House price dynamics,conditional higher-order moments,and density forecasts

Most studies on housing price dynamics are only concerned with the conditional mean and variance, but overlook other higher-order conditional moments and the structural change characteristics inherent in housing prices. In order to take into account these two important issues, this study utilizes the generalized Markov switching GARCH model to explore house price dynamics and conditional distribution for US market over 1975Q1–2007Q4. The housing return follows two distinct dynamics: the bust regime and the boom regime. The volatility pattern is different in the bust and boom regimes. In addition, the conditional densities derived by the regime-switching model change dramatically over time and are significantly different from normal distribution. More importantly, the regime-switching model can detect in advance a weak US housing market such as the one that occurred in the middle of 2007. The in-sample fitting ability of regime-switching model, which incorporates higher-order moments, has significant improvements compared to the single-regime AR and AR-GARCH models. For the out-of-sample Value-at-Risk forecasting performance, the ability of regime-switching AR-GARCH model to forecast one-step-ahead density is better compared to the single-regime AR-GARCH model.     

The risk-return relation and VIX: evidence from the S&P 500

A significantly positive risk-return relation for the S&P 500 market index is detected if the squared implied volatility index (VIX) is allowed for as an exogenous variable in the conditional variance equation of the parsimonious GARCH(1,1) model. This result holds for both daily and weekly observations, for extended conditional mean and variance specifications, and is robust to sub-samples. We show that the conditional variance obtained from the GARCH model with VIX has better predictive ability for realized volatility than the conditional variance from GARCH without VIX and VIX itself, thereby documenting an important information content of VIX for conditional variance. The results are interpreted as evidence that adding VIX squared in the conditional variance equation yields a better measure of conditional variance which, subsequently, uncovers a strong risk-return relation.     

Expectation,volatility and liquidity in the housing market

Measuring housing price volatility is fundamental to understanding the dynamics of housing price risk. This article aims to explore whether a liquidity factor plays a role in explaining the second moment (i.e. the volatility) of housing prices. Housing price volatility is measured as the conditional variance of a Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) model under the Adaptive Expectations framework. The empirical evidence reveals that volatility transmits from smaller housing units to larger housing units, which indirectly supports the trade-up effect discussed in the literature. In addition, less liquid housing classes are more sensitive to unexpected liquidity shocks, and the starter housing class is extraordinarily sensitive to negative liquidity shocks. Consistent with friction search theory, pricing errors are alleviated as the trading volume increases, because the valuation price tends to be more accurate as more information is available.     

Conditional price volatility,speculation, and excessive speculation in commodity markets: sheep or shepherd behaviour?

The present study aims to investigate the dynamics of primary commodity spot prices and the role of speculation for the period 1995–2012. Using a linear and nonlinear Granger causality analysis, the relationship between speculation and GARCH conditional price volatility on the one side, and the linkage between excessive speculation and GARCH conditional price volatility on the other side, is carefully examined with the scope to establish whether volatility drives speculation or speculation drives price volatility, or whether there are no linkages between the two variables. The results show that excessive speculation leads conditional price volatility, and that bilateral relationships often exist between price volatility and speculation. In addition, the lead-lag relationships are not found for the entire sample period, but rather when small sub-periods are taken into account. It turns out, in fact, that excessive speculation has driven price volatility for maize, rice, soybeans, and wheat in particular time frames, but the relationships are not always overlapping for all considered commodities. Generally, the results under linear causality tests are in agreement with those obtained under nonlinear counterparts.     

Noisy chaotic dynamics in commodity markets

The nonlinear testing and modeling of economic and financial time series has increased substantially in recent years, enabling us to better understand market and price behavior, risk and the formation of expectations. Such tests have also been applied to commodity market behavior, providing evidence of heteroskedasticity, chaos, long memory, cyclicity, etc. The present evaluation of futures price behavior confirms that the resulting price movements can be random, suggesting noisy chaotic behavior. Prices could thus follow a mean process that is dynamic chaotic, coupled with a variance that follows a GARCH process. Our conclusion is that models of this type could be constructed to assist in forecasting prices in the short run but not over long run time periods.First version received: June 2001/Final version received: March 2003     

Modelling the risk–return relation for the S&P 100: The role of VIX

A significantly positive risk–return relation for the S&P 100 market index is detected if the implied volatility index (VIX) is allowed for as an exogenous variable in the conditional variance equation. This result holds for 4 alternative GARCH specifications, irrespective of the conditional distribution, and regardless of whether the conditional mean equation includes a constant term. This finding is robust to sub-samples, and to using VIX innovations to control for dividend yield and trading volume effects. Monte Carlo evidence suggests that if VIX is not included, the risk–return relation is more likely to be negative or weak, in line with several previous studies. If VIX is included, the distribution of the risk–return parameter has more than 99% of its mass in the area of positive values. We conclude that VIX carries important forward-looking information which improves the precision of the conditional variance estimation and, subsequently, reveals a significantly positive relation.     

Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models

We examine and compare a large number of generalized autoregressive conditional heteroskedastic (GARCH) and stochastic volatility (SV) models using series of Bitcoin and Litecoin price returns to assess the model fit for dynamics of these cryptocurrency price returns series. The various models examined include the standard GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, t-distributed and moving average innovations. We report that the best model for Bitcoin is SV-t while it is GARCH-t for Litecoin. Overall, the t-class of models performs better than other classes for both cryptocurrencies. For Bitcoin, the SV models consistently outperform the GARCH models and the same holds true for Litecoin in most cases. Finally, the comparison of GARCH models with GARCH-GJR models reveals that the leverage effect is not significant for cryptocurrencies, suggesting that these do not behave like stock prices.     

上证180指数的GARCH族模型仿真研究——对上证300指数的间接实证建模分析

本文旨在运用GARCH族模型对即将作为股指期货标的物——上证300指数进行间接实证建模研究。本文使用上证180指数研究上证300指数具有可行性。分析结果表明:上海股市股价波动确实存在显著的GARCH效应和冲击持久效应,并存在较弱的杠杆效应;收益率条件方差序列是平稳的,模型具有可预测性,GARCH-M(1,1)模型可以很好地拟合与预测上证180指数。该仿真模型可以较好地实现点对点的长期高精度预测,克服了传统预测模型只能进行短期预测的缺陷。这不仅对于投资者规避风险,开拓利润空间,而且对于我国资本市场的稳健发展,都具有重要的理论与实践指导意义。     

Modelling risk premia in CO2 allowances spot and futures prices

This article analyzes the modelling of risk premia in CO₂ allowances spot and futures prices, valid for compliance under the EU Emissions Trading Scheme (EU ETS). Similarly to electricity markets, a salient characteristic of CO₂ allowances is that the theory of storage does not hold, as CO₂ allowances only exist on the balance sheets of companies regulated by the scheme. The main result features positive time-varying risk premia in CO₂ spot and futures prices, which are strictly higher for post-2012 contracts (€6–9/ton of CO₂) than for Phase II contracts (€0–6/ton of CO₂). Contrary to Benth et al.'s (2008) for electricity markets, a positive relationship between risk premia and time-to-maturity is found in the EU ETS. As for relative differences between CO₂ futures and spot prices, CO₂ futures traded between + 1% (December 2008 contract) and + 33% (December 2014 contract) above spot prices during February 2008–April 2009. Contrary to Bessembinder and Lemmon (2002) for the electricity market, a positive relationship between risk premia and the variance/skewness of CO₂ spot prices is found. The futures-spot bias to the EU ETS explains around 1–6% of the variance of CO₂ futures premia.     

Price volatility of south-east fishery's quota species: an empirical analysis

This study investigates the autoregressive conditional heteroscedasticity (ARCH) and generalized-ARCH (GARCH) effects in the price series of Australian South-East Fishery's quota species. It is found that in all cases significant ARCH and/or GARCH effects are present. To search for the origins of these effects a weakly exogenous variable (trading volume) is introduced to the conditional variance equation of the ARCH and GARCH models, provided that such effects are observed in the first stage of investigation. It is found that in 14 cases the estimated coefficients of the trading volume are negative. In all cases, the 'trading volume' variable does not contribute to the removal of the ARCH and/or GARCH effects. Finally, the policy implications of the findings are discussed.     

The demise of commodity price agreements: the role of exchange rates and special interests

We derive the equilibrium joint distribution of exchange rate and commodity price in a two-country rational expectations model. The correlation between commodity price and exchange rate appears crucial for the stability of commodity markets. This result arises from the common practice to quote commodity prices in consuming countries' currency, which subjects producing countries to the currency risk. Welfare results of commodity price stabilization are obtained and facilitate the interpretation of the position taken by industrialized countries long opposed to international commodity agreements. We apply our model to the Philippines and investigate the potential effects of the International Sugar Agreement (ISA) on the various conditional volatilities of the model. We conclude on the relative ineffectiveness of these agreements in limiting fluctuations of sugar prices.     

Rational Expectations is not Generally Valid for Econometric Models: Evidence from Stock Market Data

In applying the rational expectations hypothesis to generate expectations in an econometric model it is assumed that (1) the model itself is capable of generating reasonable forecasts of all required expectations variables included in the model, and that (2) the economic agents whose behavior is being modeled act as if they form their psychological expectations as conditional mathematical expectations generated by the model. Both assumptions can be invalid, as demonstrated by the historical data on Hong Kong stock prices and by the successful application of the adaptive expectations hypothesis to explain panel data of prices of individual stocks and aggregate time series data on stock price indices of the United States and of Hong Kong.     

The Effects of Subject Pool and Design Experience on Rationality in Experimental Asset Markets

Empirical evidence suggests that prices do not always reflect fundamental values and individual behavior is often inconsistent with rational expectations theory. We report the results of fourteen experimental asset markets designed to examine whether the interactive effect of subject pool and design experience (i.e., previous experience in a market under identical conditions) tempers price bubbles and improves forecasting ability. Our main findings are: 1) price run-ups are modest and dissipate quickly when traders are knowledgeable about financial markets and have participated in a previous market under identical conditions; 2) price bubbles moderate quickly when only a subset of traders are knowledgeable and experienced; 3) the heterogeneity of expectations about price changes is smaller in markets with knowledgeable and experienced traders, even if such traders only represent a subset of the market; and 4) individual forecasts of prices are not consistent with the predictions of the rational expectations model in any market, although absolute forecast errors are smaller for subjects who are knowledgeable of financial markets and for those subjects who have participated in a previous market. In sum, our findings suggest that markets populated by at least a subset of knowledgeable and experienced traders behave rationally, even though average individual behavior can be characterized as irrational.     

Riding the Bubble: Financial Market Crises in Twenty-Two OECD Countries

In the past decade, financial markets have been hit twice by crisis, followed each time by recession (i.e., Enron and the subprime mortgage crisis). I present three theories to explain the dynamics of share prices: rational expectations, behavioral finance, and an institution-oriented theory. Institutional investors are the dominant actors on financial markets. They hold the majority of the share capital in big companies. They tend to drive financial markets to a higher level of risk (volatility). The greater the percentage of the share capital held by institutional investors in a company, the higher the volatility (variance) of the share price. The results of my multilevel analysis confirm this hypothesis (a sample of 1,369 firms in twenty-two OECD countries). There are also significant differences among the OECD countries. Whereas both financial market crises originated in the United States, the country did not have the highest level of volatility in the period from 2000 to 2013.     

Rationality and the Risk Premium on the Australian dollar

A Model of the forward rate error of the USD/AUD spot exchange rate is fitted to daily data for the period 15th December 1983 to 31st December 1991. This provides a data set of 2034 daily trading observations. Explanations of the forecast error include a risk premium represented by a constant plus the conditional variance generated from a GARCH (1,1)-M analysis of the error process and information variables in the form of lagged forward rate errors. The following conclusions are drawn form estimates for the full sample: the USD/AUD spot rate is subject to a constant premium: there is little evidence to support a time varying component and the market is influenced by lagged forward errors. Sub period estimation confirms these results, although a time varying premium is evident prior to the February 1985 depreciation. The economic implications of these findings are discussed. [F31]     

Simultaneity,Forecasting and Profits in London Copper Futures

Previous research on price determination for non‐ferrous metals at the London Metal Exchange (LME) suffers from three limitations: first it has employed single equation methods only, which cannot explain the simultaneous determination of spot and futures prices; second, by focusing on current and lagged prices, previous research does not analyse the effect on price determination of critical variables such as expectations, consumption and inventories; third, the outcome of prior research regarding market efficiency is ambiguous. This paper, which addresses these issues, develops a simultaneous model of the copper market at the LME, with representation of the activities of hedgers, speculators and consumers. This model produces post‐sample forecasts of the spot price which outperform conventional benchmarks, thus providing evidence against the efficient market hypothesis. Model‐derived forecasts are employed as the foundation of a trading program which produces risk‐adjusted profits (net of commission costs) for holding periods of one week and one month, thus fulfilling the ‘sufficient condition’ for market inefficiency. This study, therefore, provides new insights into price determination on the LME copper market, and resolves the ambiguity of previous research regarding the efficiency of that market. This is the first application of the model forecasting approach to the question of performance of the market for copper.     

Asymmetry, realised volatility and stock return risk estimates

In this paper we estimate minimum capital risk requirements for short and long positions with three investment horizons, using the traditional GARCH model and two other GARCH-type models that incorporate the possibility of asymmetric responses of volatility to price changes. We also address the problem of the extremely high estimated persistence of the GARCH model to generate observed volatility patterns by including realised volatility as an explanatory variable into the model??s variance equation. The results suggest that the inclusion of realised volatility improves the GARCH forecastability as well as its ability to calculate accurate minimum capital risk requirements and makes it quite competitive when compared with asymmetric conditional heteroscedastic models such as the GJR and the EGARCH.     

Risk in supply response: an econometric application

The impact of risk aversion on supply response is empirically estimated for selected field crops in California. As indicators of risk aversion the following surrogate variables are used: variance of past prices and yields, adjusted price to reflect the role of government support price over the market price and the dummy variables indicating price expectations. In general, the econometric estimates show a negative impact of risk aversion measured by the surrogate variables and this has implications for welfare gains resulting from price support policies aimed at stabilization.     

The linkages,persistence, asymmetry in the volatility,the price discovery and efficiency,and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed support the spillover effects and the causality is bidirectional. We also have used the dummy variable for the US subprime mortgage financial crisis and found that they are statistically significant. Indian stock market is thus integrated to the world stock markets.     

Testing for weak-form efficiency of crude palm oil spot and future markets: new evidence from a GARCH unit root test with multiple structural breaks

There is a sizeable literature that tests for weak-form efficiency in commodity and energy spot and future prices. While many studies now allow for multiple structural breaks to address the criticism that conventional unit root tests have low power to reject the unit root null in the presence of structural change, the extant literature overlooks the fact that conventional unit root tests are biased in the presence of conditional heteroscedasticity. We apply a recently developed generalized autoregressive conditional heteroscedasticity (GARCH) unit root test with multiple structural breaks to crude palm oil spot and future prices and find much more evidence against weak-form efficiency than that found using tests that fail to allow for conditional heteroscedasticity. Our results point to the importance of allowing for heteroscedasticity when testing for efficiency in commodity and energy spot and future prices.