scholarly journals Empirical Evidence of Co-Movement between the Canadian CDS, Stock Market And TSX 60 Volatility Index

2020 ◽  
Vol 3 (3) ◽  
pp. 51-64
Author(s):  
Ramzan Ali ◽  
Usman Ullah Butt ◽  
Muhammad Musa Khan ◽  
Muhammad Shaheer ◽  
Farhan Abbas Zaidi
Keyword(s):  
Stock Market ◽  
Credit Default Swaps ◽  
Medium Term ◽  
Short Term ◽  
Volatility Index ◽  
Daily Data ◽  
Credit Default ◽  
Long Time ◽  
Prime Objective

Purpose- The prime objective of this study was to find the co-movement between the Canadian credit default swaps market, the Stock market and volatility index (TSX 60 Index) Design/ Methodology- To achieve this purpose, daily data containing 2870 observations starting from the 1st of January 2009 to the 30th of December 2019 were analyzed. This study employed the wavelet approach to present results in short-term, medium-term, long-term, and very long time. Findings- The findings of this study showed a negative correlation between the CDS market, stock market, and the TSX 60 index in the short-term as well as in the long-term term, while in medium-term and very long-term period correlation is strongly positive. The wavelet co-movement results in the short-term and long-term were negative, while this relationship in the medium-term and very long-term period was strongly positive. Practical Implications- This research provides simultaneous valuable information for investment decisions in the short, medium, and long term time horizons, as well as for the policymakers in the Canadian credit default swaps market, stock market, and the volatility index (TSX 60 Index).

scholarly journals Application of the Value Averaging Investment Method on the US Stock Market

2015 ◽  
Vol 63 (6) ◽  
pp. 2151-2160
Author(s):  
Martin Širůček ◽  
Ivana Škatuĺárová
Keyword(s):  
Stock Market ◽  
Real Data ◽  
Investment Horizon ◽  
Medium Term ◽  
Short Term ◽  
Specific Investment ◽  
The Us ◽  
Expansion Period ◽  
Annual Risk

The paper focuses on empirical testing and the use of the regular investment, particularly on the value averaging investment method on real data from the US stock market in the years 1990–2013. The 23-year period was chosen because of a consistently interesting situation in the market and so this regular investment method could be tested to see how it works in a bull (expansion) period and a bear (recession) period. The analysis is focused on results obtained by using this investment method from the viewpoint of return and risk on selected investment horizons (short-term 1 year, medium-term 5 years and long-term 10 years). The selected aim is reached by using the ratio between profit and risk. The revenue-risk profile is the ratio of the average annual profit rate measured for each investment by the internal rate of return and average annual risk expressed by selective standard deviation. The obtained results show that regular investment is suitable for a long investment horizon or the longer the investment horizon, the better the revenue-risk ratio (Sharpe ratio). According to the results obtained, specific investment recommendations are presented in the conclusion, e.g. if this investment method is suitable for a long investment period, if it is better to use value averaging for a growing, sinking or sluggish market, etc.

scholarly journals Implementasi Kebijakan Penanggulangan Banjir dI DKI Jakarta 2013-2017

2018 ◽  
Vol 15 (1) ◽  
pp. 78-87
Author(s):  
Gilang Ramdhan
Keyword(s):  
Policy Implementation ◽  
Prevention Policy ◽  
Medium Term ◽  
Short Term ◽  
Policy Makers ◽  
Flood Prevention ◽  
Government Organization ◽  
Long Time ◽  
The Government

The flood problem is the long-time housework which is continuously done by the DKI Jakarta Government, to overcome the problem of the flood as the output from the policy of DKI Jakarta Government is the implementation of the flood prevention policy, both short-term, medium-term and long-term programs. In the implementation of the policy there are factors that can hamper and support the success of policy implementation there are communication, resources, bureaucratic or implementing attitude, and organizational structure including bureaucratic workflow. In terms of communication the real obstacle is the government are still difficult to establish communication with intermediary parties as one of the stakeholders. In terms of bureaucratic attitudes emphasized the independence of the apparatus to policy makers who have an important role in the success of policy implementation. In the government organization of DKI Jakarta itself has been applied innovation with the yellow, blue, and orange “soldiers” that can support the success of policy implementation. But unfortunately from DKI government's own policy environment does not yet have the full support of Jakarta DPRD so it can hamper the policies to be published by the executive. The conclusion of this paper is the government of DKI has a scope of problems that must be well compromised and which is still a wedge is the communication aspect, both internal and external so that the implementation of flood prevention policy in Jakarta can run well.

scholarly journals Impact Of Union Budget On Indian Stock Market

2015 ◽  
Vol 2 (11) ◽  
pp. 21 ◽  
Author(s):  
Divya Verma Gakhar ◽  
Neha Kushwaha ◽  
Vinita Ashok
Keyword(s):  
Stock Market ◽  
T Test ◽  
Medium Term ◽  
Short Term ◽  
Statistical Tools ◽  
F Test ◽  
Indian Stock Market ◽  
The Impact ◽  
Paired T Test

This paper analyzes the impact of Union budget on NSE’s CNX NIFTY Index. The impact is measured in terms of daily average returns and volatility over the short term, medium term and long term period in pre and post budget period. The data has been collected for five budget periods from 2011 to 2015. The statistical tools used are paired T-test and F-test. Paired T-test is conducted on average returns and F-test is conducted on variances over the period i.e., 3, 10 and 30 days in pre and post budget period. The maximum impact of budget is seen in short term then it gradually decreases in medium term and finally diminishes in the long term. The implication of this paper is that the investor should fear from investing in the stock market around the budget period.

scholarly journals The Interdependence of Debt and Innovation Sustainability: Evidence from the Onset of Credit Default Swaps

2019 ◽  
Vol 11 (10) ◽  
pp. 2946
Author(s):  
Yixin Chen ◽  
Junrui Zhang
Keyword(s):  
Risk Taking ◽  
Stock Price ◽  
Negative Impact ◽  
Price Volatility ◽  
Credit Default Swaps ◽  
Short Term ◽  
Credit Default ◽  
Early Failures ◽  
Sustainable Financing

Innovation sustainability requires sustainable financing. Extensive research suggests that debt is a disfavored source of innovation financing. In this study, we show that a recent financial development, credit default swaps (CDSs), may change the institutional logics of debt, making debt useful to the financing innovation. To be specific, we find that with CDS protection, creditors become less concerned with a borrowing firm’s credit risk and risk taking, making debt tolerant of early failures and reducing the negative impact of debt on the process of Innovation. In addition, we find that the availability of CDSs is more likely to change the nature of long-term debt than that of short-term debt, making long-term debt a useful instrument for the financing of innovation. Finally, the mitigation effect of CDS on the relation between debt and innovation is more pronounced for CDS firms with higher pay sensitivity to stock price volatility (Vega) and less financial constraints, revealing that a CEO’s incentive, rather than the relaxed financing constraints, is the underlying channel for the reduced negative impact of debt on innovation after CDS trading.

Impact of FII’s and FDI’s on Indian Stock Market

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Dr. Kamlesh Kumar Shukla
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Global Economy ◽  
Short Term ◽  
Earnings Growth ◽  
The Past ◽  
Bull Market ◽  
Indian Stock Market

FIIs are companies registered outside India. In the past four years there has been more than $41 trillion worth of FII funds invested in India. This has been one of the major reasons on the bull market witnessing unprecedented growth with the BSE Sensex rising 221% in absolute terms in this span. The present downfall of the market too is influenced as these FIIs are taking out some of their invested money. Though there is a lot of value in this market and fundamentally there is a lot of upside in it. For long-term value investors, there’s little because for worry but short term traders are adversely getting affected by the role of FIIs are playing at the present. Investors should not panic and should remain invested in sectors where underlying earnings growth has little to do with financial markets or global economy.

scholarly journals Long-Term Data Traffic Forecasting for Network Dimensioning in LTE with Short Time Series

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1151
Author(s):  
Carolina Gijón ◽  
Matías Toril ◽  
Salvador Luna-Ramírez ◽  
María Luisa Marí-Altozano ◽  
José María Ruiz-Avilés
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Analysis ◽  
Data Traffic ◽  
Medium Term ◽  
Short Term ◽  
Traffic Forecasting ◽  
Series Analysis ◽  
Radio Planning

Network dimensioning is a critical task in current mobile networks, as any failure in this process leads to degraded user experience or unnecessary upgrades of network resources. For this purpose, radio planning tools often predict monthly busy-hour data traffic to detect capacity bottlenecks in advance. Supervised Learning (SL) arises as a promising solution to improve predictions obtained with legacy approaches. Previous works have shown that deep learning outperforms classical time series analysis when predicting data traffic in cellular networks in the short term (seconds/minutes) and medium term (hours/days) from long historical data series. However, long-term forecasting (several months horizon) performed in radio planning tools relies on short and noisy time series, thus requiring a separate analysis. In this work, we present the first study comparing SL and time series analysis approaches to predict monthly busy-hour data traffic on a cell basis in a live LTE network. To this end, an extensive dataset is collected, comprising data traffic per cell for a whole country during 30 months. The considered methods include Random Forest, different Neural Networks, Support Vector Regression, Seasonal Auto Regressive Integrated Moving Average and Additive Holt–Winters. Results show that SL models outperform time series approaches, while reducing data storage capacity requirements. More importantly, unlike in short-term and medium-term traffic forecasting, non-deep SL approaches are competitive with deep learning while being more computationally efficient.

Sampling estuarine copepods at different scales and resolutions: a study in Rio de la Plata

2018 ◽  
Vol 99 (5) ◽  
pp. 1059-1064 ◽  
Author(s):  
Sourav Paul ◽  
Danilo Calliari
Keyword(s):  
Sampling Effort ◽  
Rio De La Plata ◽  
Population Densities ◽  
Medium Term ◽  
Short Term ◽  
Río De La Plata ◽  
La Plata ◽  
Resource Limitations ◽  
Paracalanus Parvus

AbstractIn the Rio de la Plata salinity, temperature, chlorophyll a (chl a), and densities (ind. m−3) of the copepods Acartia tonsa and Paracalanus parvus were measured from January to November in 2003 by following a nested weekly and monthly design. Such sampling yielded two separate datasets: (i) Yearly Dataset (YD) which consists of data of one sampling effort per month for 11 consecutive months, and (ii) Seasonal Weekly Datasets (SWD) which consists of data of one sampling effort per week of any four consecutive weeks within each season. YD was assumed as a medium-term low-resolution (MTLR) dataset, and SWD as a short-term high-resolution (STHR) dataset. The hypothesis was, the SWD would always capture (shorter scales generally captures more noise in data) more detail variability of copepod populations (quantified through the regression relationships between temporal changes of salinity, temperature, chl a and copepod densities) than the YD. Analysis of both YD and SWD found that A. tonsa density was neither affected by seasonal cycles, nor temporal variability of salinity, temperature and chl a. Thus, compared to STHR sampling, MTLR sampling did not yield any further information of the variability of population densities of the perennial copepod A. tonsa. Analysis of SWD found that during summer and autumn the population densities of P. parvus had a significant positive relationship to salinity but their density was limited by higher chl a concentration; analysis of YD could not yield such detailed ecological information. That hints the effectiveness of STHR sampling over MTLR sampling in capturing details of the variability of population densities of a seasonal copepod species. Considering the institutional resource limitations (e.g. lack of long-term funding, manpower and infrastructure) and the present hypothesis under consideration, the authors suggest that a STHR sampling may provide useful complementary information to interpret results of longer-term natural changes occurring in estuaries.

scholarly journals Towards the best future for humankind: ZIPAR whitepaper.

2018 ◽  
Author(s):  
Marko Kovic ◽  
Christian Caspar ◽  
Adrian Rauchfleisch
Keyword(s):  
Medium Term ◽  
Short Term ◽  
Profound Impact ◽  
Future Challenges ◽  
The Way

Humankind is facing major challenges in the short-term, medium-term, and long-term future. Those challenges will have a profound impact on humankind’s future progress and wellbeing. In this whitepaper, we outline our understanding of humankind’s future challenges, and we describe the way in which we work towards identifying as well as managing them. In doing so, we pursue the overall goal of ZIPAR: We want to make the best future for humankind (ever so slightly) more probable.

scholarly journals Intralymphatic immunotherapy for allergic rhinoconjunctivitis: a systematic review and meta-analysis

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
M.P. Hoang ◽  
K. Seresirikachorn ◽  
W. Chitsuthipakorn ◽  
K. Snidvongs
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Specific Ige ◽  
Allergic Rhinoconjunctivitis ◽  
Medium Term ◽  
Short Term ◽  
Intralymphatic Immunotherapy ◽  
Specific Igg4 ◽  
Igg4 Level

BACKGROUND: Intralymphatic immunotherapy (ILIT) is a new route of allergen-specific immunotherapy. Data confirming its effect is restricted to a small number of studies. METHODOLOGY: A systematic review with meta-analysis was conducted. The short-term (less than 24 weeks), medium-term (24-52 weeks), and long-term (more than 52 weeks) effects of ILIT in patients with allergic rhinoconjunctivitis (ARC) were assessed. The outcomes were combined symptom and medication scores (CSMS), symptoms visual analog scale (VAS), disease-specific quality of life (QOL), specific IgG4 level, specific IgE level, and adverse events. RESULTS: Eleven randomized controlled trials and 2 cohorts (483 participants) were included. Compared with placebo, short term benefits of ILIT for seasonal ARC improved CSMS, improved VAS and increased specific IgG4 level but did not change QOL or specific IgE level. Medium-term effect improved VAS. Data on the long-term benefit of ILIT remain unavailable and require longer term follow-up studies. There were no clinical benefits of ILIT for perennial ARC. ILIT was safe and well-tolerated. CONCLUSION: ILIT showed short-term benefits for seasonal ARC. The sustained effects of ILIT were inconclusive. It was well tolerated.

scholarly journals Methods of long-term and short-term adaptation for biometric image of keystroke dynamics

2021 ◽  
Vol 7 (3D) ◽  
pp. 450-457
Author(s):  
Dmitry V. Pashchenko ◽  
Dmitry A. Trokoz ◽  
Alexey I. Martyshkin ◽  
Elena A. Balzannikova
Keyword(s):  
Working Capacity ◽  
Keystroke Dynamics ◽  
Short Term ◽  
User Identification ◽  
New Device ◽  
Short Term Adaptation ◽  
Long Time

This article discusses one of the main problems of user identification by keyboard handwriting - short-term changes in the keystroke dynamics of users in connection with its psychophysical state, as well as changes over a long time associated with the formation of keystroke dynamics by a new user or when switching to a new device. A method for determining the phase of working capacity by the time characteristics of the keystroke dynamics is proposed.

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