股票供求曲线变动与理性投资决策

股票作为一种特殊的产品,其价格的形成直接取决于市场的供求;反过来,股票价格的高低和变动又影响和调节着其供求关系。而供求关系的形成主要取决于股票的内在价值,其他因素(如基本面和市场技术等因素)都将通过内在价值影响其供求关系,进而影响股票的价格。本文通过股票供求曲线的生成机制,分析引起股价波动背后的主要理性因素,为投资决策提供理性依据。     

上市公司股票回购的相关概述

股票回购是国内外成熟证券市场中常见的资本运作方式和公司理财行为,正在世界各国的资本市场上发挥着重要的作用。股票回购就像一把双刃剑,既能给上市公司带来正的财务效应,也能给其带来负的财务效应。文章将回顾中国上市公司股票回购方式、资金来源及股票回购对公司内在价值方面的作用进行分析。     

如何成为聪明的投资者

按照劳伦斯科明汉姆的划分,世界上存在五种投资模式：第一种是价值投资,依靠对公司的财务分析,寻找市场价格低于其内在价值的股票。以格雷厄姆、巴菲特为代表。第二种是增长投资,投资者寻找那些经营收益能够保证公司内在价值迅速增长的公司。以菲利普·费舍尔和彼得·林奇为代表。第三种是指数投资。通过购买股票,来复制市场指数。以约翰·伯格为主。     

换股决定盈亏

第七章如何判断大势分析股票价格指数即股票大盘指数,它是描述股票市场总的价格水平变化的指标,是由证券交易所的表明股票行市变动的一种供参考的指示数字。作为市场价格变动的风向指标。投资者据此就可以预测股票市场的动向。     

基于GARP的技术指标增强策略

前言 基本面与技术面的激辩 一般而言,处于市场中的投资者可以大致地划分为两种类型：基于基本面分析的价值投资者及基于技术分析的趋势投资者。价值投资者依靠对公司财务表现的基础,分析找出那些市场价格低于其内在价值（公司未来现金流的现值）的股票。价值投资者着重分析的是股票市场中价格与价值的关系,认为无论是长期还是短期,股票市场都是不可预测的。而唯一有一定把握能够确认的是,基于公司过去业务表现和现有信息对其业务的长期表现进行的分析。价值投资者通过对这些信息的分析来确认公司价值并将其与市场价格作出比较,最终将市场价格低于其评估价值的个股作为理想的投资标的。     

浅谈公司价值的评估

一、公司价值评估模式在现代金融学和公司财务领域,关于公司价值的评估方法大致可分为两种类型:非贴现价值评估模式和贴现价值评估模式。1.非贴现价值评估模式。非贴现式价值评估模式可分为市场比较法、市盈率法、股息法等。(1)市场比较法。通常是将股票市场上最近平均实际交易的价格作为价值的参考,在有效的资本市场上,上市公司的股票价格反映了市场对该公司未来业绩与相关风险的预期,故上市公司的市场价值(股票市价×发行在外的普通股股数)实际是投资者对该公司内在价值的一致认可。对于非上市的目标公司,利用市场类比法进行价值评估时,可…     

增值税的价格效应北大核心CSSCI

本文运用一般均衡理论和投入产出法,讨论了增值税对最终产品价格和总体价格水平的影响机制和效果。增值税价格效应模型推导和我国历年投入产出表数据测算表明:第一,增值税对最终产品价格的影响受到税率水平、税负转嫁情况和行业间技术结构三者的综合作用。第二,考虑不同的税负转嫁情况,行业间技术结构变动条件下单档税率和多档税率的增值税价格效应是不一样的,其中,单档税率的价格效应不变,而多档税率的价格效应会发生变化。第三,2019年增值税税率改革对总体价格水平变动的影响较大,税负完全前转时,对价格水平变动的贡献度为-42%,税负完全后转且企业愿意让渡全部收益时,对价格水平变动的贡献度为50.93%。而税率为13%、6%与税率为13%、9%的两套改革方案对价格水平的影响,从影响方向看,两者是相反的,从影响程度上看,前者要低于后者。     

市值管理:迈向上市公司价值最大化之路

股票的市值就是按市场价格计算出来的股票总价值.一家上市公司每股股票的价格乘以发行总股数即为这家公司的市值.市值对于上市公司本身,不仅仅是投资价值的货币表现,它通过影响公司的资本成本、营销能力和并购成本等,从而达到上市公司市值与盈利能力的良性螺旋式递增的格局.市值管理就是要通过长效组织机制,致力于追求毛利、周转和杠杆的提升,实现公司价值最大化,为股东创造价值,并通过与资本市场保持准确、及时、有效的信息沟通,使股票价格客观反映公司的内在价值,使其服务于公司整体战略目标的实现.     

基于财务指标体系的中国上市公司投资价值分析

随着我国经济的不断发展,上市公司越来越多,选择不同的上市公司进行投资可以获取不同的利益,了解公司的财务指标,可以帮助投资者知道该公司在未来发展中存在的潜在价值,获得最大化的利益.在这里所说的上市公司的投资价值就是指上市工资公开的发行并且能够在国家的二级市场上流通的股票的投资价值.依据市场上价值投资的理念来说,股票的内在价值是和股票的价格对比来决定的,这样股票的投资价值就是一种相对价值.在国内有很多学者对价值投资进行了全方位的深度研究,主要的研究重点放在了两个方面:一个是人们对价值投资的解释与验证,另外一个就是人们群众对上市公司的股票价值的分析和测评.本文对上市公司建立了一套评价其潜在价值的财务指标评估体系和投资剖析模型,透过模型对比,可以让投资者更好的了解上市公司的发展空间,指引投资者购买更有价值的股票.     

外部资本市场与内部资本市场：替代还是互补——基于陆港通效应的实证检验

本文采用多期DID模型探究外部资本市场开放与企业内部资本市场构建的关系。研究发现：陆港通实施后,外部资本市场会替代企业内部资本市场,两者的作用路径主要源于融资约束的缓解和公司治理效率的提高,且这种作用效果在股票流动性低和分析师跟踪人数高的样本中更显著;进一步研究发现,外部资本市场开放对内部资本市场构建的替代效应最终可以带来公司价值的提升,也主要体现于低股票流动性和高分析师跟踪人数的公司中。上述研究结论对于理解陆港通效应具有一定的参考价值。     

Bubbles,Fads and Stock Price Volatility Tests: A Partial Evaluation

This is a summary and interpretation of some of the literature on stock price volatility that was stimulated by Leroy and Porter 28 and Shiller 40 . It appears that neither small-sample bias, rational bubbles nor some standard models for expected returns adequately explain stock price volatility. This suggests a role for some nonstandard models for expected returns. One possibility is a “fads” model in which noise trading by naive investors is important. At present, however, there is little direct evidence that such fads play a significant role in stock price determination.     

Option pricing model with sentiment

In this paper, we develop a closed-form option pricing model with the stock sentiment and option sentiment. First, the model shows that the price of call option is amplified by bullish stock sentiment, and is reduced by stock bearish sentiment, and the price of put option is in the opposite situation. Second, the price of call option is more sensitive to bullish stock sentiment; the price of put option is more sensitive to bearish stock sentiment. Third, the price of call option increases substantially with respect to the stock sentiment and the option sentiment. The price of put option decreases substantially with respect to the stock sentiment, increases substantially with respect to the option sentiment. Fourth, our models also reveal that the option volatility smile is steeper (flatter) when the stock sentiment becomes more bearish (bullish). Finally, stock sentiment and option sentiment lead to the option price deviating from the rational price. The model could offer a partial explanation of some option anomalies: option price bubbles and option volatility smile.     

Stock Market Volatility and Learning

We show that consumption‐based asset pricing models with time‐separable preferences generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. Rational investors with subjective beliefs about price behavior optimally learn from past price observations. This imparts momentum and mean reversion into stock prices. The model quantitatively accounts for the volatility of returns, the volatility and persistence of the price‐dividend ratio, and the predictability of long‐horizon returns. It passes a formal statistical test for the overall fit of a set of moments provided one excludes the equity premium.     

Asymmetric stock market volatility and the cyclical behavior of expected returns

Recent explanations of aggregate stock market fluctuations suggest that countercyclical stock market volatility is consistent with rational asset evaluations. In this paper, I develop a framework to study the causes of countercyclical stock market volatility. I find that countercyclical risk premia do not imply countercyclical return volatility. Instead, countercyclical stock volatility occurs if risk premia increase more in bad times than they decrease in good times, thereby inducing price–dividend ratios to fluctuate more in bad times than in good. The business cycle asymmetry in the investors’ attitude toward discounting future cash flows plays a novel and critical role in many rational explanations of asset price fluctuations.     

资产价格波动形势下货币政策工具的宏观调控效应比较研究

本文通过构建VAR模型,识别资产价格对不同货币政策工具冲击的响应程度,发现各项贷款对于调控资产价格的效力最强,其次为货币供应量和利率政策。值得注意的是,贷款增长对于股价膨胀起到了重要支撑和推动作用,同时贷款少增对股价收缩效应也非常显著。本文强调,信贷数量调控对于平抑资产价格波动十分关键,选择性货币政策工具(Selective Credit Control)对于资产价格波动具有特殊调控效力。最后,本文提出了资产价格膨胀与资产价格收缩不同时期货币政策工具的搭配建议。     

基于半参数LM-ARMAX模型的股价波动成因分析

对股票价格波动的建模分析,一直是经济与金融研究的核心领域,是什么导致了股票价格的波动,也一直是投资主体共同关注的话题。有鉴于此,本文选择沪市1991-2010年所有上市公司的数据,建立了LM-ARMAX模型来实证股票价格波动的决定因素,最后根据模型半参数估计的结果,进行了基于半参数估计的非线性检验和基于Wild Bootstrap的Smirnov检验,结果表明:市账率和成交量是股票价格波动的主要因素,而净资产收益率对股票价格波动的影响不显著。     

The Pricing of Options on Assets with Stochastic Volatilities

One option-pricing problem that has hitherto been unsolved is the pricing of a European call on an asset that has a stochastic volatility. This paper examines this problem. The option price is determined in series form for the case in which the stochastic volatility is independent of the stock price. Numerical solutions are also produced for the case in which the volatility is correlated with the stock price. It is found that the Black-Scholes price frequently overprices options and that the degree of overpricing increases with the time to maturity.     

Exploring the relationship between investor sentiment and price volatility

By performing Grey relation analysis, this study elucidates the relationship between investor sentiment and price volatility in the Taiwanese stock market. A sequential relationship is identified between investor sentiment and price volatility, and ranked according to order of importance. Analytical results show that short sales volumes may be an individual leading indicator useful in observing the effects of sentiment on price volatility, followed by open interest put/call ratios and trading volumes, and buy/sell orders. Institutional investors are related, to a lesser extent, to price volatility and sentiment. Qualified foreign institutional investors, or more rational investors, are the least influenced by price volatility, followed by securities investment trust companies and dealers. TAIEX options exert the strongest influence on sentiment during the study period, making them a valuable reference for gauging price volatility.     

Stock market volatility and equity returns: Evidence from a two-state Markov-switching model with regressors

This paper proposes a two-state Markov-switching model for stock market returns in which the state-dependent expected returns, their variance and associated regime-switching dynamics are allowed to respond to market information. More specifically, we apply this model to examine the explanatory and predictive power of price range and trading volume for return volatility. Our findings indicate that a negative relation between equity market returns and volatility prevails even after having controlled for the time-varying determinants of conditional volatility within each regime. We also find an asymmetry in the effect of price range on intra- and inter-regime return volatility. While price range has a stronger effect in the high volatility state, it appears to significantly affect only the transition probabilities when the stock market is in the low volatility state but not in the high volatility state. Finally, we provide evidence consistent with the ‘rebound’ model of asset returns proposed by Samuelson (1991), suggesting that long-horizon investors are expected to invest more in risky assets than short-horizon investors.     

A volatility model based on adaptive expectations: An improvement on the rational expectations model

Investment expectations affect stock price volatility, making asset pricing more difficult. Correctly capturing investment expectations can help alleviate this problem. In this paper, we analyze the rational expectations properties of existing volatility models. Second, we explore a volatility model based on adaptive expectations by using mathematical methods and the applicable conditions and continuity feature of the adaptive expectations volatility model. Third, under the assumption of adaptive expectations, we construct adaptive expectations GARCH (ADGARCH) and LSTM-ADGARCH models. Using daily trading data from the Shanghai stock index and SPX500 for the period 2015–2021, we find that the volatility model based on adaptive expectations has more explanatory power than one based on rational expectations.