This paper proposes a novel measure of noise trading that aims to capture uninformed retail trading. The measure, an indicator of whether the firm placed advertisement(s) in the Wall Street Journal seven calendar days earlier, is motivated by evidence that retail trading spikes seven days after ad days, that firms regularly place ads at weekly intervals, and that weekly ads frequently contain duplicate images. This ad-based measure is positively associated with informed trading and stock price volatility. Collectively, our results provide broad support for the theoretical predictions of Collin-Dufresne and Fos (2016, Econometrica).
{"title":"Noise Trading: An Ad-based Measure","authors":"Vivian W. Fang, Joshua M. Madsen, Xinyuan Shao","doi":"10.2139/ssrn.3271851","DOIUrl":"https://doi.org/10.2139/ssrn.3271851","url":null,"abstract":"This paper proposes a novel measure of noise trading that aims to capture uninformed retail trading. The measure, an indicator of whether the firm placed advertisement(s) in the Wall Street Journal seven calendar days earlier, is motivated by evidence that retail trading spikes seven days after ad days, that firms regularly place ads at weekly intervals, and that weekly ads frequently contain duplicate images. This ad-based measure is positively associated with informed trading and stock price volatility. Collectively, our results provide broad support for the theoretical predictions of Collin-Dufresne and Fos (2016, Econometrica).","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"191 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91525605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
InSc India Institute of Scholars, Dr. Kavita Patil, Dr. Sujata Chincholkar
Mutual fund industry is growing leaps and bounds in India. Numbers of investors in mutual funds are increasing rapidly. Investors invest in mutual funds either with the help of PMS or using their own judgments and knowledge. At the same time, there are sizeable numbers of people who shy away from any form of investment in stock market. Those who invest in mutual funds can share a lot about their experience of putting money into Mutual Funds. Their experiences can become a guiding path for those who still think that Mutual funds are not their cup of tea. This paper best describes the experiences of investors investing in mutual funds using primary data. Investors have shown their confidence in Mutual Fund investments. The survey revealed that mutual fund investors are taking well-informed decisions and are experiencing good returns on their investments.
{"title":"Investor's Experiences of Investing in Mutual Funds in India","authors":"InSc India Institute of Scholars, Dr. Kavita Patil, Dr. Sujata Chincholkar","doi":"10.2139/ssrn.3663877","DOIUrl":"https://doi.org/10.2139/ssrn.3663877","url":null,"abstract":"Mutual fund industry is growing leaps and bounds in India. Numbers of investors in mutual funds are increasing rapidly. Investors invest in mutual funds either with the help of PMS or using their own judgments and knowledge. At the same time, there are sizeable numbers of people who shy away from any form of investment in stock market. Those who invest in mutual funds can share a lot about their experience of putting money into Mutual Funds. Their experiences can become a guiding path for those who still think that Mutual funds are not their cup of tea. This paper best describes the experiences of investors investing in mutual funds using primary data. Investors have shown their confidence in Mutual Fund investments. The survey revealed that mutual fund investors are taking well-informed decisions and are experiencing good returns on their investments.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79163451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The effects of prior positive or negative stimuli (contrast effects) have not been extensively studied in a financial context. This study develops an experimental design to examine whether contrast effects distort the risk attitudes of individuals under a choice-based elicitation procedure. We find that individuals exposed to a positive stimulus amplify risk-seeking in investment decisions as opposed to individuals exposed to a negative stimulus. However, individuals behave similarly in making financing decisions regardless of different economic stimuli. We find that, on average, individuals spend 16% more time making financing decisions than investment decisions. The results provide robust evidence that contrast effects can lead to mistakes in investment decisions and suggest that financing decisions may require more mental effort than investment decisions.
{"title":"Contrast Effects in Investment and Financing Decisions","authors":"Jae H. Kim, E. Hoffman","doi":"10.2139/ssrn.3256087","DOIUrl":"https://doi.org/10.2139/ssrn.3256087","url":null,"abstract":"The effects of prior positive or negative stimuli (contrast effects) have not been extensively studied in a financial context. This study develops an experimental design to examine whether contrast effects distort the risk attitudes of individuals under a choice-based elicitation procedure. We find that individuals exposed to a positive stimulus amplify risk-seeking in investment decisions as opposed to individuals exposed to a negative stimulus. However, individuals behave similarly in making financing decisions regardless of different economic stimuli. We find that, on average, individuals spend 16% more time making financing decisions than investment decisions. The results provide robust evidence that contrast effects can lead to mistakes in investment decisions and suggest that financing decisions may require more mental effort than investment decisions.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88256488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We use a novel machine learning approach to tackle the problem of limit order management. Applying our framework to data, we show that the most important variable for a trader to consider is the price level of their order, followed by the queue sizes of the order book, volatility and finally queue position. Further, we show the option to cancel a limit order is valuable and contributes approximately 15% of a limit order's total expected value. This paper takes an important step towards describing pervasive features and dynamics that exist in financial markets.
{"title":"Machine Learning in a Dynamic Limit Order Market","authors":"R. Philip","doi":"10.2139/ssrn.3630018","DOIUrl":"https://doi.org/10.2139/ssrn.3630018","url":null,"abstract":"We use a novel machine learning approach to tackle the problem of limit order management. Applying our framework to data, we show that the most important variable for a trader to consider is the price level of their order, followed by the queue sizes of the order book, volatility and finally queue position. Further, we show the option to cancel a limit order is valuable and contributes approximately 15% of a limit order's total expected value. This paper takes an important step towards describing pervasive features and dynamics that exist in financial markets.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78285052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Retail investors are prone to the disposition effect and submit many more limit orders than market orders. Mechanical effects stemming from the price-contingency conditions for order executions can lead these limit orders to inflate an investor's measured disposition effect (Linnainmaa 2010). Our paper is the first to demonstrate that the relationship between the disposition effect and order choices is bi-directional. Using trading data of thousands of investors, we show that investors who are prone to the disposition effect differ from others in their use of limit orders and in their choice of limit prices.
{"title":"Retail Investors’ Disposition Effect and Order Choices","authors":"Rudy De Winne, Nhung Luong, Stefan Palan","doi":"10.2139/ssrn.3657007","DOIUrl":"https://doi.org/10.2139/ssrn.3657007","url":null,"abstract":"Retail investors are prone to the disposition effect and submit many more limit orders than market orders. Mechanical effects stemming from the price-contingency conditions for order executions can lead these limit orders to inflate an investor's measured disposition effect (Linnainmaa 2010). Our paper is the first to demonstrate that the relationship between the disposition effect and order choices is bi-directional. Using trading data of thousands of investors, we show that investors who are prone to the disposition effect differ from others in their use of limit orders and in their choice of limit prices.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91291742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We use the VIX and basic trading behavior to time entry and exit from the market. Our strategy captures 89% of the bottom and 91% from the top (you miss only 11% and 9% from the peak point, respectively). We lay our strategy down in six acts. Act I: the daily average return in the stock market is negative when VIX above 23; then sell if VIX in the way up and exceeds this threshold. Act II: the average daily return during the journey of rising VIX above 23 is -0.6%. Act III: the average daily return during the journey of declining from the peak 0.56%. Act IV: exit (enter) when you have back-to-back two downs (up) days with overall 6% or more. Act V: watch the Federal Reserve rates; exit when rates increase (decrease) during expansion (contraction). Act VII: do not trust oil prices as a predictor for future economic growth since the supply side of oil is highly politicized between OPEC and OPEC+. Collectively: when it comes to transition between bear to bull markets or vice versa, the VIX is your FIX.
{"title":"The VIX is Your FIX: a Flexible Strategy to Timing the Stock Market","authors":"Yosef Bonaparte","doi":"10.2139/ssrn.3642676","DOIUrl":"https://doi.org/10.2139/ssrn.3642676","url":null,"abstract":"We use the VIX and basic trading behavior to time entry and exit from the market. Our strategy captures 89% of the bottom and 91% from the top (you miss only 11% and 9% from the peak point, respectively). We lay our strategy down in six acts. Act I: the daily average return in the stock market is negative when VIX above 23; then sell if VIX in the way up and exceeds this threshold. Act II: the average daily return during the journey of rising VIX above 23 is -0.6%. Act III: the average daily return during the journey of declining from the peak 0.56%. Act IV: exit (enter) when you have back-to-back two downs (up) days with overall 6% or more. Act V: watch the Federal Reserve rates; exit when rates increase (decrease) during expansion (contraction). Act VII: do not trust oil prices as a predictor for future economic growth since the supply side of oil is highly politicized between OPEC and OPEC+. Collectively: when it comes to transition between bear to bull markets or vice versa, the VIX is your FIX.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82513332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lukasz Balbus, Paweł Dziewulski, K. Reffett, L. Wozny
We present a new approach to studying equilibrium dynamics in a class of stochastic games with a continuum of players with private types and strategic complementarities. We introduce a suitable equilibrium concept, called Markov Stationary Nash Distributional Equilibrium (MSNDE), prove its existence, and determine comparative statics of equilibrium paths and the steady‐state invariant distributions to which they converge. Finally, we provide numerous applications of our results including: dynamic models of growth with status concerns, social distance, and paternalistic bequests with endogenous preferences for consumption.
{"title":"Markov Distributional Equilibrium Dynamics in Games with Complementarities and No Aggregate Risk","authors":"Lukasz Balbus, Paweł Dziewulski, K. Reffett, L. Wozny","doi":"10.2139/ssrn.3642887","DOIUrl":"https://doi.org/10.2139/ssrn.3642887","url":null,"abstract":"We present a new approach to studying equilibrium dynamics in a class of stochastic games with a continuum of players with private types and strategic complementarities. We introduce a suitable equilibrium concept, called \u0000 Markov Stationary Nash Distributional Equilibrium (MSNDE), prove its existence, and determine comparative statics of equilibrium paths and the steady‐state invariant distributions to which they converge. Finally, we provide numerous applications of our results including: dynamic models of growth with status concerns, social distance, and paternalistic bequests with endogenous preferences for consumption.\u0000","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79868405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines how a target firm's trading volume, bid-ask spread, and stock return volatility respond over a two-week period to the announcement of M&A deals ("nonprice reactions"). I find that these variables are strongly correlated with changes in risk arbitrageurs' holdings surrounding the time of an announcement, whose ability to predict deal outcomes is often argued to be superior to that of other investors. I show that nonprice reactions predict deals that are more likely to be renegotiated, to feature slower completion times, and to fail even after controlling for merger arbitrage spreads and announcement returns. A trading strategy that involves investing in target firms with a low degree of failure risk, as predicted by nonprice reactions, yields positive abnormal returns. The presented results suggest that a target firm's volume, spread, and volatility after an M&A announcement reflect information about a deal's resolution not fully incorporated into stock prices and cast doubt on the notion that arbitrage spreads represent a deal's risk of failure as perceived by investors.
{"title":"Failure Risk, Risk Arbitrage, and Outcomes of Mergers and Acquisitions","authors":"Sangwon Lee","doi":"10.2139/ssrn.2941200","DOIUrl":"https://doi.org/10.2139/ssrn.2941200","url":null,"abstract":"This paper examines how a target firm's trading volume, bid-ask spread, and stock return volatility respond over a two-week period to the announcement of M&A deals (\"nonprice reactions\"). I find that these variables are strongly correlated with changes in risk arbitrageurs' holdings surrounding the time of an announcement, whose ability to predict deal outcomes is often argued to be superior to that of other investors. I show that nonprice reactions predict deals that are more likely to be renegotiated, to feature slower completion times, and to fail even after controlling for merger arbitrage spreads and announcement returns. A trading strategy that involves investing in target firms with a low degree of failure risk, as predicted by nonprice reactions, yields positive abnormal returns. The presented results suggest that a target firm's volume, spread, and volatility after an M&A announcement reflect information about a deal's resolution not fully incorporated into stock prices and cast doubt on the notion that arbitrage spreads represent a deal's risk of failure as perceived by investors.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82857847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper has analyzed the movement of US stock market during the COVID-19 pandemic. The paper has used time series analysis using Vector Autoregression (VAR) model using data from Jan 23, 2020 to June 19, 2020. The finding suggests that Standard and Poor Index which has been used as reference for capital market has shown negative causality with increase in number of new cases at global level.
{"title":"Effect of COVID-19 on Capital Market with Reference to S&P 500","authors":"Shreeram Thakur","doi":"10.2139/ssrn.3640871","DOIUrl":"https://doi.org/10.2139/ssrn.3640871","url":null,"abstract":"This paper has analyzed the movement of US stock market during the COVID-19 pandemic. The paper has used time series analysis using Vector Autoregression (VAR) model using data from Jan 23, 2020 to June 19, 2020. The finding suggests that Standard and Poor Index which has been used as reference for capital market has shown negative causality with increase in number of new cases at global level.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82365779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Bernales, Nicolás Garrido, Satchit Sagade, Marcela Valenzuela, Christian Westheide
By employing a dynamic model with two limit order books, we show that fragmentation is associated with reduced competition among liquidity suppliers and lower picking-off risk of limit orders. Due to these countervailing channels, the impact of fragmentation on liquidity and welfare differs with asset volatility: when volatility is high (low), liquidity and aggregate welfare in a fragmented market are higher (lower) than in a single market. However, fragmentation always shifts welfare away from agents with exogenous trading motives and towards intermediaries. We empirically corroborate our model’s predictions about liquidity. Our model reconciles the mixed results in the empirical literature.
{"title":"Trader Competition in Fragmented Markets: Liquidity Supply versus Picking-off Risk","authors":"A. Bernales, Nicolás Garrido, Satchit Sagade, Marcela Valenzuela, Christian Westheide","doi":"10.2139/ssrn.3276548","DOIUrl":"https://doi.org/10.2139/ssrn.3276548","url":null,"abstract":"By employing a dynamic model with two limit order books, we show that fragmentation is associated with reduced competition among liquidity suppliers and lower picking-off risk of limit orders. Due to these countervailing channels, the impact of fragmentation on liquidity and welfare differs with asset volatility: when volatility is high (low), liquidity and aggregate welfare in a fragmented market are higher (lower) than in a single market. However, fragmentation always shifts welfare away from agents with exogenous trading motives and towards intermediaries. We empirically corroborate our model’s predictions about liquidity. Our model reconciles the mixed results in the empirical literature.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76684672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：