Good Days, Bad Days: Stock Market Fluctuation and Taxi Tipping Decisions

2020 ◽  
Author(s):  
Weiqiang Tan ◽  
Jian Zhang

Using taxicab tipping records in New York City (NYC), we develop a novel measure of real-time utility and quantitatively assess the impact of wealth change on the well-being of individuals based on the core tenet of prospect theory. The baseline estimate suggests that a one-standard-deviation increase in the stock market index is associated with a 0.3% increase in the daily average tipping ratio, which translates to an elasticity estimate of 0.3. The impact is short-lived and in line with the wealth effect interpretation. Consistent with loss aversion, we find that the impact is primarily driven by wealth loss rather than gain. We exploit Global Positioning System and timestamp information and design two difference-in-differences tests to establish causal inference. Exploitation of the characteristics of individual stocks suggests that the effect of wealth change on real-time utility is more pronounced in the stocks of firms with large market capitalization. Finally, our aggregate estimate suggests that annual tip revenue in the NYC taxi industry is associated with stock market fluctuations, ranging from −$17.5 million to $12.9 million. This paper was accepted by Tyler Shumway, finance.

2017 ◽  
Vol 12 (8) ◽  
pp. 182 ◽  
Author(s):  
Mohammad AbdelMohsen Al-Afeef

This study discussed the Capital Assets Pricing model (CAPM) and its ability to measure the required return, the researcher tested this model on Amazon Company listed in S&P 500 during the period (2009-2016), to measure the impact of beta stock and market index return on the required return. Multiple regression model was used to test the effect of independent variables (Beta stock, Market Index Return) on the dependent variable (Required return), it should be noted that there is a statistically significant impact of the US stock market Return (S&P500) and Amazon stock Beta factor on Amazon stock required return, and the study model explanatory was 20% , this means that 20% of the changes in the required return are due to beta and market return, and 80% of the changes due to other factors, also find that CAPM can be applied on efficiency markets and huge companies.The researcher recommends applying the variables of the study on a group of large companies in the S&P 500 index, and looking for other factors that may affect the required return.


2020 ◽  
Vol 9 (1) ◽  
pp. 74-94
Author(s):  
Esra N Kilci

The primary aim of this study is to analyze the impact of financial services and real sector confidence indexes on some macroeconomic and financial indicators such as industrial production, inflation, stock market index, foreign exchange rates and interest rates in Turkey for the period from May 2012 to May 2019. In this study, the unit root properties of these series are tested by using the Narayan and Popp (2010) unit root test with two structural breaks and the Enders and Lee (2012) Fourier ADF unit root test with multiple structural breaks. We investigate the causal link between confidence indicators and macro-financial variables using the Fourier Toda Yamamoto causality test proposed by Nazlioglu et al. (2016). The results suggest a strong link between financial services and real sector confidence indexes on macro-financial indicators such as stock market index and inflation, supporting the evidence of the short-run impact of confidence indexes on these variables.


2020 ◽  
Vol 13 (11) ◽  
pp. 16
Author(s):  
Nader Alber ◽  
Amr Saleh

This paper attempts to investigate the effects of 2020 Covid-19 world-wide spread on stock markets of GCC countries. Coronavirus spread has been measured by cumulative cases, new cases, cumulative deaths and new deaths. Coronavirus spread has been measured by numbers per million of population, while stock market return is measured by Δ in stock market index. Papers conducted in this topic tend to analyze Coronavirus spread in the highly infected countries and focus on the developed stock markets. Countries with low level of infection that have emerging financial markets seem to be less attractive to scholars concerning with Coronavirus spread on stock markets. This is why we try to investigate the GCC stock markets reaction to Covid-19 spread.   Findings show that there are significant differences among stock market indices during the research period. Besides, stock market returns seem to be sensitive to Coronavirus new deaths. Moreover, this has been confirmed for March without any evidence about these effects during April and May 2020.


2018 ◽  
Vol 7 (2) ◽  
pp. 39-47
Author(s):  
Ibtissem Missaoui ◽  
Mohsen Brahmi ◽  
Jaleleddine BenRajeb

The aim of this article is to seek especially the impact of corruption on the bond and stock market development. For the methodology/approach, the authors analyze a sample of 20 listed Tunisian firms from the Stock Exchange and Financial market, covering the period from 2006 to 2016 by using pooling cross section techniques. The results find a significant positive effect of the level of corruption on the stock market index and the logarithm of capitalization. This is consistent with the view that corruption accelerates the economic growth by speeding up transactions and allowing private companies to overcome the inefficiencies imposed by the government. Furthermore, the results find a negative association is not significant with the dependent variable of traded value as a percentage of the number of listed companies.


2021 ◽  
Vol 25 ◽  
pp. 260-272
Author(s):  
Greta Keliuotyte-Staniuleniene ◽  
Julius Kviklis

This research aims to assess the impact of the spread of the COVID-19 pandemic on the Baltic stock market. To reach this aim, the methods of bivariate (OLS) regression and VAR-based impulse response functions are employed. We use daily new cases of COVID-19 as well as the cumulative number of COVID-19 cases as independent and OMX Baltic Benchmark GI index as dependent variables for our research. The research period, covering data from 2020 March 1st  to 2020 November 21st, is divided into three separate periods, reflecting the different phases of the spread of the COVID-19 pandemic. The results of the research revealed that the market reaction differs depending on the period; moreover, the Baltic stock market index was affected by new cases and total cases in a slightly different manner.


Author(s):  
Shahid Raza ◽  
Baiqing Sun ◽  
Pwint Kay Khine

This study will investigate different signals and events/news that determined the stock market's movements. As we know, many factors affect the stock market on a daily, weekly, and monthly basis, e.g., rate of interest, exchange rate, and oil prices, etc. Our research will investigate the impact of daily events/news in the KSE-100 index due to several policies announced and events/news in the country because the daily movements in the stock market can be determined only by different signals and events/news. Time series data is collected daily for particular reasons from "The News" (Daily Newspaper, Sunday edition) from 2010 to 2019. The results of this study show that political and global news affects the stock market index ferociously. For investors, the investment in blue chips is not less than a safe haven. When day-to-day transactions are concerned, there is always a higher panic attack than the herd behaviour in the stock exchange. Investors tend to make prompt responses to negative rather than positive news, which makes them risk averters. Our finding also confirmed that the ARCH/GARCH model is better than the simple OLS method concerning stock market upheaval.


2008 ◽  
Vol 12 (4) ◽  
pp. 44
Author(s):  
Glauber de Castro Barbosa ◽  
Otávio Ribeiro de Medeiros

The study has the purpose of analyzing the behavior of the Brazilian stock market in order to verify the existence of market efficiency immediately after the occurrence of favorable and unfavorable events (shocks). To achieve this purpose, an event study is performed in which the return on the Brazilian stock market index (Ibovespa) is regressed against the return on the Dow Jones stock market index, which represents the New York Stock Exchange, adopted as a proxy for the world stock market index. Regression residuals appearing as outliers above +2.5% or below –2.5% were adopted to determine positive and negative events, respectively. Cumulative Abnormal Returns were computed and tested for a period of 10 days after the events. The empirical results led to the conclusion that market efficiency is not observed both after positive and negative shocks, but an overreaction behavior is observed instead. Key words: economic shocks. Market efficiency. Overreaction. Uncertain information hypothesis. Underreaction. Event study.


2021 ◽  
Vol 7 (3) ◽  
pp. 383-394
Author(s):  
Rukhsana Rasheed ◽  
Mazhar Nadeem Ishaq ◽  
Rabia Anwar ◽  
Mehwish Shahid

In all emerging economies, one of the most challenging issues for investors is the multifaceted inter-relationship between volatility of gold prices and stock market index. During the COVID-19 sub-periods, gold has shown a strong hedging behavior against stock market performance. The main objective of this study was to quantify the long-run relationship among multiple independent macroeconomic variables (predictors) on stock market index (response variable) using the volatilities of gold prices as a mediator factor. This study applied the descriptive statistics, correlation, t-test and OLS multiple regression Model. The specific data comprised of period 2011-2020 regarding the fluctuations in gold prices, exchange rate, interest rate, inflation rate and performance of stock market index has been utilized. The statistical outputs of models showed that exchange rate (Dollar to PKR) was positively affecting the performance of Karachi Stock Exchange (KSE)-100 Index, whereas inflation rate and interest rate were negatively affecting the overall performance of KSE100 index. The findings of this study suggested that to achieve better performance of stock market, relatively low interest rate and inflation rate contribute a significant role. However, to increase the generalization capabilities of this study the impact of mentioned macroeconomic variables in other sectors like industrial production, oil & gas and energy sectors with wider time span can be more helpful.


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