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Academic literature on the topic 'Arbitrage Econometric models'

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Published: 10 December 2022
Last updated: 10 March 2023

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Journal articles on the topic "Arbitrage Econometric models"

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Lieu, Derming. "Estimation of empirical pricing equations for foreign-currency options: Econometric models vs. arbitrage-free models." International Review of Economics & Finance 6, no. 3 (January 1997): 259–86. http://dx.doi.org/10.1016/s1059-0560(97)90038-1.

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Sheng, Yankai, and Ding Ma. "Stock Index Spot–Futures Arbitrage Prediction Using Machine Learning Models." Entropy 24, no. 10 (October 13, 2022): 1462. http://dx.doi.org/10.3390/e24101462.

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With the development of quantitative finance, machine learning methods used in the financial fields have been given significant attention among researchers, investors, and traders. However, in the field of stock index spot–futures arbitrage, relevant work is still rare. Furthermore, existing work is mostly retrospective, rather than anticipatory of arbitrage opportunities. To close the gap, this study uses machine learning approaches based on historical high-frequency data to forecast spot–futures arbitrage opportunities for the China Security Index (CSI) 300. Firstly, the possibility of spot–futures arbitrage opportunities is identified through econometric models. Then, Exchange-Traded-Fund (ETF)-based portfolios are built to fit the movements of CSI 300 with the least tracking errors. A strategy consisting of non-arbitrage intervals and unwinding timing indicators is derived and proven profitable in a back-test. In forecasting, four machine learning methods are adopted to predict the indicator we acquired, namely Least Absolute Shrinkage and Selection Operator (LASSO), Extreme Gradient Boosting (XGBoost), Back Propagation Neural Network (BPNN), and Long Short-Term Memory neural network (LSTM). The performance of each algorithm is compared from two perspectives. One is an error perspective based on the Root-Mean-Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and goodness of fit (R2). Another is a return perspective based on the trade yield and the number of arbitrage opportunities captured. Finally, a performance heterogeneity analysis is conducted based on the separation of bull and bear markets. The results show that LSTM outperforms all other algorithms over the entire time period, with an RMSE of 0.00813, MAPE of 0.70 percent, R2 of 92.09 percent, and an arbitrage return of 58.18 percent. Meanwhile, in certain market conditions, namely both the bull market and bear market separately with a shorter period, LASSO can outperform.
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DE ALMEIDA, CAIO IBSEN RODRIGUES. "AFFINE PROCESSES, ARBITRAGE-FREE TERM STRUCTURES OF LEGENDRE POLYNOMIALS, AND OPTION PRICING." International Journal of Theoretical and Applied Finance 08, no. 02 (March 2005): 161–84. http://dx.doi.org/10.1142/s0219024905002949.

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Multivariate Affine term structure models have been increasingly used for pricing derivatives in fixed income markets. In these models, uncertainty of the term structure is driven by a state vector, while the short rate is an affine function of this vector. The model is characterized by a specific form for the stochastic differential equation (SDE) for the evolution of the state vector. This SDE presents restrictions on its drift term which rule out arbitrages in the market. In this paper we solve the following inverse problem: Suppose the term structure of interest rates is modelled by a linear combination of Legendre polynomials with random coefficients. Is there any SDE for these coefficients which rules out arbitrages? This problem is of particular empirical interest because the Legendre model is an example of factor model with clear interpretation for each factor, in which regards movements of the term structure. Moreover, the Affine structure of the Legendre model implies knowledge of its conditional characteristic function. From the econometric perspective, we propose arbitrage-free Legendre models to describe the evolution of the term structure. From the pricing perspective, we follow Duffie et al. [22] in exploring their conditional characteristic functions to obtain a computational tractable method to price fixed income derivatives.
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Pandher, Gurupdesh S. "ESTIMATION OF EXCESS RETURNS FROM DERIVATIVE PRICES AND TESTING FOR RISK NEUTRAL PRICING." Econometric Theory 17, no. 4 (July 27, 2001): 785–819. http://dx.doi.org/10.1017/s0266466601174062.

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This paper develops an econometric framework for (i) estimating excess returns of the security process from high frequency derivative prices, (ii) testing for risk neutral pricing, and (iii) measuring premiums outside the no-arbitrage pricing model. The estimator is constructed by applying quasi-likelihood and Feynman–Kac theory to the risk neutral contingent claims pricing model to generate the optimal orthogonality restriction. The strong consistency and asymptotic normality of the estimator are established in the context of a nonstationary underlying state process. These results further imply that the estimator is robust to distributional assumptions on the underlying asset process. The proposed approach is applicable to any arbitrary derivative security, does not require estimation of the risk neutral probability measure, and has application to spot rate bond pricing models. A controlled diagnostic study based on generating the S&P500 index and calls verifies the ability of the estimators to correctly estimate security excess returns and test for risk neutral pricing. The estimator is invariant to call strikes, and larger samples constructed by cycling over shorter maturity options can be used to reduce its variance.
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Barboza Martignone, Gustavo, Karl Behrendt, and Dimitrios Paparas. "Price Transmission Analysis of the International Soybean Market in a Trade War Context." Economies 10, no. 8 (August 19, 2022): 203. http://dx.doi.org/10.3390/economies10080203.

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This study analysed the dynamics of the international soybean market using econometric techniques and economic models to study the impacts of the US–China trade war. It considered the analysis of “spatial” (horizontal) price transmission during an approximately ten-year period from September 2009 to May 2019 using monthly time-series data. The research focused on the leaders in the international soybean market, namely, China, the USA, the EU, Brazil and Argentina. Several econometric techniques were employed. The stationarity of the price time series was determined using the augmented Dickey–Fuller (ADF) unit root test. Structural breaks were inferred using the ADF test with a breaks test and a Bai–Perron multiple break test. The long-term relation/cointegration amongst the series was determined using the Johansen cointegration test (1988), with the previous breaks input as dummy variables. The direction of the causality was inferred using the Granger causality test (1969). The long-term and short-term causal relations were determined using the vector autoregression model (VAR) and the vector error correction model (VECM). The results showed a highly efficient and cointegrated market. The incidents of the trade war, as represented by tariffs and subsidies, had minor effects on the market efficacy, cointegration and price transmission. The arbitrage process of the studied market managed to get around the tariffs. In other words, there was no empirical evidence to support the claim that the law of one price (LOOP) did not hold.
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Peel, David A., and Ioannis A. Venetis. "Smooth Transition Models and Arbitrage Consistency." Economica 72, no. 287 (August 2005): 413–30. http://dx.doi.org/10.1111/j.0013-0427.2005.00423.x.

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Neal, Robert. "Direct Tests of Index Arbitrage Models." Journal of Financial and Quantitative Analysis 31, no. 4 (December 1996): 541. http://dx.doi.org/10.2307/2331359.

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Tarelli, Andrea. "No-arbitrage one-factor term structure models in zero- or negative-lower-bound environments." Investment Management and Financial Innovations 17, no. 1 (March 25, 2020): 197–212. http://dx.doi.org/10.21511/imfi.17(1).2020.18.

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One-factor no-arbitrage term structure models where the instantaneous interest rate follows either the process proposed by Vasicek (1977) or by Cox, Ingersoll, and Ross (1985), commonly known as CIR, are parsimonious and analytically tractable. Models based on the original CIR process have the important characteristic of allowing for a time-varying conditional interest rate volatility but are undefined in negative interest rate environments. A Shifted-CIR no-arbitrage term structure model, where the instantaneous interest rate is given by the sum of a constant lower bound and a non-negative CIR-like process, allows for negative yields and benefits from similar tractability of the original CIR model. Based on the U.S. and German yield curve data, the Vasicek and Shifted-CIR specifications, both considering constant and time-varying risk premia, are compared in terms of information criteria and forecasting ability. Information criteria prefer the Shifted-CIR specification to models based on the Vasicek process. It also provides similar or better in-sample and out-of-sample forecasting ability of future yield curve movements. Introducing a time variation of the interest rate risk premium in no-arbitrage one-factor term structure models is instead not recommended, as it provides worse information criteria and forecasting performance.
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Backus, David, Silverio Foresi, and Stanley Zin. "Arbitrage Opportunities in Arbitrage-Free Models of Bond Pricing." Journal of Business & Economic Statistics 16, no. 1 (January 1998): 13. http://dx.doi.org/10.2307/1392012.

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Cornet, Bernard, and Lionel De Boisdeffre. "Elimination of arbitrage states in asymmetric information models." Economic Theory 38, no. 2 (March 13, 2007): 287–93. http://dx.doi.org/10.1007/s00199-007-0205-z.

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Dissertations / Theses on the topic "Arbitrage Econometric models"

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Ladrón, de Guevara Cortés Rogelio. "Techniques For Estimating the Generative Multifactor Model of Returns in a Statistical Approach to the Arbitrage Pricing Theory. Evidence from the Mexican Stock Exchange." Doctoral thesis, Universitat de Barcelona, 2016. http://hdl.handle.net/10803/386545.

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This dissertation focuses on the estimation of the generative multifactor model of returns on equities, under a statistical approach of the Arbitrage Pricing Theory (APT), in the context of the Mexican Stock Exchange. Therefore, this research takes as frameworks two main issues: (i) the multifactor asset pricing models, specially the statistical risk factors approach, and (ii) the dimension reduction or feature extraction techniques: Principal Component Analysis, Factor Analysis, Independent Component Analysis and Non-linear Principal Component Analysis, utilized to extract the underlying systematic risk factors. The models estimated are tested using two methodologies: (i) capability of reproduction of the observed returns using the estimated generative multifactor model, and (ii) results of the econometric contrast of the APT using the extracted systematic risk factors. Finally, a comparative study among techniques is carried on based on their theoretical properties and the empirical results. According to the above stated and as far as we concerned, this dissertation contributes to financial research by providing empirical evidence of the estimation of the generative multifactor model of returns on equities, extracting statistical underlying risk factors via classic and alternative dimension reduction or feature extraction techniques in the field of finance, in order to test the APT as an asset pricing model, in the context of an emerging financial market such as the Mexican Stock Exchange. In addition, this work presents an unprecedented theoretical and empirical comparative study among Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, as techniques to extract systematic risk factors from a stock exchange, analyzing the level of sensitivity of the results in function of the technique carried on. In addition, this dissertation represents a mainly empirical exhaustive study where objective evidence about the Mexican stock market is provided by way of the application of four different techniques for extraction of systematic risk factors, to four datasets, in a test window that ranged from two to nine factors.
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Fodor, Bryan D. "The effect of macroeconomic variables on the pricing of common stock under trending market conditions." Thesis, Department of Business Administration, University of New Brunswick, 2003. http://hdl.handle.net/1882/49.

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Thesis (MBA) -- University of New Brunswick, Faculty of Administration, 2003.
Typescript. Bibliography: leaves 83-84. Also available online through University of New Brunswick, UNB Electronic Theses & Dissertations.
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Bernat, Liana Oliveira. "Arbitrage pricing theory in international markets." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/12/12138/tde-01122011-203538/.

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This dissertation studies the impact of multiple pre-specified sources of risk in the return of three non-overlapping groups of countries, through an Arbitrage Pricing Theory (APT) model. The groups are composed of emerging and developed markets. Emerging markets have become important players in the world economy, especially as capital receptors, but they were not included in the majority of previous related works. Two strategies are used to choose two set of risk factors. The first one is to use macroeconomic variables, as prescribed by most of the literature, such as world excess return, exchange rates, variation in the spread between Eurodollar deposit tax and U.S. Treasury bill (TED spread) and change in the oil price. The second strategy is to extract factors by using a principal component analysis, designated as statistical factors. The first important result is a great resemblance between the first statistical factor and the world excess return. We estimate the APT model using two statistical methodologies: Iterated Nonlinear Seemingly Unrelated Regression (ITNLSUR) by McElroy and Burmeister (1988) and the Generalized Method Moments (GMM) by Hansen (1982). The results from both methods are very similar. With macroeconomic variables, only the world excess of return is priced in the three groups with a premium varying from 4.4% to 6.3% per year and, in the model with statistical variables, only the first statistical factor is priced in all groups with a premium varying from 6.2% to 8.5% per year.
Essa dissertação estuda o impacto de múltiplas fontes de riscos pré-especificados nos retornos de três grupos de países não sobrepostos, através de um modelo de Teoria de Precificação por Arbitragem (APT). Os grupos são compostos por mercados emergentes e desenvolvidos. Mercados emergentes tornaram-se importantes na economia mundial, especialmente como receptores de capital, mas não foram inclusos na maioria dos trabalhos correlatos anteriores. Duas estratégias foram adotadas para a escolha de dois conjuntos de fatores de risco. A primeira foi utilizar variáveis macroeconômicas, descritas na maior parte da literatura, como e excesso de retorno da carteira mundial, taxas de câmbio, variação da diferença entre a taxa de depósito em Eurodólar e a U.S. Treasury Bill (TED Spread) e mudanças no preço do petróleo. A segunda estratégia foi extrair fatores de risco através de uma análise de componentes principais, denominados fatores estatísticos. O primeiro resultado importante é a grande semelhança entre o primeiro fator estatístico e o retorno da carteira mundial. Nós estimamos o modelo APT usando duas metodologias estatísticas: Regressões Aparentemente não Correlacionadas Iteradas (ITNLSUR) de McElroy e Burmeister (1988) e o Método dos Momentos Generalizados (GMM) de Hansen (1982). Os resultados de ambas as metodologias são muito similares. Utilizando variáveis macroeconômicas, apenas o excesso de retorno da carteira mundial é precificado nos três grupos com prêmios variando de 4,4% a 6.3% ao ano e, no modelo com variáveis estatísticas, apenas o primeiro fator estatístico é precificado em todos os grupos com prêmios que variam entre 6,2% a 8,5% ao ano.
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Bouwman, Kees Evert. "Essays on financial econometrics : modeling the term structure of interest rates /." Enschede : PPI, 2008. http://www.gbv.de/dms/zbw/561223343.pdf.

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Becam, Adrien. "Mesure de performance et liquidité dans l'industrie des hedge funds." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED074.

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Les hedge funds ont connu une croissance rapide de leurs actifs sous gestion. Cependant, leur mauvaise performance durant la crise financière de 2008 et ces dernières années a remis en question le caractère absolu de leurs rendements. Mes travaux de thèse visent à expliciter les sources de la performance mesurée des hedge funds.Le premier chapitre démontre un lien positif entre le degré d’auto corrélation dans les rendements des hedge funds et leur sur performance. Conformément à l’hypothèse d’un biais dans les estimateurs, les fonds les plus auto corrélés ont également les plus faibles expositions mesurées aux facteurs de risques. Le chapitre deux montre que l’auto corrélation dans les rendements des hedge funds ne provient que très partiellement de problèmes de liquidité, et donc que le lissage des rendements par les gérants de fonds est très prégnant.Enfin, le troisième chapitre met en évidence que le risque de capital sur les intermédiaires financiers est un nouveau facteur de risque expliquant fortement la coupe transversale des rendements des hedge funds. Une partie de l’alpha provient en fait d’une prime de risque pour l’exposition à ce facteur
The hedge fund industry experienced a fast growth of its assets under management. However, its poor performance during the 2008 financial crisis and the recent years questioned the absolute character of hedge fund returns.My thesis work aims to explicit the sources of the measured performance of hedge funds.The first chapter demonstrates a positive link between the magnitude of serial correlation in hedge funds returns and their outperformance. In accordance with the hypothesis of a bias in the estimates, the most serially correlated funds also have the lowest measured risk exposures.The second chapter shows that serial correlation in hedge fund returns comes only really partially from liquidity issues, and so returns smoothing by fund managers is pervasive.Finally, the third chapter highlights that the risk on the capital of financial intermediaries is a new risk factor strongly explaining the cross-section of hedge fund returns. A portion of the alpha comes in fact from a risk premia for bearing an exposure to this factor
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KIERMEIER, Michaela. "Essays on the arbitrage pricing theory and wavelet analysis." Doctoral thesis, 1998. http://hdl.handle.net/1814/4976.

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Defence date: 13 July 1998
Examining board: Prof. Anindya Banerjee, Oxford University ; Prof. Søren Johansen, EUI ; Prof. Grayham Mizon, EUI, Supervisor ; Prof. Klaus Sandmann, University of Mainz
PDF of thesis uploaded from the Library digitised archive of EUI PhD theses completed between 2013 and 2017
-- Review of the arbitrage pricing theory and its estimation techniques -- The arbitrage pricing theory and the efficiency of the German stock market -- Wavelet analysis applied to the arbitrage pricing theory
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Abunyuwah, Isaac. "Market Integration Analysis and Time-series Econometrics: Conceptual Insights from Markov-switching Models." Doctoral thesis, 2008. http://hdl.handle.net/11858/00-1735-0000-000D-F156-3.

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Huang, Chih-Yueh, and 黃致越. "The Study of a Non-linear Threshold Econometric Model to the Applications of Convertible Bond Arbitrage Opportunity and Forecasting Tanker Freight Rate." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/24847667262961458083.

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碩士
國立中正大學
財務金融研究所
99
Part 1 Title：Investigating The Relationship between The Price Changing of Convertible Bond and Common Stock: A Bivariate Autoregressive Model Application in Taiwan Market Abstract： Past literature investigate the relationship between the return of convertible bond and common stock using linear VAR/VECM model and Granger causality test and find that the common stock leads convertible bond. So that most researcher view the common stock is one of the explanatory variables of convertible bond. This study investigates the relationship of price changing of convertible bond and common stock by using threshold VAR/VECM. We expects that not only the common stock affects the convertible bond but the convertible bond affects the common stock when the arbitrage opportunity exists. That's caused by the arbitrage be behaviour of investors. This study chooses the convertible bonds which issued in public capital market in Taiwan and trading days is above 150 days because of the liquidity concern. Unfortunately, there is only one convertible bond which satisfies our requirement. The empirical result support our expectation. When the arbitrage opportunity exists, the relationship is bilateral. Once there is no arbitrage chance, the common stock leads the convertible bond as past literature pointed out. Here, this offers the researchers which are interested in forecasting the stock price a new idea that they can construct a threshold model by setting the difference of revised convertible price and common stock price as threshold variable. Part 2 Title：Forecasting tanker spot and forward freights with considering seasonality and volatile volatility persistence. Abstract： This study uses a membership only data of the Baltic Exchange to conduct tanker spot and forward freight rate forecasting models. The basic bivariate VECM model is employed to extend as a series of nonlinear VECM models with considering the seasonality effect and volatility persistency phenomenon, e.g. nonlinear VECM model, nonlinear VECM GARCH model and nonlinear VECM GARCH-M model. The property test proves that the dynamic processes of tanker freight rates reveal seasonal phenomena. And all developed models support the non-linear models reveals better explanation abilities. The developed nonlinear VECM GARCH-M model is the most fitness model aiming at analyzing the recent volatile volatility persistence tanker freight rates by comparing the SBIC statistics. The developed nonlinear VECM GARCH model provides the best forecast ability in the out-of-sample predictive power test in the flat volatility regime.
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Books on the topic "Arbitrage Econometric models"

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F, Gallmeyer Michael, and National Bureau of Economic Research., eds. Arbitrage-free bond pricing with dynamic macroeconomic models. Cambridge, Mass: National Bureau of Economic Research, 2007.

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Das, Sanjiv R. A direct approach to arbitrage-free pricing of credit derivatives. Cambridge, MA: National Bureau of Economic Research, 1998.

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Gatev, Evan G. Pairs trading: Performance of a relative value arbitrage rule. Cambridge, MA: National Bureau of Economic Research, 1999.

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Obstfeld, Maurice. Non-linear aspects of goods-market arbitrage and adjustment: Heckscher's commodity points revisited. London: Centre for Economic Policy Research, 1997.

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Obstfeld, Maurice. Nonlinear aspects of goods-market arbitrage and adjustment: Heckscher's commodity points revisited. Cambridge, MA: National Bureau of Economic Research, 1997.

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O'Connell, Paul G. J. "The bigger they are, the harder they fall": How price differences across U.S. cities are arbitraged. Cambridge, MA: National Bureau of Economic Research, 1997.

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Bertsimas, Dimitris. Pricing and hedging derivative securities in incomplete markets: An e-arbitrage approach. Cambridge, MA: National Bureau of Economic Research, 1997.

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Campa, Jose. Goods arbitrage and real exchange rate stationarity. Wien: Oesterreichische Nationalbank, 1998.

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Agell, Jonas. Tax arbitrage and labor supply. Cambridge, MA: National Bureau of Economic Research, 1998.

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Elsinger, Helmut. Arbitrage and optimal portfolio choice with financial constraints. Wien: Oesterreichische Nationalbank, 2001.

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Book chapters on the topic "Arbitrage Econometric models"

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Laopodis, Nikiforos T. "Multifactor models and the Arbitrage Pricing Theory." In Financial Economics and Econometrics, 301–64. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003205005-10.

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Adams, Zeno, Roland Füss, Philipp Grüber, Ulrich Hommel, and Holger Wohlenberg. "Estimating the Arbitrage Pricing Theory Factor Sensitivities Using Quantile Regression." In Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models, 18–27. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230295223_2.

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Reports on the topic "Arbitrage Econometric models"

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Prakash, Gauri, and Alan Taylor. Measuring Market Integration: A Model of Arbitrage with an Econometric Application to the Gold Standard, 1879-1913. Cambridge, MA: National Bureau of Economic Research, June 1997. http://dx.doi.org/10.3386/w6073.

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