Search results

The purpose of this study is to determine which quantitative metrics are most representative of investor sentiment in the US equity markets. Sentiment is the aggregation of consumers', investors', and producers' thoughts and opinions about the future of the financial markets. By analyzing the change in popular economic indicators, financial market statistics, and sentiment reports, we can gain information on investor reactions. Furthermore, we will use machine learning techniques to develop predictive models that will attempt to forecast whether the stock market will go up or down based on the percent change in these indicators.

Given the maturation of the internet and virtual communities, an important emerging issue in the humanities and social sciences is how to accurately analyze the vast quantity of documents on public and social network websites. Therefore, this chapter integrates political blogs and news articles to develop a public mood dynamic prediction model for the stock market, while referencing the behavioral finance perspective and online political community characteristics. The goal of this chapter is to apply a big data and opinion mining approach to a sentiment analysis for the relationship between political status and economic development in Taiwan. The proposed model is verified using experimental datasets collected from ChinaTimes.com, cnYES.com, Yahoo stock market news, and Google stock market news, covering the period from January 1, 2016 to June 30, 2017. The empirical results indicate the accuracy rate with which the proposed model forecasts stock prices.

Purpose: Investor sentiment in financial markets has a close relationship with the general mood prevailing in the environment such as economic, social and political life. Future economic expectations are important for both investors and policymakers. Investor sentiment and macroeconomic variables are likely to affect each other. Emerging countries are particularly sensitive to interest and foreign exchange risk. Turkey is an important emerging country. The effects of interest rate and exchange fluctuations are high in this country. The aim of this study is to reveal the relationship between investor sentiment and interest and foreign exchange rates in Turkey.

Methodology: This study investigates the relationship between economic confidence index, exchange rates and interest rates in Turkey during the period between January 2012 and November 2019 using monthly data sets. The economic confidence index is used to represent the investor sentiment in the study. Interest rate variables are the deposit interest rates and the commercial credit interest rates. The representative of the US dollar currency variables is included in the analysis. This chapter used the time series vector error correction model approach of stationarity test, cointegration test and Granger causality test.

Findings: According to the causality test, there is a two-way relationship between economic confidence index and exchange rate, and there is uni-directional causality from commercial credit interest rate to economic confidence index. The results show that foreign exchange and commercial credit interest rate variables are carefully monitored by market players and are effective and influential in the formation of future expectations.

Originality/value: The study shows the direction of the relationship between economic confidence foreign exchange and commercial credit interest rate. Policymakers can shape expectations by taking into account the direction of the relationship.

In this chapter our objective was to gain an understanding of what affects Maltese individuals’ behaviors when it comes to retirement planning. Given that longevity is on the increase, state pension income is limited (and most probably unsustainable over the long term) and that many individuals expect to be able to enjoy a comfortable retirement, it sets out to determine which macro- and micro-environmental factors are likely to encourage positive behavior or otherwise.

We did this by consulting and analyzing existing literature in chapter 8 of this book and designing an online survey which was specifically created to capture qualitative data about public sentiment and behaviors with respect to retirement planning.

The study identifies a general sense of confusion in relation to financial concepts related to retirement. In line with other countries’ findings, the prevalence of myopia, procrastination and inertia has also been observed through the research undertaken.

Through established behavioral finance theories and literature, as well as actual European practical examples, the research explores the best ways of “nudging” people into recognizing the importance of acting and making the right long-term financial decisions, to their own benefit and to that of society.

Notwithstanding, that overall savings of the Maltese are around the average established for Europe, the study found that savings tend to be shorter term, and therefore insignificant when considering the actual requirements for the desired quality of life at retirement. The research showed how, as with other countries, behavioral biases have been limiting people from acting or making the right choices.

Of the most prominent of behaviors, procrastination, myopia, and inertia were observed. In the local market, these seemed to stem from a sense of disorientation as to the meaning of certain concepts, how to initiate the process and which actions to take. In fact, although many did not admit it outright, respondents showed low levels of confidence in their abilities, and avoid acting out of fear that it may not be the right choice. At the same time, they would try to rationalize their lack of action by the premise that things would sort themselves out, although this is typically labeled as overconfidence, it is likely to be an attempt to feel better about their stance on the matter.

Terrorist events are unforeseen and have the potential to shake and rattle markets and investors. The purpose of this study is to examine whether major terrorist incidents have affected the Economic Sentiment Indicator (ESI) in four European countries.

An index is constructed that weights the severity of each event and then used to evaluate through the use of vector autoregressive and impulse response analysis estimation techniques whether or not and to what extent the ESI has been affected.

Effects were more pronounced and evident in the case of France and Germany while the ESI in Spain and Great Britain did not appear to be particularly affected by terrorist incidents.

The effects of terrorism on economic sentiment in other countries will provide additional evidence that will allow more robust and conclusive statistical inferences.

The impact of terrorist activity on the ESI for the four European countries studied here has not been examined before using VAR and impulse response analysis.

This chapter derives sentiment indicators (implied volatility and implied skewness) from the option pricing models of Corrado and Su (1996), Bakshi, Kapadia, and Madan (2003), and Zhang, Zhen, Sun, and Zhao (2017), and then integrates these sentiment indicators with artificial intelligence deep neural network (AIDNN) for developing the behavioral finance AIDNN (BFAIDNN) algorithms. We apply the BFAIDNN algorithms to daily derivatives data of Taiwan Futures and Options markets from 2015 to 2017. Our results demonstrate that the trading strategies established by the BFAIDNN algorithms can generate positive rewards.

Since Jan. 1, 2019, the Centers for Medicare and Medicaid Services' (CMS) rule requiring hospitals publish their “standard charges” (also called “charge description masters” or “chargemasters”) in a public, machine-readable format has been in effect. The research at hand assesses hospital compliance with the federal regulation. In addition, a sentiment analysis of the chargemaster webpages compared to hospital homepages is performed to assess the consumer friendliness of the content in terms of language usage. A stratified sample of 212 hospitals was used to conduct observations. Strata were based on patient satisfaction scores drawn from the Hospital Consumer Assessment of health care Providers and Systems survey, and controls for hospital bed size and geographic US census region were utilized from the American Hospital Association Annual Survey. Descriptive statistics are presented, and chi-square testing is used to test for statistically significant differences. Key results are presented for compliance and sentiment. Most hospitals' websites are not presenting chargemaster data in a way that is readily collectable or comparable to other facilities. In addition, the tone of language used on chargemaster transparency webpages is generally more negative than that of hospitals' homepages. In particular, the messaging on transparency pages routinely suggests consumers to not use the data for decision-making purposes.

The Japanese economy experienced prosperity during the bubble economy and has suffered from a prolonged recession since the bubble economy collapsed. This paper examines how the interest-bearing debt burden, structural change, and instability of confidence affect dynamic systems. Moreover, it examines these factors in the Japanese economy by applying a recursive vector autoregression analysis. This paper emphasizes the interest-bearing debt burden, the economic structure resulting from the instability of confidence, and the instability of confidence resulting from debt burden play important roles in the instability of the economy. As a result, Japan’s economy was determined to be relatively stable from 1980 to 1996, but was unstable, thereafter.