The Experts below are selected from a list of 59349 Experts worldwide ranked by ideXlab platform
Alex Weissensteiner - One of the best experts on this subject based on the ideXlab platform.
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No-Arbitrage bounds for financial scenarios
European Journal of Operational Research, 2014Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Abstract We derive no-Arbitrage bounds for expected excess returns to generate scenarios used in financial applications. The bounds allow to distinguish three regions: one where Arbitrage opportunities will never exist, a second where Arbitrage may be present, and a third, where Arbitrage opportunities will always exist. No-Arbitrage bounds are derived in closed form for a given covariance matrix using the least possible number of scenarios. Empirical examples illustrate the practical potential of knowing these bounds.
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No-Arbitrage ROM simulation
Journal of Economic Dynamics and Control, 2014Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Abstract Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method׳s attractiveness by focusing on applications in finance. Many financial applications require simulated asset returns to be free of Arbitrage opportunities. We analytically derive no-Arbitrage bounds for expected excess returns to be used in the context of ROM simulation, and we establish the theoretical relation between the number of states (i.e., the sample size) and the size of (no-)Arbitrage regions. Based on these results, we present a No-Arbitrage ROM simulation algorithm, which generates Arbitrage-free random samples by purposefully rotating a simplex. Hence, the proposed algorithm completely avoids any need for checking samples for Arbitrage. Compared to the alternative of (potentially frequent) re-sampling followed by Arbitrage checks, it is considerably more efficient. As a by-product, we provide interesting geometrical insights into affine transformations associated with the No-Arbitrage ROM simulation algorithm.
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No-Arbitrage ROM Simulation
SSRN Electronic Journal, 2012Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method's attractiveness by focusing on applications in finance. It is well known that many financial applications require simulated asset returns to be free of Arbitrage opportunities. We analytically derive no-Arbitrage bounds for expected excess returns to be used in the context of ROM simulation, and we establish the theoretical relation between the number of states (i.e., the sample size) and the size of (no-)Arbitrage regions. Based on these results, we present a No-Arbitrage ROM simulation algorithm, which generates Arbitrage-free random samples by purposefully rotating a simplex. Hence, the proposed algorithm completely avoids any need for checking samples for Arbitrage. Compared to the alternative of (potentially frequent) re-sampling followed by Arbitrage checks, it is considerably more efficient. As a by-product, we provide interesting geometrical insights into affine transformations associated with the No-Arbitrage ROM simulation algorithm.
Alois Geyer - One of the best experts on this subject based on the ideXlab platform.
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No-Arbitrage bounds for financial scenarios
European Journal of Operational Research, 2014Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Abstract We derive no-Arbitrage bounds for expected excess returns to generate scenarios used in financial applications. The bounds allow to distinguish three regions: one where Arbitrage opportunities will never exist, a second where Arbitrage may be present, and a third, where Arbitrage opportunities will always exist. No-Arbitrage bounds are derived in closed form for a given covariance matrix using the least possible number of scenarios. Empirical examples illustrate the practical potential of knowing these bounds.
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No-Arbitrage ROM simulation
Journal of Economic Dynamics and Control, 2014Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Abstract Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method׳s attractiveness by focusing on applications in finance. Many financial applications require simulated asset returns to be free of Arbitrage opportunities. We analytically derive no-Arbitrage bounds for expected excess returns to be used in the context of ROM simulation, and we establish the theoretical relation between the number of states (i.e., the sample size) and the size of (no-)Arbitrage regions. Based on these results, we present a No-Arbitrage ROM simulation algorithm, which generates Arbitrage-free random samples by purposefully rotating a simplex. Hence, the proposed algorithm completely avoids any need for checking samples for Arbitrage. Compared to the alternative of (potentially frequent) re-sampling followed by Arbitrage checks, it is considerably more efficient. As a by-product, we provide interesting geometrical insights into affine transformations associated with the No-Arbitrage ROM simulation algorithm.
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No-Arbitrage ROM Simulation
SSRN Electronic Journal, 2012Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method's attractiveness by focusing on applications in finance. It is well known that many financial applications require simulated asset returns to be free of Arbitrage opportunities. We analytically derive no-Arbitrage bounds for expected excess returns to be used in the context of ROM simulation, and we establish the theoretical relation between the number of states (i.e., the sample size) and the size of (no-)Arbitrage regions. Based on these results, we present a No-Arbitrage ROM simulation algorithm, which generates Arbitrage-free random samples by purposefully rotating a simplex. Hence, the proposed algorithm completely avoids any need for checking samples for Arbitrage. Compared to the alternative of (potentially frequent) re-sampling followed by Arbitrage checks, it is considerably more efficient. As a by-product, we provide interesting geometrical insights into affine transformations associated with the No-Arbitrage ROM simulation algorithm.
Raghvendra Sisodia - One of the best experts on this subject based on the ideXlab platform.
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securities transaction tax reduction and stock futures Arbitrage in india a case study
Indian Journal of Finance, 2012Co-Authors: Ronald T Slivka, Pankaj Aggarwal, Raghvendra SisodiaAbstract:UK Sinha, Chairman of the Securities Exchange Board of India (SEBI) announced in November, 2011 that SEBI had engaged the Ministry of Finance in a discussion, that would hopefully lead to a reduction of India's Securities Transaction Tax (STT) - a discussion that would hopefully produce benefits for India's capital markets (CNBC, 2011). The matter of reducing or eliminating the STT was under study by the Ministry of Finance, Government of India and came before the Indian Parliament in February 2012. Removal of this tax has been a long-term objective of brokers, stock exchanges and investors, who compare the exceptionally high total transaction cost of fees and taxes in India with lower total costs in other countries. In this study, both intraday and inter-day data on a representative selection of single stocks and their associated futures contracts was used to explore the effects of reduction or elimination of the STT when single stocks are Arbitraged against their related futures contracts. For this purpose, data was chosen spanning selected days in June through December 2011 for eight liquid single stocks. Since the profit from a potential Arbitrage can be calculated in advance of entering a trade, the number of profitable single stock Arbitrage trades available on a specific day can be calculated after accounting for STT cost ranging from zero to 100% of its current statutory level. The result of this careful analysis suggested that a decrease in the STT of at least 75% is necessary to achieve meaningfully increased levels of Arbitrage normally found in most successful global futures markets. Such a decrease in the STT is also likely to result in the maximum transaction revenue collected by the government.
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securities transaction tax reduction and stock futures Arbitrage in india
2012Co-Authors: Ronald T Slivka, Pankaj Aggarwal, Kunal K Shastri, Raghvendra SisodiaAbstract:UK Sinha, Chairman of the Securities Exchange Board of India (SEBI) announced in November, 2011 that SEBI had engaged the Ministry of Finance in a discussion hopefully leading to a reduction of India's Securities Transaction Tax (STT) discussion that would hopefully produce benefits to India's capital markets (CNBC, 2011). The matter of reducing or eliminating the STT is presently under study by the Ministry of Finance and will come before the Indian Parliament in February 2012. Removal of this tax has been a long-term objective of brokers, stock exchanges and investors who compare the exceptionally high total transaction cost of fees and taxes in India with lower total costs in other countries. In this study both intraday and inter-day data on a representative selection of single stocks and their associated futures contracts is used to explore the effects of reduction or elimination of the STT when single stocks are Arbitraged against their related futures contracts. For this purpose data was chosen spanning selected days in June through December 2011 for eight liquid single stocks. Since the profit from a potential Arbitrage can be calculated in advance of entering a trade, the number of profitable single stock Arbitrage trades available on a specific day can be calculated after accounting for STT cost ranging from zero to 100% of its current statutory level. The result of this careful analysis suggests a decrease in the STT of at least 75% is necessary to achieve meaningfully increased levels of Arbitrage normally found in most successful global futures markets. Such a decrease in the STT is also likely to result in the maximum transaction revenue collected by the government.
Michael Hanke - One of the best experts on this subject based on the ideXlab platform.
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No-Arbitrage bounds for financial scenarios
European Journal of Operational Research, 2014Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Abstract We derive no-Arbitrage bounds for expected excess returns to generate scenarios used in financial applications. The bounds allow to distinguish three regions: one where Arbitrage opportunities will never exist, a second where Arbitrage may be present, and a third, where Arbitrage opportunities will always exist. No-Arbitrage bounds are derived in closed form for a given covariance matrix using the least possible number of scenarios. Empirical examples illustrate the practical potential of knowing these bounds.
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No-Arbitrage ROM simulation
Journal of Economic Dynamics and Control, 2014Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Abstract Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method׳s attractiveness by focusing on applications in finance. Many financial applications require simulated asset returns to be free of Arbitrage opportunities. We analytically derive no-Arbitrage bounds for expected excess returns to be used in the context of ROM simulation, and we establish the theoretical relation between the number of states (i.e., the sample size) and the size of (no-)Arbitrage regions. Based on these results, we present a No-Arbitrage ROM simulation algorithm, which generates Arbitrage-free random samples by purposefully rotating a simplex. Hence, the proposed algorithm completely avoids any need for checking samples for Arbitrage. Compared to the alternative of (potentially frequent) re-sampling followed by Arbitrage checks, it is considerably more efficient. As a by-product, we provide interesting geometrical insights into affine transformations associated with the No-Arbitrage ROM simulation algorithm.
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No-Arbitrage ROM Simulation
SSRN Electronic Journal, 2012Co-Authors: Alois Geyer, Michael Hanke, Alex WeissensteinerAbstract:Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method's attractiveness by focusing on applications in finance. It is well known that many financial applications require simulated asset returns to be free of Arbitrage opportunities. We analytically derive no-Arbitrage bounds for expected excess returns to be used in the context of ROM simulation, and we establish the theoretical relation between the number of states (i.e., the sample size) and the size of (no-)Arbitrage regions. Based on these results, we present a No-Arbitrage ROM simulation algorithm, which generates Arbitrage-free random samples by purposefully rotating a simplex. Hence, the proposed algorithm completely avoids any need for checking samples for Arbitrage. Compared to the alternative of (potentially frequent) re-sampling followed by Arbitrage checks, it is considerably more efficient. As a by-product, we provide interesting geometrical insights into affine transformations associated with the No-Arbitrage ROM simulation algorithm.
Christoph Kühn - One of the best experts on this subject based on the ideXlab platform.
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How local in time is the no-Arbitrage property under capital gains taxes?
Mathematics and Financial Economics, 2019Co-Authors: Christoph KühnAbstract:In frictionless financial markets, no-Arbitrage is a local property in time. This means that a discrete time model is Arbitrage-free if and only if there does not exist a one-period-Arbitrage. With capital gains taxes, this equivalence fails. For a model with a linear tax and one non-shortable risky stock, we introduce the concept of robust local no-Arbitrage (RLNA) as the weakest local condition which guarantees dynamic no-Arbitrage. Under a sharp dichotomy condition, we prove (RLNA). Since no-one-period-Arbitrage is necessary for no-Arbitrage, the latter is sandwiched between two local conditions, which allows us to estimate its non-locality. Furthermore, we construct a stock price process such that two long positions in the same stock hedge each other. This puzzling phenomenon that cannot occur in Arbitrage-free frictionless markets (or markets with proportional transaction costs) is used to show that no-Arbitrage alone does not imply the existence of an equivalent separating measure if the probability space is infinite. Finally, we show that the model with a linear tax on capital gains can be written as a model with proportional transaction costs by introducing several fictitious securities.
