STOCK PRICES AND EXCESSIVE VOLATILITY: SOME EVIDENCE FOR THE FT ORDINARY SHARE INDEX

In this paper the efficiency of the UK stock market is examined using the FT Ordinary share price and dividend indices for the period January 1947 to June 1987. In particular, we examine the validity of the present value model of stock prices using a vector error correction model (VECM). Amongst the findings reported in the paper are that stock prices and dividends are cointegrated and the cross-equation restrictions imposed on the VECM are strongly rejected.     

Stock Market Efficiency and Economic Efficiency: Is There a Connection?

In a capitalist economy, prices serve to equilibrate supply and demand for goods and services, continually changing to reallocate resources to their most efficient uses. However, secondary stock market prices, often viewed as the most “informationally efficient” prices in the economy, have no direct role in the allocation of equity capital since managers have discretion in determining the level of investment. What is the link between stock price informational efficiency and economic efficiency? We present a model of the stock market in which: (i) managers have discretion in making investments and must be given the right incentives; and (ii) stock market traders may have important information that managers do not have about the value of prospective investment opportunities. In equilibrium, information in stock prices will guide investment decisions because managers will be compensated based on informative stock prices in the future. The stock market indirectly guides investment by transferring two kinds of information: information about investment opportunities and information about managers' past decisions. However, because this role is only indirect, the link between price efficiency and economic efficiency is tenuous. We show that stock price efficiency is not sufficient for economic efficiency by showing that the model may have another equilibrium in which prices are strong-form efficient, but investment decisions are suboptimal. We also suggest that stock market efficiency is not necessary for investment efficiency by considering a banking system that can serve as an alternative institution for the efficient allocation of investment resources.     

基于财务数据的农业股票投资价值研究

在农业板块股票市场中,采用灰色关联度法找出与股票价格相关联的财务指标,并分别建立了对数线性模型与截面数据回归模型检验了每股净资产对股票价格的基础作用。研究结果表明：股票价格与业绩关联性显著,公司财务因素对于股价有着极强的解释能力,每股净资产是股票价格的价值基础。     

送转股对股东财富的影响——基于中国上市公司的证据

以2008、2009年的送转股除权日进行事件研究,通过均值比较与检验方法,首次实证研究我国上市公司送转股后股价变化对股东财富的影响,结果发现:相对于经过调整的除权前一日的股价,2008年股票除权后,股价以高于送转股的比例单调下降;而2009年股票除权后,股价呈上升趋势,并于第14日显著高于经过调整的除权前一日的股价。除权后20天内的股价整体上高于年末股价,说明相对基于年末股价的股利决策,送转股没有降低股价。企业发放股票股利,导致股票总市值上升,增加了股东财富。     

Efficient option pricing on stocks paying discrete or path-dependent dividends with the stair tree

Pricing options on a stock that pays discrete dividends has not been satisfactorily settled because of the conflicting demands of computational tractability and realistic modelling of the stock price process. Many papers assume that the stock price minus the present value of future dividends or the stock price plus the forward value of future dividends follows a lognormal diffusion process; however, these assumptions might produce unreasonable prices for some exotic options and American options. It is more realistic to assume that the stock price decreases by the amount of the dividend payout at the ex-dividend date and follows a lognormal diffusion process between adjacent ex-dividend dates, but analytical pricing formulas and efficient numerical methods are hard to develop. This paper introduces a new tree, the stair tree, that faithfully implements the aforementioned dividend model without approximations. The stair tree uses extra nodes only when it needs to simulate the price jumps due to dividend payouts and return to a more economical, simple structure at all other times. Thus it is simple to construct, easy to understand, and efficient. Numerous numerical calculations confirm the stair tree's superior performance to existing methods in terms of accuracy, speed, and/or generality. Besides, the stair tree can be extended to more general cases when future dividends are completely determined by past stock prices and dividends, making the stair tree able to model sophisticated dividend processes.     

A new dividend forecasting procedure that rejects bubbles in asset prices: the case of 1929's stock crash

We develop a new procedure to forecast future cash flows froma financial asset and then use the present value of our cashflow forecasts to calculate the asset's fundamental price. Asan example, we construct a nonlinear ARMA-ARCH-Artificial NeuralNetwork model to obtain out-of-sample dividend forecasts for1920 and beyond, using only in-sample dividend data. The presentvalue of our forecasted dividends yield fundamental prices thatreproduce the magnitude, timing, and time-series behavior ofthe boom and crash in 1929 stock prices. We therefore rejectthe popular claim that the 1920s stock market contained a bubble.     

Stock Prices,Earnings, and Expected Dividends

Long historical averages of real earnings help forecast present values of future real dividends. With aggregate U.S. stock market data (1871–1986), a vector-autoregressive forecast of the present value of future dividends is, for each year, roughly a weighted average of moving-average earnings and current real price, with between two thirds and three fourths of the weight on the earnings measure. We develop the implications of this for the present-value model of stock prices and for recent results that long-horizon stock returns are highly forecastable.     

TESTING THE PRESENT VALUE MODEL OF EQUITY PRICES FOR THE UK STOCK MARKET

This paper applies present value tests to the UK stock market. Using monthly data from 1965 to 1990 on real equity price and dividend indices, it is found that the restrictions imposed by the present value model on a vector autoregression comprised of the 'spread' between prices and dividends and the change in real dividends can be rejected both for the complete sample period and for a shorter sample which omits the early years of dividend control and the run up to and aftermath of the stock market 'Crash' of October 1987. These tests are supplemented by informal methods for evaluating the 'fit' of the present value model: the observed spread is found to move 'too much', so that deviations from the model are persistent and long-lasting.     

The macroeconomic determinants of technology stock price volatility

Stock prices reflect the value of anticipated future profits of companies. Since business cycle conditions impact the future profitability of firms, expectations about the business cycle will affect the current value of firms. This paper uses daily and monthly data from July 1986 to December 2000 to investigate the macroeconomic determinants of US technology stock price conditional volatility. Technology share prices are measured using the Pacific Stock Exchange Technology 100 Index. One of the novel features of this paper is to incorporate a link between technology stock price movements and oil price movements. The empirical results indicate that the conditional volatilities of oil prices, the term premium, and the consumer price index each have a significant impact on the conditional volatility of technology stock prices. Conditional volatilities calculated using daily stock return data display more persistence than conditional volatilities calculated using monthly data. These results further our understanding of the interaction between oil prices and technology share prices and should be of use to investors, hedgers, managers, and policymakers.     

Free Cash Flow,Issuance Costs,and Stock Prices

We develop a dynamic model of a firm facing agency costs of free cash flow and external financing costs, and derive an explicit solution for the firm's optimal balance sheet dynamics. Financial frictions affect issuance and dividend policies, the value of cash holdings, and the dynamics of stock prices. The model predicts that the marginal value of cash varies negatively with the stock price, and positively with the volatility of the stock price. This yields novel insights on the asymmetric volatility phenomenon, on risk management policies, and on how business cycles and agency costs affect the volatility of stock returns.     

Selectivity,Quality Adjustment and Mean Reversion in the Measurement of House Values*

This paper develops a model of price formation in the housing market which accounts for the non-random selection of those dwellings sold on the market from the stock of existing houses. The model we develop also accounts for changes in the quality of dwellings themselves and tests for mean reversion in individual house prices. The model is applied to a unique body of data representing all dwellings sold in Sweden's largest metropolitan area during the period 1982–1999. The analysis compares house price indices that account for selectivity, quality change and mean reversion with the conventional repeat sales models used to describe the course of metropolitan housing prices. We find that the repeat sales method yields systematically large biased estimates of the value of the housing stock. Our comparison suggests that the more general approach to the estimation of housing prices or housing wealth yields substantially improved estimates of the course of housing prices and housing wealth.     

Are liquidity and corporate control priced by shareholders? Empirical evidence from Swiss dual class shares

Stadard asset pricing models generally exclude corporate control and liquidity considerations as joint explanatory factors of the stock price formation process. This empirical study investigates their influence on Swiss Bearer and Registered share prices issued by the same firm. It is shown that the statistical properties of both shares' returns differ without implying profitable arbitrage opportunities. A multifactor model of the ‘premium’ between Bearer and Registered stock prices is then proposed and tested. The results show that the freely negotiable equity book value, the existence of dominant shareholder positions and ownership transfer regime changes are significant variables in explaining the dual class share price differential.     

A hyperbolic diffusion model for stock prices

In the present paper we consider a model for stock prices which is a generalization of the model behind the Black–Scholes formula for pricing European call options. We model the log-price as a deterministic linear trend plus a diffusion process with drift zero and with a diffusion coefficient (volatility) which depends in a particular way on the instantaneous stock price. It is shown that the model possesses a number of properties encountered in empirical studies of stock prices. In particular the distribution of the adjusted log-price is hyperbolic rather than normal. The model is rather successfully fitted to two different stock price data sets. Finally, the question of option pricing based on our model is discussed and comparison to the Black–Scholes formula is made. The paper also introduces a simple general way of constructing a zero-drift diffusion with a given marginal distribution, by which other models that are potentially useful in mathematical finance can be developed.     

To buy or not to buy? The value of contradictory analyst signals

We study the predictive ability of individual analyst target price changes for post-event abnormal stock returns within each recommendation category. Although prior studies generally demonstrate the investment value of target prices, we find that target price changes do not cause abnormal returns within each recommendation level. Instead, contradictory analyst signals (e.g., strong buy reiterations with large target price decreases) neutralize each other, whereas confirmatory signals reinforce each other. Further, our analysis reveals that large target price downgrades can be explained by preceding stock price decreases. However, upgrades are not preceded by stock price increases, thereby demonstrating asymmetric analyst behavior when adjusting target prices to stock prices. Our results suggest that investors should treat recommendations with caution when they are issued with large contradictory target price changes. Thus, instead of blindly following a recommendation, investors might put more weight on the change in the corresponding target price and consider transaction costs.     

The Relation between Stock Prices and Accounting Information

The functional relation between expected stock prices and accounting information is analyzed through the theory of inverse probability. The approach models the mean of the posterior distribution for price, given the information that the accounting process provides. The implications of alternative assumptions about accounting measurement error and the unconditional price distribution are discussed. Our most refined model is consistent with recent empirical evidence showing convexity in the relationship between price and accounting information. Empirical tests, while exploratory, provide further evidence of a nonlinear relation between stock price and accounting measures of earnings and book value.     

Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices

This paper examines the empirical performance of jump diffusion models of stock price dynamics from joint options and stock markets data. The paper introduces a model with discontinuous correlated jumps in stock prices and stock price volatility, and with state-dependent arrival intensity. We discuss how to perform likelihood-based inference based upon joint options/returns data and present estimates of risk premiums for jump and volatility risks. The paper finds that while complex jump specifications add little explanatory power in fitting options data, these models fare better in fitting options and returns data simultaneously.     

中国的股票价格波动及货币政策反应

本文在阐述中国的股票价格波动情况及成因的基础上，分析中国股票价格的信息功能，并对中国的股票价格与各层次货币供应量进行协整和Granger因果检验。结果表明，从总体上看，中国的股票价格在1995年之后，具备一定的信息功能；股票价格与各层次货币供应量之间存在协整、因果关系。由此，货币当局应对股票价格波动做出反应。文章以前瞻性利率规则为基础，运用IS—PC—AP模型，采用GMM法估计出中国包含股票价格因素的货币政策反应函数。     

人民币汇率与我国股价、房价的联动关系研究

近年来,我国人民币汇率形成机制、股票市场和房地产市场发生了巨大变化,人民币汇率和股价、房价之间的信息传导和波动关联备受瞩目。本文采用VAR-MGARCH-BEKK模型,分析了我国人民币汇率、股价和房价之间的联动关系。研究结果表明,从波动的溢出效应来看,人民币汇率的波动率、股票价格的增长率和房地产价格的增长率之间存在非常明显的波动溢出效应;从资产价格的水平影响来看,人民币汇率与股票价格、房地产价格等国内资产价格的水平相关性较弱,而股票价格对房地产价格的影响较明显,并就该结论提出了相关的理论解释和政策建议。     

Imperfect Information and Cross-Autocorrelation among Stock Prices

I develop a model to explain why stock returns are positively cross-autocorrelated. When market makers observe noisy signals about the value of their stocks but cannot instantaneously condition prices on the signals of other stocks, which contain marketwide information, the pricing error of one stock is correlated with the other signals. As market makers adjust prices after observing true values or previous price changes of other stocks, stock returns become positively cross-autocorrelated. If the signal quality differs among stocks, the cross-autocorrelation pattern is asymmetric. I show that both own- and cross-autocorrelations are higher when market movements are larger.     

Equity prices and fundamentals: a DDM–APT mixed approach

This paper focuses on the linkage between equity prices and fundamentals for 27 individual shares belonging to the French stock price index (CAC40). To assess fundamental value, the traditional dividend discount model (DDM) is coupled with the arbitrage pricing theory (APT), which assumes that investors hold efficient portfolios. This yields a simple equity valuation relationship for which the APT determines the long-term risk premium included in the DDM. Accordingly, equity risk premia are determined by common factors reflecting the non diversifiable risk. These factors are not a priori identified by the theory, and therefore must be exhibited through an empirical analysis. Four domestic and three international common factors are found, all being among those identified by empirical analyses of the APT in the literature. While studies related to stock price indices showed that DDM fundamental values are very smooth compared to stock indices, our DDM–APT model reproduces both trends and major fluctuations of share prices. Further, as for studies based on stock indices, a mean-reverting process of equity prices towards fundamentals is highlighted, but the linear error correction model that was considered contains shortcomings suggesting a more complex adjustment process.