, considering the...

With 23 core econometrics journals now in operation, this study fills a gap in the literature by cataloguing the editorial specifications of each journal, and, more importantly, assessing their impact based on citations to research published in each over the 15-year period beginning in 2001 and ending in 2015. Our investigation reveals that about one-half of all core econometrics journals publish in an online format only, while the others publish both online and in-print. About one-fourth of all core econometrics journals are affiliated with an academic organization or society, while the same number are published by either Elsevier, Springer or Wiley. In terms of our assessment, Econometrica, Journal of Econometrics and Journal of Applied Econometrics sit atop our citations index ranking, while the relatively-new Journal of Financial Econometrics breaks into the top five, and other younger journals, such as the Journal of Econometric Methods and Econometrics, also make a strong show...

VAR merupakan sistem persamaan dinamis yang digunakan untuk menguji hubungan antara variabel-variabel dengan menggunakan asumsi minimal atas strukturnya. VAR menjelaskan bahwa setiap variabel yang ada dalam model tergantung pada pergerakan masa lalu variabel tersebut dan juga pergerakan masa lalu seluruh variabel yang ada dalam sistem. Dalam paper ini diaplikasikan VAR untuk mencari model dari data nilai tukar rupiah terhadap USD dan AUD. Hasil analisis VAR menunjukkan bahwa dengan tingkat kepercayaan 99% untuk variabel tak bebas USD, USD tidak Granger menyebabkan AUD sedangkan untuk variabel tak bebas AUD, AUD Granger menyebabkan USD. Hal ini menunjukkan apabila variabel USD dimasukkan dalam komponen variabel untuk memprediksi nilai USD, hasilnya secara statistik tidak signifikan. Namun,apabila variabel AUD dijadikan variabel untuk memprediksi besarnya USD, hasilnya secara statistik signifikan. Kata kunci: VAR, kausalitas Granger, uji stasioner, impulse response, dekomposisi Cholesky. VAR (Vector Autoregression) merupakan sistem persamaan dinamis yang digunakan untuk menguji hubungan antara variabel-variabel dengan menggunakan asumsi minimal atas strukturnya. VAR menjelaskan bahwa setiap variabel yang ada dalam model tergantung pada pergerakan masa lalu dari variabel itu sendiri dan juga pergerakan masa lalu seluruh variabel lainnya yang ada dalam sistem. Dalam analisis VAR, dicari model sistem persamaan dari variabel-variabel runtun waktu dalam bentuk vektor yang nantinya akan digunakan untuk mengetahui hubungan kausalitas (interrelationship) dari variabel-variabel tersebut. Pada dasarnya, analisis VAR bisa dipadankan dengan suatu model persamaan simultan. Perbedaannya, pada model persamaan simultan perlu dibedakan mana variabel yang endogen dan mana yang eksogen, sedangkan dalam analisis VAR semua variabel dianggap sebagai variabel endogen, [1]. Ini berarti bahwa, dalam VAR, setiap variabel diterangkan nilainya di masa lampau dan dipengaruhi oleh nilai masa lalu dari variabel endogen lainnya dalam model yang diamati. Dalam paper ini diaplikasikan VAR untuk mencari model dari data nilai tukar rupiah terhadap dolar Amerika (United State Dollar, disingkat USD) dan dolar Australia (Australian Dollar, disingkat AUD).

This paper examines the history of econometrics through a particular case study modelling the tradeoff between inflation and unemployment. It focuses on the questions of what econometric tools modellers would choose to model the tradeoff, how their choices helped shape the ways that they obtained, interpreted and theorised the empirical evidence and how their different concerns and the different problems that they encountered has fed back into the development of econometrics. The study reveals that much of the interaction between econometrics and economics involved modellers taking certain tradeoffs between theory and data, and their different positions generated disputes, factions as well as confusions. It also reveals that the history of modelling the tradeoff mirrors the evolving process of how the Cowles structural modelling paradigm in econometrics became consolidated, challenged, reformed or abandoned.

El traspaso del tipo de cambio hacia precios domesticos en escenarios de dolarizacion impone mayores retos a la politica monetaria. Mas aun, estos retos aumentan cuando las transacciones reales estan dolarizadas y contaminan la formacion de expectativas de inflacion al introducir asimetrias y no linealidades en la relacion entre el tipo de cambio y la inflacion durante periodos de alta depreciacion cambiaria en contraste a episodios de depreciacion moderada y periodos de apreciacion.

Decentralized Finance (DeFi) has emerged as a revolutionary paradigm in the global financial ecosystem, challenging the conventional banking systems by utilizing blockchain technology and smart contracts. This paper explores the rise of DeFi, its foundational principles, and its impact on traditional financial systems. DeFi eliminates the need for intermediaries such as banks, enabling peer-to-peer financial services such as lending, borrowing, trading, and asset management. By leveraging decentralized protocols, DeFi offers greater financial inclusion, transparency, and security, while providing users with complete control over their assets. The paper critically evaluates the advantages of DeFi, including reduced transaction costs, faster processing times, and the democratization of financial services. It also highlights the challenges and risks, such as regulatory uncertainty, scalability issues, and security vulnerabilities that could hinder widespread adoption. Furthermore, the review examines key DeFi applications, such as decentralized exchanges (DEXs), liquidity pools, and stablecoins, that are reshaping financial practices. While DeFi holds the potential to disrupt traditional banking by providing innovative alternatives, it also raises concerns related to market volatility and the lack of consumer protection. The paper concludes by reflecting on the future of DeFi, including its integration with mainstream finance and the regulatory frameworks that may shape its evolution. As DeFi continues to gain traction, understanding its potential and limitations is essential for policymakers, financial institutions, and participants in the global financial markets.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Este paper muestra el pronóstico de la tasa de cambio entre el peso colombiano y el dólar estadounidense (en adelante dólar) desde Diciembre del 2019 hasta Diciembre del 2020, basado en un modelo VEC (Vector Error Correction) a partir de la hipótesis de paridad de poder adquisitivo débil. Con esto, se propone que la tasa de cambio se ajusta no solamente para equilibrar las diferencias en precios entre Estados Unidos y Colombia, sino también para equilibrar una tercera variable, en este caso el precio del petróleo WTI. Dado que la principal fuente de ingresos por exportaciones para Colombia son los recursos petroleros, se consideró valioso usar las cotizaciones del WTI como proxy para estimar la probable dirección que siga la tasa de cambio en el corto y medio plazo.

The future of e-money is crypocurrencies, it is the decentralize digital and virtual currency that is secured by cryptography. It has become increasingly popular in recent years attracting the attention of the individual, investor, media, academia and governments worldwide. This study aims to model and forecast the volatilities and returns of three top cryptocurrencies, namely; Bitcoin, Ethereum and Binance Coin. The data utilized in the study was extracted from the higher market capitalization at 31 st December, 2021 and the data for the period starting from 9 th November, 2017 to 31 st December 2021. The Generalised Autoregressive conditional heteroscedasticity (GARCH) type models with several distributions were fitted to the three cryptocurrencies dataset with their performances assessed using some model criteria. The result shows that the mean of all the returns are positive indicating the fact that the price of this three crptocurrencies increase throughout the period of study. The ARCH-LM test shows that there is no ARCH effect in volatility of Bitcoin and Ethereum but present in Binance Coin. The GARCH model was fitted on Binance Coin, the AIC and log L shows that the CGARCH is the best model for Binance Coin. Automatic forecasting was perform based on the selected ARIMA (2,0,1), ARIMA (0,1,2) and the random walk model which has the lowest AIC for ETH-USD, BNB-USD and BTC-USD respectively. This finding could aid investors in determining a cryptocurrency's unique risk-reward characteristics. The study contributes to a better deployment of investor's resources and prediction of the future prices the three cryptocurrencies.

This study examined the major factors that drive changes in yam consumption patterns across income groups, seasons and urban centers in Ghana to inform food policy formulation. The study, among other things, sought to provide evidence on whether or not yam had become a luxury food commodity in Ghanaian urban communities. Special attention was also given to the question of whether household income allocation between males and females had any significant effect on yam consumption. The study estimated yam expenditure elasticities for the pooled/aggregate data and the four different urban centers across different income groups to test Engel's law. Results of the study showed that majority (>80%) of yam consumers in Ghanaian urban communities preferred white yam to yellow and water yams, and the most important reason for their preference was taste. Boiled yam (ampesi) was the most preferred yam product in Ghanaian urban centers followed by pounded yam (fufu). Rice was identified as the most important substitute for yam in urban communities. In a typical Ghanaian urban center, household food budget formed about 51% of the total household budget. Yam constituted about 12% of household at-home food budget and 13% of its away-from-home food budget.

El creciente interés por construir sistemas de procesamiento de señales mediante redes neuronales, especialmente durante los últimos veinte años, se debe a la posibilidad de avances significativos en campos poco explorados y cuyo manejo resulta de naturaleza compleja. Uno de estos campos es la predicción de señales. Una señal es una colección de valores que, generalmente, representan mediciones sucesivas de un evento del mundo real, los valores se toman durante un tiempo específico a intervalos regulares, representando una muestra del evento que se desea estudiar o de las características propias del mismo. La predicción de una señal consiste en obtener un conjunto de valores que, según un margen de error aceptable, constituyen una estimación del comportamiento futuro de la señal. El proceso de predicción es mucho más que la posición simplista de aventurar valores; puesto que requiere la construcción de un modelo adecuado de la dinámica del sistema a tratar.

Using panel data from 144 countries, this study constructed an inclusive financial evaluation index and depicted the inclusive finance development worldwide under digital empowerment through classification. It reviewed the spatial effect of financial inclusion in developed and developing countries by throwing light on demand, supply, and regulatory factors via the spatial Durbin model. The mediating and regulatory effects model examines the transmission mechanism of financial inclusion with a focus on financial literacy, scientific and technological levels, and regulatory quality. The results show that the level of financial inclusion in developed countries is significantly higher than in developing countries. The economic level of developed countries positively impacts financial inclusion in their countries and neighbouring ones. Enhancing financial literacy, science and technological level, and supervision quality improve the development of inclusive finance. While the economic level and urbanization rate in developing countries inhibit the development of financial inclusion, countries with lower economic development and urbanization rates have a greater incentive to develop digital financial inclusion. The improved economic development in developing countries favours financial inclusion in countries nearby. Moreover, financial literacy plays a positive moderating role in the effect of digital finance on financial inclusion. The technology level can exert a transmission effect on financial inclusion through an elevated level of digital finance. The impact of regulatory quality on financial inclusion can be conveyede by creating a stable economic and financial environment and improving economic development levels. This study expands the theoretical research on constructing an inclusive finance evaluation system and its impact mechanism. It provides essential decision-making references for governments, relevant decision-making departments, financial institutions and financial technology enterprises to develop inclusive finance.

The ARIMA (Autoregressive Integrated Moving Average) was applied to the series of SPI -1. The results of the evaluation of the model showed good agreement between observations and forecasts , as was also confirmed by the values of some performance indices and the results seem to be better for better SPI Serial and this may be due to increase the filter length reduces the effective noise .

European, national governments and regional authorities, in recent times, are actively encouraging technology transfer from universities to industries as a fulfilment of the well embraced "third mission" of universities. To pursue this, governments have mediated this process by enacting and enforcing legislative instruments and efficiently appropriating research outcomes by providing public funding support structures to aid universities in their research commercialization efforts. The paper aims to examine various public funding schemes available for firm's innovation collaborations and how they influence firm's cooperation. Using data from the Eurostat's Community Innovation Survey (2012–2014) and the binary logistic regression model, we found that funding from the central government was a significant determinant influencing firm's collaborations with universities, other enterprises in the enterprises group and with government research centres. Conversely,...

Econometric estimation using simulation techniques, such as the efficient method of moments, may be time consuming. The use of ordinary matrix-programming languages such as GAUSS, MATLAB, Ox, or S-PLUS will often cause extra delays. For the efficient method of moments implemented to estimate stochastic volatility models, this will surely be the case; therefore, the author made a C/C++ library containing the bulk of the procedures needed in the implemention of the efficient method of moments technique for a broad range of univariate stochastic volatility models. As a side effect of the efficient method of moments, EGARCH models with a variety of non-normal distributions can be estimated with this package. Implementations have been made for the Intel Pentium platform linked under Windows and for the IBM RS/6000 platform under AIX. The library is dynamically linked to Ox under Windows and statically linked under AIX. The speed improvements are considerable compared with pure Ox code. This paper serves as a manual for this library. It describes the efficient method of moments for this specific case of stochastic volatility models, and it describes the program. Some examples are given from other work of the author. Technicalities are given in the appendices. Acknowledgments. The author thanks Peter Boswijk, Jurgen Doornik, Ruud Koning, Neil Shephard, and an anonymous referee for comments.

Abdullah ÖZDEMİR ii , Alican BİLGEN iii Öz Döviz kuru; bir ülkenin para biriminin başka bir para birimi cinsinden fiyatı olarak tanımlanmaktadır. Döviz kuru dalgalanması veya istikrarı ise ekonomik büyümenin kuantumunu ve yönünü belirleyen temel sorundur. Döviz kuru dalgalanması, döviz kurundaki öngörülemeyen hareketlerle ilişkili risk olarak tanımlanmaktadır. Dolayısıyla bu konu hem gelişmiş ekonomiler hem de Türkiye gibi gelişmekte olan ekonomiler için oldukça önemli bir konu olarak karşımıza çıkmaktadır. Çalışmanın amacı, Türkiye'de döviz kuru oynaklığının ekonomik büyüme üzerindeki etkilerini ortaya koymaktır. Bu hususta 2003Ç1 ile 2019Ç4 yılları arasında çeyreklik veriler kullanılarak Vectör Otoregresif yöntemi yardımıyla analiz gerçekleştirilmiş ve bulgularda; Türkiye'de döviz kurundaki azalmaların veya azaltıcı politikaların, ekonomik büyümeyi pozitif yönde etkilediği tespit edilmiştir. Bu sonucun bağlayıcıları, politika yapıcıları tarafından uygulanan ekonomi politikalarıdır. Diğer bir ifadeyle bulguların, teorik çerçeveyle uyumlu olmadığı görülmüştür.

Energy markets have been undergoing dramatic transformations in recent decades. Deregulation in the electricity and gas markets has forced a whole new world of trading and risk management. Risk managers, scholars, and experts of energy matters are more and more challenged with the choice of the adequate instrument or risk management strategy. The 51st international conference of the EWGCFM devoted 3 days to this topic with 140 participants from academia and the commercial world presenting new tools and ideas on how to face these challenges. Sixty-five of the 120 researches presented during the conference provided original and interesting contributions on this topic and were submitted for publication in this special issue. 1 One third of the papers submitted, precisely twenty-seven, were finally accepted for publication. The 27 papers deal with five main areas of research: 1. The role of fossil fuels in the energy commodity risk management. 2. The role of renewable energy sources in power market's dynamics. 3. Recent developments in technological and institutional interventions affecting the power markets. 4. The level of integration of energy commodities in Europe. 5. Recent dynamics in energy commodity markets: volatility issues, the role of speculation, the role of derivative contracts in providing efficient information, the performance of energy companies.

Several phenomena are available representing market activity: volumes, number of trades, durations between trades or quotes, volatility -however measured -all share the feature to be represented as positive valued time series. When modeled, persistence in their behavior and reaction to new information suggested to adopt an autoregressive-type framework. The Multiplicative Error Model (MEM) is borne of an extension of the popular GARCH approach for modeling and forecasting conditional volatility of asset returns. It is obtained by multiplicatively combining the conditional expectation of a process (deterministically dependent upon an information set at a previous time period) with a random disturbance representing unpredictable news: MEMs have proved to parsimoniously achieve their task of producing good performing forecasts. In this paper we discuss various aspects of model specification and inference both for the univariate and the multivariate case. The applications are illustrative examples of how the presence of a slow moving low-frequency component can improve the properties of the estimated models.

Stock prices are impacted by an array of different factors that can affect movement of prices daily. It is essential to investors and traders to understand the volatility of the nature of the stock, before investing in it. In today’s markets, it is very common for different algorithms dictating the movement of prices, which are trained on variety of features or factors that can impact the price of the stock and/or the share. This project aims to use Tensor Flow’s Artificial Neural Network to predict stock prices and compare it to the estimations done by conventional forecasting methods and see if there is a need to develop such networks which it comes to quantitative forecasting.

La politique économique a pour objectif final le bien-être de la population.
En se référant à Nicholas Kaldor, le bien-être de la population, c’est lutter contre
l’inflation, réduire le chômage, améliorer la croissance économique et équilibrer la
balance des paiements.
Le présent travail essaye de vérifier dans le contexte congolais, l’impact des
politiques économiques sur le bien-être de la population. Pour y parvenir, trois (3)
politiques économiques conjoncturelles ont été utilisées à savoir : la politique
monétaire, la politique budgétaire et la politique de change.
Apres analyse économétrique par le modèle ARDL, l’étude est arrivée à la
conclusion selon laquelle la politique monétaire mise en œuvre par la BCC ne permet
pas d’atteindre la croissance économique et d’améliorer le bien-être de la population.
Quant à la politique budgétaire et la politique de change, les analyses ont montré un
impact positif mais non significatif.
Mots clés : Politique économique, Bien-être de la population, Modèle ARDL

Bu calismanin amaci, ekonomiyi etkileyen makro degiskenlerden olan enflasyon, faiz oranlari ve para arzinin doviz kuru uzerinde etkili olup olmadiginin arastirilmasidir. Bu amac dogrultusunda, soz konusu degiskenlerin doviz kuru uzerindeki etkilerinin Turkiye ile BRICS (Brezilya, Rusya, Hindistan, Cin ve Guney Afrika) ulkelerinde karsilastirmasi yapilmistir. Calisma 2002M01-2017M12 yillarina ait 16 yillik 192 aylik donemde incelenmistir. Calismada ADF Birim Kok testi, Johansen Esbutunlesme Testi, VAR Analizi, FMOLS Yontemi, VEC Hata Duzeltme Modeline dayali Granger Nedensellik testleri kullanilmistir. Calisma sonucunda, Guney Afrika haric diger butun BRICS-T ulkelerinde doviz kuru ile ayni yonlu bir iliski vardir. Faiz orani katsayilarinin diger degiskenlere nazaran fazla yuksek olmamasi nedeniyle calismada yer alan butun ulkelerde faiz orani ile doviz kuru arasinda guclu bir iliskinin olmadigini ortaya cikmistir. Enflasyon orani ise Cin haric calismada yer alan butun ulkeler icin d...

Among various kinds of options we can found at the market, some are traded at organized exchanges and therefore are quite liquid, while others are traded only between particular parties. Whereas there is no need to look for a model to price liquid exchange traded options, since their price is generally accepted by the demand and supply, for illiquid or even exotic options new efficient models are still developed. The current market practice is to obtain the implied volatility of liquid options as based on Black-Scholes type (BS hereafter) models. Since the BS model at one time moment can be related to a large set of IVs as given by different parameters (maturity/moneyness relation) of tradable options leading to IV curve or surface. Since there is no continuum of options with various parameters, the curve / surface must be obtained by suitable smoothing and interpolation. However, it can bring an arbitrage opportunity, if noarbitrage conditions on state price density (SPD) are ignored. The focus of this paper is to study the behavior of IV and SPD for several kernel functions and with respect to different choices of bandwidth parameter h. Specifically, we show several interesting implications of the change of h on the violation of no arbitrage condition and the total area of SPD under zero.

This paper makes an attempt to examine the financial integration between emerging countries and developed countries. Stock market data for six countries USA, CANADA, UK, India, Malaysia and Singapore have been used for the purpose of the study. Cointegration was tested on the basis of various alternative techniques. Results contradict existing literatures and suggest that although developments at international level significantly influence national stock markets, but they are driven mainly by the developments at domestic level. Study also indicates that world equity market is segmented; where developed nations and emerging markets have made separate grouping. In case of India we find that it is positively correlated with all the markets, but this relationship is not highly positive.

This paper makes an attempt to examine the financial integration between emerging countries and developed countries. Stock market data for six countries USA, CANADA, UK, India, Malaysia and Singapore have been used for the purpose of the study. Cointegration was tested on the basis of various alternative techniques. Results contradict existing literatures and suggest that although developments at international level significantly influence national stock markets, but they are driven mainly by the developments at domestic level. Study also indicates that world equity market is segmented; where developed nations and emerging markets have made separate grouping. In case of India we find that it is positively correlated with all the markets, but this relationship is not highly positive.

A multivariate positive definite estimator of the integrated covariance matrix of noisy and asynchronously observed asset returns is proposed. We adopt a Bayesian Dynamic Linear Model where microstructure noise is interpreted as measurement error, and asynchronous trading as missing observations in an otherwise synchronous series. Missing observations are treated as any other parameter, as typical in a Bayesian framework. An augmented Gibbs algorithm is used since all full conditionals are available and its convergence and robustness are discussed. A realistic simulation study compares our estimator with existing alternatives, under different liquidity and microstructure noise conditions. The results suggest that our estimator is superior in terms of RMSE particularly under severe conditions, such as portfolios of assets with heterogeneous liquidity and high level of microstructure noise. The application to the empirical dataset of ten tick-by-tick stock price series confirms the simulation results.

This paper is the first attempt to assess the impact of official FOREX interventions of the three major central banks in terms of the dynamics of the currency components of the major exchange rates (EUR/USD and YEN/USD) over the period 1989-2003. We identify the currency components of the mean and the volatility processes of exchange rates using the recent Bayesian framework developed by . Our results show that in general, the concerted interventions tend to affect the dynamics of both currency components of the exchange rate. In contrast, unilateral interventions are found to primarily affect the currency of the central bank present in the market. Our findings also emphasize a role for interventions conducted by these central banks on other related FOREX markets.

Ketimpangan upah merupakan isu global yang terus berkembang, mencakup perbedaan upah antar tempat kerja meskipun pekerja memiliki kualifikasi yang serupa. Sistem upah konvensional yang berfokus pada efisiensi ekonomi cenderung mengabaikan keseimbangan dan keadilan sosial, menyebabkan kelompok rentan seperti pekerja berpendidikan rendah dan perempuan menghadapi ketidakadilan pendapatan. Konsep maqashid syariah menawarkan kerangka alternatif yang holistik untuk mengintegrasikan nilai keadilan dan kesejahteraan dalam sistem pengupahan. Penelitian ini menggunakan pendekatan kualitatif dengan metode studi pustaka untuk menggali relevansi prinsip maqashid syariah dalam kebijakan upah. Hasil penelitian menunjukkan bahwa sistem pengupahan berbasis maqashid syariah memastikan upah mencerminkan kontribusi tenaga kerja sekaligus memenuhi kebutuhan dasar mereka. Prinsip keadilan, kesejahteraan, dan keseimbangan yang diusung maqashid syariah mampu menciptakan hubungan industrial yang harmonis dan produktivitas yang berkelanjutan. Selain itu, peran institusi syariah sebagai regulator dan fasilitator memperkuat implementasi nilai-nilai maqashid syariah dalam kebijakan upah, memastikan kebijakan tersebut memenuhi standar etika Islam. Penelitian ini merekomendasikan integrasi prinsip maqashid syariah dalam kebijakan upah sebagai langkah strategis untuk menciptakan sistem tenaga kerja yang lebih manusiawi, adil, dan berkelanjutan. Kata kunci: keadilan distributif; maqashid syariah; sistem upah Islami.

Predicting the future accurately is of vital importance in all disciplines, as well as in the field of social sciences. Especially today, due to the development of technology and the presence of package programs that can process huge data, it is a very important development for all fields, including econometrics, that we can reach more accurate estimates. As a result, it is a situation that is directly related to the decrease in the error rates of the forecasts and more accurate planning for the future. In this study, time series analyzes were made over the proportional changes of the closing values of the Borsa Istanbul (BIST30) index, that is, the monthly average closing values, and 24-month forecasts were calculated. For this purpose, in order to increase the accuracy of the prediction results of the classical ARIMA models and the models based on the Box-Cox transform, new prediction results were obtained with the models modified with the Fourier series. Mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE) and mean absolute percent error (MAPE) performance criteria were used to evaluate the success of the established models. It was concluded that the model with the lowest value for MSE, RMSE, MAE and MAPE performance criteria was more successful than the other models. As a result, more successful results were obtained with more accurate estimation results, that is, with lower error rates.

Predicting the future accurately is of vital importance in all disciplines, as well as in the field of social sciences. Especially today, due to the development of technology and the presence of package programs that can process huge data, it is a very important development for all fields, including econometrics, that we can reach more accurate estimates. As a result, it is a situation that is directly related to the decrease in the error rates of the forecasts and more accurate planning for the future. In this study, time series analyzes were made over the proportional changes of the closing values of the Borsa Istanbul (BIST30) index, that is, the monthly average closing values, and 24-month forecasts were calculated. For this purpose, in order to increase the accuracy of the prediction results of the classical ARIMA models and the models based on the Box-Cox transform, new prediction results were obtained with the models modified with the Fourier series. Mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE) and mean absolute percent error (MAPE) performance criteria were used to evaluate the success of the established models. It was concluded that the model with the lowest value for MSE, RMSE, MAE and MAPE performance criteria was more successful than the other models. As a result, more successful results were obtained with more accurate estimation results, that is, with lower error rates.

This paper investigates, both in finite samples and asymptotically, statistical inference on predictive regressions where time series are generated by present value models of stock prices. We show that regression-based tests, including robust tests such as the conditional test and the Q-test, are inconsistent and thus suffer from lack of power in local-to-unity models for the regressor persistence. The main reason is that, despite the near-integrated dividend-price ratio, the convergence rates of the estimates are slowed down because the present value model implies a shrinking innovation variance on the predictor, an effect which is masked in a predictive regression analysis with exogenous constant covariance of innovations. We illustrate these properties in a simulation study.

Research on the driving role of digital finance in urban innovation is scarce. Most existing literature focuses on whether digital or traditional finance contributes more to innovation, ignoring the spatial spillover effect of digital finance and failing to explore whether digital finance complements traditional finance in promoting innovation. Moreover, current studies focus on the provincial dimension but elaborate very little on the implications of BRI node cities. This study fills in the gaps by focusing on the spatial spillover effects of digital finance on urban innovation and complementary functions of traditional finance. It applies the spatial Durbin model to 26 China BRI node cities from 2013 to 2020. The results indicated that digital finance has a significant positive effect on the innovation level of these cities, suggesting that digital and traditional finance systems are complementary in promoting innovation. Moreover, the evidence of spatial spillover proves that innovations in node cities influence neighboring regions. This paper contributes to the interaction between digital finance and urban innovation with new insights. It also fills the literature gap by underlining the spatial dynamics rather than traditional panel approaches. The results are useful for policymakers in harnessing financial mechanisms for innovation and economic growth.

This paper examines the intertemporal relation between expected return and risk for 30 stocks in the Dow Jones Industrial Average. The mean-reverting dynamic conditional correlation model of Engle ( ) is used to estimate a stock's conditional covariance with the market and test whether the conditional covariance predicts time-variation in the stock's expected return. The risk-aversion coefficient, restricted to be the same across stocks in panel regression, is estimated to be between two and four and highly significant. This result is robust across different market portfolios, different sample periods, alternative specifications of the conditional mean and covariance processes, and including a wide variety of state variables that proxy for the intertemporal hedging demand component of the ICAPM. Risk premium induced by the conditional covariation of individual stocks with the market portfolio remains economically and statistically significant after controlling for risk premiums induced by conditional covariation with macroeconomic variables (federal funds rate, default spread, and term spread), financial factors (size, book-to-market, and momentum), and volatility measures (implied, GARCH, and range volatility).

The purpose of Education should be gauged in its ability to inculcate morals, value system and skill set among the learners so as to make them an asset for the nation. Human Capital formation is going to play a very important role in development of the nation. The nation's education system has largely remained unchanged since last 3 decades. It is to be noted that, that advent of Information communication technology which has paved way to knowledge economy has disrupted the ways in which how things are taught, how things are learnt and how things are done. In this context, to ensure our youth are endowed with skill set relevant for 21 st century, revamping our education system was the need of the hour. This paper analyses the evolution of National Education Policy and the relevance of latest upgradation in meeting the needs and aspirations of young India.

has adversely affected all the nations and all the sectors of all nations. However, the effect of the same on all the sectors of the economy need not be uniform. Moreover, the severity of impact need not be the same across consequent waves. Knowing the severity of the impact across the waves as well as across the time periods shall be quite useful for the purpose of policy formulation. ARCH modelling helps us to gauge the intensity of shocks sustained across the sectors through heteroscedasticity which can be read as a proxy for shock. To understand the severity of shock across the sectors, the share value of the prominent companies across the sectors have been taken as a proxy for their performance. Evaluating the severity of shocks across the sectors shall help the government to note which sector needs greater support so as to create conducive fiscal and monetary initiatives to enable the economy to achieve the state of normality. This paper is designed to bridge the aforementioned research gap.

Saat ini kita hidup dalam ekonomi global. Suka atau tidak suka, setuju atau tidak setuju dampak ekonomi global kita rasakan. Apa yang terjadi di belahan bumi lain, dampaknya terasa dalam perekonomian nasional. Oleh karena itu, sebagai warga bumi kita harus mempersiapkan diri agar bisa survive. Di lain pihak, mereka yang tidak setuju dengan globalisasi ekonomi berusaha mengubahnya dengan menggalang kekuatan. Mereka percaya bahwa kesejahteraan manusia hanya dapat dicapai bila masa depan dipusatkan pada manusia itu sendiri dan kemajuan-kemajuan harus bersifat swadaya, bukannya pada globalisasi Kata kunci : ekonomi global, negara maju, negara sedang berkembang.

El enfoque metodologico que se sigue en este trabajo para estudiar el co-movimiento de los cinco principales mercados de capital europeos es el de Copula-GARCH, ajustando primero modelos GARCH para estimar las distribuciones marginales de los rendimientos de cada uno de dichos mercados. Con base en las distribuciones marginales estimadas, se procede a llevar a cabo el modelado de la distribucion conjunta de los rendimientos mediante la estimacion de un modelo canonico de vina de copulas (vine copula). / The Copula-GARCH model is used to assess the simultaneous movement of the main five European Capital Markets. First, the returns marginal distributions were estimated with GARCH models, with these estimations, the returns joint distributions modeling was carried out using a canonic vine copula model.

The aims of this study were threefold: 1) study the research gap in carpark and price index via big data and natural language processing, 2) examine the research gap of carpark indices, and 3) construct carpark price indices via repeat sales methods and predict carpark indices via the AutoML. By researching the keyword "carpark" in Google Scholar, the largest electronic academic database that covers Web of Science and Scopus indexed articles, this study obtained 999 articles and book chapters from 1910 to 2019. It confirmed that most carpark research threw light on multi-storey carparks, management and ventilation systems, and reinforced concrete carparks. The most common research method was case studies. Regarding price index research, many previous studies focused on consumer, stock, press and futures, with many keywords being related to finance and economics. These indicated that there is no research predicting carpark price indices based on an AutoML approach. This study constructed repeat sales indices for 18 districts in Hong Kong by using 34,562 carpark transaction records from December 2009 to June 2019. Wanchai's carpark price was about four times that of Yuen Long's carpark price, indicating the considerable carpark price differences in Hong Kong. This research evidenced the features that affected the carpark price indices models most: gold price ranked the first in all 19 models; oil price or Link stock price ranked second depending on the district, and carpark affordability ranked third.

This study attempted to investigate the effectiveness of the interest rate channel in the transmission of monetary policy by employing a structural vector autoregressive (SVAR) model using sign restriction. It used a set of policy and non-policy macroeconomic variables based on monthly data spanning the period 2007 and 2020. The structural impulse response functions provided evidence to support the use of the MPR as a signaling rate for domestic interest rates but was, however, found to be ineffective in stabilizing prices or increasing output. Furthermore, results from the variance decomposition of the non-policy variables found the effect of exchange rate innovations to be more significant in explaining variations in the price level. The study, therefore, concludes that the effectiveness of the policy rate in stabilizing prices is dampened by shocks prevalent from the external sector. Given the importance of international trade, the study recommends aggressive exchange rate manage...

The ascendancy of impropriety, embezzlement and fraud in most public institutions and good governance which has now assume a political jargon in Ghana inspired the study to be undertaken. The purposive method of sampling was used for selecting the staff, internal audit agency and Audit Service staffs respectively. The study uncovered the following facts in the activities of ARIC in MDAs/MMDAs. ARIC serves as a proper ingredient for management efficient performance, however the committee cannot be considered as fully independent and there are materials and financial constraints that makes it difficult for the committee to obtain its full benefits. The research revealed that AKDA has an ARIC and it is their responsibility to promote good governance. A call is made to MDAs/MMDAs to recognize the existence of the ARIC, be independent from management and should not delay to reply all audit reports.

The series "Studies in Systems, Decision and Control" (SSDC) covers both new developments and advances, as well as the state of the art, in the various areas of broadly perceived systems, decision making and control-quickly, up to date and with a high quality. The intent is to cover the theory, applications, and perspectives on the state of the art and future developments relevant to systems, decision making, control, complex processes and related areas, as embedded in the fields of engineering, computer science, physics, economics, social and life sciences, as well as the paradigms and methodologies behind them. The series contains monographs, textbooks, lecture notes and edited volumes in systems, decision making and control spanning the areas of Cyber-

We define the extreme values of any random sample of size n from a distribution function F as the observations exceeding a threshold and following a type of generalized Pareto distribution (GPD) involving the tail index of F. The threshold is the order statistic that minimizes a Kolmogorov-Smirnov statistic between the empirical distribution of the corresponding largest observations and the corresponding GPD. To formalize the definition we use a semiparametric bootstrap to test the corresponding GPD approximation. Finally, we use our methodology to estimate the tail index and value at risk (VaR) of some financial indexes of major stock markets.