Man pages for ylwpaopao/cnquant
Quantitative Analysis Tools in Chinese Stock Market
| calc_IC | Title |
| calc_PIC | Calculate daily price impact cost using wind tick data |
| calculate_AR | Calculate abnormal return by factor model |
| calculate_price_impact_cost | Calculate daily price impact cost using wind tick data |
| clean_stock_daily_data | Title |
| cnquant | cnquant: China stock market quant toolbox |
| df_to_ts | Transform from data.frame to time series |
| divide | Divide numeric into quantile groups |
| forecast_arima_h1 | Title |
| gen_index_dict | Generate an index dictionary |
| geomean | Title |
| lag_certain | Title |
| layer_return | Calculate layer returns from raw stock daily data data frame |
| MAE | Mean absolute error |
| match_industry | Title |
| month_end | Get the last day of month |
| move_para | Move parallel a matrix and pad NAs |
| mre | Title |
| na.fill_mean | Title |
| na.fill_mod | Title |
| neutralize | Neutralize one variable upon others |
| parse_tick_time | Parse tick time |
| portf_stats | Summary statistics for portfolio(s) |
| read_csmar_data | Read CSMAR data |
| read_tick_data | Read tick data |
| relative_error | Title |
| replace_certain | Replace a certain value to another |
| RMSE | Root of mean square error |
| show_na | Show the number of NAs of each column of a data frame |
| spread_single_var | Title |
| summ_stats | Calculate summary statistics |
| summ_stats.data.frame | Title |
| summ_stats.default | Title |
| sum_square | Title |
| ts_to_df | Title |
| uncumsum | Title |
| w_edb | Revised w.edb for friendly Chinese index names |
| weighted_mean | Weighted arithmetic mean |
| weight_estimate | Estimate component weight |
| wind_sql_connect | Title |
| winsorize | Winsorize data |
