FM - Economics & Finance

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Browsing FM - Economics & Finance by Author "Ermiș, Simona Ioana"

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    Financial market interconnections analyzed using GARCH univariate and multivariate models
    (Bucharest University of Economic Studies , 2022) Anghel, Lucian Claudiu; Zwak Cantoriu, Maria Cristina; Mendon, Suhan; Attila, Gyorgy; Ermiș, Simona Ioana; Trivedi, Jatin
    Given that the financial markets are facing the effects of the coronavirus pandemic, we chose to perform an analysis on them, in order to see the transmission of volatility, the effects of the contagion and the interconnection between the financial markets. Using stock indices from different countries and applying theoretical and empirical methods such as univariate and multivariate models (ARCH–GARCH, BEKK), we aim to capture volatility and bidirectional contagion, as well as testing and occurring the phenomenon of clustering volatility and its transmission effect.
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    The impact of disturbances on the US stock market’s spread and investor sentiment through the perspective of risk management
    (Faculty of Management (SNSPA), 2023-03-21) Zwak Cantoriu, Maria Cristina; Anghel, Lucian Claudiu; Ermiș, Simona Ioana
    The paper aims to address a topic of interest, namely: the influence and effect of the major disruptions from recent years on one of the largest important stock markets. The purpose of the paper is to show the influence of these disruptions on the US stock market, considering market efficiency and measuring the estimated Bid-Ask spread. Using daily and weekly data sets over a period of 13 years, based on the closing stock prices of 10 companies listed in the category of the NASDAQ and NYSE stock indexes and calculating the return at (t) and (t+1) for each stock, the covariance of the two returns at (t) and (t+1) and using at t and (t+1) a "rolling window" of 21 days, which represents the trading days, as well as using the weekly data series in the same way, we obtained the relationship between the spread measurement and its size, a strong negative cross-sectional relationship, for which we performed a series of statistical tests summarized in the paper. Later, we split the data for each year separately so that we’d be able to use for each year a cross-sectional regression of the spread over the logarithmic values of the size and we noticed that there is a strong negative relationship between the two of them. According to the results obtained, it can be observed that the strongest negative correlations are in 2019and 2021 in the case of data with daily frequency and 2020, and 2021 in the case of data with weekly frequency, for an informationally efficient market, where transaction costs are zero and in which the market price contains all the relevant information. The strongly negative correlations recorded can be explained by the fact that strong negative influences took place during these periods, which contributed to the disruption of the stock market and not only. At the same time, these negative correlations on the stock market analyzed in the last period also show a wider spread increase which theoretically shows low liquidity.
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    Market risk management : modelling the distribution of losses using Romanian securities
    (MDKE. Faculty of Management (SNSPA), 2021-10-20) Zwak Cantoriu, Maria Cristina; Anghel, Lucian Claudiu; Ermiș, Simona Ioana
    Market risk with its major components, such as the risk of interest rate instruments, currency risk, and risk related to stock and commodity investigations, represents the risk of losses in balance sheet and off-balance sheet positions, resulting from negative market price movements. Portfolios of instruments traded for short-term profits, called trading portfolios, are exposed to market risk or risk of loss, resulting from changes in the prices of instruments, such as stocks, bonds, and currencies. This paper, through theoretical and empirical methods, assesses risk by using the probability distribution of daily variations in government bond yields. Long-term government securities in most cases have a higher return due to the higher level of risk assumed regarding changes in risk factors such as interest rates, which, when raised above a certain threshold, cause a price decrease, which illustrates the price sensitivity to long-term bonds. Using Value at Risk as the main element for determining the maximum possible loss on investment in a trading book, as well as statistical tests to measure the similarity between two or more distributions such as the KolmogorovSmirnov test, Anderson -Darling or Chi-squared, we identified the most representative theoretical probabilistic distribution both for the value of losses and for the frequency of risk events. At the same time, the most used distributions to manage the market risk by advanced methods and, of course, the distributions used in this paper, were Weibull and Pareto (including the generalized form), as well as other distributions, because they better capture the asymmetry in queues and the presence of thick tails. Modeling the distribution of losses requires choosing from a set of probable distributions, the one with the highest log-likelihood.