The volatility characteristics of Vietnamese coffee export price and transmission mechanism of influencing factors: a Markov switching approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
TrungTuyen Dang ◽  
Zhang Caihong ◽  
ThiHong Nguyen ◽  
NgocTrung Nguyen ◽  
Cuong Tran
Keyword(s):  
Design Methodology ◽  
Markov Switching ◽  
Export Price ◽  
Transmission Mechanism ◽  
Coffee Bean ◽  
Content Type ◽  
Vector Autoregressive ◽  
Robusta Coffee ◽  
Characteristic Fluctuation ◽  
Coffee Price

Purpose This study aims to examine the transmission mechanism of factors on the characteristic fluctuation of Vietnamese coffee bean export price (PVN). Design/methodology/approach Applying Markov switching–vector autoregressive model. Findings Significantly, the empirical results showed that the transmission of independent variables on PVN is non-linear, and the fluctuation of PVN is affected by many factors, especially PVN in the previous period. In addition, the effect of Robusta coffee price was the greatest with coefficient is 0.28785, and the correlation between PVN and it was also the highest in both regimes with coefficients are 0.5317 and 0.3959, respectively. Originality/value These obtained results are in accordance with reality, as Vietnam is the largest exporter of Robusta coffee in the world.

Volatility discovery in cryptocurrency markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thomas Dimpfl ◽  
Dalia Elshiaty
Keyword(s):  
Design Methodology ◽  
Stochastic Volatility Model ◽  
Discrete Version ◽  
Data Series ◽  
Content Type ◽  
Vector Autoregressive ◽  
Volatility Model ◽  
Information Shares ◽  
The Common ◽  
To Come

PurposeCryptocurrency markets are notoriously noisy, but not all markets might behave in the exact same way. Therefore, the aim of this paper is to investigate which one of the cryptocurrency markets contributes the most to the common volatility component inherent in the market.Design/methodology/approachThe paper extracts each of the cryptocurrency's markets' latent volatility using a stochastic volatility model and, subsequently, models their dynamics in a fractionally cointegrated vector autoregressive model. The authors use the refinement of Lien and Shrestha (2009, J. Futures Mark) to come up with unique Hasbrouck (1995, J. Finance) information shares.FindingsThe authors’ findings indicate that Bitfinex is the leading market for Bitcoin and Ripple, while Bitstamp dominates for Ethereum and Litecoin. Based on the dominant market for each cryptocurrency, the authors find that the volatility of Bitcoin explains most of the volatility among the different cryptocurrencies.Research limitations/implicationsThe authors’ findings are limited by the availability of the cryptocurrency data. Apart from Bitcoin, the data series for the other cryptocurrencies are not long enough to ensure the precision of the authors’ estimates.Originality/valueTo date, only price discovery in cryptocurrencies has been studied and identified. This paper extends the current literature into the realm of volatility discovery. In addition, the authors propose a discrete version for the evolution of a markets fundamental volatility, extending the work of Dias et al. (2018).

Returns and volatility spillovers among cryptocurrency portfolios

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ismail Olaleke Fasanya ◽  
Oluwatomisin Oyewole ◽  
Temitope Odudu
Keyword(s):  
Design Methodology ◽  
Asset Returns ◽  
Volatility Spillover ◽  
Content Type ◽  
Vector Autoregressive ◽  
Volatility Spillovers ◽  
Dynamic Relationship ◽  
Major Market ◽  
Daily Data ◽  
Variance Decompositions

PurposeThis paper examines the return and volatility spillovers among major cryptocurrency using daily data from 10/08/2015 to 15/04/2018.Design/methodology/approachThe authors employ the Dielbold and Yilmaz (2012) spillover approach and rolling sample analysis to capture the inherent secular and cyclical movements in the cryptocurrency market.FindingsThe authors show that there is substantial difference between the behaviour of the cryptocurrency portfolios return and volatility spillover indices over time. The authors find evidence of interdependence among cryptocurrency portfolios given the spillover indices. While the return spillover index reveals increased integration among the currency portfolios, the volatility spillover index experiences significant bursts during major market crises. Interestingly, return and volatility spillovers exhibit both trends and bursts respectively.Originality/valueThis study makes a methodological contribution by adopting Dielbold and Yilmaz (2012) approach to quantify the returns and volatility transmissions among cryptocurrencies. To the best of our knowledge, little or no study has adopted the Dielbold and Yilmaz (2012) methodology to investigate this dynamic relationship in the cryptocurrencies market. The Dielbold and Yilmaz (2012) approach provides a simple and intuitive measure of interdependence of asset returns and volatilities by exploiting the generalized vector autoregressive framework, which produces variance decompositions that are unaffected by ordering.

scholarly journals Construction of China’s financial conditions index in the post-crisis era

2019 ◽  
Vol 2 (2) ◽  
pp. 258-276
Author(s):  
Nan Li ◽  
Liu Yuanchun
Keyword(s):  
Financial Stability ◽  
Design Methodology ◽  
Predictive Power ◽  
Time Varying ◽  
Content Type ◽  
Vector Autoregressive ◽  
Financial Variables ◽  
Financial Conditions ◽  
Time Varying Parameter ◽  
Better Than

Purpose The purpose of this paper is to summarize different methods of constructing the financial conditions index (FCI) and analyze current studies on constructing FCI for China. Due to shifts of China’s financial mechanisms in the post-crisis era, conventional ways of FCI construction have their limitations. Design/methodology/approach The paper suggests improvements in two aspects, i.e. using time-varying weights and introducing non-financial variables. In the empirical study, the author first develops an FCI with fixed weights for comparison, constructs a post-crisis FCI based on time-varying parameter vector autoregressive model and finally examines the FCI with time-varying weights concerning its explanatory and predictive power for inflation. Findings Results suggest that the FCI with time-varying weights performs better than one with fixed weights and the former better reflects China’s financial conditions. Furthermore, introduction of credit availability improves the FCI. Originality/value FCI constructed in this paper goes ahead of inflation by about 11 months, and it has strong explanatory and predictive power for inflation. Constructing an appropriate FCI is important for improving the effectiveness and predictive power of the post-crisis monetary policy and foe achieving both economic and financial stability.

scholarly journals The welfare effects of coffee price volatility for Ethiopian coffee producers

2016 ◽  
Vol 8 (4) ◽  
pp. 288-304 ◽  
Author(s):  
Sushil Mohan ◽  
Firdu Gemech ◽  
Alan Reeves ◽  
John Struthers
Keyword(s):  
Design Methodology ◽  
Price Volatility ◽  
Welfare Effects ◽  
Policy Implications ◽  
Relative Risk Aversion ◽  
Welfare Gain ◽  
Content Type ◽  
Price Stabilisation ◽  
Unconditional Variance ◽  
Coffee Price

Purpose This paper aims to estimate the welfare effects for Ethiopian coffee producers from eliminating coffee price volatility. Design/methodology/approach To estimate volatility, the generalised autoregressive conditional heteroskedasticity technique is applied to monthly coffee prices in Ethiopia for the period 1976-2012. To distinguish between the unpredictable and predictable components of volatility, we obtain separate estimates of the conditional and unconditional variance of the residual. This is combined with estimates of the coefficient of relative risk aversion to measure the welfare effects from eliminating the unpredictable component of price volatility. Findings A key finding is that the welfare gain from eliminating coffee price volatility is small; the gain per producer comes to a meagre US$0.76 in a year. Originality/value This has important policy implications for the efficacy of price stabilisation mechanisms for coffee producers, i.e. any attempt to eliminate coffee price volatility at a cost may not be a preferred outcome for Ethiopian producers. The contribution of the paper lies in using the unconditional variance, as it more truly reflects price risk faced by coffee producers without overestimating it.

Markov-switching impacts of housing-market expectations on credit markets

2019 ◽  
Vol 46 (3) ◽  
pp. 381-400
Author(s):  
MeiChi Huang
Keyword(s):  
Housing Market ◽  
Design Methodology ◽  
Credit Markets ◽  
Markov Switching ◽  
Good Time ◽  
Mortgage Default ◽  
Housing Crisis ◽  
Content Type ◽  
Default Rates ◽  
Mortgage Defaults

Purpose The purpose of this paper is to investigate linkages between households’ expectations and credit markets in the housing crisis. Design/methodology/approach In the Markov-switching framework, the sample period is classified into high- and low-impact regimes based on impacts of expectations on default rates, and the good-time-to-buy (GTTB) index is chosen to proxy for expectations toward the housing-market dynamics. Findings The results suggest that in high-impact regimes, optimistic expectations are substantially associated with lower defaults for all default rates analyzed, and second mortgage defaults are more sensitive to households’ expectations than first mortgage defaults. In low-impact regimes, the GTTB index significantly influences composite and first-mortgage default rates, but its impact is insignificant for second mortgage and bankcard default rates. Originality/value The results provide compelling evidence that households’ expectations play more important roles in credit markets in turmoil periods.

On the relationship between oil and equity markets: evidence from South Asia

2017 ◽  
Vol 13 (3) ◽  
pp. 287-303 ◽  
Author(s):  
Md Hasib Noor ◽  
Anupam Dutta
Keyword(s):  
South Asian ◽  
Design Methodology ◽  
Equity Markets ◽  
Content Type ◽  
Vector Autoregressive ◽  
Volatility Transmission ◽  
Oil Market ◽  
Hedge Ratios ◽  
The Relationship ◽  
The Empirical Analysis

Purpose The purpose of this paper is to investigate the volatility linkage between global oil market and major South Asian equity markets. Design/methodology/approach In order to serve the purpose, the authors employ a recently developed vector autoregressive-generalized autoregressive conditional heteroskedastic model to examine whether shocks and volatility spill over from the oil market to various equity markets under consideration. Findings The findings of the empirical analysis suggest that all the markets studied do receive volatility from the oil market. Not surprisingly, the authors do not find any significant evidence of volatility transmission from the equity markets to the global oil market. Additionally, while computing the optimal portfolio weights and hedge ratios, the authors document that inclusion of oil in the portfolio of stocks tends to reduce the risk of the resultant portfolio. Originality/value Fully original.

scholarly journals Have institutional investors stocks portfolio strategies affected oil prices in a financialization context?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Antonio Focacci
Keyword(s):  
Financial Markets ◽  
Design Methodology ◽  
Management Strategies ◽  
Oil Prices ◽  
Content Type ◽  
Vector Autoregressive ◽  
Portfolio Strategies ◽  
Financial Perspective ◽  
Key Factor ◽  
Stock Indexes

Purpose The purpose of this paper is to investigate whether management strategies implemented by non-commercial traders may be identified as a key factor in affecting oil price paths in the conventional pre- and post-financialization periods. Design/methodology/approach By using a vector autoregressive approach the dynamic analysis of the daily stock indexes for some of the most important world economies and the oil prices is conducted starting from 1992 to the end of 2020. Findings The findings do not support the idea that the financial markets act as a privileged conduit in transmitting the shocks to the oil spot quotations. Originality/value Such a direct assessment has not been previously proposed in literature wherein – under a financial perspective – the returns are generally taken into consideration.

Dynamic analysis of sin stocks and investor sentiment

2018 ◽  
Vol 14 (5) ◽  
pp. 558-573 ◽  
Author(s):  
Daniel Liston-Perez ◽  
Juan Pablo Gutierrez
Keyword(s):  
Stock Returns ◽  
Design Methodology ◽  
Investor Sentiment ◽  
Institutional Investor ◽  
Potential Influence ◽  
Vector Autoregressive Models ◽  
Content Type ◽  
Vector Autoregressive ◽  
Dynamic Relationships ◽  
Sin Stocks

Purpose The purpose of this paper is to examine the temporal impact of individual and institutional investor sentiment on sin stock returns. Design/methodology/approach The authors estimate vector autoregressive models (VARs) to assess the dynamic relationships amongst pure sin returns and both types of investor sentiment. The justification for estimating VARs is that it allows one to study the potential influence that shocks (i.e. innovations) in individual and institutional investor sentiment might have on pure sin returns over time. Sin stock returns are separated into a market-based and pure sin component. Additionally, the authors split both measures of investor sentiment into rational- and irrational-based components. Findings This study finds that shocks to both individual and institutional rational-based sentiment positively influence pure sin returns for up to four months. However, irrational-based shocks have a positive, weaker and insignificant effect on pure sin returns. In addition, the results for the pure sin portfolio are compared to the S&P 500 and a comparables portfolio. The results show that sin stocks are less responsive than the S&P and the comparables portfolio to shocks in investor sentiment. Originality/value This study addresses some of the limitations found in the only prior study of sin stocks and investor sentiment (Perez Liston, 2016). Specially, this study investigates the link between sin stocks and sentiment in a dynamic context and also focuses the analysis on pure sin returns.

The effect of commodity price shock on the Ethiopian economy

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Naser Yenus Nuru ◽  
Hayelom Yrgaw Gereziher
Keyword(s):  
Design Methodology ◽  
Commodity Price ◽  
Real Effective Exchange Rate ◽  
Content Type ◽  
Vector Autoregressive ◽  
Price Shock ◽  
Effective Exchange ◽  
Short Run ◽  
Effective Exchange Rate ◽  
Positive Effect

PurposeThe main purpose of this study is to examine the effect of commodity price shock on the Ethiopian economy for the sample period of 1991 Q1–2016 Q1.Design/methodology/approachThe effect of commodity price shock is analyzed using Jorda's (2005) local projection method. The shock is, however, identified by applying short-run contemporaneous restrictions in a vector autoregressive model based on Cholesky decomposition.FindingsThe results signify that output is positively affected by the shock to the commodity price. In addition, domestic consumer price responds positively and significantly to world commodity price shock after the first quarter. The commodity price shock has also a positive effect, on impact, on money supply. Foreign exchange reserve increases significantly from the fourth quarter onwards and real effective exchange rate appreciates on impact, though insignificantly, in response to the increase in commodity price.Originality/valueThis paper adds to the limited available literature on the effect of commodity price shock for developing countries in general and the Ethiopian economy in particular.

Infrastructure financing and economic growth in India: an empirical investigation

2018 ◽  
Vol 23 (3) ◽  
pp. 258-273 ◽  
Author(s):  
Varun Chotia ◽  
N.V.M. Rao
Keyword(s):  
Unit Root ◽  
Design Methodology ◽  
Empirical Investigation ◽  
Positive Impact ◽  
Economic Policies ◽  
Indian Government ◽  
Content Type ◽  
Vector Autoregressive ◽  
Structural Vector ◽  
Practical Implications

Purpose This paper aims to suggest the preferred mode of financing for major sub-sectors of infrastructure: roads, seaports, telecommunication and energy by examining which mode of infrastructure financing – public, private or public–private partnership (PPP) – has the maximum positive impact on the overall GDP of India. The same exercise was carried out for the overall infrastructure sector by integrating data from all the four sub-sectors. Design/methodology/approach The structural vector autoregressive approach was used with the period of analysis taken from 1995 to 2014. The stationary properties of the variables were checked by the Phillips–Perron unit root. Findings The PPP mode of financing was found to make the maximum positive impact on the GDP of India. Considering the four sub-sectors individually, it was concluded that the private mode of financing in roads, energy and telecom sectors has the maximum positive impact on the GDP, while the PPP gives optimal benefit to the seaports sector. Practical implications Results will aid the Indian Government and policymakers to efficiently design and develop their economic policies accordingly. Originality/value The study is novel in a sense that it helps to address the lack of research into the area of infrastructure financing in India.

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