Volatility

DESCRIPTION Prior research finds a weak relation between cash-flow volatility and leverage. Using a novel measure of cash-flow volatility, we find that volatility matters more for firms that are financially constrained. Constrained firms issue debt when volatility is low, but have trouble deleveraging in response to increases in volatility. Constrained firms also hoard the proceeds from debt issues undertaken during low-volatility regimes, but invest the proceeds from debt issues when volatility is high. Overall, the observed relation between cash-flow volatility and capital structure choice is driven by financially constrained firms’ desire to ensure future financial flexibility.

This paper investigates which events of World War II (WWII) the US investors (at that time) considered as turning points (structural breaks) of the war. The empirical study employs daily Dow Jones industrial average stock index and volatility from January 1939 to December 1945 and applies structural shift oriented test to determine endogenously the structural breaks during the WWII period. Results show that the majority of the wartime events (on and off the battlefield) labelled important by historians did result in structural breaks in both price movement and stock returns volatility (risk). These results have major implications for investors of the present and future. 1 Tsiakas is able to show that events during trading and non-trading hours both have substantial effect on both stock price and volatility. During wartime, events can take place during trading and non-trading hours. 2 According to Mazouz et al. (2009) investors under-react to both positive and negative shocks, irrespective of the magnitude of the shocks.

With the emergence of the World Wide Web, analyzing and improving Web communication has become essential to adapt the Web content to the visitors’ expectations. Web communication analysis is traditionally performed by Web analytics software, which produce long lists of page-based audience metrics. These results suffer from page synonymy, page polysemy, page temporality, and page volatility. In addition, the metrics contain little semantics and are too detailed to be exploited by organization managers and chief editors, who need summarized and conceptual information to take high-level decisions. To obtain such metrics, we propose to classify the Web site pages into categories representing the Web site topics and to aggregate the page hits accordingly. In this paper, we show how to compute and visualize these metrics using OLAP tools. To solve the page-temporality issue, we propose to classify the versions of the pages using automatic classifiers.

An identical two-sector productivity shock causes Rybczynski (1955) and Stolper and Samuelson (1941) effects that release leisure time and initially raise the relative price of human capital investment so as to favor it over goods production. Modified by having the household sector produce human capital investment sector, the RBC model follows the international approach of Maffezzoli (2000) and so adds a second sector relative to Jones et al. (2005). This captures key major US RBC data: output growth persistence, with hump-shaped impulse responses; hump-shaped physical capital investment impulse responses; Gali's (1999) negative impulse response of labour supply; and hours volatility.

OBJECTIVES
This research aimed to verify the performance of the Volatility Timing (VT) and Reward to Risk Timing (RRT) models of portfolio selection when compared with the Naïve and Mean-Variance ones, applied to the Brazilian stock market.
METHODOLOGY
The methodology consists in applying the VT, RRT, Naïve and the Mean-Variance portfolio strategies, considering different tuning levels of rebalancing portfolios. The assets employed in the analysis were those included in the Ibovespa Index in the period from January of 2004 through December of 2014. We used statistical and financial indicators to measure the performance of the strategies, and measure its turnover and transaction costs.
RESULTS AND CONCLUSIONS
It was possible to compare strategies against the Minimum Variance (Wvm) portfolio, the Ibovespa (Ibov) and the Naïve portfolios. The Ibov and Naïve presented the lowest portfolios returns. In the other the hand the Wvm, VT and RRT, with high investors aggressiveness in favor to less volatile assets (η=4), had the highest performance (monthly Sharpe Index 6.6%, 5.98% and 5.08%, respectively). In addition, the VT4 and the Wvm portfolios consistently preserved a low turnover. However, the RRT portfolios present-ed high turnover. Analyzed by sub-periods, the results pointed out that the best choice of portfolio de-pends upon the Brazilian economic scenario. During the first sub period RRTbm4 had the best results with 45.65% annualized return and a 223.7% Sharpe Ratio. In the second sub period the RRTk4 featured with a 21.33% annualized return and a Sharpe Ratio of 62.33%. In the last sub period, however, no strat-egies presented positive returns or Sharpe Ratios.
PRACTICAL ISSUES
This research evidenced that the best choice of portfolio strategies depends upon the economic setting that the Brazilian market is undergoing, because some of the strategies had better results in specific peri-ods. However, in most cases, portfolios that give more weights to less volatile assets, such as minimum variance, and volatility timing and reward to risk timing with η=4, would produce better performance (Sharpe Ratio) without significant increase in transaction costs.
KEY WORDS
Portfolio selection, Volatility Timing, Reward to Risk Timing.

Citation
IQUIAPAZA, R.A.; VAZ, G. F. C.; BORGES, S. L. A Avaliação de Portfólio de Estratégias de Investimento de Timing de Volatilidade e Timing de
Recompensa ao Risco: O Caso Brasileiro. Revista de Finanças Aplicadas. V. 7, n.2, 2016. pp.1-19.

Saunders (1993) and Hirshleifer and Shumway (2001) document the effect of weather on stock returns. The proposed explanation in both papers is that investor mood affects cognitive processes and trading decisions. In this paper, we use a database of individual investor accounts to examine the weather effects on traders. Our analysis of the trading activity in five major U.S. cities over a six-year period finds vistually no difference in individuals propensity to buy or sell equities on cloudy days as opposed to sunny days. If the association between cloud cover and stock returns documented for New York and other world cities is indeed caused by investor mood swings, our findings suggest that researchers should focus on the attitudes of market-makers, news providers or other agents physically located in the city hosting the exchange. NYSE spreads widen on cloudy days. When we control for this, the significance of the weather effect is dramatically reduced. We interpret this as evidence that the behavior of market-makers, rather than individual investors, may be responsible for the relation between returns and weather.

Information affects stock prices, even if it is not truthful. The news piped through the business press may contain deliberately planted misinformation. This study examines the effect of erroneous news and analysis by a leading daily newspaper on the performance of stock returns in the Dhaka Stock Exchange in Bangladesh. The reaction to the false news involves an unsustained jump in stock prices under misguided optimism. We also investigate the scope of legal remedies against false news and stock price manipulation. The responsibility and accountability of the media involved in spreading misinformation is also an issue

Opening ceremony Romanian local public finance decentralization Tatiana Moşteanu, Carmen Maria Lăcătuş / 13 The domestic economic policy -from macroeconomic influences to strengthening the competitive equity Ioan Cuzman, Daniel Manaţe, Pavel Fărcaş / 20 The performance of romanian open-end funds and the crisis context Carmen Corduneanu, Daniela Ţurcaş / 26 Financial crime and the securization of banking circuits in order to prevent and fight against money laundering Ion Stancu, Daniel Rece, Filip Iorgulescu / 34

Forecasting the volatility of financial markets is one of the important issues in empirical finance that absorbed the interest of many researchers in the last decade. As it is known, there has been many studies uncovering the properties of competing volatility models. In this study, both traditional (unconditional) and conditional volatility models, which have the implications for finance that investors can predict the risk, are analyzed. In this study, Box-Jenkins model (ARIMA) and ARCH-type models (ARCH-GARCH-EGARCH-TARCH and GARCH-M) are discussed for the time–dependence in variance that is regularly observed in financial time series and various classical volatility forecasting approaches are compared using ISE-100 Stock Index for the time period between the years 1987 and 2009. As a result, it is found that IMKB-100 returns series include; leptokurtosis, leverage effects, volatility clustering (or pooling), volatility smile and long memory and TGARCH (1,1) is the best fitting mo...

This paper investigates the consequences of stochastic volatility for pricing spot foreign currency options. A diffusion model for exchange rates with stochastic volatility is proposed and estimated. The parameter estimates are then used to price foreign currency options and the predictions are compared to observed market prices. We find that allowing volatility to be stochastic results in a much better fit to the empirical distribution of the Canada-U.S. exchange rate, and that this improvement in fit results in more accurate predictions of observed option prices.

In this study, we test whether the overconfidence bias explains several stylized market anomalous, including a short-term continuation (momentum), a long-term reversal in stock returns, high levels of trading volume and excessive volatility. Using data of French stocks market, we find empirical evidence in support of overconfidence hypothesis. First, based on a restricted VAR framework, we show that overconfident investors overreact to private information and underreact to public information. Second, by performing Granger-causality tests of stock returns and trading volume, we find that overconfident investors trade more aggressively in periods subsequent to market gains. Third, based on a two GARCH specifications, we show that self attribution bias, conditioned by right forecasts, increases investors overconfidence and trading volume. Fourth, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a contribution to the observed excessive volatility.

Volatility in the stock return is an integral part of stock market with the alternating bull and bear phases. In the bullish market, the share prices soar high and in the bearish market share prices fall down and these ups and downs determine the return and volatility of the stock market. Volatility is a symptom of a highly liquid stock market. Volatility of returns in financial markets can be a major stumbling block for attracting investment. In this study, we use the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to model volatility. The analysis was done using a time series data for the period 1st January 2008 to I0th April 2012 on 18 banks in India and empirical findings revealed that all banks stock return series reports an evidence of time varying volatility which exhibits clustering and high persistence.

This paper examines the effects of time to maturity, volume and open interest on the price volatility of futures contracts in Turkish derivative markets. The determinant of volatility is tested using conditional variance models during the period from January 2, 2008 to June 30, 2015. The sample set consists of 457 futures contracts backed by gold, currency, indices and single stocks. Empirical results show that the time to maturity, volume and open interest significantly impact the volatility of futures contracts. It is found that as the maturity date approaches, volatility increases. Furthermore, a positive correlation is found between the price volatility of futures contracts and volume, whereas volatility and open interest are found to correlate negatively. Thus, both the Samuelson Hypothesis and the Mixture of Distributions Hypothesis are supported in Turkish derivative markets.

The study aimed to explore the impact of investment decision making on financial performance of the textile industry from managers perceptions. The Indian textile industry is the second largest industry in the world, after China. After agriculture, textiles play a major role in the country’s economy, in terms of exports. Textile is providing the second-highest employment opportunities in India. Tamil Nadu is also making the highest contribution in the total domestic production, consumption and exports, after Maharashtra, Haryana and Gujarat. As is well-known, the Indian economy had faced the crunch due to the impact of meltdown on exchange rate volatility, interest rate changes, raw material cost fluctuation, import restrictions, demand for export, worker’s shortage and competitive products with modern innovations. Researchers concentrated only on the factors impacting investment decision in the textile industry and found the different perception among the finance manager and CEO using Independent sample test.

Discounted cash flow is the main tool for valuing projects and companies. Real options techniques can augment valuation. The case of Netscape is used to demonstrate this. We begin with a defensive cash flow scenario. On top of this, we superimpose a number of real options valuations. Some experts would dispute our methodology because it is not built upon market-priced risk. Nonetheless, it provides an approximate valuation. We prefer equity valuation using various methodologies, including real options where appropriate, to arrive at a range of value. But we cannot, using financial logic, justify the high Netscape flotation price. 

The aim of this paper was to accurately and efficiently forecast from multivariate generalized autoregressive conditional heteroscedastic models. The Rotated Dynamic Conditional Correlation (RDCC) model with the Normal, Student’s-t and Multivariate Exponential Power distributions for errors were used to account for heavy tails commonly observed in financial time series data. The daily stock price data of Karachi, Bombay, Kuala Lumpur and Singapore stock exchanges from January 2008 to December 2017 were used. The predictive capability of RDCC models, with various error distributions, in forecasting one-day-ahead Value-at-Risk (VaR) was assessed by several back-testing procedures. The empirical results of the study revealed that the RDCC model with Student’s-t distribution produced more accurate and reliable risk forecasts than other competing models. To cite this article [Farid, S. & Iqbal, F. (2020). Forecasting Value-at-Risk of Asian Stock Markets Using the RDCC-GARCH Model Under D...

The purpose of this project is to construct an investment portfolio including 10 O&G equity instruments by minimising the risks in form of volatility and VaR. We shall namely collect historical share price data for 5 years in order to illustrate our points. Various techniques such as scenario and Monte Carlo simulations are going to be used in order to verify our hypotheses with respect to risk projections. In addition to that, we reference to different sources including books and scientific articles in order to define various theoretical concepts which are necessary for our analysis. Papers illustrating various econometric and statistical concepts provide the theoretical basis for the essay. Statistical sources include Yahoo! Finance and Statista.

This study examines the performance of the S & P 100 implied volatility as a forecast of future stock market volatility. The results indicate that the implied volatility is an upward biased forecast, but also that it contains relevant information regarding future volatility. The implied volatility dominates the historical volatility rate in terms of ex ante forecasting power, and its forecast error is orthogonal to parameters frequently linked to conditional volatility, including those employed in various ARCH specifications. These findings suggest that a linear model which corrects for the implied volatility's bias can provide a useful market-based estimator of conditional volatility. q 1998 Elsevier Science B.V. All rights reserved. JEL classification: G12; G13

The primary objective of present study is to examine the impact of merger and acquisition announcements during 2000–2018 on stock returns and intraday volatility of banks listed on National Stock Exchange in India. The sample of 383 mergers and acquisitions events has been analyzed with the help of event study methodology. Findings suggest that consolidation in Indian banking sector leads to positive average abnormal returns and wealth creation for acquirer bank’s shareholders. These findings are in agreement with Onikoyi et al. (2014), Kumar et al. (2011), and Anand and Singh (2008), and contrary to the evidence provided by Sim (2015), Asimakopoulos and Athanasoglou (2012), and Cybo-Ottone and Murgia, (2000). Further, results show that merger and acquisition in banking sector lead to curvy jumps in volatility around announcement date, which implies that disclosure of restructuring events in the banking sector affects return variability. These results confirm the observations by Pessanha et al. (2016), Kamau (2016), and Louhichi (2008).

Introduzione Questo è il primo di una collana di papers che pubblicherò nei prossimi mesi sulla volatilità. Ha un carattere introduttivo, con lo scopo di avvicinare ad uno studio quantitativo gli operatori che hanno a che fare quotinianamente con la volatilità, ma che utilizzano, nell'analisi dei mercati finanziari e in particolare del rischio, approcci tecnici, fondamentali o addirittura discrezionali. Lo scopo principale è quello di promuovere, tra gli operatori sui mercati finanziari e gli analisti, una conoscenza approfondita delle dinamiche relative alla volatilità, sia per quanto riguarda il pricing di strumenti finanziari come le opzioni, sia per quanto riguarda il risk management, argomento di particolare interesse soprattutto dopo la crisi del 2008. Nelle pagine seguenti ci occuperemo della la stima della volatilità con metodi statistici. Successivamente andremo ad approfondire sia le basi teoriche stanno alla base di questa categoria, in senso ampio, di modelli. Inoltre, vedremo le implicazoni dell'utilizzo di queste metodologie in termini di analisi del comportamento degli asset finanziari e la componente previsionale dei modelli. Analizzeremo anche metologie più complesse ed innovative, valutandone il valore aggiunto rispetto ai modelli presentati nelle pagine seguenti, che agiscono da benchmark, fino all'implementazione di diversi modelli operativi, della stessa famiglia di quelli da noi utilizzati. Vedremo, in seguito, anche un'altra categoria di modelli di volatilità che si riferiscono ad analisi stocastica. In questo primo contributo, la matematica è più semplice possibile, con continui riferimenti dalle formule al loro significato e alla loro applicazione concreta. Troppi utenti, appena vedono formule, tendono ad allontanarsi temendo un'estrema complicazione. Al contrario, gran parte della finanza quantitativa è relativamente semplice sotto un profilo matematico, una volta digerite le basi e presa dimestichezza col linguaggio. Andremo ad analizzare ed implementare in Excel e MC.NET divversi modelli univariati per la stima e previsione della volatilità realizzata. Lo scopo è quello di fornire immediatamente strumenti analitici

In this paper, we investigate the price interdependence between seven international stock markets, namely Irish, UK, Portuguese, US, Brazilian, Japanese and Hong Kong, using a new testing method, based on the wavelet transform to reconstruct the data series, as suggested by Lee [11]. We find evidence of intra-European (Irish, UK and Portuguese) market co-movements with the US market also weakly influencing the Irish market. We also find co-movement between the US and Brazilian markets and similar intra-Asian co-movements (Japanese and Hong Kong). Finally, we conclude that the circle of impact is that of the European markets (Irish, UK and Portuguese) on both American markets (US and Brazilian), with these in turn impacting on the Asian markets (Japanese and Hong Kong) which in turn influence the European markets. In summary, we find evidence for intra-continental relationships and an increase in importance of international spillover effects since the mid 1990s, while the importance ...

Yüksek volatilite dönemlerinde hisse senedi yatırımı yapmak, volatilitenin nispeten düşük olduğu dönemlere göre yatırımcılar açısından daha zor olmaktadır. Bu dönemlerde, piyasaların etkinlik seviyeleri azalış göstermekte ve yatırımcıların asimetrik bilgilere maruz kalmaları daha fazla söz konusu olmaktadır. Bu nedenle, gerek hisse senedi seçimi yapılırken gerekse seçilen hisse senetleri ile portföy oluştururken birtakım modem yaklaşımlara sahip modellere oldukça ihtiyaç duyulmaktadır.

Bu çalışmada, yüksek volatilitenin hakim olduğu 2008 Küresel Finansal Krizi döneminde, Gri Sistem Teorisi Destekli Markowitz Portföy Optimizasyonu yapılmıştır. Böylece belirsizliklerin hakim olduğu bu dönemde yatırımcıların karar verme süreçlerinde kullanabilecekleri bir modelin geliştirilmesi amaçlanmıştır. Ayrıca geliştirilen bu modelin oluşturulan Melez Portföyler ve Geleneksel Portföyler ile performans karşılaştırmaları yapılmıştır. Çalışm anın sonuçları, geliştirilen modem yaklaşıma sahip modellerin, yüksek volatilite dönemleri için kullanılabilir olduğu ve başarılı performansı gösterebildiği ortaya konulmuştur.

This paper revisits the volume-volatility relationship documented in in a bull versus a bear market by using data from the period surrounding the subprime crisis in 2008. The relationship is predicted to be asymmetric because of the greater cost of short positions, the lack of liquidity and the differing trading strategies adopted in a bearish market. Our analysis shows the trading patterns in the bull and bear markets are different. Particularly, in a falling market characterised by higher volatility and lower liquidity, the frequency of order placement has doubled but orders are smaller in size. This provides evidence of investors' shift of trading strategy in relation to the status change of the market. Furthermore, we find evidence to support the proposition that volume is more informative in a bear market than in a bull market.

A business incurs much higher charges when attempting to win new customers than to retain existing ones. As a result, much research has been invested into new ways of identifying those customers who have a high risk of churning. However customer retention efforts have also been costing organisations large amounts of resource. In response to these issues, the next generation of churn management should focus on accuracy. A variety of churn management techniques have been developed as a response to the above requirements. The focus of this paper is to review some of the most popular technologies that have been identified in the literature for the development of a customer churn management platform. The advantages and disadvantages of the identified technologies are discussed, and a discussion on the future research directions is offered.

The purpose of this project paper is to report the implementation of some of the in class presented statistical models and forecasting procedures. We started with the idea of employing an autoregressive conditional heteroscedasticity (ARCH) model for the analysis of stock return data and generate forecasts of the volatility of this high-frequency financial data series. In the following we present the underlying model, provide tests for model selection, compute the selected model and conduct forecasts.

This paper analyzes the effect of leverage financing on corporate performance using debt-equity, coverage ratios and earnings per share as proxies. The study is motivated by need to assess the extent to which leverage affects optimizes financing risk as well as maximize returns to shareholders in the Nigerian banking industry. The study made use of F-ratios, Durbin-Watson, Akaikeand Schwarz Information Criteria as well as to log likelihood parameters in arriving at conclusions. Though the results across banks studied shows mixed outcome, leverage financing was established as critical strategy for maximization of shareholders returns. The conclusion therefore is that in order to ensure that leverage financing leads to desired outcome business organisations must established their optimum level as well as strike a strategic balance with associated financing risk and returns to owners of the firm.

Allocations of wealth across different asset classes and specific investments have become a challenging task for the investors, portfolio managers and fund managers. Essentially, investors participate in financial markets over time in order to share and diversify various risks, which arise in their investment decisions. Investors use financial markets not only to share risk but to make risk-return trade-off in a better way. Mutual funds help the investors make optimal trading strategies economically feasible to mitigate the risk and optimise the return. The performance of mutual funds that depends on volatility of the market and macro economy will play a pervasive role in deciding the fate of investment decisions of investors a lot. The present paper is a modest attempt to discuss on the performance of benchmark mutual funds in India through a select Equity, Debt and Balanced Growth Fund.

The purpose of this paper is to measure whether the investor operating on the Casablanca Stock Exchange displays a behavior of overconfidence, and to examine, under this hypothesis, the role of overconfidence in the explanation of fluctuations in the value of the MASI benchmark index over a 16-year period from 2002 to 2017. Using the econometric techniques in terms of causality and conditional volatility modeling, the results of this research show the presence of the overconfidence behavior and the positive effect of the latter on the conditional volatility of the monthly return of the MASI index.

The study aims to extend the GARCH type volatility models to their nonlinear TAR (Tong, 1990) and STAR-based (Terasvirta, 1994) counter parts where both the conditional mean and the conditional variance processes follow TAR and STAR nonlinearity. The paper further investigates the models under their fractional integration and asymmetric power variants. The STAR-based models are LSTARLST- GARCH, LSTAR-LST-FIGARCH, LSTAR-LST-FIPGARCH and LSTAR-LSTFIAPGARCH models, which may be easily applied to model and forecast various financial time series. In the empirical section, an application is provided to model the daily returns in WTI crude oil prices considering the regime shifts the crude oil prices were subject to during history. Models are evaluated in terms of their out-of-sample forecasting capabilities with equal forecast accuracy tests and also in terms of various error criteria. The results suggest that volatility clustering, asymmetry and nonlinearity characteristics are modeled m...

In the first years after the emergence of deregulated power markets it became apparent that for the valuation of electricity derivatives we cannot simply rely on models developed for financial or other commodity markets. However, before adequate models can be put forward the unique characteristics of electricity (spot) prices have to be thoroughly analyzed. In particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of returns. In this paper we first analyze the stylized facts of electricity prices, then present two modeling approaches: jump-diffusion and regime-switching, which to some extent address the pertinent issues.

El presente Trabajo Fin de Master plantea como objetivo la aplicación práctica del modelo GARCH y distribuciones de colas anchas en el cálculo del riesgo de mercado, mediante metodología VeR Paramétrica, en una cartera de renta variable en el periodo de 1/1/2014 al 31/12/2018 para los principales títulos del sector bancario y financiero que cotizan en el mercado bursátil español y que pertenecen al IBEX-35. Se escogen los valores cotizados de Santander, BBVA, CaixaBank, Sabadell y Bankia. Se realiza metodología empírica mediante técnicas matemáticas, estadísticas y econométricas. Se comparan resultados obtenidos entre distribución normal y distribución T-Student (colas anchas), y según la forma de cálculo de la volatilidad (Estándar o GARCH). Finalmente se realiza el Backtesting en el periodo de 1/1/2019 al 30/6/2019 para los resultados de la cartera y se establecen las conclusiones finales del estudio.

Özet Psikoterapist-danışan ilişkisi, farklı kuramsal yaklaşımlarla şekillenen, bireysel ve kişilerarası dinamikler üzerine inşa edilen karmaşık bir ilişkidir. Bu ilişki, danışan rolündeki kişinin afektif kırılganlığının ve yaralanabilirliğinin davet edildiği bir ilişkidir. Bu nedenle terapi ilişkisi içerisinde terapistin gücünü kötüye kullandığı her edim terapi odasının dışındaki kötüye kullanımlardan daha şiddetlidir. Mesleki örgütlerin belirledikleri etik ilke ve kurallar, bu asimetrik ilişkide mağduriyet yaşaması mümkün olan danışan için koruyucudur ve danışanın zarar görmesini, istismar edilmesini ya da danışandan haksız kazanç elde edilmesini engellemeyi hedefler. Ancak etik ilke ve kuralların varlığı etik ihlallerin yapılmadığı anlamına gelmemektedir. Psikoterapistin danışanını cinsel tacizi büyük bir sorun olsa da psikoterapi ilişkisinin niteliğinden dolayı rapor etme yükünü danışana yüklenmesi sorunun boyutunu anlamayı güçleştirmektedir. Taciz yasal düzleme taşındığında da psikoterapistin danışana cinsel saldırısı diğer cinsel saldırı vakalarına benzer bir perspektifle ele alınır. Psikoterapi disiplini, kırılganlık ve güç dinamiklerinin yol açtığı zarar verebilirlikle henüz tam olarak yüzleşmemiştir. Bu yüzleşmenin gerçekleşmesi için konuşulmayanı konuşmak, psikoterapiden hayatta kalanların örgütlülüğüne destek olmak ve meslek örgütlerini "aile" kurumları olmaktan çıkarmak gerekmektedir. Abstract The psychotherapist-client relationship is a complex relationship shaped by various theoretical approaches and built on individual and interpersonal dynamics. The person in the role of the client is invited to be fragile and vulnerable in this relationship. Therefore, any act in which the therapist abuses their power is more violent than abuses of power outside of the therapeutic relationship. Professional organizations aim to protect the client from harm and prevent the client being maltreated, abused or taken advantage of, by setting ethical principles and rules. The existence of such principles and rules, however, does not mean that ethical violations do not take place. Psychotherapists' sexual harassment of clients is a significant problem obscured by encumbering the client with the burden to report due to the nature of the therapeutic relationship. In the legal realm, psychotherapist's sexual attack is treated similarly to other sexual attack cases. Psychotherapy, as a discipline, is yet to recognize the capacity to harm generated by the fragility and power dynamics. In order for this recognition to occur, the unspoken has to be spoken, the organization efforts of survivors of psychotherapy should be supported, and professional organizations must cease to be 'family organizations'.

This master's thesis compares and identifies the advantages and disadvantages of methods for forecasting volatility in precious metals markets. The objectives of the thesis include reviewing risk definitions and synthesis of risk breakdowns, describing the stages of risk management, reviewing risk measures used in finance, reviewing concepts and models using measures of volatility, reviewing volatility forecasting methods, conducting a fundamental analysis of precious metals markets, presenting research results on volatility forecasting using selected methods, and possibly selecting one or more of the most effective volatility forecasting methods. The thesis' main contribution is a comparison and analysis of volatility forecasting methods for precious metals markets.

Modeling is important because scientists investigate the world around us by building models that simulate real-world problems. Modeling is neither science nor mathematics; it is the
craft that builds bridges between the two. Progress in modeling dynamics has always been closely associated with advances in computing. Monte Carlo simulation/modeling or probability simulation is a technique frequently used in the financial markets to understand complex financial instruments. It is used to scrutinise the impact of risk and uncertainty in
financial and other forecasting models. It is very useful when complex financial instruments need to be priced. Exotic options are listed on the JSE on its Can-Do platform. Most listed exotic options are marked-to-model and the JSE needs accurate values at the end of every day. Monte Carlo methods in a local volatility framework are implemented. This paper discusses how Monte Carlo (MC) simulation is implemented when exotic options like Barriers are valued. We further summarise the historical development in modern computing and the development of the Monte Carlo method.

The U.S. pharmaceutical industry consumes almost $1 billion in energy annually. Energy efficiency improvement is an important way to reduce these costs and to increase predictable earnings, especially in times of high energy price volatility. There are a variety of opportunities available at individual plants in the U.S. pharmaceutical industry to reduce energy consumption in a cost-effective manner. This Energy Guide discusses energy efficiency practices and energy efficient technologies that can be implemented at the component, process, system, and organizational levels. A discussion of the trends, structure, and energy consumption characteristics of the U.S. pharmaceutical industry is provided along with a description of the major process steps in the pharmaceutical manufacturing process. Expected savings in energy and energy-related costs are given for many energy efficiency measures, based on case study data from real-world applications in pharmaceutical and related facilities worldwide. Typical measure payback periods and references to further information in the technical literature are also provided, when available. The information in this Energy Guide is intended to help energy and plant managers reduce energy consumption in a cost-effective manner while meeting regulatory requirements and maintaining the quality of products manufactured. At individual plants, further research on the economics of the measures-as well as their applicability to different production practices-is needed to assess potential implementation of selected technologies.