Financial Econometrics

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.

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.

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.

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.

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 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.

Sovereign wealth funds (SWFs) have over $11.5 trillion in assets under management as of February 2023. Most of these 176 funds are sponsored by non-Western countries and their growth has made SWFs important international investors, particularly in private equity funding. We first define SWFs, then discuss their evolution into today's categories of stabilization, savings, and development/strategic funds. We discuss the documented importance of SWF funding sources -oil sales revenues versus excess reserves from export earnings -and summarize the empirical literature studying how SWFs allocate funds geographically and across asset classes. Next, we summarize empirical evidence on the impact of SWF stock investments on target firm financial and operating performance and discuss the evidence showing that the announcement of SWF investment causes target firm stock prices to rise in the short term, but the positive impact is significantly less than the positive return following large stock purchases by private investors, and the longer-term effect of SWF investment on target firms is generally negative. SWFs' recent focus on promoting ESG policies of investee companies is assessed and briefly compared to the effectiveness of other institutional investors' ESG efforts.

The sustainable growth requires a holistic approach, where all members of the society grow equally. This
study compares two states—Madhya Pradesh and Chhattisgarh in an effort to analyze financial inclusion,
including the use of banking and other regulated products at an affordable price. To support the study, primary
data has been gathered from different rural areas in both states during 2023. Primary information was collected
from 200 households for each state. Financial inclusion is receiving attention from all around the world since
it has been identified as one of the main causes of poverty. The findings of the study show Madhya Pradesh
has performed a little better as compared to Chhattisgarh in making the population of the state financially
inclusive.

This study investigates financial markets’ volatility and verifies the model that is suitable in BRICS stocks (2003-2018). The data were gotten from Yahoo finance. For the methodology, the ADF was applied to test stationary of the BRICS stocks while heteroskedasticity test was used to check if the BRICS stocks were suitable for ARCH family model. All the BRICS stocks were stationary following differencing at first level because statistical values of ADF were less compared to critical ones at 1%, 5% and 10% respectively. The criteria for selecting the suitable model is one with the smallest value of AIC & SIC. TARCH model had the lowest values of SIC & AIC of BRICS stocks. TARCH was model that was best fitted and the stock with the lowest value of AIC and SIC was South Africa stock with AIC = 15.23 and SIC = 15.24. Also, the GARCH model had the lowest AIC and SIC values for BRICS daily returns. GARCH model was the best-fitted model for daily returns with the lowest value of AIC and S...

In this paper, we compare the statistical properties of some of the most popular GARCH models with leverage e¤ect when their parameters satisfy the positivity, stationarity and nite fourth order moment restrictions. We show that the EGARCH speci cation is the most exible while the GJR model may have important limitations when restricted to have nite kurtosis. On the other hand, we show empirically that the conditional standard deviations estimated by the TGARCH and EGARCH models are almost identical and very similar to those estimated by the APARCH model. However, the estimates of the QGARCH and GJR models di¤er among them and with respect to the other three speci cations.

proposes the FIFGARCH model to represent long memory asymmetric conditional variance. Although he claims that this model nests many previous models, we show that it does not and that the model is badly specified. We propose and alternative specification.

This paper studies the predictive power of several financial variables usually used as proxies for global liquidity, volatility, and risk aversion in forecasting exchange rates for a set of countries from January 2001 to April 2013. The results indicate that changes in the long-term interest rate, in the VIX, in the high yield spread, and in the market liquidity indicators have strong in-sample and outof-sample predictive power with respect to exchange rates. The results indicate that the relationship between the financial variables and the exchange rate is relatively stable. The paper shows that the predictability of the models is persistent over time and does not depend on the choice of the window size adopted in the forecasting exercises.

Purpose-The purpose of this study is to analyze the effects on economic growth of export in the leading countries ICT exports. In this context, the relationship between information communication technology exports and economic growth of 7 selected countries using annual data between 2000-2015 was investigated with the help of panel data analysis. Methodology-The relationship between information communication technology exports and economic growth of 7 selected countries using annual data between 2000-2015 was investigated with the help of panel data analysis. Findings-The existence of cross section dependency and the slope coefficients are homogeneous. According to the analysis of causality, there is a bi-directional causality relation from export of information technologies to economic growth. Conclusion-This result reveals the importance of information and communication technologies' export to support economic growth. As a result of policies to be implemented in this direction, the growing sector can make a significant contribution to growth by creating production and export increases.

This paper examines the interactions among CDS spreads across 13 European countries using spatial econometrics techniques. Our model allows for the estimation of direct and indirect transmission of sovereign risk and feedback effects across the network of these countries. The novelty of this paper is to link macroeconomic variables and CDS spreads in a new context of analysis to uncover new channels affecting sovereign risk across countries during the European debt crisis. We show that the key channel in driving sovereign risk spillovers is trade linkages between the countries. Our results also reveal that a country's CDS spread is approximately 7 basis points (bps) higher for a 1% increase in public debt-to-GDP levels while that increase in indebtedness is associated with roughly 2 bps higher spreads in all other countries.

The Indian stock market is one of the most dynamic and promising in emerging markets. Domestic institutional investors (DIIs) and foreign institutional investors (FIIs) are the two major players in the Indian capital market. Foreign institutional investors (FIIs) have always been regarded as the primary drivers of the Indian securities market. The growing presence of domestic institutional investors (DIIs) in the Indian securities market is rarely discussed. Meanwhile, FIIs’ stake has consistently declined in recent years, owing to the emergence of domestic institutional investors (DIIs) as a potent counterforce to FIIs with opposing investing and trading strategies in India. The study attempts to investigate the investing behaviour of DIIs and FIIs and their impact on the Indian security market, as well as shed light on the direction of causality between FIIs, DIIs, and BSE Sensex returns. For this purpose, the study employs correlation analysis, the Granger causality test, and the vector autoregression (VAR) model. Our findings show that, at present, FIIs are not the sole drivers anymore; domestic investors can also make the Indian stock market resilient amidst global uncertainties.

The authors illustrate how a firm can face the challenge of forecasting consumer reaction for a really-new product. For the case of an electric vehicle, the authors describe how one firm combines managerial judgment and stateof-the-art market measurement to determine whether (1) the really-new product would be a viable business venture at its target launch date, (2) the firm should plan for improvements in technology that would reduce price and/or increase benefits enough so that the business venture would be profitable, or (3) the firm should stop development. The new market measurement system combines existing methods with a multimedia virtual-buying environment that conditions respondents for future situations, simulates user experience, and encourages consumers to actively search for information on the product. The authors comment on the advantages and disadvantages of the methodology and summarize the lessons they have learned from this application. N ew product development has been and will continue to be important to corporate profit and social welfare. For firms, and even countries, to stay competitive they must maintain a stream of profitable new products. Some of these new products are new variants-new flavors of cereals, the next generation laser printers, or the next model-year minivan. Other products are new brands in existing markets-a new brand of cereal, a combined laserbased printer-scanner-facsimile-copier, or a new brand (e.g., Lexus) of luxury automobile. In general, market researchers can forecast the potential sales of new variants and new brands well. However, some products revolutionize product categories or define new categories. Hewlett-Packard's Laserjet printers, Apple's (then IBM) personal computers, Sony's Walkman, beta-blockers (i.e., hypertension medicine), Visicalc (then Lotus, Quattro, and Excel) spreadsheets, Black & Decker's Dustbuster, Swatch (i.e., watch-as-fashion), and cellular telephones are really-new products. Really-new products shift market structures, represent new technologies, require consumer learning, and induce behavior changes. Forecasts must consider the diffusion of information, the evolution of the technology, the discovery of new uses, the reduction in price from high initial levels, the growth of an infrastructure, and the entry of competition. Forecasts can be made and are made, often with a judgmen-

In this paper stock market development as proxied by market capitalisation is examined. The study period is January 2010 to May 2019. The data frequency is monthly. The paper concentrates on the Zimbabwe Stock Market, but briefly walks through Stock Markets in Africa. Examining stock market development is critical, as evidenced by growing number of debates on the dual link of economic growth and stock market development. The study applied the ARIMA model to examine the predictability of stock market development. Using the selection criteria for forecasting, two models have been found to be efficient, ARIMA (7, 1, 2) and ARIMA (12, 1, 2). Both models indicated the significance of past values of market capitalisation to determine current and future values. This implies that a previous level of stock market development determines the future levels of development. Forecasted values indicated a positive fluctuating growth in the near future. The study recommends policies that should aim ...

This paper applies the mildly explosive/multiple bubbles testing methodology developed by Phillips, Shi and Yu (2013, Cowles Foundation Discussion Paper Nos. 1914 and 1915) to examine the recent time series behaviour of London Metal Exchange (LME) non-ferrous metals futures prices. The methodology allows for consistent date-stamping of the origination and collapse of bubbles. We find bubbles in all non-ferrous metals apart from aluminium. The bubble dates differ across the other five metals but fall into four distinct groups that can be related to the behaviour of fundamentals that economic theory suggests underlie them. This offers support for the efficacy of the PSY test if metals prices are primarily driven by fundamentals.

In the second chapter 2, Gökçe and Kızılkaya discuss unemployment hysteresis in selected OECD countries. According to results of panel stationary test, the hypothesis of unemployment hysteria is invalid for the panel. In addition, when the results of the individual unit root tests for each country are examined, unemployment hysteria is not valid for Austria,

We establish the strong consistency and the asymptotic normality of the variance-targeting estimator (VTE) of the parameters of the multivariate CCC-GARCH(p, q) processes. This method alleviates the numerical difficulties encountered in the maximization of the quasi likelihood by using an estimator of the unconditional variance. It is shown that the distribution of the VTE can be consistently estimated by a simple residual bootstrap technique. We also use the VTE for testing the model adequacy. A test statistic in the spirit of the score test is constructed, and its asymptotic properties are derived under the null assumption that the model is well specified. An extension of the VT method to asymmetric CCC-GARCH models incorporating leverage effects is studied. Numerical illustrations are provided and an empirical application based on daily exchange rates is proposed.

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.