Can We Reckon Bitcoin as a Hedge, a Safe Haven or a Diversifier for US Dollars?

2020 ◽  
pp. 097215092096816
Author(s):  
Rym Regaieg ◽  
Wajdi Moussa ◽  
Nidhal Mgadmi
Keyword(s):  
Markov Switching ◽  
Ar Model ◽  
Portfolio Risk ◽  
Safe Haven ◽  
The Us ◽  
Research Findings ◽  
Us Dollar ◽  
Risk Managers

This article aims to analyse the hedging, diversifier and safe-haven properties of Bitcoin for the US Dollar Index (USDI). We explore the long-term relationship between USDI and Bitcoin by estimating a Markov-switching autoregressive (MS-AR) model with two regimes. Thus, the data used cover the period from 18 January 2010 to 30 June 2017 for both USDI and Bitcoin. The empirical findings based on the analysis of the MS-AR model report that investing in Bitcoin involves more benefits than USDI even if the economy is in a recession. However, by examining Bitcoin and USDI volatility, the research findings underline positive dependency between the two. Such results denote that Bitcoin does not act as a hedge, and not even as a safe haven, against USDI. We found that Bitcoin is merely a diversifier for USDI. Accordingly, the outcomes will help investors and portfolio risk managers to make more up-to-date investment analyses and decisions.

scholarly journals Cointegration of Stock Market and Exchange Rate in Indonesia

2019 ◽  
Vol 2 (2) ◽  
pp. 125 ◽  
Author(s):  
Pribawa E Pantas ◽  
Muhamad Nafik Hadi Ryandono ◽  
Misbahul Munir ◽  
Rofiul Wahyudi
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Capital Market ◽  
Global Financial Crisis ◽  
The Us ◽  
Us Dollar ◽  
The Exchange Rate ◽  
Johansen Cointegration Test ◽  
The Global Financial Crisis

This study aims to determine the long-term relationship between stock market and exchange rate in Indonesia. The research method used is Johansen cointegration test. The results of this study found no cointegration between the variables tested. Thus the exchange rate, JII, and IHSG have no relationship in the long term. The fluctuation of the rupiah exchange rate in recent years did not generally affect the performance of stock indices especially after the global financial crisis of 2008. This shows the capital market in Indonesia has a good performance so that it is not so sensitive to the sentiment of the decline in the rupiah against the US dollar. This finding is in line with the findings of Syahrer (2010) which states the exchange rate has no effect on the stock market.

The Effect of Covid-19, Rupiah Exchange Rate, and Inflation on the Indonesia Sharia Stock Index during the Covid-19 Pandemic

2021 ◽  
Vol 4 (1) ◽  
pp. 313-336
Author(s):  
Achmad Agus Priyono ◽  
Ari Kartiko
Keyword(s):  
Exchange Rate ◽  
Time Series Data ◽  
Negative Impact ◽  
Stock Index ◽  
Series Data ◽  
Stock Market Index ◽  
Short Term ◽  
The Us ◽  
Us Dollar

Purpose of this study is to clarify the effect of the number of daily cases reported to have contracted the Covid-19 virus, the exchange rate of the rupiah against the US dollar and inflation on the movement of the Indonesian Sharia stock index (ISSI) during the Pandemic Covid 19 in the short term and long term. Data analysis methods that used is analysis Error Correction Mechanism (ECM) using Eviews software 10. The data collected is daily time series data starting from March 2, 2020 to May 31, 2021 so that the number of samples collected obtained as many as 283 samples . The results of the study stated that the addition of the daily number of reported cases of contracting the Covid-19 virus has a negative impact on The Indonesian Sharia Stock Market Index (ISSI) during the Covid-19 pandemic, so that encourage the weakening of the Stock Index both in the long and long term short. Likewise, the weakening of the rupiah against the US dollar will caused the fall of the sharia index during the Covid 19 pandemic, both in the long term and long and short term. However, the study found no effect inflation on the Indonesian Sharia Stock Index (ISSI) during the Covid19 pandemic, good long term and short term

scholarly journals Fed and ECB: which is informative in determining the DCC between bitcoin and energy commodities?

2020 ◽  
Vol 4 (1) ◽  
pp. 77-102
Author(s):  
Abdelkader Derbali ◽  
Lamia Jamel ◽  
Monia Ben Ltaifa ◽  
Ahmed K. Elnagar ◽  
Ali Lamouchi
Keyword(s):  
Monetary Policy ◽  
Design Methodology ◽  
Commodity Markets ◽  
Portfolio Risk ◽  
Conditional Correlation ◽  
Predictive Capacity ◽  
Federal Funds ◽  
Content Type ◽  
The Us ◽  
Risk Managers

PurposeThis paper provides an important perspective to the predictive capacity of Fed and European Central Bank (ECB) meeting dates and production announcements for the dynamic conditional correlation (DCC) between Bitcoin and energy commodities returns and volatilities during the period from August 11, 2015 to March 31, 2018.Design/methodology/approachTo assess empirically the unanticipated component of the US and ECB monetary policy, the authors pursue the Kuttner's approach and use the federal funds futures and the ECB funds futures to assess the surprise component. The authors use the approach of DCC as introduced by Engle (2002) during the period from August 11, 2015 to March 31, 2018.FindingsThe authors’ results suggest strong significant DCCs between Bitcoin and energy commodity markets if monetary policy surprises are incorporated in variance. These results confirmed the financialization of Bitcoin and commodity energy markets. Finally, the DCC between Bitcoin and energy commodity markets appears to respond considerably more in the case of Fed surprises than ECB surprises.Originality/valueThis study is a crucial topic for policymakers and portfolio risk managers.

scholarly journals Russia and Iran in Conditions of Economic Sanctions: Anti-Sanction Policy and Resistance Economy

2021 ◽  
Vol 18 (2) ◽  
pp. 5-12
Author(s):  
I. P. Khominich ◽  
S. Alikhani
Keyword(s):  
National Economy ◽  
Small And Medium Enterprises ◽  
Economic Sanctions ◽  
Trade Flows ◽  
Business Climate ◽  
The Us ◽  
Research Findings ◽  
Us Dollar ◽  
Medium Enterprises ◽  
Sanction Policy

Economic sanctions always have destructive impact on economic structures of states, especially such developing countries as Iran and Russia. These countries used anti-sanction economic approach in order to oppose western sanctions. Strategy of anti-sanction economy is a tool of counteracting adverse impact of sanctions on national economy as a sanction target. The authors investigate the influence of strategy of anti-sanction economy on national economy of Iran and Russia, which are facing economic sanctions introduced by western countries. Research findings demonstrate that strategy of anti-sanction economy is a key priority of both Iran and Russia. This strategy helps these countries improve the local business climate, support small and medium enterprises and raise efficiency of local production units. Principle recommendations of our research for Iran and Russia imply that apart from using strategy of anti-sanction economy these countries should do their best to lower their dependence on the US dollar (strategy of dollarization), improve bilateral economic cooperation and eliminate trade barriers to increase trade flows.

scholarly journals Perbandingan Metode ANN-PSO dan ANN-GA untuk Peningkatan Akurasi Prediksi Harga Emas Antam

2019 ◽  
Vol 10 (2) ◽  
pp. 101-106
Author(s):  
Nadia Annisa Maori ◽  
Keyword(s):  
Neural Network ◽  
Algorithm Optimization ◽  
Swarm Optimization ◽  
A Value ◽  
The Neural Network ◽  
The Us ◽  
Us Dollar ◽  
Artificial Neural Network Ann ◽  
Backpropagation Artificial Neural Network

Antam's gold price is more expensive than the price of gold used by more investors for long-term use. Sometimes the price of antam gold cannot be predicted at any time. Antam's rising gold prices were moved by many factors, sent in exchange rates of US dollars (USD). If the exchange rate of the US dollar (USD) decreases, the price of gold will rise and vice versa, if the value of the US dollar (USD) strengthens, the price of gold will increase. This condition makes it difficult for investors to predict the price of gold in the future. Backpropagation Artificial Neural Network (ANN) is known as one of the good methods in predicting. In this study an evaluation of the results of the price of gold using ANN with the help of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) optimization. PSO has many similarities with GA, which is an algorithm adopted from the process of supporting humans. The results of the study prove that PSO Optimization is able to provide an increase in optimizing the weights on the Neural Network by producing the best RMSE value, which is equal to 0.026, while GA optimization only produces a value of 0.09.

scholarly journals The Budget rule: reducing oil dependence

2020 ◽  
Vol 164 ◽  
pp. 11041
Author(s):  
Andrey Brodunov ◽  
Natalia Bushueva ◽  
Alexander Averin ◽  
Ekaterina Berezina
Keyword(s):  
Comparative Analysis ◽  
Oil Prices ◽  
International Market ◽  
Close Correlation ◽  
National Currency ◽  
The Us ◽  
Budget Policy ◽  
The Russian Federation ◽  
Us Dollar

The article explores a way to reduce the dependence of the national currency on oil prices. A retrospective analysis of the data showed a close correlation between the ruble, the US dollar and the price of oil in the international market. Since 2004, a budget rule has been in effect in Russia, imposing a long-term restriction on budget policy through quantitative restrictions on budget indicators. The study analyzes the limitations of the budget rule in the Russian Federation in various periods and its results. The authors conducted a comparative analysis of foreign experience in reducing dependence on petrodollars on the basis of five reserve funds. The study demonstrates that the budget rule could be one of the possible measures to reduce the dependence of the national currency on oil prices.

FACTORS OF CRISIS AND RESTRUCTURING WORLD FINANCIAL SYSTEM

2021 ◽  
Vol 1 (7) ◽  
pp. 171-178
Author(s):  
V. V. ZAGARSKIKH ◽  
◽  
E. V. KARANINA ◽  
Keyword(s):  
New World ◽  
Financial System ◽  
Economic Structure ◽  
Economic Security ◽  
The Us ◽  
World Economic ◽  
Us Dollar ◽  
Hybrid War ◽  
World Economic Order

The article analyzes long-term economic patterns, examines the reasons for international integration and the creation of a new world economic order. Some reasons for the destabilization of the financial system of the planet are revealed, including the depreciation of the US dollar and the redistribution of property rights through the financial market. The analysis of the dollar financial system in the modern conditions of hybrid war is given, possible types of a new world economic structure, solutions for Russia and the world as a whole to create an economic security zone are considered. The conclusion is made about the need for de-dollarization of mutual trade and joint investments.

scholarly journals Export Determinant of Micro, Small, and Medium Enterprise Products (MSMEs) in Indonesia with Error Correction Model (ECM) Approach

2021 ◽  
Vol 6 (6) ◽  
pp. 149-155
Author(s):  
Cicih Ratnasih ◽  
. Sumarni ◽  
M. Imron Rosyadi ◽  
Dedy Triharjanto ◽  
. Yolanda
Keyword(s):  
Exchange Rate ◽  
Error Correction ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Major Effect ◽  
Short Term ◽  
Substantial Impact ◽  
The Us ◽  
Us Dollar

This study analyzes the relationship between the exchange rate of the rupiah against the US dollar, MSME growth, investment, MSME credit, and inflation all have an effect on MSME exports in Indonesia. The purpose of this study is to determine the extent to which the independent factors above have an effect on MSME product exports using multiple linear regression analysis. The Error Correction Mechanism (ECM) analytical approach was employed in this study, which covered the period 2010-2020. ECM analysis is capable of resolving short- to long-term imbalances. This study demonstrates that there is no such thing as a short-term-long-term equilibrium. Partially, the rupiah exchange rate against the US dollar, investment, and inflation all had a significant effect on the export of MSME products in Indonesia, while the rupiah exchange rate against the US dollar, MSME growth, and investment all had a significant effect on the export of MSME products in the short term. At various points in time (long and short term), it can be seen that the rupiah's exchange rate against the US dollar and investment had a substantial impact on MSME exports. Simultaneously, all variables had a major effect on the export of MSME products in Indonesia, both in the long and short term.

scholarly journals Safe Haven Currencies

2020 ◽  
Vol 26 (4) ◽  
pp. 579-591
Keyword(s):  
Financial Risk ◽  
Swiss Franc ◽  
Global Risk ◽  
Safe Haven ◽  
Number Of Factors ◽  
The Us ◽  
Us Dollar ◽  
Japanese Yen ◽  
The Stability ◽  
Safe Haven Currency

As other safe haven assets, safe haven currencies are sought by investors to mitigate financial risk when economic turbulence hits. Three major safe haven currencies are the US dollar (USD), the Japanese yen (JPY) and the Swiss franc (CHF). The euro is now in competition as an alternative safe haven currency. US dollar will remain the best safe haven currency in the short term and the best investment currency in the medium term. In every uncertainty of the US equity market as well as in the case of a decline of the US dollar, the investor may consider investing in a safe haven currency like the yen or the Swiss franc. Given the stability of Swiss government and financial system of the country, the increased foreign demand for the currency usually pushes the Swiss franc upward. There are number of factors, characterizing the dynamics in which the investors fall, rushing to the Japanese yen during periods of global risk aversion. Traders looked for refuge in the cryptocurrency because they cannot find refuge elsewhere.

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