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Description: ARMA model. GARCH. stitionary. LBQtest.
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Size: 1024 |
Author: Andrey |
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Description: Calculates various ARMA-GARCH models for a specified returns time series. Output: model matrix with tests on model residuals and AIC BIC criteria
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Size: 1024 |
Author: Lexiko |
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Description: Discrete-time models: random walk, ARMA, fractional integration, GARCH). Continuous-time counterparts: Levy processes, Ornstein-Uhlenbeck, fractional Brownian motion, stochastic volatility, subordination.
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Size: 4914176 |
Author: Kevin |
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Description: 金融时间序列分析
1. 采用Pandas从Yahoo网上下载上市公司的5到10年的日收盘数据，上证指数的日收盘数据。
2. 计算上市公司和上证指数的收益率，
3. 针对上市公司收益率进行ARMA建模，确定P和q，并对残差进行分析，最后向前预测多期，显示预测图。
4. 针对上市公司收益率进行ARCH建模，确定阶数，并对残差进行分析，最后进行预测。
5. 针对上市公司收益率进行GARCH建模，确定阶数，并对残差进行分析，最后进行预测。(use Arch Model to ananlyse and predict yields from public companies. Python. pandas)
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Size: 424960 |
Author: xting
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Description: 1、根据财务因子选择10只股票，具体财务因子不限；2、运用投资组合理论建立投资组合，计算出每只股票的权重（协方差、相关系数）；3、将构建的投资组合收益率与指数对比，计算看是否存在超阿尔法收益；4、将构建的投资组合收益率序列建立模型（ARMA、GARCH等），并预测未来一周、一月的收益率；(1, according to the financial factor selection of 10 stocks, the specific financial factor is not limited; 2, portfolio theory is used to establish the portfolio, calculate the weight of each stock (covariance, correlation coefficient); 3, will build the portfolio yield and the index calculation comparison, see if the presence of super Alfa 4, revenue; the portfolio construction rate sequence model (ARMA, GARCH), and to predict the future a week or a month rate of return;)
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Size: 126976 |
Author: huagong
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Description: garch copula
带论文和code例句(garch copula
with paper and code)
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Size: 10517504 |
Author: 刘德华984 |
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