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1
Davies, Philip R. "Empirical tests of asset pricing models". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1184592627.
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Fu, Jun, i 付君. "Asset pricing, hedging and portfolio optimization". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48199345.
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Starting from the most famous Black-Scholes model for the underlying asset
price, there has been a large variety of extensions made in recent decades.
One main strand is about the models which allow a jump component in the
asset price. The first topic of this thesis is about the study of jump risk
premium by an equilibrium approach. Different from others, this work provides
a more general result by modeling the underlying asset price as the ordinary
exponential of a L?vy process. For any given asset price process, the equity
premium, pricing kernel and an equilibrium option pricing formula can be
derived. Moreover, some empirical evidence such as the negative variance risk
premium, implied volatility smirk, and negative skewness risk premium can
be well explained by using the relation between the physical and risk-neutral
distributions for the jump component.
Another strand of the extensions of the Black-Scholes model is about the
models which can incorporate stochastic volatility in the asset price. The second
topic of this thesis is about the replication of exponential variance, where
the key risks are the ones induced by the stochastic volatility and moreover it
can be correlated with the returns of the asset, referred to as leverage effect.
A time-changed L?vy process is used to incorporate jumps, stochastic volatility
and leverage effect all together. The exponential variance can be robustly
replicated by European portfolios, without any specification of a model for the
stochastic volatility.
Beyond the above asset pricing and hedging, portfolio optimization is also
discussed. Based on the Merton (1969, 1971)'s reduced portfolio optimization
and the delta hedging problem, a portfolio of an option, the underlying stock
and a risk-free bond can be optimized in discrete time and its optimal solution
can be shown to be a mixture of the Merton's result and the delta hedging
strategy. The main approach is the elasticity approach, which has initially
been proposed in continuous time.
In addition to the above optimization problem in discrete time, the same
topic but in a continuous-time regime-switching market is also presented. The
use of regime-switching makes our market incomplete, and makes it difficult to
use some approaches which are applicable in complete market. To overcome
this challenge, two methods are provided. The first method is that we simply
do not price the regime-switching risk when obtaining the risk-neutral probability.
Then by the idea of elasticity, the utility maximization problem can be
formulated as a stochastic control problem with only a single control variable,
and explicit solutions can be obtained. The second method is to introduce
a functional operator to general value functions of stochastic control problem
in such a way that the optimal value function in our setting can be given by
the limit of a sequence of value functions defined by iterating the operator.
Hence the original problem can be deduced to an auxiliary optimization problem,
which can be solved as if we were in a single-regime market, which is
complete.published_or_final_version
Statistics and Actuarial Science
Doctoral
Doctor of Philosophy
3
Murara, Jean-Paul. "Asset Pricing Models with Stochastic Volatility". Licentiate thesis, Mälardalens högskola, Utbildningsvetenskap och Matematik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-31576.
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Asset pricing modeling is a wide range area of research in Financial Engineering. In this thesis, which consists of an introduction, three papers and appendices; we deal with asset pricing models with stochastic volatility. Here stochastic volatility modeling includes diffusion models and regime-switching models. Stochastic volatility models appear as a response to the weakness of the constant volatility models. In Paper A , we present a survey on popular diffusion models where the volatility is itself a random process and we present the techniques of pricing European options under each model. Comparing single factor stochastic volatility models to constant factor volatility models it seems evident that the stochastic volatility models represent nicely the movement of the asset price and its relations with changes in the risk. However, these models fail to explain the large independent fluctuations in the volatility levels and slope. We consider Chiarella and Ziveyi model, which is a subclass of the model presented in Christoffersen and in paper A, we also explain a multi-factor stochastic volatility model presented in Chiarella and Ziveyi. We review the first-order asymptotic expansion method for determining European option price in such model. Multiscale stochastic volatilities models can capture the smile and skew of volatilities and therefore describe more accurately the movements of the trading prices. In paper B, we provide experimental and numerical studies on investigating the accuracy of the approximation formulae given by this asymptotic expansion. We present also a procedure for calibrating the parameters produced by our first-order asymptotic approximation formulae. Our approximated option prices will be compared to the approximation obtained by Chiarella and Ziveyi. In paper C, we implement and analyze the Regime-Switching GARCH model using real NordPool Electricity spot data. We allow the model parameters to switch between a regular regime and a non-regular regime, which is justified by the so-called structural break behaviour of electricity price series. In splitting the two regimes we consider three criteria, namely the intercountry price di_erence criterion, the capacity/flow difference criterion and the spikes-in-Finland criterion. We study the correlation relationships among these criteria using the mean-square contingency coe_cient and the co-occurrence measure. We also estimate our model parameters and present empirical validity of the model.
4
Limkriangkrai, Manapon. "An empirical investigation of asset-pricing models in Australia". University of Western Australia. Faculty of Business, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0197.
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[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.
5
Galagedera, Don U. A. "Investment performance appraisal and asset pricing models". Monash University, Dept. of Econometrics and Business Statistics, 2003. http://arrow.monash.edu.au/hdl/1959.1/5780.
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Chen, Ping, i 陈平. "Asset-liability management under regime-switching models". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43223928.
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Ong, Alen Sen Kay. "Asset location decision models in life insurance". Thesis, City University London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336430.
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Hong, Harrison G. (Harrison Gregory). "Dyanmic models of asset returns and trading". Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10315.
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De, Araujo Pedro Falcão. "Heterogeneity in macro models of asset accumulation". [Bloomington, Ind.] : Indiana University, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3337250.
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Thesis (Ph.D.)--Indiana University, Dept. of Economics, 2008.Title from PDF t.p. (viewed on Jul 28, 2009). Source: Dissertation Abstracts International, Volume: 69-12, Section: A, page: 4804. Adviser: Gerhard Glomm.
10
Chen, Ping. "Asset-liability management under regime-switching models". Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43223928.
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Dharmawan, Komang School of Mathematics UNSW. "Superreplication method for multi-asset barrier options". Awarded by:University of New South Wales. School of Mathematics, 2005. http://handle.unsw.edu.au/1959.4/30169.
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The aim of this thesis is to study multi-asset barrier options, where the volatilities of the stocks are assumed to define a matrix-valued bounded stochastic process. The bounds on volatilities may represent, for instance, the extreme values of the volatilities of traded options. As the volatilities are not known exactly, the value of the option can not be determined. Nevertheless, it is possible to calculate extreme values. We show that these values correspond to the best and the worst case scenarios of the future volatilities for short positions and long positions in the portfolio of the options. Our main tool is the equivalence of the option pricing and a certain stochastic control problem and the resulting concept of superhedging. This concept has been well known for some time but never applied to barrier options. First, we prove the dynamic programming principle (DPP) for the control problem. Next, using rather standard arguments we derive the Hamilton-Jacobi-Bellman equation for the value function. We show that the value function is a unique viscosity solution of the Hamilton-Jacobi-Bellman equation. Then we define the super price and superhedging strategy for the barrier options and show equivalence with the control problem studied above. The superprice price can be found by solving the nonlinear Hamilton-Jacobi-Equation studied above. It is called sometimes the Black-Scholes-Barenblatt (BSB) equation. This is the Hamilton-Jacobi-Bellman equation of the exit control problem. The sup term in the BSB equation is determined dynamically: it is either the upper bound or the lower bound of the volatility matrix, according to the convexity or concavity of the value function with respect to the stock prices. By utilizing a probabilistic approach, we show that the value function of the exit control problem is continuous. Then, we also obtain bounds for the first derivative of the value function with respect to the space variable. This derivative has an important financial interpretation. Namely, it allows us to define the superhedging strategy. We include an example: pricing and hedging of a single-asset barrier option and its numerical solution using the finite difference method.
12
Parmler, Johan. "Essays in empirical asset pricing". Doctoral thesis, Stockholm : Economic Research Institute (EFI), Stockholm School of Economics, 2005. http://www.hhs.se/efi/summary/691.htm.
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Brandão, Diego Gusmão. "Three essays on the estimation of asset pricing models". reponame:Repositório Institucional do FGV, 2016. http://hdl.handle.net/10438/17994.
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The thesis consists in three articles about the estimation of asset pricing models. The first paper analyses small sample properties of Generalized Empirical Likelihood estimators for the risk aversion parameter in CRRA preferences when the economy is characterized by rare disasters. In the second article, we develop and test a methodology to assess misspeci fied asset pricing models by taking into account the smallest probability distortion necessary to assign correct prices. In the final paper, we estimate an approximate long run risks model using Brazilian data.
Esta tese consiste em três artigos sobre a estimação de modelos de apreçamento de ativos. No primeiro artigo, analisamos as propriedades de amostra pequena dos estimadores da classe Generalized Empirical Likelihood para o coeficiente de aversão ao risco de preferências CRRA quando a economia é suscetível a desastres. No segundo artigo, apresentamos e testamos uma metodologia de avaliação de modelos de apreçamento mal especificados que leva em conta a menor distorção de probabilidade necessária sobre a medida real para que modelo aprece corretamente ativos. No terceiro artigo, estimamos uma versão aproximada do modelo de riscos de longo prazo utilizando dados brasileiros.
14
Yoon, Jai-Hyung. "Four essays on international real business cycle and asset pricing models". Monash University, Dept. of Accounting and Finance, 2002. http://arrow.monash.edu.au/hdl/1959.1/8520.
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Yang, Cheng-Yu. "Essays on multi-asset jump diffusion models : estimation, asset allocation and American option pricing". Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/93986/.
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In the first essay (Chapter 2), we develop an efficient payoff function approximation approach to estimating lower and upper bounds for pricing American arithmetic average options with a large number of underlying assets. This method is particularly efficient for asset prices modeled by jump-diffusion processes with deterministic volatilities because the geometric mean is always a one-dimensional Markov process regardless of the number of underlying assets and thus is free from the curse of dimensionality. Another appealing feature of our method is that it provides an extremely efficient way to obtain tight upper bounds with no nested simulation involved as opposed to some existing duality approaches. Various numerical examples with up to 50 underlying stocks suggest that our algorithm is able to produce computationally efficient results. Chapter 3 solves portfolio choice problem in multi-dimensional jump-diffusion models designed to capture empirical features of stock prices and financial contagion effect. To obtain closed-form solution, we develop a novel general decomposition technique with which we reduce the problem into two relative simple ones: Portfolio choice in a pure-diffusion market and in a jump-diffusion market with less dimension. The latter can be reduced further to be a bunch of portfolio choice problems in one-dimensional jump-diffusion markets. By virtue of the decomposition, we obtain a semi-closed form solution for the primary optimal portfolio choice problem. Our solution provides new insights into the structure of an optimal portfolio when jumps are present in asset prices and/or their variance-covariance. In Chapter 4, we develop a estimation procedure based on Markov Chain Monte Carlo methods and aim to provide systematic ways to estimating general multivariate stochastic volatility models. In particular, this estimation technique is proved to be efficient for multivariate jump-diffusion process such as the model developed in Chapter 3 with various simulation studies. As a result, it contributes to the asset pricing literature by providing an efficient estimation technique for asset pricing models.
16
Spurway, Kayleigh Fay Nanette. "A study of the Consumption Capital Asset Pricing Model's appilcability across four countries". Thesis, Rhodes University, 2014. http://hdl.handle.net/10962/d1013016.
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Historically, the Consumption Capital Asset Pricing Method (C-CAPM) has performed poorly in that estimated parameters are implausible, model restrictions are often rejected and inferences appear to be very sensitive to the choice of economic agents' preferences. In this study, we estimate and test the C-CAPM with Constant Relative Risk Aversion (CRRA) using time series data from Germany, South Africa, Britain and America during relatively short time periods with the latest available data sets. Hansen's GMM approach is applied to estimate the parameters arising from this model. In general, estimated parameters fall outside the bounds specified by Lund & Engsted (1996) and Cuthbertson & Nitzsche (2004), even though the models are not rejected by the J-test and are associated with relatively small minimum distances.
17
Näsström, Jens. "Volatility Modelling of Asset Prices using GARCH Models". Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1625.
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The objective for this master thesis is to investigate the possibility to predict the risk of stocks in financial markets. The data used for model estimation has been gathered from different branches and different European countries. The four data series that are used in the estimation are price series from: Münchner Rück, Suez-Lyonnaise des Eaux, Volkswagen and OMX, a Swedish stock index. The risk prediction is done with univariate GARCH models. GARCH models are estimated and validated for these four data series.
Conclusions are drawn regarding different GARCH models, their numbers of lags and distributions. The model that performs best, out-of-sample, is the APARCH model but the standard GARCH is also a good choice. The use of non-normal distributions is not clearly supported. The result from this master thesis could be used in option pricing, hedging strategies and portfolio selection.
18
Rossvoll, Eivind. "Asset Pricing Models and the Norwegian Stock Market". Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for samfunnsøkonomi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23067.
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Vassalou, Maria G. "A test of alternative international asset pricing models". Thesis, London Business School (University of London), 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261703.
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Petherick, Stuart Gary. "Fractal activity time risky asset models with dependence". Thesis, Cardiff University, 2011. http://orca.cf.ac.uk/55127/.
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The paradigm Black-Scholes model for risky asset prices has occupied a central place in asset-liability management since its discovery in 1973. While the underlying geometric Brownian motion surely captured the essence of option pricing (helping spawn a multi-billion pound derivatives industry), three decades of statistical study has shown that the model departs significantly from the realities of returns (increments in the logarithm of risky asset price) data. To remedy the shortcomings of the Black-Scholes model, we present the fractal activity time geometric Brownian motion model proposed by Chris Heyde in 1999. This model supports the desired empirical features of returns including no correlation but dependence, and distributions with heavier tails and higher peaks than Gaussian. In particular, the model generalises geometric Brownian motion whereby the standard Brownian motion is evaluated at random activity time instead of calendar time. There are also strong suggestions from literature that the activity time process here is approximately self-similar. Thus we require a way to accommodate both the desired distributional and dependence features as well as the property of asymptotic self-similarity. In this thesis, we describe the construction of this fractal activity time based on chi-square type processes, through Ornstein-Uhlenbeck processes driven by Levy noise, and via diffusion-type processes. Once we validate the model by fitting real data, we endeavour to state a new explicit formula for the price of a European option. This is made possible as Heyde's model remains within the Black-Scholes framework of option pricing, which allows us to use their engendered arbitrage-free methodology. Finally, we introduce an alternative to the previously considered approach. The motivation for which comes from the understanding that activity time cannot be exactly self-similar. We provide evidence that multi-scaling occurs in financial data and outline another construction for the activity time process.
21
Dalderop, Jeroen Wilhelmus Paulus. "Essays on nonparametric estimation of asset pricing models". Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/277966.
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This thesis studies the use of nonparametric econometric methods to reconcile the empirical behaviour of financial asset prices with theoretical valuation models. The confrontation of economic theory with asset price data requires various functional form assumptions about the preferences and beliefs of investors. Nonparametric methods provide a flexible class of models that can prevent misspecification of agents’ utility functions or the distribution of asset returns. Evidence for potential nonlinearity is seen in the presence of non-Gaussian distributions and excessive volatility of stock returns, or non-monotonic stochastic discount factors in option prices. More robust model specifications are therefore likely to contribute to risk management and return predictability, and lend credibility to economists’ assertions. Each of the chapters in this thesis relaxes certain functional form assumptions that seem most important for understanding certain asset price data. Chapter 1 focuses on the state-price density in option prices, which confounds the nonlinearity in both the preferences and the beliefs of investors. To understand both sources of nonlinearity in equity prices, Chapter 2 introduces a semiparametric generalization of the standard representative agent consumption-based asset pricing model. Chapter 3 returns to option prices to understand the relative importance of changes in the distribution of returns and in the shape of the pricing kernel. More specifically, Chapter 1 studies the use of noisy high-frequency data to estimate the time-varying state-price density implicit in European option prices. A dynamic kernel estimator of the conditional pricing function and its derivatives is proposed that can be used for model-free risk measurement. Infill asymptotic theory is derived that applies when the pricing function is either smoothly varying or driven by diffusive state variables. Trading times and moneyness levels are modelled by marked point processes to capture intraday trading patterns. A simulation study investigates the performance of the estimator using an iterated plug-in bandwidth in various scenarios. Empirical results using S&P 500 E-mini European option quotes finds significant time-variation at intraday frequencies. An application towards delta- and minimum variance-hedging further illustrates the use of the estimator. Chapter 2 proposes a semiparametric asset pricing model to measure how consumption and dividend policies depend on unobserved state variables, such as economic uncertainty and risk aversion. Under a flexible specification of the stochastic discount factor, the state variables are recovered from cross-sections of asset prices and volatility proxies, and the shape of the policy functions is identified from the pricing functions. The model leads to closed-form price-dividend ratios under polynomial approximations of the unknown functions and affine state variable dynamics. In the empirical application uncertainty and risk aversion are separately identified from size-sorted stock portfolios exploiting the heterogeneous impact of uncertainty on dividend policy across small and large firms. I find an asymmetric and convex response in consumption (-) and dividend growth (+) towards uncertainty shocks, which together with moderate uncertainty aversion, can generate large leverage effects and divergence between macroeconomic and stock market volatility. Chapter 3 studies the nonparametric identification and estimation of projected pricing kernels implicit in the pricing of options, the underlying asset, and a riskfree bond. The sieve minimum-distance estimator based on conditional moment restrictions avoids the need to compute ratios of estimated risk-neutral and physical densities, and leads to stable estimates even in regions with low probability mass. The conditional empirical likelihood (CEL) variant of the estimator is used to extract implied densities that satisfy the pricing restrictions while incorporating the forwardlooking information from option prices. Moreover, I introduce density combinations in the CEL framework to measure the relative importance of changes in the physical return distribution and in the pricing kernel. The nonlinear dynamic pricing kernels can be used to understand return predictability, and provide model-free quantities that can be compared against those implied by structural asset pricing models.
22
Zhou, Xinfeng. "Application of robust statistics to asset allocation models". Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36231.
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Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006.Includes bibliographical references (p. 105-107).
Many strategies for asset allocation involve the computation of expected returns and the covariance or correlation matrix of financial instruments returns. How much of each instrument to own is determined by an attempt to minimize risk (the variance of linear combinations of investments in these financial assets) subject to various constraints such as a given level of return, concentration limits, etc. The expected returns and the covariance matrix contain many parameters to estimate and two main problems arise. First, the data will very likely have outliers that will seriously affect the covariance matrix. Second, with so many parameters to estimate, a large number of observations are required and the nature of markets may change substantially over such a long period. In this thesis we use robust covariance procedures, such as FAST-MCD, quadrant-correlation-based covariance and 2D-Huber-based covariance, to address the first problem and regularization (Bayesian) methods that fully utilize the market weights of all assets for the second. High breakdown affine equivariant robust methods are effective, but tend to be costly when cross-validation is required to determine regularization parameters.
(cont.) We, therefore, also consider non-affine invariant robust covariance estimation. When back-tested on market data, these methods appear to be effective in improving portfolio performance. In conclusion, robust asset allocation methods have great potential to improve risk-adjusted portfolio returns and therefore deserve further exploration in investment management research.
by Xinfeng Zhou.
S.M.
23
Endekovski, Jessica. "Pricing multi-asset options in exponential levy models". Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/31437.
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This dissertation looks at implementing exponential Levy models whereby the un- ´ derlyings are driven by Levy processes, which are able to account for stylised facts ´ that traditional models do not, in order to price basket options more efficiently. In particular, two exponential Levy models are implemented and tested: the multi- ´ variate Variance Gamma (VG) model and the multivariate normal inverse Gaussian (NIG) model. Both models are calibrated to real market data and then used to price basket options, where the underlyings are the constituents of the KBW Bank Index. Two pricing methods are also compared: a closed-form (analytical) approximation of the price, derived by Linders and Stassen (2016) and the standard Monte Carlo method. The convergence of the analytical approximation to Monte Carlo prices was found to improve as the time to maturity of the option increased. In comparison to real market data, the multivariate NIG model was able to fit the data more accurately for shorter maturities and the multivariate VG model for longer maturities. However, when looking at Monte Carlo prices, the multivariate VG model was found to outperform the results of the multivariate NIG model, as it was able to converge to Monte Carlo prices to a greater degree.
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Simin, Timothy T. "The poor predictive performance of asset pricing models /". Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/8823.
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Liu, Liu. "Essays in asset pricing". Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/essays-in-asset-pricing(c5e4c9b3-04b2-4e6e-97bc-e445b1ee6b4d).html.
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This thesis improves our understanding of asset prices and returns as it documents a regime shift risk premium in currencies, corrects the estimation bias in the term premium of bond yields, and shows the impact of ambiguity aversion towards parameter uncertainty on equities. The thesis consists of three essays. The first essay "The Yen Risk Premiums: A Story of Regime Shifts in Bond Markets" documents a new monetary mechanism, namely the shift of monetary policies, to account for the forward premium puzzle in the USD-JPY currency pair. The shift of monetary policy regimes is modelled by a regime switching dynamic term structure model where the risk of regime shifts is priced. Our model estimation characterises two policy regimes in the Japanese bond market---a conventional monetary policy regime and an unconventional policy regime of quantitative easing. Using foreign exchange data from 1985 to 2009, we find that the shift of monetary policies generates currency risk: the yen excess return is predicted by the Japanese regime shift premium, and the emergence of the yen carry trade in the mid 1990s is associated with the transition from the conventional to the unconventional monetary policy in Japan. The second essay "Correcting Estimation Bias in Regime Switching Dynamic Term Structure Models" examines the small sample bias in the estimation of a regime switching dynamic term structure model. Using US data from 1971 to 2009, we document two regimes driven by the conditional volatility of bond yields and risk factors. In both regimes, the process of bond yields is highly persistent, which is the source of estimation bias when the sample size is small. After bias correction, the inference about expectations of future policy rates and long-maturity term premia changes dramatically in two high-volatility episodes: the 1979--1982 monetary experiment and the recent financial crisis. Empirical findings are supported by Monte Carlo simulation, which shows that correcting small sample bias leads to more accurate inference about expectations of future policy rates and term premia compared to before bias correction. The third essay "Learning about the Persistence of Recessions under Ambiguity Aversion" incorporates ambiguity aversion into the process of parameter learning and assess the asset pricing implications of the model. Ambiguity is characterised by the unknown parameter that governs the persistence of recessions, and the representative investor learns about this parameter while being ambiguity averse towards parameter uncertainty. We examine model-implied conditional moments and simulated moments of asset prices and returns, and document an uncertainty effect that characterises the difference between learning under ambiguity aversion and learning under standard recursive utility. This uncertainty effect is asymmetric across economic expansions and recessions, and this asymmetry generates in simulation a sharp increase in the equity premium at the onset of recessions, as in the recent financial crisis.
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Ajrapetova, Tamara. "Asset Pricing in Emerging Markets". Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-359270.
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General content: Current methods of estimation of cost of capital in the emerging markets are often neglecting various contradictions with the essentials of the model structure and assumptions. As the result of such imprecisions, the cost of equity is often understated (overstated). This thesis will attempt to assess current level of emerging market integration, liquidity and concentration. This will be followed by evaluation of traditional and alternative models for estimation of cost of equity. The author will address several currently available models such as Credit Rating Model, D-CAPM model, various versions of traditional CAPM models. Furthermore, she will compare and contrast their limitations taking into account the context of emerging markets. The testing of the models will be performed on country basis through the means of index data. In the last chapter, discussion of the results and possible improvements of the valuation approaches will take place.
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Hatgioannides, John. "Essays on asset pricing in continuous time". Thesis, Birkbeck (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244543.
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Sagi, Jacob S. "Partial ordering of risky choices : anchoring, preference for flexibility and applications to asset pricing". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0019/NQ56611.pdf.
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Chaieb, Ines. "Essays on international asset pricing under segmentation and PPP deviations". Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102485.
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This dissertation comprises two essays. The first essay develops and tests a theoretical model that provides new insights when markets are partially segmented and the purchasing power parity (PPP) is violated which seems to be the case for the majority of national markets. The theoretical part derives closed form solutions for asset prices and portfolio holdings. Particularly, we show that deviations from PPP in mildly segmented markets induce a new form of systematic risk, termed segflation risk, and in equilibrium investors require compensation for this risk. A strong feature of the model is that it provides a theoretical framework for testing important issues; such as, pricing of foreign exchange risk and world market structure. The model also nests several existing international asset pricing models and thus provides a framework to distinguish empirically between competing models. The empirical part of the essay provides an empirical validation of the model for eight major emerging markets. The results give support to the model and point to the importance of the segflation risk which is statistically and economically significant.The second essay uses our theoretical model to address the question of whether the IFC investable indices are priced globally or locally. Indeed S&P/IFC provides two emerging market indices: the IFC global index (IFCG) and its subset the IFC investable index (IFCI). Since the IFCI is fully investable, both the academic and practitioners implicitly assume that this subset of emerging markets is priced in the global context. This is a critical assumption for corporate finance decisions and portfolio management. Hence, this essay investigates the pricing behavior of the IFCI index returns using a conditional version of our model that allows for segmentation and PPP deviations. The results suggest that local factors are important in explaining returns of the IFC investable indices and that the return behavior of IFCI indices is similar to that of the IFCG.
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Caliskan, Nilufer. "Asset Pricing Models: Stochastic Volatility And Information-based Approaches". Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608213/index.pdf.
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We present two option pricing models, both different from the classical Black-Scholes-Merton model. The first model, suggested by Heston, considers the case where the asset price volatility is stochastic. For this model we study the asset
price process and give in detail the derivation of the European call option price process. The second model, suggested by Brody-Hughston-Macrina, describes the observation of certain information about the claim perturbed by a noise represented by a Brownian bridge. Here we also study in detail the properties of this noisy information process and give the derivations of both asset price dynamics and the European call option price process.
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Bäurer, Patrick [Verfasser], i Ernst [Akademischer Betreuer] Eberlein. "Credit and liquidity risk in Lévy asset price models". Freiburg : Universität, 2015. http://d-nb.info/1115861794/34.
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Oagile, Joel. "Sequential Calibration of Asset Pricing Models to Option Prices". Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29840.
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This paper implements four calibration methods on stochastic volatility models. We estimate the latent state and parameters of the models using three non-linear filtering methods, namely the extended Kalman filter (EKF), iterated extended Kalman filter (IEKF) and the unscented Kalman filter (UKF). A simulation study is performed and the non-linear filtering methods are compared to the standard least square method (LSQ). The results show that both methods are capable of tracking the hidden state and time varying parameters with varying success. The non-linear filtering methods are faster and generally perform better on validation. To test the stability of the parameters, we carry out a delta hedging study. This exercise is not only of interest to academics, but also to traders who have to hedge their positions. Our results do not show any significant benefits resulting from performing delta hedging using parameter estimates obtained from non-linear filtering methods as compared to least square parameter estimates.
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Wang, Shuo. "Optimization Models for Network-Level Transportation Asset Preservation Strategies". University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1416578565.
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Bach, Christian. "Asset Pricing and Habit Models for Calculating Bond Prices /". Aarhus : Institut for Økonomi, Aarhus Universitet, 2008. http://mit.econ.au.dk/Library/Specialer/2008/20033894.pdf.
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Chu, Kai-cheung, i 朱啟祥. "The effects of mean reversion on dynamic corporate finance and asset pricing". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47752762.
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This thesis aims to investigate the effects of mean reversion on dynamic corporate finance decisions and stock pricing.
In Chapter 1, a continuous-time real option model of mature firm that produces product with exogenous mean reverting price is developed to study the firm’s optimal exit and leverage policies. Simulation results show that both liquidation and bankruptcy triggers are negatively related to the long run price levels, while the speed of mean reversion interacts with the long run price level to affect the firm’s exit decisions in two opposite directions depending on the level’s relative magnitude to total operating expenses (the firm’s instantaneous operation costs plus coupon payments). Regarding the leverage policy, apart from showing the static tradeoff result that firm uses more debts when the current revenues are high, the model exhibits at high long run price levels low-debt scenarios that are analogous to the pecking order prediction, suggesting that both static tradeoff and pecking order effects coexist under a mean reversion environment. Because equity values increase more vigorously with prices than debt values do, the tradeoff effect is overwhelmed and the resulting optimal leverage ratios are generally decreasing with the current price levels.
Chapter 2 extends the model in Chapter 1 to derive the closed-form expression of the firm’s equity beta. Because expected stock returns are linearly related to the equity beta by model assumption, several implications to the cross-sectional behaviors of stock returns are obtained. First, it is predicted that firms with mean reverting characteristics should earn lower average returns than others without. The model further reveals the coexistence of positive book-to-market and leverage premiums to stock returns. Most importantly, due to the possession of bankruptcy option by equity holders, high distress risk stocks are expected to earn lower average returns than otherwise similar but low distress risk stocks. This provides an extra dimension to study the ‘distress premium puzzle’. Finally to verify the model predictions, empirical tests using historical market and accounting data from CRSP and COMPUSTAT are conducted, and supportive results are generally obtained.published_or_final_version
Economics and Finance
Doctoral
Doctor of Philosophy
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Kam, Wai-hung Simon, i 甘偉雄. "Capital asset pricing model: is it relevant in Hong Kong". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31265686.
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Zaffaroni, Paolo. "Nonlinear long memory models with applications in finance". Thesis, London School of Economics and Political Science (University of London), 1997. http://etheses.lse.ac.uk/1468/.
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The last decade has witnessed a great deal of research in modelling volatility of financial asset returns, expressed by time-varying variances and covariances. The importance of modelling volatility lies in the dependence of any financial investment decision on the expected risk and return as formalized in classical asset pricing theory. Precise evaluation of volatilities is a compulsory step in order to perform correct options pricing according to recent theories of the term structure of interest rates and for the construction of dynamic hedge portfolios. Models of time varying volatility represent an important ground for the development of new estimation and forecasting techniques for situations not reconcilable with the Gaussian or, more generally, a linear time series framework. This is particularly true for the statistical analysis of time series with long range dependence in a nonlinear framework. The aim of this thesis is to introduce parametric nonlinear time series models with long memory, with particular emphasis on volatility models, and to provide a methodology which yields asymptotically exact inference on the parameters of the models. The importance of these results stems from: (i) rigorous asymptotics was lacking from the stochastic volatility literature; (ii) the statistical literature does not cover the analysis of the asymptotic behaviour of quadratic forms in nonlinear non-Gaussian variates that characterizes our problem.
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Hambouri, Zaphiro. "Risk and asset/liability management of fixed income portfolios". Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312022.
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Karam, Philippe Doumit. "Dynamic asset pricing models with incomplete markets and market frictions". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq22471.pdf.
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Sherif, Mohamed A. "Modelling consumption asset pricing models : empirical evidence from the UK". Thesis, University of Manchester, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.633243.
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This thesis adopts a range of different methodologies in an attempt to evaluate the performance of consumption-based asset pricing models. In particular, it sets out to investigate the relationship between asset prices, consumption and investment decisions. Different utility functions are used in an attempt to examine their roles in pricing assets, reducing pricing errors and solving the equity premium puzzle. First considered is whether the value of relative risk aversion can be changed by using parametric tests and different utility functions. Whereas the power utility model introduces a basic learning framework of the relation between consumption and asset returns, there is general consensus that there is evidence against the model as an asset pricing tool and for its ability to resolve the equity premium puzzle. Within the context of representation of agent models, various studies have attempted to introduce more general preferences. In this study, tests are made of the traditional CCAPM, the Epstein and Zin (1989, 1991) model, and two external habit formation specifications using GMM on a quarterly data set spanning 35 years. In a novel approach the models are estimated for both the whole economy and four separate industrial sector groupings. The structural stability tests advocated by Hall and Sen (1999) are used to test the models further. There is little evidence found to support the traditional CCAPM and the recursive preferences model of Epstein and Zin (1989, 1991). There is highly supportive evidence for the performance of the habit formation models, particularly the Campbell-Cochrane specification. Importantly, the analysis of the four sector groupings shows that estimated levels of risk aversion are similar across these groupings, conforming with theory. In line with previous studies, the models show signs of sensitivity to choices of asset return data, consumption measures, and particularly, instrumental variables. Second, a non-parametric framework is used in an attempt to investigate the performance of the models. In particular, investigation of the pricing errors of consumption asset pricing models by estimating the vertical and minimum distances to the Hansen-Jagannathan bound. Additionally, bootstrap experiments are conducted in a further attempt to examine the performance of the models. The power utility model produces high pricing errors associated with higher values of relative risk aversion. The Epstein-Zin (1991) recursive preferences model and the Abel (1990) formulation manage to reduce the pricing errors. However, these pricing errors are associated with higher values of relative risk aversion. In the bootstrap experiments, in the majority of simulations, the models violate the Hansen and Jagannathan bound, and the distance is an order of magnitude larger than the IMRS volatility. However, the lower risk aversion coefficient associated with the lower distance is obtained from the Campbell-Cochrane model. Third, investigation of the performance of the consumption-based asset pricing models in pricing bonds. Additionally, an investigation of whether the term structure in the UK can reflect information about consumption growth. In this study, the methodology adopted by Harvey (1988) is used to test the relation between term structure and the consumption asset pricing models. Also used are the structure stability tests of Hall and Sen (1999). The models perform better with longer horizons. The results suggest that the estimates of the coefficient of relative risk aversion/curvature parameter are negative and insignificant, very often with the models that no longer consider the habit formation specification. The empirical evidence based on the regression are broadly supportive of efficiency in using lagged consumption and yield spread as predictors of consumption growth, rather than other lagged stock returns. The final study investigates the recent explorations of asset pricing in the UK, using the OLS and GMM methodology to revisit the conditional Sharp-Linter CAPM model with fixed and time varying parameters. Additionally, an examination is made to the performance of the consumption-based asset pricing models and the conditional asset pricing model with the Famma-F'rench factors, 8MB and HML. Following Harvey (1988), a specification is estimated that allows for the time variation in conditional covariance, conditionally expected returns, and the conditional variance of the market and it is found that the restriction can not be rejected. However, there is evidence that the conditional Sharpe-Linter model with fixed parameter is unable to capture the dynamic behaviour of asset returns. Additionally, the estimation of the conditional CAPM that allows for time variation performs better with the inclusion of BMS and HML. As for the consumption-based asset pricing models, the Campbell-Cochrane specification still best characterises the UK market.
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Bart-Williams, Claudius Pythias. "On asset pricing and the equity premium puzzle". Thesis, Brunel University, 2000. http://bura.brunel.ac.uk/handle/2438/6371.
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Presented here are consumption and production related asset pricing models which seek to explain stock market behaviour through the stock premium over risk-free bonds and to do so using parameter values consistent with theory. Our results show that there are models capable of explaining stock market behaviour. For the consumption-based model, we avoid many of the suggestions to artificially boost the predicted stock premium such as modelling consumption as leverage claims; instead we use the notion of surplus consumption. We find that with surplus consumption, there are models including the much-maligned power utility model, capable of yielding theory consistent estimates for the discount rate, risk-free rate as well as the coefficient of relative risk aversion, y. Since real business cycle theory assumes a risk aversion coefficient of 1, we conclude that our model which gives a value close to but not equal to 1, provides an indication of the impact of market imperfections. For production, we present many of the existing models which seek to explain stock market behaviour using production data which we find to be generally incapable of explaining stock market behaviour. We conclude by presenting a profit based formulation which uses deviations of actual from expected profits and dividends via stock price reaction parameters to successfully explain stock market behaviour. We also conclude that the use of a profit based formulation allows for a link to investment, output and pricing decisions and hence link consumption and production.
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Kim, Joocheol. "Stochastic programming approach to asset liability management under uncertainty". Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/25324.
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Carter, Bradley. "Capital asset pricing model (CAPM) applicability in the South African context and alternative pricing models". Diss., University of Pretoria, 2015. http://hdl.handle.net/2263/52363.
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The ability to accurately price equity is an ineluctable requirement within businesses where decisions need to be taken daily that impact upon the future viability of that business.
The Capital asset pricing model (CAPM) is the preeminent tool that has become entrenched within academia and business for exactly the purpose of costing equity capital.
This study aimed to prove whether the application of the CAPM, in various forms, including the Black s CAPM, was merely a myopic inculcation of the academic and business spheres, or whether it truly reflected the empirical reality of the South African markets.
The research discredited eight variations of the CAPM through a quantitative causal design, which employed t-tests and ANOVAs, tested upon a judgmental sample of the largest 160 shares on the JSE. Reaching this opprobrium would have been a Pyrrhic victory, had an alternative model not been proposed.
Thus, a quartet of styles was employed in tests against both non-resource and resource shares in an attempt to generate two multi-factor models known as the Optimised Returns Score (ORS) combined models. The generated model for the non-resource shares explained 36.5% of the variation in the observed cost of equity capital, at a 95% level of significance. However, a statistically significant predictive model for resource shares was unable to be found, possibly due to the small sample size available.Mini Dissertation (MBA)--University of Pretoria, 2015.
sn2016
Gordon Institute of Business Science (GIBS)
MBA
Unrestricted
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Manopchantarote, Chatsupa. "The performance of adaptive simulated annealing in building asset pricing models /". Available to subscribers only, 2005. http://proquest.umi.com/pqdweb?did=1095439881&sid=11&Fmt=2&clientId=1509&RQT=309&VName=PQD.
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Thesis (M.S.)--Southern Illinois University Carbondale, 2005. Regression analysis is a method for determining the association between a dependent variable and one or more independent variables. It plays an important role in various research and practical application. Up until now, there is no single best technique to find solution because the problem turns out to be intractable when the number of independent variables become large. Presently, there are many techniques to solve this problem both greedy algorithms and exhaustive searches. Therefore, the quality of solution depends on computation time and resources. This thesis focuses on using Adaptive Simulated Annealing (ASA) to search best subset combination. The ASA algorithm has annealing schedule that is faster than previous annealing. To measure the quality of solution, we use low C p statistics and C p less than the number of selected independent variables as the criterion. This study was shown that ASA was always able to discover the subset solution that yielded low C p statistics."Department of Computer Science." Includes bibliographical references (leaves 52-54). Also available online.
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Roman, Diana. "Models for choice under risk with applications to optimum asset allocation". Thesis, Brunel University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427730.
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Hussain, Syed Iqbal. "Financial distress, asset pricing models and market anomalies : the UK evidence". Thesis, University of Nottingham, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.251738.
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Moyo, Nigel A. P. "Evaluation of Asset Pricing Models in the South African Equities Market". Master's thesis, Faculty of Commerce, 2021. http://hdl.handle.net/11427/32887.
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Asset pricing models have been of interest since their origin in modern finance. The Capital Asset Pricing Model is a widely used tool and is one of the early developed asset pricing models in modern finance. There are continual improvements of this model with the evident multifactor models of Fama and French (2015), Carhart (1997) and the South African two – factor arbitrage pricing models of Van Rensburg (2002) and Laird-Smith et al. (2016). This research empirically investigates the performance of eight-different multi-factor asset pricing models in describing average portfolio returns in the South African Johannesburg Stock Exchange. We find that the Carhart (1997) four factor model comprising of the market factor, size factor, value factor and the momentum factor is the most parsimonious model and thus better explains the average portfolio returns in the South African JSE. This model is an improvement of the Fama and French (1992) three factor model. Additionally, we investigate the performance of the two factor Asset Pricing Theory (APT) model of Laird-Smith et al. (2016) and Van Rensburg (2002) that consists of the South African Financial Index (SAFI) and the South African Resources Index (SARI). We observe that the model performs better than the traditional CAPM that is widely used in industry. Adding the SAFI and the SARI to the six-factor model results in an eight-factor model that has a significant improvement in explaining average returns. The results indicate that the market factor, the South African Financial Index and the South African Resources Index (SARI) poorly explain each other but their linear combination improves the eight-factor asset pricing model in explaining average portfolio returns in the South African market. The eight – factor model comprises of the market, size, value, investment, profitability, momentum factors and the two South African indices namely, the South African Financials Index (SAFI) and the South African Resources Index (SARI).
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Semenov, Andrei. "Intertemporal utility models for asset pricing : reference levels and individual heterogeneity". Thèse, [Montréal] : Université de Montréal, 2003. http://wwwlib.umi.com/cr/umontreal/fullcit?pNQ92724.
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Thèse (Ph.D.) -- Université de Montréal, 2004."Thèse présentée à la Faculté des études supérieures en vue de l'obtention du grade de Philosophiae Doctor (Ph.D.) en sciences économiques" Version électronique également disponible sur Internet.
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Cunningham, James K. (James Kenneth). "A Canadian study of admissible monetary asset groupings using nonparametric demand analysis". Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=22577.
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Structural change and innovation in the market for financial services in recent years have drawn attention to the fact that traditional definitions of money as included in demand for money models and monetary aggregation measures may be misspecified. It is unclear whether or to what extent broader measures of money should be used as targets in monetary policy or as indicators of changes in the real economy. This thesis is a nonparametric empirical test of monetary asset, leisure and consumption good data which seeks to examine whether the underlying structure of preferences implied by monetary aggregation can be said to be justified. Using recent software routines, we test Canadian data for the years 1968-I to 1989-IV in order to determine whether it meets the criteria for utility maximization and for a structure of preferences represented by weak separability. We find that only a narrow grouping of monetary assets meets these requirements. Further, we conclude that many other studies in the literature which have merely assumed weak separability have been misspecified.
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Jordan-Wagner, James M. (James Michael). "Arbitrage Pricing Theory and the Capital Asset Pricing Model: Evidence from the Eurodollar Bond Market". Thesis, University of North Texas, 1988. https://digital.library.unt.edu/ark:/67531/metadc330578/.
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Monthly returns on twenty-seven Eurobonds from July 1982 to June 1986 were examined. There were no consistent differences in returns based on the country in which a firm is located. There were consistent differences due to industry classification, with energy-related firms exhibiting higher average returns and variances.
Excess returns were calculated using the capital asset pricing model and arbitrage pricing theory. The results from calculation of mean average deviation, root mean square, and R2 all indicate that the arbitrage pricing theory was a better descriptor of the Eurobond market.
The excess returns were also examined using stochastic dominance. Arbitrage pricing theory never dominated the capital asset pricing model using first-order criteria, but consistently dominated using second-order criteria. The results were discussed in terms of the implications for investors and portfolio managers.