Valuation of american interest rate options by the least-squares Monte Carlo method

Cescato, Claudia Dourado; Lemgruber, Eduardo Facó

doi:10.1590/s0101-74382011000300007

Cited by 2 publications

(2 citation statements)

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“…The covariance is then maximized so that the correlation between 𝜐 1 and 𝜈 1 𝑖𝑠 maximized. This can be computed using the inner product of the score vectors 𝑢 ̂1 and 𝜈̂1 : max ⟨𝑢 ̂1, 𝜈̂1⟩ = 𝜌 1 𝑇 AB 𝛾 1 [13]. Applying the Lagrange multiplier method, the problem reduces to solving for the unit vectors 𝜌 1 and 𝛾 1 so that 𝛾 1 is maximized, and it is simply a matter of computing the eigenvalues of the matrix M=𝐴 𝑇 B𝐵 𝑇 A with the eigenvectors.…”

Section: Discussionmentioning

confidence: 99%

“…The table above displays factor loading coefficients, which enable the assessment of the significance of hidden variables within each factor. Skillfully employing Principal Component Analysis (PCA), it's possible to convert high-dimensional data into a lower-dimensional form, thereby improving the results of data analysis and machine learning tasks [13]. Concurrently, it can eliminate superfluous information, averting adverse effects on analysis and modeling.…”

Section: Table Of Factor Loading Coefficientsmentioning

confidence: 99%

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Implementing stock prediction using partial least squares

Peng

2024

HSET

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This paper demonstrates that a considerable number of investors are entering the stock market as the economy displays signs of post-epidemic recovery. Nevertheless, even though the stock market acts as the foundation of the financial sector, not all stockholders can achieve significant profits from it. Yet, stock prices in the stock market have been challenging to keep rational and lack a stable pattern, marked by a notable level of uncertainty, which complicates investment decisions. Consequently, this paper aims to employ scientific mathematical techniques for the analysis and prediction of stock prices, with the goal of achieving a more comprehensive grasp of the stock market's general trend, thereby promoting prudent investment planning.

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Section: Discussionmentioning

confidence: 99%

Section: Table Of Factor Loading Coefficientsmentioning

confidence: 99%

Implementing stock prediction using partial least squares

Peng

2024

HSET

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Pricing 50ETF in the Way of American Options Based on Least Squares Monte Carlo Simulation

Gao¹,

Zhao²

2016

AFA

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50ETF appears on the Chinese stock market on 9th February,2015, the contracts are European Options and the options are priced by B-S model.50ETF is the only one option that can be traded, there are no American Options in Chinese stock market. This paper studies 50ETF pricing analysis in accordance with the way of American Option. We use Least Squares Monte Carlo Simulation to price 50ETF and analyze them, give the numerical results by matlab program. This issue is worth studying, because the paper studies 50ETF, and price it in the way of American Options, we try to employ Monte Carlo Simulation to solve this problem in china and the results of the paper can enrich the option products in the stock market of China.

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Valuation of american interest rate options by the least-squares Monte Carlo method

Cited by 2 publications

References 10 publications

Implementing stock prediction using partial least squares

Implementing stock prediction using partial least squares

Pricing 50ETF in the Way of American Options Based on Least Squares Monte Carlo Simulation

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