Dynamic correlations across REIT sub-sectors

The issue of whether Real Estate Investment Trusts should pursue a focused or diversified investment strategy remains an ongoing debate within both the academic and industry communities. This paper considers the relationship between REITs focused on different property sectors in a GARCH-DCC framework. The daily conditional correlations reveal that since 1990 there has been a marked upward trend in the coefficients between US REIT sub-sectors. The findings imply that REITs are behaving in a far more homogeneous manner than in the past. Furthermore, the argument that REITs should be focused in order that investors can make the diversification decision is reduced

Behavioral Corporate Finance: A Survey

Research in behavioral corporate finance takes two distinct approaches. The first emphasizes that investors are less than fully rational. It views managerial financing and investment decisions as rational responses to securities market mispricing. The second approach emphasizes that managers are less than fully rational. It studies the effect of nonstandard preferences and judgmental biases on managerial decisions. This survey reviews the theory, empirical challenges, and current evidence pertaining to each approach. Overall, the behavioral approaches help to explain a number of important financing and investment patterns. The survey closes with a list of open questions.

CLASSICAL LASSICAL AND BEHAVIOURAL FINANCE IN INVESTOR DECISION

Conceptual model of individual investor behavior presented in this paper aims to structure a part of the vast knowledge about investor behavior that is present in the finance field. The investment process could be seen as driven by dual mental processes (cognitive and affective) and the interplay between these systems contributes to bounded rational behavior manifested through various heuristics and biases. The investment decision is seen as a result of an interaction between the investor and the investment environmentinvestor behaviour; financial decisions making; cognitive modelling,;sentiments; market efficiency

Dynamic Correlations across REIT Sub-Sectors

The issue of whether Real Estate Investment Trusts should pursue a focused or diversified investment strategy remains an ongoing debate within both the academic and industry communities. This paper considers the relationship between REITs focused on different property sectors in a GARCH-DCC framework. The daily conditional correlations reveal that since 1990 there has been a marked upward trend in the coefficients between US REIT sub-sectors. The findings imply that REITs are behaving in a far more homogeneous manner than in the past. Furthermore, the argument that REITs should be focused in order that investors can make the diversification decision is reduced.

The disposition effect among mutual fund participants : a re- examination

Using information on mutual fund trades executed from 1998 to 2017 by 31,513 individual investor clients of a major Portuguese financial institution, we study the relationship between the disposition effect, financial literacy and trading experience. We find that mutual fund investors exhibit strong disposition effect. The tendency to hold losers is partially offset with literacy: not only holding a university degree reduces the propensity to hold on to loser funds but also higher financial knowledge and stronger math skills reduce the disposition effect. Literacy also plays a role in shaping the way experience affects this bias. Evidence of the disposition effect persists after accounting for redemption fees, bad emotions, irrational beliefs, market sentiment and the existence of someone to blame.info:eu-repo/semantics/publishedVersio

Integrating Non-Topical Aspects Into Information Retrieval

When users investigate a topic, they are often interested in results that are not just relevant, but also strongly opinionated or covering a range of times. To get such results, users are forced to formulate ambiguous, complex, or longer queries. Commonly this becomes a burden, since users need to issue several queries with reformulations if initial search results are not completely satisfactory. In this thesis, we focus on those two non-topical dimensions: opinionatedness and time. We develop measures for quantifying them in documents and incorporate them into search results. For improving search results with respect to non-topical dimensions, we use diversification approaches. To achieve controlled variety in results, our methods are integrated with a general bias framework, which seamlessly unifies extreme biases for each dimension. Results can be diversified across a single or multiple non-topical dimensions. Our experiments are performed on the TREC Blog Track. As a result of this research, we can determine how temporal or opinionated a unit of text is. By means of diversification we provide a retrieval framework to users with which they can more easily find different kinds of opinionated or temporal results with only one submitted query. The burden of analyzing pre-existing biases for a query and discovering times at which important events happened is fully carried by the system. As opposed to prior work in this area, pre-existing biases in search results are analyzed, and diversification is performed in a controlled manner for each dimension. We show how to combine several dimensions with individual biases for each, while also presenting approaches to time and sentiment diversification. The insights from this work will be very valuable for next generation search engines and retrieval systems

On Measuring Bias in Online Information

Bias in online information has recently become a pressing issue, with search engines, social networks and recommendation services being accused of exhibiting some form of bias. In this vision paper, we make the case for a systematic approach towards measuring bias. To this end, we discuss formal measures for quantifying the various types of bias, we outline the system components necessary for realizing them, and we highlight the related research challenges and open problems.Comment: 6 pages, 1 figur

Uncertainty triggers overreaction: evidence from corporate takeovers

Behavioural finance models suggest that under uncertainty, investors overweight their private information and overreact to it. We test this theoretical prediction in an M&A framework. We find that under high information uncertainty, when investors are more likely to possess firm-specific information, acquiring firms generate highly positive and significant gains following the announcement of private stock and private cash acquisitions (positive news) while the market heavily punishes public stock (negative news) deals. On the other hand, under conditions of low information uncertainty, when investors do not possess private information, the market reaction is complete (i.e. zero abnormal returns) irrespective of the type of acquisition. Overall, we provide empirical evidence that shows that information uncertainty plays a significant role in explaining short-run acquirer abnormal returns

Behavioral finance: Its history and its future

The field of behavioral finance has attempted to explain a litany of biases, heuristics, and inefficiencies present in financial markets since its creation in the 1980’s. This paper is structured as a comprehensive literature review of behavioral finance, and includes both the seminal works as well as more recent papers. The various subtopics of behavioral finance will also be analyzed, which include loss aversion, corporate finance, and momentum/contrarian investing. Finally, this paper will draw unique conclusions across behavioral finance and hypothesize about what topics within behavioral finance are likely to yield the most interesting research in the near future