How Important is Social Trust During the COVID-19 Crisis Period? Evidence from the Fed Announcements

2020 ◽  
Author(s):  
Sharif Mazumder
Keyword(s):  
Social Trust ◽  
Crisis Period

On the Exchange Rate Policy

2010 ◽  
pp. 21-28
Author(s):  
K. Yudaeva
Keyword(s):  
Monetary Policy ◽  
Exchange Rate ◽  
Inflation Targeting ◽  
Exchange Rate Policy ◽  
Institutional Changes ◽  
Crisis Period ◽  
Local Currency ◽  
High Inflation ◽  
Rate Policy ◽  
The Exchange Rate

The level of trust in the local currency in Russia is very low largely because of relatively high inflation. As a result, Bank of Russia during crisis times can not afford monetary policy loosening and has to fight devaluation expectations. To change the situation in the post-crisis period Russia needs to live through a continuous period of low inflation. Modified inflation targeting can help achieve such a result. However, it should be amended with institutional changes, particularly development of hedging instruments.

The Determinants of Merger Withdrawals’ Abnormal Returns in The Australian Market

2015 ◽  
pp. 89-110 ◽  
Author(s):  
Thuy Nguyen Thu ◽  
Giang Dao Thi Thu ◽  
Hoang Truong Huy
Keyword(s):  
Financial Crisis ◽  
Event Study ◽  
Abnormal Returns ◽  
Market Response ◽  
Crisis Period ◽  
Valuation Effects ◽  
Event Study Method ◽  
Private And Public ◽  
Method Of Payment ◽  
The Impact

This paper examines the abnormal returns in merger withdrawals in Australia, especially distinguishing the market response between private and public targets. We also study the determinants of those abnormal returns, including the method of payment and the impact of financial crisis periods. Using the event study method, we document that in the Australian context, the announced withdrawal of mergers involving private targets creates significantly negative valuation effects in comparison with the valuation effects in withdrawal of mergers involving public targets. We also find that a financial crisis period strongly affects abnormal returns of merger withdrawals. However, the method of payment does not have any impact on the abnormal returns.

Conceptions of Trust in the Qur'an

2011 ◽  
Vol 13 (2) ◽  
pp. 56-85 ◽  
Author(s):  
Nora S. Eggen
Keyword(s):  
Social Trust ◽  
Social Ethics ◽  
Religious Discourse ◽  
Human Being ◽  
Human Beings ◽  
Normative Claim ◽  
Trust Relationship ◽  
Trust Relationships ◽  
The Absolute ◽  
The Guardian

In the Qur'an we find different concepts of trust situated within different ethical discourses. A rather unambiguous ethico-religious discourse of the trust relationship between the believer and God can be seen embodied in conceptions of tawakkul. God is the absolute wakīl, the guardian, trustee or protector. Consequently He is the only holder of an all-encompassing trusteeship, and the normative claim upon the human being is to trust God unconditionally. There are however other, more polyvalent, conceptions of trust. The main discussion in this article evolves around the conceptions of trust as expressed in the polysemic notion of amāna, involving both trust relationships between God and man and inter-human trust relationships. This concept of trust involves both trusting and being trusted, although the strongest and most explicit normative claim put forward is on being trustworthy in terms of social ethics as well as in ethico-religious discourse. However, ‘trusting’ when it comes to fellow human beings is, as we shall see, framed in the Qur'an in less absolute terms, and conditioned by circumstantial factors; the Qur'anic antithesis to social trust is primarily betrayal, ‘khiyāna’, rather than mistrust.

TrustSVD: A Novel Trust-Based Matrix Factorization Model with User Trust and Item Ratings

2017 ◽  
Vol 7 (11) ◽  
pp. 7 ◽  
Author(s):  
K Sobha Rani
Keyword(s):  
Matrix Factorization ◽  
Social Trust ◽  
State Of The Art ◽  
Data Sets ◽  
Real World Data ◽  
Recommendation Algorithm ◽  
Active User ◽  
Factorization Model ◽  
The Social ◽  
Matrix Factorization Technique

Collaborative filtering suffers from the problems of data sparsity and cold start, which dramatically degrade recommendation performance. To help resolve these issues, we propose TrustSVD, a trust-based matrix factorization technique. By analyzing the social trust data from four real-world data sets, we conclude that not only the explicit but also the implicit influence of both ratings and trust should be taken into consideration in a recommendation model. Hence, we build on top of a state-of-the-art recommendation algorithm SVD++ which inherently involves the explicit and implicit influence of rated items, by further incorporating both the explicit and implicit influence of trusted users on the prediction of items for an active user. To our knowledge, the work reported is the first to extend SVD++ with social trust information. Experimental results on the four data sets demonstrate that our approach TrustSVD achieves better accuracy than other ten counterparts, and can better handle the concerned issues.

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