984 resultados para trading volume
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Researchers have used stylized facts on asset prices and trading volumein stock markets (in particular, the mean reversion of asset returnsand the correlations between trading volume, price changes and pricelevels) to support theories where agents are not rational expected utilitymaximizers. This paper shows that this empirical evidence is in factconsistent with a standard infite horizon perfect information expectedutility economy where some agents face leverage constraints similar tothose found in todays financial markets. In addition, and in sharpcontrast to the theories above, we explain some qualitative differencesthat are observed in the price-volume relation on stock and on futuresmarkets. We consider a continuous-time economy where agents maximize theintegral of their discounted utility from consumption under both budgetand leverage con-straints. Building on the work by Vila and Zariphopoulou(1997), we find a closed form solution, up to a negative constant, for theequilibrium prices and demands in the region of the state space where theconstraint is non-binding. We show that, at the equilibrium, stock holdingsvolatility as well as its ratio to stock price volatility are increasingfunctions of the stock price and interpret this finding in terms of theprice-volume relation.
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This thesis examines the impact of a corporate name change on stock price and trading volume of Canadian companies around the announcement date, the approval date, and the adoption date over the time period from 1997 to 2011. Name changes are classified into six categories: major and minor, structural and pure, diversified and focused, accompanied with a change in ticker symbol and without a change in ticker symbol, “Gold” name addition and deletion, and different reasons for name changes (e.g., merger and acquisition, change of structure, change of strategy, and better image). The thesis uses the standard event study methodology to perform abnormal return and trading volume analyses. In addition, regression analysis is employed to examine which type of a name change has the largest impact on cumulative abnormal returns. Sample stocks exhibit a significant positive abnormal return one-day prior to the approval day and one day after the adoption date. Around the approval date we observe significant abnormal returns for stocks with a structural name change. On the day after the adoption date we document abnormal returns for stocks with major, minor, structural, pure, focused, and ticker symbol name changes. If a merger or acquisition is the reason for a name change, companies tend to experience a significant positive abnormal return one-day before the approval date and on the adoption date. If a change of structure is the reason for a name change, companies exhibit a significant positive abnormal return on the approval date and a significant negative abnormal return on the adoption date. In case of a change of strategy as the reason for a name change, companies show a significant negative abnormal return around the approval date and a significant positive abnormal return around the adoption date.
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Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.
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This paper considers how trading volume impacts upon the first three moments of REIT returns. Consistent with previous studies of the broader stock market, we find that volume is a significant factor with respect to both returns and volatility. We also find evidence supportive of the Hong & Stein’s (2003) Investor Heterogeneity Theory with respect to the finding that skewness in REIT index returns is significantly related to volume. Furthermore, we also report findings that show the influence of the variability of volume with skewness.
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We study the relationship between the volatility and the price of stocks and the impact that variables such as past volatility, financial gearing, interest rates, stock return and turnover have on the present volatility of these securities. The results show the persistent behavior of volatility and the relationship between interest rate and volatility. The results also showed that a reduction in stock prices are associated with an increase in volatility. Finally we found a greater trading volume tends to increase the volatility.
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We examine the stock price and volume effects associated with changes in the composition of the FTSE Bursa Malaysia Kuala Lumpur Composite Index (KLCI), over the time period of 2005–2012. We find evidence to support the price pressure hypothesis for both additions to and deletions from the KLCI. This is because significant stock price and trading volume effects in the pre index revision period are entirely reversed after the announcement of the news. Our empirical findings can be explained by the market microstructure literature. Significant changes in liquidity cause trading volume and stock prices to reverse back to their original level before the index revisions took place.
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In this paper we analyze the relationship between volatility in index futures markets and the number of open and closed positions. We observe that, although in general both positions are positively correlated with contemporaneous volatility, in the case of S&P 500, only the number of open positions has influence over the volatility. Additionally, we observe a stronger positive relationship on days characterized by extreme movements of these contracting movements dominating the market. Finally, our findings suggest that day-traders are not associated to an increment of volatility, whereas uninformed traders, both opening and closing their positions, have to do with it.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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This paper is mainly concerned with the tracking accuracy of Exchange Traded Funds (ETFs) listed on the London Stock Exchange (LSE) but also evaluates their performance and pricing efficiency. The findings show that ETFs offer virtually the same return but exhibit higher volatility than their benchmark. It seems that the pricing efficiency, which should come from the creation and redemption process, does not fully hold as equity ETFs show consistent price premiums. The tracking error of the funds is generally small and is decreasing over time. The risk of the ETF, daily price volatility and the total expense ratio explain a large part of the tracking error. Trading volume, fund size, bid-ask spread and average price premium or discount did not have an impact on the tracking error. Finally, it is concluded that market volatility and the tracking error are positively correlated.
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Doubts about the reliability of a company's qualitative financial disclosure increase market participant expectations from the auditor's report. The auditing process is supposed to serve as a monitoring device that reduces management incentives to manipulate reported earnings. Empirical research confirms that it could be an efficient device under some circumstancesand recognizes that our estimates of the informativeness of audit reports are unavoidably biased (e.g., because of a client's anticipation of the auditing process). This empirical study supports the significant role of auditors in the financial market, in particular in the prevention of earnings management practice. We focus on earnings misstatements, which auditors correct with anadjustment, using a sample of past and current constituents of the benchmark market index in Spain, IBEX 35, and manually collected audit adjustments reported over the 1997-2004 period (42 companies, 336 annual reports, 75 earnings misstatements). Our findings confirm that companies more often overstate than understate their earnings. An investor may foresee earningsmisreporting, as manipulators have a similar profile (e.g., more leveraged and with lower sales). However, he may receive valuable information from the audit adjustment on the size of earnings misstatement, which can be significantly large (i.e., material in almost all cases). We suggest that the magnitude of an audit adjustment depends, other things constant, on annual revenues and free cash levels. We also examine how the audit adjustment relates to the observed market price, trading volume and stock returns. Our findings are that earnings manipulators have a lower price and larger trading volume compared to their rivals. Their returns are positively associated with the magnitude of earnings misreporting, which is not consistent with the possible pricing of audit information.
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The paper analyzes the effects of strategic behavior by an insider in a price discovery process, akin to an information tatonnement, in the presence of a competitive informed sector. Such processes are used in the preopening period of continuous trading systems in several exchanges. It is found that the insider manipulates the market using a contrarian strategy in order to neutralize the effect of the trades of competitive informed agents. Furthermore, consistently with the empirical evidence available, we find that information revelation accelerates close to the opening, that the market price does not converge to the fundamental value no matter how many rounds the tatonnement has, and that the expected trading volume displays a U-shaped pattern. We also find that a market with a larger competitive sector (smaller insider) has an improved informational efficiency and an increased trading volume. The insider provides a public good (a lower informativeness of the price) for the competitive informed sector.
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A speculative security is an asset whose payoff depends on a random shock uncorrelated with economic fundamentals (a sunspot) about which some traders have superior information. In this paper we show that agents may find it desirable to trade such a security in spite of the fact that it is a poorer hedge against their endowment risks as the time oftrade, and has an associated adverse selection cost. In the specific institutional setting of innovation of futures contracts, we show that a futures exchange may not have an incentive to introduce a speculative security even when all traders favor it.