39、股票市场预测与信号噪声比测量研究

股票市场预测与信号噪声比测量研究

股票市场预测部分

在股票市场预测中，为了准确预测股票走势，采用了五种常见的回归技术，分别是线性回归、随机森林、支持向量回归（SVR）、向量自回归（VAR）和长短期记忆网络（LSTM）。以下是这五种模型的具体参数设置：
| 模型 | 具体参数 |
| — | — |
| 线性回归 | copy_X = True, fit_intercept = True, n_jobs = None, normalize = False |
| 随机森林 | bootstrap = True, ccp_alpha = 0.0, criterion = ’mse’, max_depth = None, max_features = ’auto’, max_leaf_nodes = None, max_samples = None, min_impurity_decrease = 0.0, min_impurity_split = None, min_samples_leaf = 1, min_samples_split = 2, min_weight_fraction_leaf = 0.0, n_estimators = 50, n_jobs = None, oob_score = False, random_state = 42, verbose = 0, warm_start = False |
| SVR | Kernal: linear, C: 1, Epsilon: 0.1, Gamma: scale, Degree: 3, Tolerance: 0.001, Shrinking Heuristic: True, Cache Size: 200m