Time-varying diversification strategies: The roles of state-level housing assets in optimal portfolios

2018 ◽  
Vol 55 ◽  
pp. 145-172 ◽  
Author(s):  
MeiChi Huang
Keyword(s):  
State Level ◽  
Time Varying ◽  
Optimal Portfolios ◽  
Diversification Strategies ◽  
Housing Assets

Structural change and economic growth in India: a comparative study of Punjab

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anirban Sanyal ◽  
Nirvikar Singh
Keyword(s):  
Economic Growth ◽  
Structural Change ◽  
Structural Changes ◽  
Green Revolution ◽  
State Level ◽  
Productivity Change ◽  
Time Varying ◽  
Content Type ◽  
Panel Regressions ◽  
Time Varying Parameter

Purpose The Green Revolution transformed agriculture in the Indian State of Punjab, with positive spillovers to the rest of India, but recently the state’s economy has fallen dramatically in rankings of per capita state output. Understanding the trajectory of Punjab’s economy has important lessons for all of India. Economic development is typically associated with changes in economic structure, but Punjab has remained relatively reliant on agriculture rather than shifting economic activity to manufacturing and services, where productivity growth might be greater. Design/methodology/approach The authors empirically examine structural change in the Punjab economy in the context of structural change and economic growth across the States of India. The authors calculate structural change indices and map their pattern over time. The authors estimate panel regressions and time-varying parameter regressions, as well as performing productivity change decompositions into within-sector and structural changes. Findings Panel regressions and time-varying-coefficient regressions suggest a significant positive influence of structural change on state-level growth. In addition, growth positively affected structural change across India’s states. The relative lack of structural change in Punjab’s economy is implicated in its relatively poor recent growth performance. Comparisons with a handful of other states reinforce this conclusion: Punjab’s lack of economic diversification is a plausible explanation for its lagging economic performance. Originality/value This paper performs a novel empirical analysis of structural change and growth, simultaneously using three different approaches: panel regressions, time-varying parameter regressions and productivity decompositions. To the best of the authors’ knowledge, it is the only paper we are aware of that combines these three approaches.

scholarly journals Risk Appetite and Jumps in Realized Correlation

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2255
Author(s):  
Riza Demirer ◽  
Konstantinos Gkillas ◽  
Christos Kountzakis ◽  
Amaryllis Mavragani
Keyword(s):  
Risk Aversion ◽  
Financial Markets ◽  
Cash Flow ◽  
Predictive Power ◽  
Investor Sentiment ◽  
Time Varying ◽  
Risk Appetite ◽  
Diversification Strategies ◽  
Intraday Data

This paper examines the role of non-cash flow factors over correlation jumps in financial markets. Utilizing time-varying risk aversion measure as a proxy for investor sentiment and the cross-quantilogram method applied to intraday data, we show that risk aversion captures significant predictive power over realized stock-bond correlation jumps at different quantiles and lags. The predictive relation between correlation jumps and time-varying risk aversion is found to be asymmetric, as we detect a heterogeneous dependence pattern across different quantiles and lag orders. Our findings underline the importance of non-cash flow factors over correlation jumps, highlighting the role of behavioral factors in optimal portfolio allocations and the effectiveness of diversification strategies.

scholarly journals Understanding how Victoria, Australia gained control of its second COVID-19 wave

2021 ◽  
Author(s):  
James M Trauer ◽  
Michael J Lydeamore ◽  
Gregory W Dalton ◽  
David V Pilcher ◽  
Michael T Meehan ◽  
...  
Keyword(s):  
State Level ◽  
Credible Interval ◽  
Adverse Outcomes ◽  
Transmission Risk ◽  
Service Needs ◽  
Time Varying ◽  
Population Mobility ◽  
Detection Rates ◽  
Individual Level ◽  
Policy Interventions

Victoria has been Australia's hardest hit state by the COVID-19 pandemic, but was successful in reversing its second wave of infections through aggressive policy interventions. The clear reversal in the epidemic trajectory combined with information on the timing and geographical scope of policy interventions offers the opportunity to estimate the relative contribution of each change. We developed a compartmental model of the COVID-19 epidemic in Victoria that incorporated age and geographical structure, and calibrated it to data on case notifications, deaths and health service needs according to the administrative divisions of Victoria's healthcare, termed clusters. We achieved a good fit to epidemiological indicators, at both the state level and for individual clusters, through a combination of time-varying processes that included changes to case detection rates, population mobility, school closures, seasonal forcing, physical distancing and use of face coverings. Estimates of the risk of hospitalisation and death among persons with disease that were needed to achieve this close fit were markedly higher than international estimates, likely reflecting the concentration of the epidemic in groups at particular risk of adverse outcomes, such as residential facilities. Otherwise, most fitted parameters were consistent with the existing literature on COVID-19 epidemiology and outcomes. We estimated a significant effect for each of the calibrated time-varying processes on reducing the risk of transmission per contact, with broad estimates of the reduction in transmission risk attributable to seasonal forcing (27.8%, 95% credible interval [95%CI] 9.26-44.7% for mid-summer compared to mid-winter), but narrower estimates for the individual-level effect of physical distancing of 12.5% (95%CI 5.69-27.9%) and of face coverings of 39.1% (95%CI 31.3-45.8%). That the multi-factorial public health interventions and mobility restrictions led to the dramatic reversal in the epidemic trajectory is supported by our model results, with the mandatory face coverings likely to have been particularly important.

scholarly journals Time-Varying Conditional Co-movement between Inter-Sector Stock Returns: Evidence from Ghana Stock Market

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Thomas Appiah ◽  
Abednego Forson
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Time Varying ◽  
Conditional Correlation ◽  
Domestic Markets ◽  
Dynamic Conditional Correlation ◽  
Fund Managers ◽  
Diversification Strategies ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Sector Returns

Investors generally exhibit home bias with regards to their investment destinations. To diversify their portfolio, such investors invest in different sectors within the domestic economy. However, such behaviour could be counter-productive in periods of increased co-movement of assets returns.  In this paper, we examine the inter-sector stock return co-movement among the major sectors of the Ghanaian economy with the view to shedding some light on the nature of assets return correlations and its implications for portfolio diversification.  A sample of 332 weekly observations of stock returns of five major sectors within the Ghanaian economy is used to undertake the analysis. Dynamic Conditional Correlation - Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) techniques are applied to the weekly stock return series from January 2010 to June 2017. The DCC-GARCH model was estimated with correlation targeting and asymmetric DCC. We find dynamic conditional correlation among stock returns of all the sectors, implying that the correlation between the sector returns is time-varying. This result challenges the assumption of constant correlation among stock returns of different sectors in the domestic markets. We also find that the conditional correlation between returns of the various sectors ranges from 0.234 to 0.998, which indicates medium to very high interdependence among the stock returns. Based on the result of this study, we propose that fund managers and investors should not limit their diversification strategies to inter-sector investments since in periods of uncertainty, the ability of the investor to enjoy diversification benefits is seriously undermined.

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