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1.
《Journal of Financial Economics》1987,18(2):341-371
This paper evaluates the power of multivariate tests of the Capital Asset Pricing Model. The results indicate that when employing an unspecified alternative hypothesis, the ability of the tests to distinguish between the CAPM and other pricing models is poor. An upper bound is derived for the distance the alternative distribution of the test statistic can be from the null distribution when the deviations from the CAPM are due to missing factors. This upper bound explains the low power of the tests. 相似文献
2.
This paper examines the power of the cross-sectional and multivariate tests of the CAPM under ideal conditions. When the CAPM is true the positively weighted market portfolio is MV-efficient and securities plot on the security market line. When the CAPM is false an alternative asset pricing model determines prices. An examination of the population intercepts, slopes and R2 from cross-sectional regressions of expected returns on betas indicates that all three are unreliable indicators of whether the CAPM holds. Simulation analysis of the power of the cross-sectional tests expands on and reinforces the analysis based on the population values. The Gibbons et al. (1989) multivariate test fares much better. 相似文献
3.
Jay Shanken 《Journal of Financial Economics》1985,14(3):327-348
A ‘cross-sectional regression test’ (CSRT) of the CAPM is developed and its connection to the Hotelling T2 test of multivariate statistical analysis is explored. Algebraic relations between the CSRT, the likehood ratio test and the Langrange multiplier test are derived and a useful small-sample bound on the distribution function of the CSRT is obtained. An application of the CSRT suggests that the CRSP equally-weighted index is inefficient, but that the inefficiency is not explained by a firm size-effect from February to December. 相似文献
4.
Phelim P. Boyle 《Journal of Financial Economics》1977,4(3):323-338
This paper develops a Monte Carlo simulation method for solving option valuation problems. The method simulates the process generating the returns on the underlying asset and invokes the risk neutrality assumption to derive the value of the option. Techniques for improving the efficiency of the method are introduced. Some numerical examples are given to illustrate the procedure and additional applications are suggested. 相似文献
5.
A Monte Carlo Method for Optimal Portfolios 总被引:6,自引:0,他引:6
This paper proposes a new simulation-based approach for optimal portfolio allocation in realistic environments with complex dynamics for the state variables and large numbers of factors and assets. A first illustration involves a choice between equity and cash with nonlinear interest rate and market price of risk dynamics. Intertemporal hedging demands significantly increase the demand for stocks and exhibit low volatility. We then analyze settings where stock returns are also predicted by dividend yields and where investors have wealth-dependent relative risk aversion. Large-scale problems with many assets, including the Nasdaq, SP500, bonds, and cash, are also examined. 相似文献
6.
Anthonie W. van der Stoep Lech A. Grzelak Cornelis W. Oosterlee 《Quantitative Finance》2017,17(9):1347-1366
We present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant. Finance, 2014, 14, 1899–1922], Piterbarg [Risk, 2007, April, 84–89], Tataru and Fisher [Quantitative Development Group, Bloomberg Version 1, 2010], Lipton [Risk, 2002, 15, 61–66]—and the local volatility model incorporating stochastic interest rates—see e.g. Atlan [ArXiV preprint math/0604316, 2006], Piterbarg [Risk, 2006, 19, 66–71], Deelstra and Rayée [Appl. Math. Finance, 2012, 1–23], Ren et al. [Risk, 2007, 20, 138–143]. For both model classes a particular (conditional) expectation needs to be evaluated which cannot be extracted from the market and is expensive to compute. We establish accurate and ‘cheap to evaluate’ approximations for the expectations by means of the stochastic collocation method [SIAM J. Numer. Anal., 2007, 45, 1005–1034], [SIAM J. Sci. Comput., 2005, 27, 1118–1139], [Math. Models Methods Appl. Sci., 2012, 22, 1–33], [SIAM J. Numer. Anal., 2008, 46, 2309–2345], [J. Biomech. Eng., 2011, 133, 031001], which was recently applied in the financial context [Available at SSRN 2529691, 2014], [J. Comput. Finance, 2016, 20, 1–19], combined with standard regression techniques. Monte Carlo pricing experiments confirm that our method is highly accurate and fast. 相似文献
7.
We show that in the presence of non-zero pricing errors, the Fama–MacBeth (FM) cross-sectional regression test is very likely to either reject the Capital Asset Pricing Model (CAPM) when it (almost) holds or accept the model when it grossly fails. We investigate the case when pricing errors are correlated with betas and demonstrate that the test performance depends crucially on the correlation, cross-sectional distribution of betas, and several other parameter values. Even when the CAPM holds exactly (pricing errors are zero) the FM test is equally likely to either reject or accept the model when typical sample sizes are used. 相似文献
8.
In this evaluation of energy assets related to natural gas, our particular focus is on a base load natural gas combined cycle power plant and a liquefied natural gas facility in a realistic setting. We also value several American-type investment options following the least squares Monte Carlo approach. We calibrate mean-reverting stochastic processes for gas and electricity prices by using data from NYMEX NG futures contracts and the Spanish wholesale electricity market, respectively. Additional sources of uncertainty concern the initial investment outlay, or the option's time to maturity, or the cost of CO2 emission permits. 相似文献
9.
The effects of monetary policy shocks on financial conditions are often estimated by appealing to recursive Vector AutoRegressions (VARs). We assess the ability of this class of VARs to recover the true effects of a monetary policy shock via a Monte Carlo experiment in which the Data Generating Process is a Dynamic Stochastic General Equilibrium (DSGE) model featuring macro-finance interactions and estimated with U.S. quarterly data. Our DSGE model predicts a negative and significant reaction of financial conditions to an unexpected monetary policy tightening. We point out that such reaction is just overlooked by recursive VARs. Moreover, we show that Cholesky-VARs may substantially underestimate the welfare costs due to macroeconomic fluctuations. 相似文献
10.
亚式期权定价的模拟方法研究 总被引:1,自引:0,他引:1
赵建忠 《上海金融学院学报》2006,(5):58-61
由于算术平均价格亚式期权的定价没有解析公式,所以文章用Monte Carlo模拟方法通过Matlab软件编写程序对亚式期权进行了定价。发现在某些情况下,亚式期权的价值并不是国内外一些研究者所认为的低于相应的欧式期权的价值。 相似文献
11.
Ryan McCrickerd 《Quantitative Finance》2013,13(11):1877-1886
The rough Bergomi model, introduced by Bayer et al. [Quant. Finance, 2016, 16(6), 887–904], is one of the recent rough volatility models that are consistent with the stylised fact of implied volatility surfaces being essentially time-invariant, and are able to capture the term structure of skew observed in equity markets. In the absence of analytical European option pricing methods for the model, we focus on reducing the runtime-adjusted variance of Monte Carlo implied volatilities, thereby contributing to the model’s calibration by simulation. We employ a novel composition of variance reduction methods, immediately applicable to any conditionally log-normal stochastic volatility model. Assuming one targets implied volatility estimates with a given degree of confidence, thus calibration RMSE, the results we demonstrate equate to significant runtime reductions—roughly 20 times on average, across different correlation regimes. 相似文献
12.
收益法是预测性和主观性委强的一种价值评估方法.本文介绍了蒙特卡罗模拟预测原理对收益法价值评估的优化作用,并在一个评估实例中对蒙特卡罗技术进行了两个层次的应用.本文认为蒙特卡罗模拟可以扩大收益法参数分析的覆盖范围,提高评估计算的精确度,增强评估结果的说服力和可信度,同时减少评估人员对评估结果的人为操纵. 相似文献
13.
14.
Adjoint methods have recently gained considerable importance in the finance sector, because they allow to quickly compute option sensitivities with respect to a large number of model parameters. In this paper we investigate how the efficiency of adjoint methods can be exploited to speed up the Monte Carlo-based calibration of financial market models. After analyzing the calibration problem both theoretically and numerically, we derive the associated adjoint equation and propose its application in combination with a multi-layer method, for which we prove convergence to a stationary point of the underlying optimization problem. Detailed numerical examples illustrate the performance of the method. In particular, the proposed algorithm reduces the calibration time for a typical equity market model with time-dependent model parameters from over three hours to less than ten minutes on a usual desktop PC. 相似文献
15.
This paper studies various possible approaches to improving the least squares Monte Carlo option valuation method. We test different regression algorithms and suggest a variation to estimating the option continuation value, which can reduce the execution time of the algorithm by one third. We test the choice of varying polynomial families with different number of basis functions. We compare several variance reduction techniques, and find that using low discrepancy sequences can improve the accuracy up to four times. We also extend our analysis to compound and mutually exclusive options. For the latter, we propose an improved algorithm which is faster and more accurate. 相似文献
16.
The least squares Monte Carlo method of Longstaff and Schwartz has become a standard numerical method for option pricing with many potential risk factors. An important choice in the method is the number of regressors to use and using too few or too many regressors leads to biased results. This is so particularly when considering multiple risk factors or when simulation is computationally expensive and hence relatively few paths can be used. In this paper we show that by imposing structure in the regression problem we can improve the method by reducing the bias. This holds across different maturities, for different categories of moneyness and for different types of option payoffs and often leads to significantly increased efficiency. 相似文献
17.
Given a multi-dimensional Markov diffusion X, the Malliavin integration by parts formula provides a family of representations of the conditional expectation E[g(X
2)|X1]. The different representations are determined by some localizing functions. We discuss the problem of variance reduction within this family. We characterize an exponential function as the unique integrated mean-square-error minimizer among the class of separable localizing functions. For general localizing functions, we prove existence and uniqueness of the optimal localizing function in a suitable Sobolev space. We also provide a PDE characterization of the optimal solution which allows to draw the following observation : the separable exponential function does not minimize the integrated mean square error, except for the trivial one-dimensional case. We provide an application to a portfolio allocation problem, by use of the dynamic programming principle.Mathematics Subject Classification:
60H07, 65C05, 49-00JEL Classification:
G10, C10The authors gratefully acknowledge for the comments raised by an anonymous referee, which helped understanding the existence result of Sect. [4.2] of this paper. 相似文献
18.
In this paper we propose a Bayesian method to estimate the hyperbolic diffusion model. The approach is based on the Markov chain Monte Carlo (MCMC) method with the likelihood of the discretized process as the approximate posterior likelihood. We demonstrate that the MCMC method Provides a useful tool in analysing hyperbolic diffusions. In particular, quantities of posterior distributions obtained from the MCMC outputs can be used for statistical inference. The MCMC method based on the Milstein scheme is unsatisfactory. Our simulation study shows that the hyperbolic diffusion exhibits many of the stylized facts about asset returns documented in the discrete-time financial econometrics literature, such as the Taylor effect, a slowly declining autocorrelation function of the squared returns, and thick tails. 相似文献
19.
William T. Hughes 《The Journal of Real Estate Finance and Economics》1995,11(2):177-187
Introduction of the Present Value Distribution Model (PVD) offers an alternative method for the valuation of projects yielding intertemporal stochastic rents. A combination of concepts from many areas of the literature yields the given model. The base procedure relies on Monte Carlo Simulation with the application of recently established theories on stochastic rents, path dependent cash flow trajectories, and period dependent discount rates.Among the benefits of the (PVD) are exogenous risk discounting and consistent distribution determination. Risk discounting is applied to the resultant of the distribution model rather than within the model. Furthermore, the present value distributions are independent of analyst's perceptions yielding an objective single period gamble. 相似文献
20.
蒙特卡罗方差减小技术以及在金融中的应用 总被引:1,自引:0,他引:1
本文主要介绍MonteCarlo方差减小技术及其在金融中衍生证券定价的一些的应用。对近几年来国际上取得的主要研究成果作了简要的介绍和比较。并提出一些目前待解决的问题。 相似文献