Stock Market Rumors and Credibility

2019 ◽  
Vol 33 (8) ◽  
pp. 3804-3853
Author(s):  
Daniel Schmidt
Keyword(s):  
Stock Market ◽  
Information Sharing ◽  
Stock Prices ◽  
Information Acquisition ◽  
Investment Horizon ◽  
Data Set ◽  
Market Prices ◽  
Oxford University ◽  
Credible Information ◽  
Published Paper

Abstract Stock prices occasionally move in response to unverified rumors. I propose a cheap talk model in which a rumormonger’s incentives to tell the truth depend on the interaction between her investment horizon and the information acquisition decisions of message-receiving investors. The model’s key prediction is that short investment horizons can facilitate credible information sharing between investors, thereby accelerating the information capitalization into market prices. Analyzing a data set of takeover rumors covered by U.S. newspapers, I find suggestive evidence in support of this prediction. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

scholarly journals The Dynamics of Gold Prices, Gold Mining Stock Prices and Stock Market Prices Comovements

2009 ◽  
Vol 1 (1) ◽  
Author(s):  
Claire G. Gilmore ◽  
Ginette M. McManus ◽  
Rajneesh Sharma ◽  
Ahmet Tezel
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Gold Mining ◽  
Market Prices

Macroeconomic Tail Risks and Asset Prices

2019 ◽  
Vol 33 (8) ◽  
pp. 3541-3582 ◽  
Author(s):  
David Schreindorfer
Keyword(s):  
Stock Market ◽  
Asset Prices ◽  
Equity Premium ◽  
Return Predictability ◽  
Risk Premiums ◽  
Asset Pricing Model ◽  
Oxford University ◽  
Excess Volatility ◽  
Equity Index ◽  
Published Paper

Abstract I document that dividend growth and returns on the aggregate U.S. stock market are more correlated with consumption growth in bad economic times. In a consumption-based asset pricing model with a generalized disappointment-averse investor and small, IID consumption shocks, this feature results in a realistic equity premium despite low risk aversion. The model is consistent with the main facts about stock market risk premiums inferred from equity index options, remains tightly parameterized, and allows for analytical solutions for asset prices. An extension with non-IID dynamics accounts for excess volatility and return predictability, while preserving the model’s consistency with option moments. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

scholarly journals Socioeconomic Status and Macroeconomic Expectations

2019 ◽  
Vol 33 (1) ◽  
pp. 395-432 ◽  
Author(s):  
Sreyoshi Das ◽  
Camelia M Kuhnen ◽  
Stefan Nagel
Keyword(s):  
Socioeconomic Status ◽  
Stock Market ◽  
Durable Goods ◽  
Low Ses ◽  
Market Returns ◽  
Stock Market Returns ◽  
Oxford University ◽  
Editorial Decision ◽  
Business Conditions ◽  
Published Paper

Abstract We show that individuals’ macroeconomic expectations are influenced by their socioeconomic status (SES). People with higher income or higher education are more optimistic about future macroeconomic developments, including business conditions, the national unemployment rate, and stock market returns. The spread in beliefs between high- and low-SES individuals diminishes significantly during recessions. A comparison with professional forecasters and historical data reveals that the beliefs wedge reflects excessive pessimism on the part of low-SES individuals. SES-driven expectations help explain why higher-SES individuals are more inclined to invest in the stock market and more likely to consider purchasing homes, durable goods, or cars. Received November 13, 2017; editorial decision February 12, 2019 by Editor Wei Jiang. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Performance and development of a thin stock market: the Stockholm Stock Exchange 1912–2017

2020 ◽  
pp. 1-19
Author(s):  
Kristian Rydqvist ◽  
Rong Guo
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Selection ◽  
Data Set ◽  
Transaction Prices ◽  
Limit Orders ◽  
A Value

We estimate historical stock returns for Swedish listed companies in a newly constructed data set of daily stock prices that spans more than 100 years. Stock returns exhibit all the familiar characteristics. The growth of the public sector depressed the stock market, and the process of globalization revitalized it. Banks played an important role in the early development of the stock market. There was little trading in the past, and we examine the effects on return measurement from missing data. Stock selection and the replacement of missing transaction prices through search back procedures or limit orders make little difference to a value-weighted stock price index, while ignoring the price effects of capital operations makes a big difference.

How Did Japanese Investments Influence International Art Prices?

2009 ◽  
Vol 44 (6) ◽  
pp. 1489-1514 ◽  
Author(s):  
Takato Hiraki ◽  
Akitoshi Ito ◽  
Darius A. Spieth ◽  
Naoya Takezawa
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Japanese Economy ◽  
Asset Markets ◽  
Data Set ◽  
Luxury Consumption ◽  
Market Data ◽  
Works Of Art ◽  
Export Flow ◽  
Art Prices

AbstractWe test the luxury consumption hypothesis of Ait-Sahalia, Parker, and Yogo (2004), using a unique international art price, import/export flow, and stock market data set. We find that the demand for art by Japanese collectors is positively correlated with art prices and Japanese stock prices. This correlation is magnified during the “bubble period” of the Japanese economy (the mid-1980s to the early 1990s) and gains even further strength for works of art typically favored by Japanese collectors. Our results suggest that Japanese investors (or Japanese asset markets) indeed affect international art prices—especially during the bubble period and its aftermath.

scholarly journals Historical Returns of the Market Portfolio

2019 ◽  
Vol 10 (3) ◽  
pp. 521-567 ◽  
Author(s):  
Ronald Doeswijk ◽  
Trevin Lam ◽  
Laurens Swinkels
Keyword(s):  
Standard Deviation ◽  
Asset Pricing ◽  
Corporate Finance ◽  
Set Covering ◽  
Data Set ◽  
Oxford University ◽  
Unique Data ◽  
Market Portfolio ◽  
Editorial Decision ◽  
Published Paper

Abstract We create an annual return index for the invested global multiasset market portfolio. We use a newly constructed unique data set covering the entire market of financial investors. We analyze returns and risk from 1960 to 2017, a period during which the market portfolio realized a compounded real return in U.S. dollars of 4.45%, with a standard deviation of annual returns of 11.2%. The compounded excess return was 3.39%. We publish these data on returns of the market portfolio, so they can be used for future asset pricing and corporate finance studies. Received March 4, 2019; editorial decision October 9, 2019 by Editor Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

scholarly journals Investor Information Acquisition and Money Market Fund Risk Rebalancing during the 2011–2012 Eurozone Crisis*

2019 ◽  
Vol 33 (4) ◽  
pp. 1445-1483 ◽  
Author(s):  
Emily A Gallagher ◽  
Lawrence D W Schmidt ◽  
Allan Timmermann ◽  
Russ Wermers
Keyword(s):  
Mutual Funds ◽  
Information Acquisition ◽  
Money Market ◽  
Portfolio Risk ◽  
Eurozone Crisis ◽  
Portfolio Rebalancing ◽  
Oxford University ◽  
Money Market Mutual Funds ◽  
Increasing Risk ◽  
Published Paper

Abstract We study investor redemptions and portfolio rebalancing decisions of prime money market mutual funds (MMFs) during the Eurozone crisis. We find that sophisticated investors selectively acquire information about MMFs’ risk exposures to Europe, which leads managers to withdraw funding from information-sensitive European issuers. That is, MMF managers, particularly those serving the most sophisticated investors, selectively adjust their portfolio risk exposures to avoid information-sensitive European risks, while maintaining or increasing risk exposures to other regions. This mechanism helps to explain the occurrence of selective “dry-ups” in debt markets where delegation is common and returns to information production are usually low. (JEL G01, G21, G23) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

scholarly journals EFFECT OF DIVIDEND POLICY ON STOCK PRICES

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Adnan ALİ ◽  
Farzand Ali Jan ◽  
Ilyas Sharif
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Dividend Policy ◽  
Random Effect ◽  
Capital Gains ◽  
Upward Movement ◽  
Significant Relation ◽  
Market Prices ◽  
Return On Equity ◽  
Share Prices

This investigates the effect of dividend policy on stock prices. Objective of the study is to see if there exists any relationship between dividend policy and stock prices. We analyzed 45 non-financial companies listed on KSE-100 index that have earned profits and paid dividend for a period of twelve year w.e.f. 2001. Technique adopted for sampling adopted is convenience sampling. As the nature of data is panel therefore, pooled regression, fixed and random effect tests are run. Random effect results are focused after applying Hausman’s test.Regression Results witness that Dividend per Share andRetention Ratio havean insignificant relationship with Share Market Prices.Dividend Payout Ratio has a significant positive relationship with Share Prices as supported by the Bird in hand theory suggested that owners give preference to a dollar of estimated dividends over a likely dollar of capital gains. Profit after tax, Earning per share and Return on Equity are the three control variables. Profit after Tax has insignificant relation to Stock Prices. Earnings per Share have positive significant relation to Stock Prices. There is negative significant relation between Return on Equity and Share Prices. It is recommended that firms in the sample should regularly pay dividend as it will cause an upward movement in the stock market prices. Whereas profit retention by firms will result in a decrease in the value of the stock market prices.

scholarly journals Stock Market Prices Prediction using Random Forest and Extra Tree Regression

2019 ◽  
Vol 8 (3) ◽  
pp. 1224-1228
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Research Area ◽  
Support Vector ◽  
Market Prices ◽  
Machine Learning Approach ◽  
Innovative Work

Prediction of Stock price is now a day’s an existing and interesting research area in financial and academic sectors to know the scale of economies. There did not exists any significant set of rules to estimate and predict the scale of share in the stock exchange. Many evolutionary technologies are existing such as technical, fundamental, time, statistical and series analysis which help us to attempt the prediction process, but none of the methods are proved as reliable and accurate tool to the society in the estimation of stock exchange or share market scales. Here in this paper we attempted to do innovative work through Machine Learning approach to predict or sense the behaviour tracking of the stock market sensex. Linear regression, Support Vector regression, Decision Tree, Ramdom Forest Regressor and Extra Tree Regressor are the Machine Learning models implemented effectively in predicting the stock prices and define the activity between the exchanges the securities between the buyers and sellers. We predicted the price of the stock based on the closing value and stock price. An algorithm with high accuracy we do the process of comparison for the accuracy of each of the model and finally is considered as better algorithm for predicting stock price. As share market is a vague domain we cannot predict the conditions occur, and also share market can never be predicted, this job can be done easily and technically through this work and the main aim of this paper is to apply algorithms in Machine Learning in predicting the stock prices.

scholarly journals Modelling Macroeconomic Determinants Of Stock Market Prices: Evidence From Namibia

2012 ◽  
Vol 28 (5) ◽  
pp. 871 ◽  
Author(s):  
Joel Hinaunye Eita
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Money Supply ◽  
Stock Prices ◽  
Economic Activity ◽  
Market Price ◽  
Font Size ◽  
Market Prices ◽  
Econometric Methodology ◽  
Macroeconomic Determinants

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none;" class="MsoNormal"><span lang="EN-GB" style="color: black; font-size: 10pt; mso-ansi-language: EN-GB; mso-themecolor: text1;"><span style="font-family: Times New Roman;">This paper investigates the macroeconomic determinants of stock market prices in Namibia. The investigation was conducted using a VECM econometric methodology and revealed that Namibian stock market prices are chiefly determined by economic activity, interest rates, inflation, money supply and exchange rates.<span style="mso-spacerun: yes;"> </span>An increase in economic activity and the money supply increases stock market prices, while increases in inflation and interest rates decrease stock prices.<span style="mso-spacerun: yes;"> </span>The results suggest that equities are not a hedge against inflation in Namibia, and contractionary monetary policy generally depresses stock prices.<span style="mso-spacerun: yes;"> </span>Increasing economic activity promotes stock market price development.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

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