scholarly journals Applying Quantum Mechanics for Extreme Value Prediction of VaR and ES in the ASEAN Stock Exchange

Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Chukiat Chaiboonsri ◽  
Satawat Wannapan
Keyword(s):  
Quantum Mechanics ◽  
Value At Risk ◽  
Stock Exchange ◽  
Value Prediction ◽  
Bayesian Inferences ◽  
Quantum Mechanism ◽  
Quantum Wave ◽  
Wave Distribution ◽  
Asean Countries ◽  
Quantum Distributions

The advantage of quantum mechanics to shift up the ability to econometrically understand extreme tail losses in financial data has become more desirable, especially in cases of Value at Risk (VaR) and Expected Shortfall (ES) predictions. Behind the non-novel quantum mechanism, it does interestingly connect with the distributional signals of humans’ brainstorms. The highlighted purpose of this article is to devise a quantum-wave distribution methodically to analyze better risks and returns for stock markets in The Association of Southeast Asian Nations (ASEAN) countries, including Thailand (SET), Singapore (STI), Malaysia (FTSE), Philippines (PSEI), and Indonesia (PCI). Data samples were observed as quarterly trends between 1994 and 2019. Bayesian statistics and simulations were applied to present estimations’ outputs. Empirically, quantum distributions are remarkable for providing “real distributions”, which computationally conform to Bayesian inferences and crucially contribute to the higher level of extreme data analyses in financial economics.

scholarly journals Value at risk: Evidence from Pakistan Stock Exchange

2011 ◽  
Vol 5 (17) ◽  
pp. 7474-7480 ◽  
Author(s):  
Nawaz Faisal ◽  
Afzal Muhammad
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange

scholarly journals ANALISA RISIKO DAN KEUNTUNGAN INVESTASI SAHAM BATU BARA DI BURSA EFEK INDONESIA (Tahun 2010-2014)

2016 ◽  
Vol 13 (1) ◽  
pp. 42
Author(s):  
Siti Nur Zahroh
Keyword(s):  
Coal Mining ◽  
Value At Risk ◽  
Stock Exchange ◽  
Mining Company ◽  
Benefit Ratio ◽  
Production And Consumption ◽  
Value Loss ◽  
Return On Capital ◽  
Risk And Benefit ◽  
Level Of Risk

This research was motivated by the increasing value of the production and consumption of coal from year to year, but is not offset by an increase in new investment in this sector. Each selection of investment decisions certainly linked to the degree of risk and benefit ratio, in order to know how much future investment results that will be obtained with the level of risk to a minimum. The purpose of this study was to measure the level of risk and benefit ratio of shares in a coal mining company listed on the Stock Exchange during the study period 2010-2014. Calculation of the level of risk in this study was measured by VaR (Value at Risk) and the profit rate is measured with RAROC (Risk Adjusted Return on Capital). The results of this study indicate that the coal mining stocks are a potential value loss (high risk low return). The highest VaR value during the study period experienced by PKPK of 0.64300 or 64.30% in 2010. The market value of the highest RAROC during the observation period by ITMG in 2010 amounted to 0.4304 or 43%.

scholarly journals Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company

2017 ◽  
Vol 65 (5) ◽  
pp. 1687-1694
Author(s):  
Tomáš Konderla ◽  
Václav Klepáč
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Estimation ◽  
Listed Company ◽  
Mixture Distribution ◽  
Normal Mixture ◽  
Development Characteristic ◽  
The Common

The article points out the possibilities of using Hidden Markov model (abbrev. HMM) for estimation of Value at Risk metrics (abbrev. VaR) in sample. For the illustration we use data of the company listed on Prague Stock Exchange in range from January 2011 to June 2016. HMM approach allows us to classify time series into different states based on their development characteristic. Due to a deeper shortage of existing domestic results or comparison studies with advanced volatility governed VaR forecasts we tested HMM with univariate ARMA‑GARCH model based VaR estimates. The common testing via Kupiec and Christoffersen procedures offer generalization that HMM model performs better that volatility based VaR estimation technique in terms of accuracy, even with the simpler HMM with normal‑mixture distribution against previously used GARCH with many types of non‑normal innovations.

scholarly journals Penggunaan Metode Orthogonal GARCH untuk Meramalkan Matriks Kovarians Return Indeks Harga Saham Sektoral Di Bursa Efek Indonesia

2019 ◽  
Vol 12 (2) ◽  
pp. 30
Author(s):  
Robiyanto Robiyanto
Keyword(s):  
Risk Factor ◽  
Value At Risk ◽  
Stock Price ◽  
Stock Exchange ◽  
Principal Component ◽  
Jel Classification ◽  
Stock Index ◽  
Price Indices ◽  
Exchange Value ◽  
Autoregressive Conditional Heteroscedasticity

ABSTRACT   This study conducted a risk communality assessment on sectoral stock price indices in Indonesia Stock Exchange by using Orthogonal Generalized Autoregressive Conditional Heteroscedasticity (Orthogonal GARCH) method. Data used in this research is daily closing of sectoral stock price indices at Indonesia Stock Exchange which consisting of 10 sectoral price indices. Research period are during January 4, 2011 until July 17, 2017. Of 10 sectoral stock price indices which studied apparently there are two principal component influencing its conditional variance. The result of this research is that stock index of agriculture and mining sector have the same risk factor, while other sectoral stock price indices have the same risk factor. These findings imply that investment managers must differentiate risk factors for agricultural and mining sectors from other sectors.   Keywords : Orthogonal GARCH; Indonesia Stock Exchange; Value-at-Risk (VaR); Sectoral stock price indices; Covariance matrix   JEL Classification : C58; G11.  

Electron diffraction chez Thomson: early responses to quantum physics in Britain

2010 ◽  
Vol 43 (2) ◽  
pp. 245-275 ◽  
Author(s):  
JAUME NAVARRO
Keyword(s):  
Quantum Mechanics ◽  
Electron Diffraction ◽  
Quantum Physics ◽  
Wave Mechanics ◽  
Basic Tenet ◽  
Wave Particle Duality ◽  
Quantum Wave ◽  
The University ◽  
Total Agreement ◽  
Father And Son

AbstractIn 1927, George Paget Thomson, professor at the University of Aberdeen, obtained photographs that he interpreted as evidence for electron diffraction. These photographs were in total agreement with de Broglie's principle of wave–particle duality, a basic tenet of the new quantum wave mechanics. His experiments were an initially unforeseen spin-off from a project he had started in Cambridge with his father, Joseph John Thomson, on the study of positive rays. This paper addresses the scientific relationship between the Thomsons, father and son, as well as the influence that the institutional milieu of Cambridge had on the early work of the latter. Both Thomsons were trained in the pedagogical tradition of classical physics in the Cambridge Mathematical Tripos, and this certainly influenced their understanding of quantum physics and early quantum mechanics. In this paper, I analyse the responses of both father and son to the photographs of electron diffraction: a confirmation of the existence of the ether in the former, and a partial embrace of some ideas of the new quantum mechanics in the latter.

Firm, industry and economic determinants of working capital at risk

2016 ◽  
Vol 03 (04) ◽  
pp. 1650031 ◽  
Author(s):  
Tarek Ibrahim Eldomiaty ◽  
Mohamed Hashem Rashwan ◽  
Mohamed Bahaa El Din ◽  
Waleed Tayel
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange ◽  
Statistical Tests ◽  
Working Capital ◽  
Short Term ◽  
Firm Level ◽  
Cash Conversion Cycle ◽  
Wide Range ◽  
Capital At Risk

Purpose: The objective of this study is to examine the relative contribution of firm-level, industry-level and country level variables to working capital at risk. Working capital at risk is treated as the value at risk for a portfolio of firm’s current assets. As far as short-term liquidity is concerned, working capital at risk, being the maximum amount that a firm may lose at a certain confidence interval, must be the most important part that a firm’s management must focus on. Design/methodology/approach: This study empirically examines the possible associations between wide range of variables and working capital at risk. The sample firms include 143 non-financial firms listed in Egypt stock exchange. The data cover the years 2000–2014. The statistical tests include the fixed and random effects, testing for linearity versus nonlinearity. The least squares dummy variables and discriminant analysis are utilized. The working capital at risk is classified into three levels: low, medium and high. Findings: The general findings of the study show that cash conversion cycle and the leverage are the most significant determinants of working capital at risk. Both determinants have significant influence on the level of volatility of working capital throughout the three categories of working capital at risk. Originality/value: This study offers a new approach that deals with working capital as a portfolio, rather than single ratios, that firm’s management must decrease its volatility (value at risk), therefore, short-term liquidity can be improved significantly. This approach can be considered a financial engineering in terms of monitoring and managing short-term liquidity exposure.

scholarly journals VALUE-AT-RISK (VaR) FOR LQ – 45 COMPANIES

2011 ◽  
Vol 3 (2) ◽  
pp. 93-108
Author(s):  
Rangga Handika
Keyword(s):  
At Risk ◽  
Standard Deviation ◽  
Normal Distribution ◽  
Analytical Methods ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Measure ◽  
Percent Level ◽  
Level Of Confidence

This paper offers a new measurement of risk, Value-at-Risk (VaR) for LQ-45 index in Indonesian Stock Exchange (ISX). Basic finance uses standard deviation in measuring and quantifying the risks. This paper uses VaR as a risk measure by using historical and analytical methods. This study uses the data containing all LQ-45 weekly data from January 1st, 2005 to December, 31st 2010. Moreover, this paper also calculates VaR of three indices (IHSG, Dow Jones, and S&P 500) for benchmarking purpose. This study finds that LQ-45 companies have VaR ranging from -5.30 to -41.05 percent with 95 percent level of confidence. It means that we can expect to suffer a minimum weekly loss between 5.30 to 41.05 percent in 5 percent probability when we invest in the LQ-45 companies stocks individually. Furthermore, this study finds that individual LQ-45 stock is riskier than indices based on VaR measure. This paper also concludes that individual LQ-45 stock tends not to follow normal distribution while index tends to follow by comparing their historical and analytical VaR calculation.

scholarly journals An analytical method of estimating Value-at-Risk on the Belgrade Stock Exchange

2009 ◽  
Vol 54 (183) ◽  
pp. 119-138 ◽  
Author(s):  
Milica Obadovic ◽  
Mirjana Obadovic
Keyword(s):  
At Risk ◽  
Failure Rate ◽  
Confidence Level ◽  
Analytical Method ◽  
Value At Risk ◽  
Risk Evaluation ◽  
Risk Model ◽  
Stock Exchange ◽  
Confidence Levels ◽  
The Given

This paper presents market risk evaluation for a portfolio consisting of shares that are continuously traded on the Belgrade Stock Exchange, by applying the Value-at-Risk model - the analytical method. It describes the manner of analytical method application and compares the results obtained by implementing this method at different confidence levels. Method verification was carried out on the basis of the failure rate that demonstrated the confidence level for which this method was acceptable in view of the given conditions.

scholarly journals Dynamic value at risk estimation for BELEX15

2011 ◽  
Vol 8 (1) ◽  
Author(s):  
Emilija Nikolić-Đorić ◽  
Dragan Đorić
Keyword(s):  
At Risk ◽  
Stock Returns ◽  
Long Memory ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Estimation ◽  
Value Theory ◽  
Garch Models ◽  
Measurement Models ◽  
Standardized Residuals

This paper uses RiskMetrics, GARCH and IGARCH models to calculate daily VaR for Belgrade Stock Exchange index BELEX15 returns based on the normal and Student t innovation distribution. In the case of GARCH and IGARCH models VaR values are obtained applying Extreme Value Theory on the standardized residuals. The Kupiec's LR statistics was used to test the accuracy of risk measurement models. The main conclusions are: (1) when modelling value-at-risk it is very important to have a good model for volatility of stock returns; (2) both stationary and integrated GARCH models outperform RiskMetrics in estimating VaR; (3) although long memory volatility is present in the BELEX15 index, IGARCH models cannot outperform GARCH type models in VaR evaluations for this index.

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