The Impact of Monetary Policy on Stock Market Bubbles and Trading Behavior: Evidence from the Lab

Author(s):  
Urs Fischbacher ◽  
Thorsten Hens ◽  
Stefan Zeisberger

2013 ◽  
Vol 37 (10) ◽  
pp. 2104-2122 ◽  
Author(s):  
Urs Fischbacher ◽  
Thorsten Hens ◽  
Stefan Zeisberger




Author(s):  
Vladimír Pícha

This paper observes effect of money supply on the stock market through the portfolio balance channel as a transmission mechanism of monetary policy. National flow of funds accounts, specifically assets from US households’ portfolios, represent a key data source. Johansen’s cointegration methodology is employed in the empirical part of the paper to analyze both short term and long term relationships among researched variables. Estimates of vector error correction model help to reliably quantify intensity of the effect. Results show money supply excercises influence on valuation of S&P 500 index with 6 months lag. The impact is also distinguishable in the long run, whereas all observed asset classes can positively influence price of S&P 500. Findings are then contextualized in the concluding part of the paper using a monetary policy framework.



2016 ◽  
Vol 23 (02) ◽  
pp. 02-21
Author(s):  
Ly Tran Thi Hai

This study investigates the impact of monetary policy on liquidity of Vietnam’s stock market from September 2007 to November 2014. Time series of liquidity are determined by monthly liquidity data for 643 enterprises in the surveyed period. Two variables of the monetary policy, including growth in money supply and interbank rate, are employed in VAR model along with four different measures of market liquidity. The results show that unexpected variance in the two monetary policy variables has no significant impact on the market liquidity, which, in turn, may be improved by the positive shocks of market returns, inflation, and growth in industrial production. Market variance does produce certain effects, but discrepancies occur in the signs of various liquidity measures.





2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhongdong Chen

PurposeThis study disentangles the investor-base effect and the information effect of investor attention. The former leads to a larger investor base and higher stock returns, while the latter facilitates the dissemination of information among investors and impacts informational trading.Design/methodology/approachUsing positive volume shocks as a proxy for increased investor attention, this study evaluates the impacts of the investor-base effect and the information effect of investor attention on market correction following extreme daily returns in the US stock market from 1966 to 2018.FindingsThis study finds that the investor-base effect increases subsequent returns of both daily winner and daily loser stocks. The information effect leads to economically less significant return reversals for both the daily winner and daily loser stocks. These two effects tend to have economically more significant impacts on the daily loser stocks. The economic significance of these two effects is also related to firm size and the state of the stock market.Originality/valueThis study is the first to disentangle the investor-base effect and the information effect of increased investor attention. The evidence that the information effect facilitates the dissemination of new information and impacts stock returns contributes to the strand of studies on the impact of investor attention on market efficiency. This evidence also contributes to the strand of studies analyzing the impact of informational trading on stock returns. In addition, this study provides evidence for market overreaction and the subsequent correction. The results for up and down markets contribute to the literature on the investors' trading behavior.



2017 ◽  
Vol 43 (5) ◽  
pp. 545-566 ◽  
Author(s):  
Muhammad Zubair Tauni ◽  
Zia-ur-Rehman Rao ◽  
Hong-Xing Fang ◽  
Minghao Gao

Purpose The purpose of this paper is to investigate the impact of the key sources of information, namely, financial advice, word-of-mouth communication and specialized press, on trading behavior of Chinese stock investors. The study also analyzed if the association between the key sources of information and trading behavior is influenced by investor personality. Design/methodology/approach The authors adopted the Big Five personality framework and examined the survey results of individual stock investors (n=541) in China. Personality traits of investors were measured by the NEO-Five Factor Inventory (Costa and McCrae, 1989). The authors performed probit regression analysis to evaluate the moderating influence of investor personality traits on the association between sources of information and stock trading behavior. Findings The results of the study confirm the previous findings that the key sources of information used by investors as a foundation of their financial choices have a significant influence on their trading behavior. The study also provides empirical evidence that investor personality traits moderate the relationship between the key sources of information and trading behavior. Financial advisors tend to increase the frequency of trading in investors with openness, extraversion, neuroticism and agreeableness personality traits, and tend to decrease the intensity of trading in investors with conscientiousness trait. On the other hand, financial information acquired from word-of-mouth communication is more likely to enhance trading frequency in extraverted and agreeable investors, and is more likely to reduce trading frequency in investors with openness, conscientiousness and neuroticism traits. Finally, the use of specialized press leads to more adjustment in portfolios of the investors with openness and conscientiousness traits than those with other personality traits. An alternative mediated model was not supported. Originality/value This research contributes to information search literature and behavioral finance literature and provides empirical evidence that the psychological characteristics of investors are significant predictors of the variations in information-trading link. The study offers new theoretical insights of investors’ behavior due to the characteristics of Chinese stock market which are unique from other stock markets in the world. To the authors’ best knowledge, no previous study has been conducted so far in Chinese stock market to explore variations with regards to the impact of the key sources of information on trading behavior by the Big Five investor personality and this paper seeks to fill this gap.



2019 ◽  
Vol 1 (1) ◽  
pp. 35-46
Author(s):  
Muhammad Rasyidin ◽  
Zunaidah Sulong

AbstractPurpose - The impact of stock market and capital formation on economic growth in Indonesia for the period of January 2015 – May 2019. This paper examines a long-run equilibrium relation between stock market, capital formation and economic growth and other control variables.Method - This study uses autoregressive distributed lag (ARDL) model.Result - Findings revealed that none of the models was stationary at level but were all stationary at first difference. There is not a short run significant relationship between stock market, capital formation and economic growth in Indonesia. In the long run, capital formation has a significant positive association on economic growth and a negative non-significant relationship between stock market and economic growth in Indonesia.Implication - This research is useful to know the response of Sharia market to monetary policy instruments in Indonesia so that the Sharia stock market strategy is potentially developing in the future to encourage the achievement of characteristics such as An alternative source of financing and investment for economic actors and able to facilitate risk mitigation needs for market participants and able to drive the efficiency of transactions in the market through the improvement of the quality of stock market infrastructure Sharia.  Originality - The update of this research is response of Sharia stock market response to monetary policy instruments in Indonesia that are researched using ARDL models.



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