基于组合预测模型的我国能源需求预测分析

本文根据预测理论,结合我国历年能源消费的相关数据,分别采用多元线性回归方法、灰色预测、指数模型方法建立我国能源需求的单项预测模型,并对各单项模型的结果进行分析比较和检验,然后采用误差平方和最小法进行权重分配,建立了我国未来能源需求量的组合预测模型,最后,应用该模型对我国未来10年的能源需求量进行预测,结果表明：组合预测的精度要远远优于单项预测;我国未来10年的能源需求仍呈现较快的增长趋势。     

Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility

This paper develops a two-step estimation methodology that allows us to apply catastrophe theory to stock market returns with time-varying volatility and to model stock market crashes. In the first step, we utilize high-frequency data to estimate daily realized volatility from returns. Then, we use stochastic cusp catastrophe theory on data normalized by the estimated volatility in the second step to study possible discontinuities in the markets. We support our methodology through simulations in which we discuss the importance of stochastic noise and volatility in a deterministic cusp catastrophe model. The methodology is empirically tested on nearly 27 years of US stock market returns covering several important recessions and crisis periods. While we find that the stock markets showed signs of bifurcation in the first half of the period, catastrophe theory was not able to confirm this behaviour in the second half. Translating the results, we find that the US stock market’s downturns were more likely to be driven by the endogenous market forces during the first half of the studied period, while during the second half of the period, exogenous forces seem to be driving the market’s instability. The results suggest that the proposed methodology provides an important shift in the application of catastrophe theory to stock markets.     

Stochastic volatility: A tale of co-jumps,non-normality,GMM and high frequency data

In this article we introduce a linear–quadratic volatility model with co-jumps and show how to calibrate this model to a rich dataset. We apply GMM and more specifically match the moments of realized power and multi-power variations, which are obtained from high-frequency stock market data. Our model incorporates two salient features: the setting of simultaneous jumps in both return process and volatility process and the superposition structure of a continuous linear–quadratic volatility process and a Lévy-driven Ornstein–Uhlenbeck process. We compare the quality of fit for several models, and show that our model outperforms the conventional jump diffusion or Bates model. Besides that, we find evidence that the jump sizes are not normally distributed and that our model performs best when the distribution of jump-sizes is only specified through certain (co-) moment conditions. Monte Carlo experiments are employed to confirm this.     

On detection of volatility spillovers in overlapping stock markets

This paper applies a recently proposed structural vector autoregressive model identification method to an established, previously unidentified theoretical model of stock market volatility spillovers. The structural model is identified and can be estimated with the method of maximum likelihood. Volatility spillovers can then be tested with the standard likelihood ratio test. This way our test, unlike the majority of the existing volatility spillover tests, has its foundations firmly in the economic theory. Our test is developed for fully overlapping stock markets. The empirical application of the paper considers stock markets of the eurozone in the years 2010–2011. Evidence of volatility spillovers is found.     

A Pricing Model for Quantity Contracts

An economic model is proposed for a combined price futures and yield futures market. The innovation of the article is a technique of transforming from quantity and price to a model of two genuine pricing processes. This is required in order to apply modern financial theory. It is demonstrated that the resulting model can be estimated solely from data for a yield futures market and a price futures market. We develop a set of pricing formulas, some of which are partially tested, using price data for area yield options from the Chicago Board of Trade. Compared to a simple application of the standard Black and Scholes model, our approach seems promising.     

Estimation of default probabilities using incomplete contracts data

This paper develops a count data model for credit scoring which allows the estimation of default probabilities using incomplete contracts data. The main advantage of the proposed approach is that it permits a more efficient use of the data, including that for the most recent clients. Moreover, because the probability of default is specified as a function of the age of the contract, the model provides some information on the timing of the defaults. The model is based on the beta-binomial distribution, which is found to be particularly adequate for this purpose. A well-known dataset on personal loans is used to illustrate the application of the proposed model.     

Sequential auctions: theory and evidence from the Seattle Fur Exchange

We develop a model that incorporates salient features of the Seattle Fur Exchange: identical lots of furs are auctioned sequentially, bids must be raised by specified increments, and the winner of a lot has the privilege of beginning the bidding on the subsequent lot. Predictions of the theory are consistent with the data. Revenue implications of the theory are also explored.     

Implied migration rates from credit barrier models

The risk-neutral credit migration process captures quantitative information which is relevant to the pricing theory and risk management of credit derivatives. In this article, we derive implied migration rates by means of a recently introduced credit barrier model which is calibrated on the basis of aggregate information such as credit migration rates and credit spread curves. The model is characterized by an underlying stochastic process that represents credit quality, and default events are associated to barrier crossings. The stochastic process has state dependent volatility and jumps which are estimated by using empirical migration and default rates. A risk-neutralizing drift and forward liquidity spreads are estimated to consistently match the average spread curves corresponding to all the various ratings. The implied migration rates obtained with our credit barrier model are then compared with those obtained via the Kijima–Komoribayashi model.     

Efficiency tests with overlapping data: an application to the currency options market

This paper presents the results of an empirical study into the efficiency of the currency options market. The methodology derives from a simple model often applied to the spot and forward markets for foreign exchange. It relates the historic volatility of the underlying asset to the implied volatility of an option on the underlying at a specified prior time and then proceeds to test obvious hypotheses about the values of the coefficients. The study uses panel regression to address the problem of overlapping data which leads to dependence between observations. It also uses volatility data directly quoted on the market in order to avoid the biases which may occur when ‘backing out’ volatility from specific option pricing models. In general, the evidence rejects the hypothesis that the currency option market is efficient. This suggests that implied volatility is not the best predictor of future exchange rate volatility and should not be used without modification: the models presented in this paper could be a way of producing revised forecasts.     

ON THE RATIONALITY OF COMMON STOCK RETURN VOLATILITY

This paper derives the relationship between the population unconditional variance of common stock returns and the variance of expected returns conditional on a well-specified information set. As a consequence, a lower bound is obtained for the variance of common stock returns. The sample counterpart of this bound is then empirically tested against the sample variance of returns. The paper's main conclusion can be stated as follows: the observed volatility of real (inflation-adjusted) common stock returns is not “irrationally” large. The paper admits of this conclusion because the point estimate of the lower-bound variance derived in this model is actually larger than the point estimate of common stock return volatility. However, since these point estimates are found to have a statistically insignificant difference, equality of the two variances cannot be ruled out. Hence, “rationality” of common stock returns—as implied by a utility-based valuation conditional on a specified information set—cannot be rejected.     

Capital and risk in property-liability insurance markets

This paper investigates the capital and portfolio risk decisions of property-liability insurance firms. A theoretical model based on option pricing theory is developed which predicts a positive relationship between insurer capital and risk, as firms balance these two factors to achieve their desired overall insolvency risk. The implications of the model are then tested empirically using a simultaneous equations methodology. The results support the predictions of the model. They also provide evidence that managerial incentives play a role in determining capital and risk in insurance markets. The findings have significant implications for insurance solvency regulation.     

An Investigation of Commodity Futures Prices Using the Consumption-Based Intertemporal Capital Asset Pricing Model

In this paper we extend the multigood futures pricing model of Grauer and Litzenberger 9 to a dynamic discrete time setting. We then test the model using data on futures prices for corn, wheat, and soybeans. The parameter estimates we obtain are similar to those obtained by other researchers using stock return data. The model itself is rejected and we offer some suggestions as to which assumption may be violated. We also give an interpretation to the Hansen-Singleton nonlinear instrumental variables estimation technique used in our empirical work.     

多元化与资本成本的关系——来自中国股票市场的证据

根据期权定价模型,多元化降低了公司风险,但其受益者是债权人,而不是股东,这使得公司部分财富从股东手中转移到债权人手中,由此降低了股东财富,因此,多元化可能并不为股东所欢迎,从而多元化公司的权益资本成本可能高于专业化公司。同时,由于内部资本市场在公司内部的资源再配置作用,使得公司降低了对融资成本较高的外部资本市场的依赖,因此,多元化经营公司的总资本成本可能低于专业化经营公司。本文以2001—2004年我国上市公司为例,对多元化与公司权益资本成本和总资本成本之间的关系进行了实证检验。研究结果表明,多元化与权益资本成本正相关,而与总资本成本负相关。     

The pricing of adjustable rate mortgage contracts

This article analyzes the structure of ARM contracts and the pricing of their component features, based on the view of ARMs as a complex bundle. Unlike previous studies, which have generally relied on option-based simulation techniques, our analysis specifies a microeconomic model of the lender as a profit-maximizer which is then tested using firm-specific data. The empirical results, which are consistent with the microeconomic model, indicate that the lender acts as a profit-maximizing firm in pricing the features of the ARM contract. Furthermore, the results suggest that while the interest-rate cap parameters dominate in the pricing of ARMs, other features are also important. Thus, theoretical and empirical ARM pricing models should embrace other features of the contract besides the cap parameters.     

Robust outlier detection for Asia–Pacific stock index returns

Outliers can lead to model misspecifications, poor forecasts and invalid inferences. Their identification and correction is therefore an important objective of financial modeling.This paper introduces a simple method to detect outliers in a financial series. It uses an AR(1)–GARCH(1,1) model to calculate interval forecasts for one-step ahead returns that are then compared to realized returns to determine whether or not we are in the presence of an aberrant observation. The GARCH model, however, is only used as a filter and the identification algorithm remains robust to model misspecifications.The efficiency of this outlier-correction technique is first tested with a simulation study, before being applied to five Asian stock market returns to identify the outlying observations. After an analysis of these extreme fluctuations, the out-of-sample forecasting performance of our outlier-corrected model is then compared to the classical forecasts of a GARCH model in which no account is taken of outliers.     

THE ARBITRAGE PRICING THEORY AND COST-OF-CAPITAL ESTIMATION: THE CASE OF ELECTRIC UTILITIES

Capital asset pricing model (CAPM) and alternative arbitrage pricing theory (APT) methodologies are used to estimate the cost of capital for a sample of electric utilities. The statistical factors APT method is found to produce significantly different estimates depending on the number of factors specified and the set of firms factor analyzed. The use of macroeconomic factors is explored, and it is shown that this methodology has advantages over the statistical factors APT and the market model.     

Prospect theory–based portfolio optimization: an empirical study and analysis using intelligent algorithms

The behaviourally based portfolio selection problem with investor’s loss aversion and risk aversion biases in portfolio choice under uncertainty is studied. The main results of this work are: developed heuristic approaches for the prospect theory model proposed by Kahneman and Tversky in 1979 as well as an empirical comparative analysis of this model and the index tracking model. The crucial assumption is that behavioural features of the prospect theory model provide better downside protection than traditional approaches to the portfolio selection problem. In this research the large-scale computational results for the prospect theory model have been obtained for real financial market data with up to 225 assets. Previously, as far as we are aware, only small laboratory tests (2–3 artificial assets) have been presented in the literature. In order to investigate empirically the performance of the behaviourally based model, a differential evolution algorithm and a genetic algorithm which are capable of dealing with a large universe of assets have been developed. Specific breeding and mutation, as well as normalization, have been implemented in the algorithms. A tabulated comparative analysis of the algorithms’ parameter choice is presented. The prospect theory model with the reference point being the index is compared to the index tracking model. A cardinality constraint has been implemented to the basic index tracking and the prospect theory models. The portfolio diversification benefit has been found. The aggressive behaviour in terms of returns of the prospect theory model with the reference point being the index leads to better performance of this model in a bullish market. However, it performed worse in a bearish market than the index tracking model. A tabulated comparative analysis of the performance of the two studied models is provided in this paper for in-sample and out-of-sample tests. The performance of the studied models has been tested out-of-sample in different conditions using simulation of the distribution of a growing market and simulation of the t-distribution with fat tails which characterises the dynamics of a decreasing or crisis market.     

Rising to the challenge: A model of contest performance

Contests are a ubiquitous form of promotion widely adopted by financial services advertisers, yet, paradoxically, academic research on them is conspicuous in its absence. This work addresses this gap by developing a model of contest engagement and performance. Using motivation theory, factors that drive participant engagement are modeled, and engagement's effect on experience and marketing success of the contest specified. Measures of contest performance, in-contest engagement and post-contest enduring interest are included. From the model, propositions are developed. Overall, the model provides financial service marketers with a theory-based foundation for designing and operating successful contests.     

Rising to the challenge: A model of contest performance

Contests are a ubiquitous form of promotion widely adopted by financial services advertisers, yet, paradoxically, academic research on them is conspicuous in its absence. This work addresses this gap by developing a model of contest engagement and performance. Using motivation theory, factors that drive participant engagement are modeled, and engagement's effect on experience and marketing success of the contest specified. Measures of contest performance, in-contest engagement and post-contest enduring interest are included. From the model, propositions are developed. Overall, the model provides financial service marketers with a theory-based foundation for designing and operating successful contests.     

Endogenous objectives and the evaluation of targeting rules for monetary policy

Recent research in monetary economics has followed the advice of McCallum [1988. Robustness properties of a rule for monetary policy. Carnegie-Rochester Conference Series on Public Policy 29, 173-203] and investigated the robustness properties of monetary policy rules by evaluating them in a variety of models. Evaluation across models is typically based on an exogenously specified loss function. However, the theory on which many recent monetary policy models are based implies that changes in the structure of the model also have consequences for the policy objectives the central bank should pursue. Objectives are endogenous, not exogenous to the model. In this paper, I investigate the impact of endogenous objectives on the evaluation of targeting rules for monetary policy.