Informed Trading Volume and Asset Prices: The Role for Aggressive Investors

2017 ◽  
Author(s):  
Christian T. Lundblad ◽  
Zhishu Yang ◽  
Qi Zhang
Keyword(s):  
Asset Prices ◽  
Trading Volume ◽  
Informed Trading

scholarly journals Asset Prices and Trading Volume Under Fixed Transactions Costs

10.3386/w8311 ◽  
2001 ◽  
Author(s):  
Andrew Lo ◽  
Harry Mamaysky ◽  
Jiang Wang
Keyword(s):  
Asset Prices ◽  
Trading Volume ◽  
Transactions Costs

Asset Prices and Trading Volume in a Beauty Contest

1998 ◽  
Vol 65 (2) ◽  
pp. 307-340 ◽  
Author(s):  
Bruno Biais ◽  
Peter Bossaerts
Keyword(s):  
Asset Prices ◽  
Trading Volume ◽  
Beauty Contest

scholarly journals Asset Prices and Trading Volume under Fixed Transactions Costs

2004 ◽  
Vol 112 (5) ◽  
pp. 1054-1090 ◽  
Author(s):  
Andrew W. Lo ◽  
Harry Mamaysky ◽  
Jiang Wang
Keyword(s):  
Asset Prices ◽  
Trading Volume ◽  
Transactions Costs

scholarly journals Heterogeneous traders, price-volume signals, and complex asset price dynamics

2005 ◽  
Vol 2005 (1) ◽  
pp. 19-29 ◽  
Author(s):  
Frank H. Westerhoff
Keyword(s):  
Asset Pricing ◽  
Asset Prices ◽  
Trading Volume ◽  
Deterministic Model ◽  
Asset Price ◽  
Pricing Model ◽  
Price Trend ◽  
Asset Pricing Model ◽  
Intrinsic Values ◽  
Current Price

We seek to develop a novel asset pricing model with heterogeneous traders. Fundamental traders expect that asset prices converge towards their intrinsic values, whereas chart traders rely on both price and volume signals to determine their orders. To be precise, the larger the trading volume, the more they believe in the persistence of the current price trend. Simulations of our nonlinear deterministic model reveal that interactions between fundamentalists and chartists may cause intricate endogenous price fluctuations. Contrary to the intuition, we find that chart trading may increase market stability.

Effects of Introducing Equity-Linked Warrants on Stock Market Behavior

2010 ◽  
Vol 18 (4) ◽  
pp. 23-50
Author(s):  
Doojin Ryu
Keyword(s):  
Stock Price ◽  
Trading Volume ◽  
Informed Trading ◽  
Short Sales ◽  
Short Sale ◽  
Market Completeness ◽  
Announcement Date ◽  
Event Date ◽  
Study Methodology ◽  
Event Study Methodology

This paper investigates the effects of introducing equity-linked warrants (ELWs) on the stock price, trading volume, volatility, and systematic risk (beta) by using the event study methodology. The study defines the event date as the announcement date as well as the listing date. In addition, whereas previous research has investigated only call ELWs, this study analyzes the effects of introducing both call and put ELWs. The results provide no evidence of hedging effects of issuers before the announcement dates and information effects after the announcement dates. In addition, we can't find any significant changes of variables associated with the market completeness hypothesis near the listing dates. However, the trading volume of the stock tends to increase in the days immediately following the listing of call ELWs, which may be due to the “informed trading effect”. The empirical results also provide support for the “diminishing short-sales restrictions” hypothesis related to the listing of put ELWs, which implies that short-sale restrictions can be reduced because put ELWs can provide investors with short positions in the underlying stock.

Information, Trading Volume, and International Stock Return Comovements: Evidence from Cross-Listed Stocks

2009 ◽  
Vol 44 (4) ◽  
pp. 953-986 ◽  
Author(s):  
Louis Gagnon ◽  
G. Andrew Karolyi
Keyword(s):  
Trading Volume ◽  
Stock Return ◽  
High Volume ◽  
Informed Trading ◽  
Home Market ◽  
Heterogeneous Agent ◽  
Portfolio Rebalancing ◽  
Joint Dynamics ◽  
The U.S

AbstractWe investigate the joint dynamics of returns and trading volume of 556 foreign stocks cross-listed on U.S. markets. Heterogeneous-agent trading models rationalize how trading volume reflects the quality of traders’ information signals and how it helps to disentangle whether returns are associated with portfolio-rebalancing trades or information-motivated trades. Based on these models, we hypothesize that returns in the home (U.S.) market on high-volume days are more likely to continue to spill over into the U.S. (home) market for those cross-listed stocks subject to the risk of greater informed trading. Our empirical evidence provides support for these predictions, which confirms the link between information, trading volume, and international stock return comovements that has eluded previous empirical investigations.

scholarly journals An Empirical Analysis of Bitcoin Price Jump Risk

2019 ◽  
Vol 11 (7) ◽  
pp. 2012 ◽  
Author(s):  
Naeyoung Kang ◽  
Jungmu Kim
Keyword(s):  
Asset Pricing ◽  
Empirical Analysis ◽  
Asset Prices ◽  
Trading Volume ◽  
Daily Basis ◽  
Rate Of Return ◽  
Total Rate ◽  
Jump Risk ◽  
Jump Rate ◽  
Jump Risks

Given that there are both continuous and discontinuous components in the movement of asset prices, existing asset pricing models that assume only continuous price movements should be revised. In this paper, we explore the features of jumps, which are discontinuous movements, by examining Bitcoin pricing. First, we identify jumps in the Bitcoin price on a daily basis, applying a non-parametric methodology and then break down the Bitcoin total rate of return into a jump rate of return and a continuous rate of return. In our empirical analysis, price jumps turn out to be independent of volatility. Moreover, the jumps in the Bitcoin price do not appear at regular intervals; rather, they tend to be concentrated in clusters during special periods, implying that once an economic crisis occurs, the crisis will last for a long time due to contagion effects and the economy will take a considerable amount of time to recover fully. Further, the contribution of the jump rate of return to the total rate of return of the Bitcoin price is lower than the contribution of the continuous return, implying that the pursuit of sustainable returns rather than large but temporary returns will improve the total rate of return over the long term. Finally, more jumps are observed when trading volume is lower, implying that market illiquidity drives discontinuous movement in asset prices. Overall, the features of jump risk are like two sides of the same coin and jump risks are expected to have a significant effect on asset pricing, suggesting that consideration of jumps is essential for risk management as well as asset pricing.

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