U.K. Financial Market Returns, 1955–2000

CFA Digest ◽  
2001 ◽  
Vol 31 (3) ◽  
pp. 56-58
Author(s):  
Joseph Spivack
2021 ◽  
Author(s):  
Charles A. Aziegbemhin

Many techniques like technical analysis, fundamental analysis, neural networks etc are used to forecast market behavior but none of these methods has been consistently acceptable forecasting tool. This thesis surveys more than 200 related published articles that study investor sentiment techniques as derived and applied to forecasting equity, debt and alternative markets. From the literatures, it shows that the application of investor sentiment for evaluating market behavior is gaining wide acceptance. Changes in investor sentiment can trigger changes in the valuation and pricing of assets, therefore offering the ability to forecasting market directions more accurately than other techniques. This study is the most comprehensive survey on investor sentiment techniques and its impact on forecasting a panel of assets in the equity, debt, derivative and other alternative investment markets. It examines forecasting as it affects sentiment, investor sentiment, it influence on market returns, news analytics and its use as profit and risk management tool.


1998 ◽  
Vol 24 (8) ◽  
pp. 16-25
Author(s):  
Michael J. Seiler ◽  
Peter Shyu ◽  
J.L. Sharma

Author(s):  
Osamah Al-Khazali

Virtually all previous studies of seasonal variation in stock returns have used mean/variance analysis despite it being well documented that stock returns in developed and emerging markets are non-normally distributed. This paper details the distributional characteristics of emerging Amman financial market returns. Further more, it uses stochastic dominance and parametric analyses to investigate the turn-of-the-year and the-week effects from 1978 to 2001. Results indicate that returns of Amman financial market exhibit substantial deviation from normality. And parametric analysis tests show there is January and week effects. However, stochastic dominance results indicate that January and week effects are not exist in the AFM. This implies that the results of parametric analysis are being driven by violations of parametric assumptions.


Author(s):  
Neşe Algan ◽  
Mehmet Balcılar ◽  
Harun Bal ◽  
Müge Manga

This study investigates the impact of terrorism on the Turkish financial market using daily data from Jan 4, 1988 to May 24, 2016. In order to measure the impacts of terrorist attacks in Turkey we test for causality from terrorism index to returns and volatilities of 3 aggregate and 16 sector level stock indices using a recently developed nonparametric causality-in-test test of Balcilar et al. (2016). The results obtained indicate that there is no causality from terrorist activities to stock market returns (1st moment). However, we find significant causality at various quantiles from terrorist activates to volatility (2nd moment) of tourism, food and basic materials sectors.


Author(s):  
G. P. Samanta

This chapter deals with the measurement of Value-at-Risk parameter for a portfolio using historical returns. The main issue here is the estimation of suitable percentile of the underlying return distribution. If returns were normal variates, the task would have been very simple. But it is well documented in the literature that financial market returns seldom follow normal distribution. So, one has to identify suitable distribution, mostly other than normal, for the returns and find out the percentile of the identified distribution. The class of non-normal distribution, however, is extremely wide and heterogeneous, and one faces a decision-making problem of identifying the best distributional form from such a wide class of potential alternatives. In order to simplify the task of handling non-normality while estimating VaR, we adopt the transformation-based approach used in Samanta (2003). The performance of the transformation-based approach is compared with two widely used VaR models. Empirical results are quite encouraging and identify the transformation-based approach as a useful and sensible alternative.


Organizacija ◽  
2017 ◽  
Vol 50 (2) ◽  
pp. 97-111
Author(s):  
Andrzej Cwynar ◽  
Wiktor Cwynar ◽  
Robert Pater

Abstract Background and Purpose: In recent years classic financial market theory based on decision makers’ rationality has been challenged by repeated anomalies that became a ‘new normal’. As a result, what we witness today is a considerable turn to behavioral concepts that can shed a new light on choices made by market participants. The astonishing development of social media accelerated scientific validation of such concepts, since the media opened new and capacious ‘laboratory space’ for testing behavioral hypotheses. The main purpose of the article is to examine whether financial market professionals believe that social media content can be useful in achieving additional financial market returns and to investigate the factors behind this belief. Design/Methodology/Approach: We surveyed a sample of over 400 financial market professionals at institutions operating in Poland, and analyzed the results using logit regression models. Results: We established that almost 60% of the surveyed finance professionals recognized the potential of social media for achieving additional returns. We also found out that the differences in respondents’ perception of this potential could be explained mainly by heterogeneity of their job experience and, to a lesser degree, by their job position. Interestingly, more experienced individuals were less likely to recognize this potential. Firm-specific factors did not have a significant effect on the dependent variable. Conclusion: The opinions of financial market professionals regarding the link between social media and additional returns are mixed, which is consistent with the current body of evidence brought by sentiment-based research. Our findings confirm the key role of previous experience in explaining attitudes towards novelties and innovations (such as social media), a phenomenon known from other fields and everyday experience.


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