Jumps in equilibrium prices and market microstructure noise

Asset prices observed in financial markets combine equilibrium prices and market microstructure noise. In this paper, we study how to tell apart large shifts in equilibrium prices from noise using high frequency data. We propose a new nonparametric test which allows us to asymptotically remove the noise from observable price data and to discover jumps in fundamental asset values. We provide its asymptotic distribution to decide when such jumps occur. In finite samples, our test offers reasonable power for distinguishing between noise and jumps. Empirical evidence indicates that it is necessary to incorporate the presence of jumps in equilibrium prices.     

Econometric analysis of jump-driven stochastic volatility models

This paper introduces and studies the econometric properties of a general new class of models, which I refer to as jump-driven stochastic volatility models, in which the volatility is a moving average of past jumps. I focus attention on two particular semiparametric classes of jump-driven stochastic volatility models. In the first, the price has a continuous component with time-varying volatility and time-homogeneous jumps. The second jump-driven stochastic volatility model analyzed here has only jumps in the price, which have time-varying size. In the empirical application I model the memory of the stochastic variance with a CARMA(2,1) kernel and set the jumps in the variance to be proportional to the squared price jumps. The estimation, which is based on matching moments of certain realized power variation statistics calculated from high-frequency foreign exchange data, shows that the jump-driven stochastic volatility model containing continuous component in the price performs best. It outperforms a standard two-factor affine jump–diffusion model, but also the pure-jump jump-driven stochastic volatility model for the particular jump specification.     

Monetary effects on nominal oil prices

The paper presents a theory of nominal asset prices for competitively owned oil. Focusing on monetary effects, with flexible oil prices the US dollar oil price should follow the aggregate US price level. But with rigid nominal oil prices, the nominal oil price jumps proportionally to nominal interest rate increases. We find evidence for structural breaks in the nominal oil price that are used to illustrate the theory of oil price jumps. The evidence also indicates strong Granger causality of the oil price by US inflation as is consistent with the theory.     

Jumps,cojumps and macro announcements

We use recently proposed tests to extract jumps and cojumps from three types of assets: stock index futures, bond futures, and exchange rates. We then characterize the dynamics of these discontinuities and informally relate them to US macroeconomic releases before using limited dependent variable models to formally model how news surprises explain (co)jumps. Nonfarm payroll and federal funds target announcements are the most important news across asset classes. Trade balance shocks are important for foreign exchange jumps. We relate the size, frequency and timing of jumps across asset classes to the likely sources of shocks and the relation of asset prices to fundamentals in the respective classes. Copyright © 2010 John Wiley & Sons, Ltd.     

Impact of volatility jumps in a mean-reverting model: Derivative pricing and empirical evidence

This paper investigates the critical role of volatility jumps under mean reversion models. Based on the empirical tests conducted on the historical prices of commodities, we demonstrate that allowing for the presence of jumps in volatility in addition to price jumps is a crucial factor when confronting non-Gaussian return distributions. By employing the particle filtering method, a comparison of results drawn among several mean-reverting models suggests that incorporating volatility jumps ensures an improved fit to the data. We infer further empirical evidence for the existence of volatility jumps from the possible paths of filtered state variables. Our numerical results indicate that volatility jumps significantly affect the level and shape of implied volatility smiles. Finally, we consider the pricing of options under the mean reversion model, where the underlying asset price and its volatility both have jump components.     

Option pricing with stochastic volatility models

A general class of models for derivative pricing with stochastic volatility is analyzed. We include the possibility of jumps for the paths of the asset's price and for those of its volatility. We also consider the case of correlation between the process of the asset's price and that of its volatility. In this way we are able to give a unifying view on most of the models studied in the literature. We will examine theoretical issues related to the market price of volatility risk, the equivalent martingale measures and the possibility of obtaining a numerically tractable formula for contingent claim pricing. Finally, we propose some methodologies to test the behavior of stochastic volatility models when applied to market data.     

Diagnosing housing fever with an econometric thermometer

Housing fever is a popular term to describe an overheated housing market or housing price bubble. Like other financial asset bubbles, housing fever can inflict harm on the real economy, as indeed the U.S. housing bubble did in the period following 2006 leading up to the general financial crisis and great recession. One contribution that econometricians can make to minimize the harm created by a housing bubble is to provide a quantitative “thermometer” for diagnosing ongoing housing fever. Early diagnosis can enable prompt and effective policy action that reduces long-term damage to the real economy. This paper provides a selective review of the relevant literature on econometric methods for identifying housing bubbles together with some new methods of research and an empirical application. We first present a technical definition of a housing bubble that facilitates empirical work and discuss significant difficulties encountered in practical work and the solutions that have been proposed in the past literature. A major challenge in all econometric identification procedures is to assess prices in relation to fundamentals, which requires measurement of fundamentals. One solution to address this challenge is to estimate the fundamental component from an underlying structural relationship involving measurable variables. A second aim of the paper is to improve the estimation accuracy of fundamentals by means of an easy-to-implement reduced-form approach. Since many of the relevant variables that determine fundamentals are nonstationary and interdependent we use the endogenous instrumental variable based method (IVX) to estimate the reduced-form model to reduce the finite sample bias which arises from highly persistent regressors and endogeneity. The recursive evolving test proposed by Phillips, Shi, and Yu (PSY) is applied to the estimated nonfundamental component for the identification of speculative bubbles. The new bubble test developed here is referred to as PSY-IVX. An empirical application to the eight Australian capital city housing markets over the period 1999–2017 shows that bubble testing results are sensitive to different ways of controlling for fundamentals and highlights the importance of accurate estimation of these housing market fundamentals.     

News and intraday jumps: Evidence from regularization and class imbalance

We study how information provokes intraday price jumps taking into account, besides news timing, the sentiment of news stories and other high-frequency indicators. By applying penalized logistic regression and addressing the rare nature of jumps, in addition to the previous evidence showing that causes of jumps are rate decisions and earnings announcements, we find that news provoking jumps is often followed by other news about the same company, that news stories sentiment and macro-surprises sign help to predict the jump sign, and, finally, that market players sometimes anticipate company-specific news.     

Is a co-jump in prices a sparse jump?

Systematic co-jumps in asset prices are generally thought to account for only a small proportion of overall jumps. In actual observations, however, jumps in asset prices are often persistent, and the time of persistence varies. In this context, we develop a new rule to identify co-jumps and improve traditional tests by considering different sampling frequencies and different sampling starting points to re-evaluate the occurrence rate of systematic co-jumps in financial assets. We conduct a simulation experiment to show that the current test procedures generally underestimate the number of co-jumps when considering persistence, but that the proposed procedure can identify co-jumps more accurately. We also perform an empirical analysis using price data from the Shanghai 50 Index and its 25 constituent stocks in China’s stock market. The average proportion of systematic co-jumps detected by the improved s-BNS is approximately 30%, which shows that the co-jump and even the systematic co-jump are not sparse jumps. The results also reveal the shortcomings of traditional jump tests in estimating persistent jumps and demonstrate that the proposed method can better detect the possible nondiversifiable risks between market indices and their constituent stocks, thereby contributing to financial risk management.     

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.     

Margin trade,short sales and financial stability

We model how leveraged trading activities constrained by dynamic funding availability affect financial stability. In the market, customers trade based on the fundamental value of the risky asset and make full payment for their transactions, while speculators take trading position based on margin, which is constantly adjusted by the financier, the fund provider, according to the price volatility. As a result of equilibrium price discontinuity triggered by dynamic margin requirements, trivial shocks to external supply, wealth or fundamental value can be transmitted into asset price crashes or jumps. We find that tightening margin requirements improves (mitigates) the market liquidity in the bull (bear) market, and that imposing short sale constraints helps prevent the price from falling further when the asset is sufficiently under-priced and accelerate price collapse when the asset is over-priced.

     

Risk,jumps, and diversification

We test for price discontinuities, or jumps, in a panel of high-frequency intraday stock returns and an equiweighted index constructed from the same stocks. Using a new test for common jumps that explicitly utilizes the cross-covariance structure in the returns to identify non-diversifiable jumps, we find strong evidence for many modest-sized, yet highly significant, cojumps that simply pass through standard jump detection statistics when applied on a stock-by-stock basis. Our results are further corroborated by a striking within-day pattern in the significant cojumps, with a sharp peak at the time of regularly scheduled macroeconomic news announcements.     

Inference on Self‐Exciting Jumps in Prices and Volatility Using High‐Frequency Measures

Dynamic jumps in the price and volatility of an asset are modelled using a joint Hawkes process in conjunction with a bivariate jump diffusion. A state‐space representation is used to link observed returns, plus nonparametric measures of integrated volatility and price jumps, to the specified model components, with Bayesian inference conducted using a Markov chain Monte Carlo algorithm. An evaluation of marginal likelihoods for the proposed model relative to a large number of alternative models, including some that have featured in the literature, is provided. An extensive empirical investigation is undertaken using data on the S&P 500 market index over the 1996–2014 period, with substantial support for dynamic jump intensities—including in terms of predictive accuracy—documented. Copyright © 2016 John Wiley & Sons, Ltd.     

河北省房地产价格波动影响因素的实证分析

本文以河北省2004年第1季度至2009年第4季度的房地产平均销售价格及相关数据为样本,运用计量经济学的逐步回归法分析了河北省宏观经济基本层面对房地产价格的影响和作用程度。实证分析发现:人口因素、地区生产总值和货币供应量对房地产价格波动影响较大,其中货币供应量与河北省房地产的价格波动呈现正相关,对房地产价格的影响非常显著。因此,我国的货币政策要逐步关注各地区的房地产价格。     

ECONOMETRIC TESTS OF ASSET PRICE BUBBLES: TAKING STOCK*

Abstract Can asset price bubbles be detected? This survey of econometric tests of asset price bubbles shows that, despite recent advances, econometric detection of asset price bubbles cannot be achieved with a satisfactory degree of certainty. For each paper that finds evidence of bubbles, there is another one that fits the data equally well without allowing for a bubble. We are still unable to distinguish bubbles from time‐varying or regime‐switching fundamentals, while many small sample econometrics problems of bubble tests remain unresolved.     

Modelling oil price expectations: Evidence from survey data

Using Consensus Forecast survey data on WTI oil price expectations for 3- and 12-month horizons over the period November 1989 to December 2008, we find that the rational expectation hypothesis is rejected and that none of the traditional extrapolative, regressive and adaptive processes fits the data by itself. We suggest a mixed expectation model defined as a linear combination of these traditional processes, which we interpret as the aggregation of individual mixing behavior and of heterogenous groups of agents using these simple processes. This approach is consistent with the economically rational expectations theory. We show that the target oil price included in the regressive component of this model depends on the long-run marginal cost of crude oil production and on short term macroeconomic fundamentals whose effects are subject to structural changes. For the two horizons, estimation results provide evidence for our mixed expectation model incorporating this break-dependent target price.     

河北省房地产价格波动影响因素的实证分析

本文以河北省2004年第1季度至2009年第4季度的房地产平均销售价格及相关数据为样本,运用计量经济学的逐步回归法分析了河北省宏观经济基本层面对房地产价格的影响和作用程度。实证分析发现：人口因素、地区生产总值和货币供应量对房地产价格波动影响较大,其中货币供应量与河北省房地产的价格波动呈现正相关,对房地产价格的影响非常显著。因此,我国的货币政策要逐步关注各地区的房地产价格。     

Good luck or good policy? An expectational theory of macro volatility switches

In an otherwise unique-equilibrium model, agents are segmented into a few informational islands according to the signal they receive about others' expectations. Even if agents perfectly observe fundamentals, rational-exuberance equilibria (REX) can arise as they put weight on expectational signals to refine their forecasts. Constant-gain adaptive learning can trigger jumps between the equilibrium where only fundamentals are weighted and a REX. This determines regime switching in macro volatility despite unchanged monetary policy and time-invariant distribution of exogenous shocks. In this context, a tight inflation-targeting policy can lower expectational complementarity preventing rational exuberance, although its effect is non-monotone.     

基于小波变换和支持向量的国际原油价格预测

本文将小波分析与支持向量回归结合应用于国际原油价格预测,通过小波多尺度分析方法将油价时间序列分解为长期趋势和随机扰动项,然后采用支持向量回归对分解后的油价长期趋势进行预测。油价长期趋势的预测采用多因素预测方法,主要考虑市场供需基本面、库存、经济、投机等因素对石油价格走势的影响,建立多输入单输出的支持向量回归模型。实证研究表明,支持向量回归模型具有较高的预测性能,对原油价格长期趋势预测中,该方法比回归方法的预测精度高。     

Robustness of stable volatility strategies

The paper analyzes the robustness of stable volatility strategies, i.e. strategies in which the portfolio weight of the stock is inversely proportional to its local volatility. These strategies are optimal for a CRRA investor if the stock follows a diffusion process, the expected excess return is proportional to its volatility, and the hedging demand is zero. We assess the performance of stable volatility strategies when these restrictive assumptions do not hold, in particular, when the risk premium is not proportional to volatility and when the stock price is subject to jumps. We find that stable volatility strategies are indeed robust or close to robust under a maxmin decision rule. In addition to our theoretical results, we perform a simulation analysis to evaluate strategies that scale the portfolio weight by the volatility, variance or a constant portfolio weight, and also analyze the strategies using empirical excess returns. Both analyses confirm the robustness of stable volatility strategies.