scholarly journals A brief overview of the types of ETFs

10.26458/1534 ◽  
2015 ◽  
Vol 15 (3) ◽  
pp. 39
Author(s):  
Elitsa PETROVA
Keyword(s):  
Scientific Literature ◽  
Stock Exchange ◽  
Stock Index ◽  
Financial Asset ◽  
Exchange Traded Funds ◽  
Financial Assets ◽  
Literature Study ◽  
Currency Exchange ◽  
Different Types ◽  
Exchange Traded Fund

 Exchange-traded fund is a type of exchange-traded product. ETF is a fund that is traded as a typical financial asset. Just like an index fund, ETF represents a basket of assets that reflect popular stock index. ETF traded just like any other company on the stock exchange. By owning ETF investor receives two important advantages – the diversification of index fund plus the flexibility of trading financial assets. There are different types of ETFs. Mainly divided into index, commodity, bond, currency, exchange-traded trusts and leveraged exchange-traded funds. The article discusses the basics of exchange-traded fund, does a brief history review on the emergence of exchange-traded funds, and provides information on the basic and specific types of exchange-traded funds.The used scientific tools include:study of scientific literature;study the performance of different markets which operate with exchange-traded funds;meaningful analysis and summary of theoretical and practical applied information.  

An Assessment of Impact of Domestic Price of Gold on NAV of Selected Gold Exchange Traded Funds

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Shefali Sinha ◽  
Dr. Mahua Dutta
Keyword(s):  
Standard Deviation ◽  
Mutual Fund ◽  
Research Study ◽  
Stock Exchange ◽  
Arithmetic Mean ◽  
Exchange Traded Funds ◽  
Statistical Calculation ◽  
Domestic Price ◽  
Exchange Traded Fund ◽  
The Impact

Study undertaken assesses the impact of behavior of domestic price of gold on selected gold exchange traded funds which were launched in the year 2010 at National Stock Exchange. The selected gold exchange traded funds constitute HDFC Gold Exchange Traded Fund, ICICI Prudential Gold Exchange Traded Fund and Religare Gold Exchange Traded Fund. Since, the investment objective of every selected scheme under research study is directly related to the domestic price of gold. So, the daily fluctuations of domestic price of gold are taken into account for assessing the impact on NAV prices of selected gold exchange traded funds. The study is aimed to meet objectives of (a) identifying whether NAV of all the selected three funds under research study is dependent upon Domestic Price of Gold. (b) Identifying in which respects NAV of the selected gold exchange traded funds differ from each other. Statistical calculation involves calculating arithmetic mean, standard deviation and standard error. The method for interpretation of data is application of Z-test that will assess the validity in results. This study helps investors to get a detailed insight in what respects NAV gets dependent upon domestic price of gold and the differentiating factors that differs NAV of the selected three Gold ETF mutual fund schemes under research study. This will prompt the investors to check the differentiating parameters of NAV while selecting the mutual fund house for investing in Gold ETF.

scholarly journals A challenge to triumphant optimists? A blue chips index for the Paris stock exchange, 1854–2007

2010 ◽  
Vol 17 (2) ◽  
pp. 141-183 ◽  
Author(s):  
David Le Bris ◽  
Pierre-Cyrille Hautcœur
Keyword(s):  
Economic History ◽  
Stock Exchange ◽  
Equity Premium ◽  
Stock Index ◽  
Financial Asset ◽  
Positive Real ◽  
Stock Indices ◽  
Long Run ◽  
The Us ◽  
Real Performance

We have reconstructed a new blue chips (large caps) stock index for France from 1854 to 1998, based on a modern methodology. Our index differs profoundly from earlier indices, and is more consistent with French financial and economic history. We suggest this result casts some doubt on many historical stock indices, such as those used in Dimson, Marsh and Staunton's Triumph of the Optimists. Investment in French stocks provided a positive real return during the nineteenth century, but a negative one – because of inflation and wars – in the twentieth. Despite this secular negative real performance, stocks proved the best financial asset in the very long run, although with an equity premium lower than in the US.

scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS HARGA SAHAM DI INDONESIA

2017 ◽  
Vol 4 (2) ◽  
pp. 94
Author(s):  
Daryono Soebagiyo ◽  
Endah Heni Prasetyowati
Keyword(s):  
Foreign Currency ◽  
Time Series Data ◽  
Stock Exchange ◽  
Rapid Development ◽  
Stock Index ◽  
Series Data ◽  
Partial Adjustment ◽  
Currency Exchange ◽  
Adjustment Model ◽  
Adaptive Expectation

Since 1998, Indonesia capital market experiencing rapid development, go public activity in stock exchange and stock trading activity getting crowded. People interest observes monetary factors such as money circulation, deposit interest, foreign currency exchange, and inflation that predicted affecting compound stock index in Jakarta stock exchange from 1998 to 2002. Time series data from 1998-2002 gained from published issues like financial statement Indonesian Bank, Body of Statistic Center, and other sources. This research using adaptive expectation model analysis tools, that is rationalization model proposed by Nerlove, as stock adjustment model or partial adjustment model (PAM). Use of this model bring advantage in short and long term analysis.

scholarly journals Calibrating and Simulating Copula Functions in Financial Applications

2021 ◽  
Vol 7 ◽  
Author(s):  
Annalisa Di Clemente ◽  
Claudio Romano
Keyword(s):  
Financial Market ◽  
Asset Returns ◽  
Copula Function ◽  
Dependence Structure ◽  
Financial Asset ◽  
Financial Assets ◽  
Copula Functions ◽  
Financial Applications ◽  
Different Types ◽  
Financial Asset Returns

Copula functions can be utilized in financial applications to determine the dependence structure of the financial asset returns in the portfolio. Empirical evidence has proved the inadequacy of the multi-normal distribution, traditionally adopted to model the financial asset returns distribution. Copula functions can be employed in a flexible way for building efficient algorithms and to simulate a more adequate distribution of the financial assets. This paper aims to describe some simple statistical procedures currently employed to calibrate the copula functions to the financial market data. Furthermore, we present some useful methods for choosing which copula function better fits the real financial data. Also, some algorithms to simulate random variates from certain types of copula functions are illustrated. Finally, for illustration purposes, the previous procedures described are applied to two Italian equities. In particular, we show how to generate efficient Monte Carlo scenarios of equity log-returns in the bivariate case using different types of copula functions.

Digital financial assets as an object of accounting: Debating points

2020 ◽  
Vol 23 (3) ◽  
pp. 297-313
Author(s):  
E.A. Suprunova
Keyword(s):  
Scientific Literature ◽  
Balance Sheet ◽  
Financial Assets ◽  
Practical Application ◽  
Different Types ◽  
Legislative Framework ◽  
Russian Law ◽  
Scientific Nature ◽  
Logical Research

Subject. This article discusses the issues related to the valuation of digital financial assets, their reflection on accounts and the relevant balance sheet item classification. Objectives. The article aims to identify the main areas of digital financial asset accounting development in the context of ongoing changes in Russian law, and assess if there is any possibility to use foreign practices in digital financial assets accounting. Methods. For the study, I used the methods of classification, analogy, comparison, logical research, and relevant scientific literature generalization. Results. The article provides a comparative characterization of possible options for categorizing digital financial assets as certain items of asset, as well as arguments in favor of or against the choice of an asset. It offers standard accounting transactions to reflect digital financial assets in accounts based on their channels of origin. The article also assesses the possibility of applying international practices of digital financial assets accounting. Conclusions and Relevance. Practical application of the results of the study is possible if the appropriate legislative framework is formed, which could determine the structure of regulation of different types of digital financial assets. The findings and conclusions presented in the article can be used by the scientific and business communities for further polemic. The results of the study are of a scientific nature and can be used in teaching the Accounting course.

META-ANALYSIS ON AMERICAN PRESIDENTIAL ELECTION - 2016 AND AMERICAN STOCK MARKET

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Farhan Ahmed ◽  
Salman Bahoo ◽  
Sohail Aslam ◽  
Muhammad Asif Qureshi
Keyword(s):  
Content Analysis ◽  
Stock Market ◽  
Event Study ◽  
Presidential Election ◽  
Republican Party ◽  
Stock Exchange ◽  
Meta Analysis ◽  
Composite Index ◽  
Stock Index ◽  
Political Event

This paper aims to analyze the efficient stock market hypothesis as responsive to American Presidential Election, 2016. The meta-analysis has been done combining content analysis and event study methodology. The all major newspapers, news channels, public polls, literature and five important indices as Dow Jones Industrial Average (DJIA), NASDAQ Stock Market Composit Indexe (NASDAQ-COMP), Standard & Poor's 500 Index (SPX-500), New York Stock Exchange Composite Index (NYSE-COMP) and Other U.S Indexes-Russell 2000 (RUT-2000) are critically examined and empirically analyzed. The findings from content analysis reflect that stunned winning of Mr Trump from Republican Party worked as shock for American stock market. From event study, findings confirmed that all the major indices reflected a decline on winning of Trump and losing of Ms. Clinton from Democratic. The results are supported empirically and practically through the political event like BREXIT that resulted in shock to Global stock index and loss of $2 Trillion.

Commodity Exchange-Traded Funds

2018 ◽  
Author(s):  
Christopher Milliken
Keyword(s):  
Portfolio Diversification ◽  
Futures Contracts ◽  
Spot Price ◽  
Exchange Traded Funds ◽  
Investment Strategies ◽  
Regulatory Structure ◽  
Commodity Exchange ◽  
Asset Class ◽  
Exchange Traded Fund

Commodity exchange-traded funds (ETCs), which debuted in 2004, enable investors to access an asset class previously difficult or expensive to access. Although a small segment of the overall exchange-traded fund (ETF) universe, ETCs have grown in popularity with both speculators and investors looking for long-term portfolio diversification. Examples of the types of commodities that are now accessible through ETCs include gold, oil, and agricultural. The literature on ETCs is limited, but academic and industry work has centered on using futures contracts to replicate the performance of the underlying commodities spot price as well as the effect additional capital has had on the integrity of the futures market. This chapter covers this topic by reviewing the growth, investment strategies, and regulatory structure of ETCs as well as the underlying effects these funds have had on the underlying markets with which they engage.

scholarly journals A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 455 ◽  
Author(s):  
Hongjun Guan ◽  
Zongli Dai ◽  
Shuang Guan ◽  
Aiwu Zhao
Keyword(s):  
Time Series ◽  
Information Entropy ◽  
Stock Exchange ◽  
Time Series Forecasting ◽  
High Order ◽  
Stock Index ◽  
Neutrosophic Set ◽  
Forecasting Model ◽  
Forecasting Models ◽  
Proposed Model

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data. Then, the upward trend of each of fluctuation data is mapped to the truth-membership of a neutrosophic set, while a falsity-membership is used for the downward trend. Information entropy of high-order fluctuation time series is introduced to describe the inconsistency of historical fluctuations and is mapped to the indeterminacy-membership of the neutrosophic set. Finally, an existing similarity measurement method for the neutrosophic set is introduced to find similar states during the forecasting stage. Then, a weighted arithmetic averaging (WAA) aggregation operator is introduced to obtain the forecasting result according to the corresponding similarity. Compared to existing forecasting models, the neutrosophic forecasting model based on information entropy (NFM-IE) can represent both fluctuation trend and fluctuation consistency information. In order to test its performance, we used the proposed model to forecast some realistic time series, such as the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), the Shanghai Stock Exchange Composite Index (SHSECI), and the Hang Seng Index (HSI). The experimental results show that the proposed model can stably predict for different datasets. Simultaneously, comparing the prediction error to other approaches proves that the model has outstanding prediction accuracy and universality.

scholarly journals A Compensatory Fuzzy Logic Model in Technical Trading

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Norma P. Rodríguez-Cándido ◽  
Rafael A. Espin-Andrade ◽  
Efrain Solares ◽  
Witold Pedrycz
Keyword(s):  
Fuzzy Logic ◽  
Technical Analysis ◽  
Graphical Analysis ◽  
Logic Model ◽  
Financial Asset ◽  
Financial Assets ◽  
Novel Approach ◽  
Subjective Assessments ◽  
Efficient Prediction ◽  
High Degree

This work presents a novel approach to prediction of financial asset prices. Its main contribution is the combination of compensatory fuzzy logic and the classical technical analysis to build an efficient prediction model. The interpretability properties of the model allow its users to incorporate and consider virtually any set of rules from technical analysis, in addition to the investors’ knowledge related to the actual market conditions. This knowledge can be incorporated into the model in the form of subjective assessments made by investors. Such assessments can be obtained, for example, from the graphical analysis commonly performed by traders. The effectiveness of the model was assessed through its systematic application in the stock and cryptocurrency markets. From the results, we conclude that when the model shows a high degree of recommendation, the actual financial assets show high effectiveness.

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