The behavior of speculative prices and the consistency of economic models

Modern financial economic theory suggest that changes in speculative prices should follow simple ‘fair game’ processes in an informationally efficient capital market. The observation that changes in speculative prices follow simple time series processes both supports this theoretical proposition and suggest restrictions on the transfer functions of structural econometric models in which speculative prices appear as output variables. The simplicity of the time series processes for observed changes in speculative prices are shown to impose strong restrictions on potential equilibrium models of asset pricing, informational disequilibrium models of financial markets, and many monetary and macroeconomic models as well.     

Estimating the Competitive Storage Model with Trending Commodity Prices

We present a method to estimate jointly the parameters of a standard commodity storage model and the parameters characterizing the trend in commodity prices. This procedure allows the influence of a possible trend to be removed without restricting the model specification, and allows model and trend selection based on statistical criteria. The trend is modeled deterministically using linear or cubic spline functions of time. The results show that storage models with trend are always preferred to models without trend. They yield more plausible estimates of the structural parameters, with storage costs and demand elasticities that are more consistent with the literature. They imply occasional stockouts, whereas without trend the estimated models predict no stockouts over the sample period for most commodities. Moreover, accounting for a trend in the estimation implies price moments closer to those observed in commodity prices. Our results support the empirical relevance of the speculative storage model, and show that storage model estimations should not neglect the possibility of long‐run price trends. Copyright © 2016 John Wiley & Sons, Ltd.     

对上证指数波动性的实证分析

股票价格频繁波动是股票市场中最明显的特征之一。ARCH类模型可以成功的预测金融资产收益的方差。通过对我国股价指数的统计描述,表明我国金融资产收益率存在自回归条件异方差,并表现出非正态性。并且应用GARCH、TARCH、EGARCH模型理论,进一步分析了日收益率波动的条件异方差性、非对称性。     

On the behavior of commodity prices when speculative storage is bounded

This paper investigates the implications of bounded speculative storage, storage bounded from below at zero and above at a capacity, on commodity prices. Binding capacity mirrors the non-negativity constraint on storage and leads to negative price spiking and higher volatility when the market is in deep contango, i.e. low current prices at high stock levels. With bounded storage there is no need to restrict storage to be costly to ensure a rational expectations equilibrium. This allows the model to cover a wide range of storage technologies, including free and productive storage. We also provide an alternative expression for speculative prices that highlights the key role of the storage boundaries. The competitive equilibrium price is the sum of discounted future probability weighted boundary prices. The boundary prices can be viewed as dividends on commodities in storage reflecting the realization of economic profits from storage.     

Optimal speculative trade among large traders

A collection of large traders holds heterogeneous prior beliefs regarding market fundamentals. This gives them a motive to engage in speculative trade with respect to market prices. Rather than assuming a particular institution or market for speculative trade, we take a mechanism-design approach by attempting to characterize the mechanism that maximizes the traders’ gains from speculative trade, subject to the incentive constraints that result from the traders’ ability to manipulate market prices. Within a stylized market model, we show that this mechanism affects price volatility without destroying ex-post efficient allocations. We also characterize the implementability of optimal speculative trade when the traders’ prior beliefs are private information. Financial support from the US-Israel Binational Science Foundation, Grant No. 2002298 is gratefully acknowledged.     

Fundamentals, Feedback Trading, and Housing Market Speculation: Evidence from California

Housing market researchers have long suspected that the market for single family homes is not efficient. The apparent predictability in housing prices, at least in the short run, leaves open the possibility of speculative purchases in the housing market. The purpose of this paper is to investigate the relative influence of speculative and economic demand on median house price on the Santa Barbara South Coast. An empirical model is presented that allows for decomposition of house price appreciation into that driven by economic and demographic forces and that resulting from speculative demand. The decomposition reveals a speculative bubble in the housing market forming in late 1987 and collapsing in mid 1990.     

Duration dependence testing for speculative bubbles

Prior research has employed a number of methods to test for speculative bubbles in asset prices, including a method based on the concept of duration dependence. This study explores whether duration dependence tests for speculative bubbles are sensitive to specification decisions. Our results question the efficacy of using measures of duration dependence to test for speculative bubbles. In particular, we find that evidence of duration dependence is sensitive to the method of correcting for discrete observation of continuous duration, the use of value-weighted versus equally weighted portfolios, and the use of monthly versus weekly runs of abnormal returns. (JEL C41, G12)     

Role of credit and monetary policy in determining asset prices: Evidence from emerging market economies

We examine the relative dominance of credit and monetary policy shocks in influencing asset prices in emerging markets. Estimates from panel VAR models for 22 EMEs provide evidence of a significant impact of bank credit on house prices in contrast to trivial impact on stock prices, possibly due to prudential regulations on banks’ exposure to stock markets. Contractionary monetary policy triggers sizeable and persistent decline in stock than housing prices as higher interest rates may render the funding of leverage costlier. Global shocks play an important role in explaining fluctuations in domestic stock prices rather than house prices since the latter class of asset is largely non-tradable across countries.     

Approximate Bayesian Computation for a Class of Time Series Models

In the following article, we consider approximate Bayesian computation (ABC) for certain classes of time series models. In particular, we focus upon scenarios where the likelihoods of the observations and parameter are intractable, by which we mean that one cannot evaluate the likelihood even up to a non‐negative unbiased estimate. This paper reviews and develops a class of approximation procedures based upon the idea of ABC, but specifically maintains the probabilistic structure of the original statistical model. This latter idea is useful, in that one can adopt or adapt established computational methods for statistical inference. Several existing results in the literature are surveyed, and novel developments with regards to computation are given.     

国有土地使用权出让中“地王”现象分析

“地王”的产生既有土地供应、需求等基本层面的因素,也有分税制、招拍挂、土地国有等制度层面的因素,同时又受到国际国内经济运行大环境的影响.“地王”不仅会直接推高房价,还会提高房价上涨预期,形成地价房价相互抬高的恶性循环.“地王”增加了经济运行风险,不利于国民经济长期可持续发展.为抑制“地王”产生,要坚决遏制投资投机性住房...     

Modeling Speculative Activity in the Hong Kong Residential Property Market

Using the Granger definition in a bivariate context, this paper investigates the relation between speculation and real estate prices in Hong Kong. Based on monthly data, the paper shows that in the mass residential property market, speculation and property prices are each integrated of order one, and hence cointegrated. A vector error correction model is then estimated for speculation. The error correction term is found to be statistically significant, implying Granger causality running from property prices to speculation in the mass residential property market. The empirical findings provide evidence that fluctuations in residential property prices cause fluctuations in housing speculation. A long-term solution to curb speculative activities and stabilize property prices is to increase the supply of housing land, and in turn the supply of private residential property. Steady property supply of will reduce acceleration of property prices and thus restrict speculation.     

Detecting speculative bubbles in an IT-intensive stock market

Using a battery of unit root test procedures and cointegration analysis with alternative null hypotheses we find some evidence of speculative bubbles in the Finnish stock market for monthly data on industry portfolio stock prices and returns from the 1990s. When analyzing the time series behavior of stock market prices and returns against the development of certain macroeconomic fundamentals, the bubbles seem to be present especially in the information technology (IT) prices and only during the latter half of the decade. (JEL C22, G12)     

国有控股上市公司股权激励市场效应的实证分析

本文采集了21家国有控股上市公司实施股权激励首次披露日前后三十个交易日的股票收盘价,并对这些股价进行了统计分析。实证结果显示,国有控股上市公司股票价格在股权激励方案首次披露日之后给投资者带来了超额收益,国有控股上市公司实施股权激励给个股股价带来正面的市场效应,并且能够提高国有控股上市公司的短期融资能力。分析认为,广大证券投资者没有过分担心因国有控股上市公司实施股权激励可能带来的国有资产流失问题,多数投资者持积极认同态度。     

Applications of the Likelihood Theory in Finance: Modelling and Pricing

This paper discusses the connection between mathematical finance and statistical modelling which turns out to be more than a formal mathematical correspondence. We like to figure out how common results and notions in statistics and their meaning can be translated to the world of mathematical finance and vice versa. A lot of similarities can be expressed in terms of LeCam’s theory for statistical experiments which is the theory of the behaviour of likelihood processes. For positive prices the arbitrage free financial assets fit into statistical experiments. It is shown that they are given by filtered likelihood ratio processes. From the statistical point of view, martingale measures, completeness, and pricing formulas are revisited. The pricing formulas for various options are connected with the power functions of tests. For instance the Black–Scholes price of a European option is related to Neyman–Pearson tests and it has an interpretation as Bayes risk. Under contiguity the convergence of financial experiments and option prices are obtained. In particular, the approximation of Itô type price processes by discrete models and the convergence of associated option prices is studied. The result relies on the central limit theorem for statistical experiments, which is well known in statistics in connection with local asymptotic normal (LAN) families. As application certain continuous time option prices can be approximated by related discrete time pricing formulas.     

Forecasting the volatility of currency exchange rates

Currency volatility is defined to be the standard deviation of day-to-day changes in the logarithm of the exchange rate. After a discussion of statistical models for exchange rates, the paper describes methods for choosing and assessing volatility forecasts using open, high, low and close prices. Results for DM/$ futures prices at the IMM in Chicago from 1977 to 1983 show high and low prices are valuable when seeking accurate volatility forecasts. The best forecasts are a weighted average of present and past high, low and close prices, with adjustments for weekend and holiday effects. The forecasts can be used to value currency options.     

User costs and bubbles in land markets

In asset markets with speculative behavior, the long-run equilibrium relationship between asset prices and the discounted flow of future rents may become invalid. We distinguish short-term user costs and longer-term user costs with variables that reflect fundamentals. We show how to work around the empirical problem of measuring speculative expectations about asset price changes and derive a simple user cost formula where the asset price change in the short-term relationship comes out as the long-run change in the overall price level.     

Forecasting stock prices with commodity prices: New evidence from Feasible Quasi Generalized Least Squares (FQGLS) with non-linearities

The complexities in modern stock markets make it imperative to unravel the possible predictors of their future values. This paper thus provides insights into the predictability of stock prices of the BRICS countries with large dependence on commodities either for foreign exchange earnings or industrial while accounting for the role of asymmetries. Essentially, empirical evidence abound for the high volatility in world commodity markets, thus making us to determine if positive and negative changes in commodity prices predict stock prices differently. In addition, unlike the traditional forecast models, our choice of forecast models additionally addresses certain statistical features, including conditional heteroskedasticity, serial dependence, persistence and endogeneity, inherent in the predictors, which have the potential of causing estimation bias. In all, we find evidence in favour of the ability of commodity prices to predict stock prices of Brazil, Russia and South Africa. Also, both the in-sample and out-of-sample forecast performances of the predicted models support asymmetries in a number of commodity prices in each of these three countries. Our results are robust to different data samples and forecast horizons.     

GARCH models without positivity constraints: Exponential or log GARCH?

This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, which both rely on multiplicative volatility dynamics without positivity constraints. We compare the main probabilistic properties (strict stationarity, existence of moments, tails) of the EGARCH model, which are already known, with those of an asymmetric version of the log-GARCH. The quasi-maximum likelihood estimation of the log-GARCH parameters is shown to be strongly consistent and asymptotically normal. Similar estimation results are only available for the EGARCH (1,1) model, and under much stronger assumptions. The comparison is pursued via simulation experiments and estimation on real data.     

A simple framework for analysing bull and bear markets

Bull and bear markets are a common way of describing cycles in equity prices. To fully describe such cycles one would need to know the data generating process (DGP) for equity prices. We begin with a definition of bull and bear markets and use an algorithm based on it to sort a given time series of equity prices into periods that can be designated as bull and bear markets. The rule to do this is then studied analytically and it is shown that bull and bear market characteristics depend upon the DGP for capital gains. By simulation methods we examine a number of DGPs that are known to fit the data quite well—random walks, GARCH models, and models with duration dependence. We find that a pure random walk provides as good an explanation of bull and bear markets as the more complex statistical models. In the final section of the paper we look at some asset pricing models that appear in the literature from the viewpoint of their success in producing bull and bear markets which resemble those in the data. Copyright © 2002 John Wiley & Sons, Ltd.     

A Model for Positively Correlated Count Variables

An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work.