P2SAMAPA/p2-etf-trendfolios-replication-data

--- dataset_info: - config_name: equity_a_calendar features: - name: Year dtype: int32 - name: Strategy (Gross) dtype: float64 - name: Strategy (Net) dtype: float64 - name: Benchmark dtype: float64 - name: Excess Return (Gross) dtype: float64 - name: Excess Return (Net) dtype: float64 splits: - name: train num_bytes: 968 num_examples: 22 download_size: 4214 dataset_size: 968 - config_name: equity_a_growth features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 182603 num_examples: 5351 download_size: 133373 dataset_size: 182603 - config_name: equity_a_inclusion features: - name: date dtype: string - name: IWD dtype: int64 - name: IWF dtype: int64 - name: IWN dtype: int64 - name: IWO dtype: int64 - name: EFA dtype: int64 - name: EEM dtype: int64 - name: EWZ dtype: int64 - name: QQQ dtype: int64 - name: XLV dtype: int64 - name: XLF dtype: int64 - name: XLE dtype: int64 - name: XLI dtype: int64 - name: XLK dtype: int64 - name: XLY dtype: int64 - name: XLP dtype: int64 - name: XLB dtype: int64 - name: XLRE dtype: int64 - name: XLU dtype: int64 - name: XLC dtype: int64 - name: XBI dtype: int64 - name: XME dtype: int64 - name: XHB dtype: int64 - name: XSD dtype: int64 - name: XRT dtype: int64 - name: XAR dtype: int64 - name: XNTK dtype: int64 splits: - name: train num_bytes: 1209326 num_examples: 5351 download_size: 55441 dataset_size: 1209326 - config_name: equity_a_returns features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: portfolio_net dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 225411 num_examples: 5351 download_size: 184923 dataset_size: 225411 - config_name: equity_a_rolling features: - name: date dtype: string - name: rolling_1y dtype: float64 - name: rolling_3y dtype: float64 - name: rolling_5y dtype: float64 splits: - name: train num_bytes: 226749 num_examples: 5351 download_size: 175784 dataset_size: 226749 - config_name: equity_a_summary features: - name: Period dtype: string - name: Composite Gross Return dtype: float64 - name: Composite Net Return dtype: float64 - name: Index Return dtype: float64 - name: Excess Return (gross) dtype: float64 - name: Excess Return (net) dtype: float64 - name: Composite Std Dev dtype: float64 - name: Index Std Dev dtype: float64 - name: Composite Sharpe dtype: float64 - name: Index Sharpe dtype: float64 - name: Tracking Error dtype: float64 - name: Information Ratio dtype: float64 - name: Max Drawdown dtype: float64 splits: - name: train num_bytes: 560 num_examples: 5 download_size: 6992 dataset_size: 560 - config_name: equity_a_weights features: - name: date dtype: string - name: IWD dtype: float64 - name: IWF dtype: float64 - name: IWN dtype: float64 - name: IWO dtype: float64 - name: EFA dtype: float64 - name: EEM dtype: float64 - name: EWZ dtype: float64 - name: QQQ dtype: float64 - name: XLV dtype: float64 - name: XLF dtype: float64 - name: XLE dtype: float64 - name: XLI dtype: float64 - name: XLK dtype: float64 - name: XLY dtype: float64 - name: XLP dtype: float64 - name: XLB dtype: float64 - name: XLRE dtype: float64 - name: XLU dtype: float64 - name: XLC dtype: float64 - name: XBI dtype: float64 - name: XME dtype: float64 - name: XHB dtype: float64 - name: XSD dtype: float64 - name: XRT dtype: float64 - name: XAR dtype: float64 - name: XNTK dtype: float64 splits: - name: train num_bytes: 1209326 num_examples: 5351 download_size: 53581 dataset_size: 1209326 - config_name: equity_b_calendar features: - name: Year dtype: int32 - name: Strategy (Gross) dtype: float64 - name: Strategy (Net) dtype: float64 - name: Benchmark dtype: float64 - name: Excess Return (Gross) dtype: float64 - name: Excess Return (Net) dtype: float64 splits: - name: train num_bytes: 968 num_examples: 22 download_size: 4214 dataset_size: 968 - config_name: equity_b_growth features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 182603 num_examples: 5351 download_size: 120994 dataset_size: 182603 - config_name: equity_b_inclusion features: - name: date dtype: string - name: IWD dtype: int64 - name: IWF dtype: int64 - name: IWN dtype: int64 - name: IWO dtype: int64 - name: EFA dtype: int64 - name: EEM dtype: int64 - name: EWZ dtype: int64 - name: QQQ dtype: int64 - name: XLV dtype: int64 - name: XLF dtype: int64 - name: XLE dtype: int64 - name: XLI dtype: int64 - name: XLK dtype: int64 - name: XLY dtype: int64 - name: XLP dtype: int64 - name: XLB dtype: int64 - name: XLRE dtype: int64 - name: XLU dtype: int64 - name: XLC dtype: int64 - name: XBI dtype: int64 - name: XME dtype: int64 - name: XHB dtype: int64 - name: XSD dtype: int64 - name: XRT dtype: int64 - name: XAR dtype: int64 - name: XNTK dtype: int64 splits: - name: train num_bytes: 1209326 num_examples: 5351 download_size: 53236 dataset_size: 1209326 - config_name: equity_b_returns features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: portfolio_net dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 225411 num_examples: 5351 download_size: 160259 dataset_size: 225411 - config_name: equity_b_rolling features: - name: date dtype: string - name: rolling_1y dtype: float64 - name: rolling_3y dtype: float64 - name: rolling_5y dtype: float64 splits: - name: train num_bytes: 226749 num_examples: 5351 download_size: 175784 dataset_size: 226749 - config_name: equity_b_summary features: - name: Period dtype: string - name: Composite Gross Return dtype: float64 - name: Composite Net Return dtype: float64 - name: Index Return dtype: float64 - name: Excess Return (gross) dtype: float64 - name: Excess Return (net) dtype: float64 - name: Composite Std Dev dtype: float64 - name: Index Std Dev dtype: float64 - name: Composite Sharpe dtype: float64 - name: Index Sharpe dtype: float64 - name: Tracking Error dtype: float64 - name: Information Ratio dtype: float64 - name: Max Drawdown dtype: float64 splits: - name: train num_bytes: 560 num_examples: 5 download_size: 6988 dataset_size: 560 - config_name: equity_b_weights features: - name: date dtype: string - name: IWD dtype: float64 - name: IWF dtype: float64 - name: IWN dtype: float64 - name: IWO dtype: float64 - name: EFA dtype: float64 - name: EEM dtype: float64 - name: EWZ dtype: float64 - name: QQQ dtype: float64 - name: XLV dtype: float64 - name: XLF dtype: float64 - name: XLE dtype: float64 - name: XLI dtype: float64 - name: XLK dtype: float64 - name: XLY dtype: float64 - name: XLP dtype: float64 - name: XLB dtype: float64 - name: XLRE dtype: float64 - name: XLU dtype: float64 - name: XLC dtype: float64 - name: XBI dtype: float64 - name: XME dtype: float64 - name: XHB dtype: float64 - name: XSD dtype: float64 - name: XRT dtype: float64 - name: XAR dtype: float64 - name: XNTK dtype: float64 splits: - name: train num_bytes: 1209326 num_examples: 5351 download_size: 60857 dataset_size: 1209326 - config_name: equity_calendar features: - name: Year dtype: int32 - name: Strategy (Gross) dtype: float64 - name: Strategy (Net) dtype: float64 - name: Benchmark dtype: float64 - name: Excess Return (Gross) dtype: float64 - name: Excess Return (Net) dtype: float64 splits: - name: train num_bytes: 968 num_examples: 22 download_size: 4214 dataset_size: 968 - config_name: equity_growth features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 160747 num_examples: 5336 download_size: 132927 dataset_size: 160747 - config_name: equity_inclusion features: - name: date dtype: string - name: IWD dtype: int64 - name: IWF dtype: int64 - name: IWN dtype: int64 - name: IWO dtype: int64 - name: EFA dtype: int64 - name: EEM dtype: int64 - name: EWZ dtype: int64 - name: QQQ dtype: int64 - name: XLV dtype: int64 - name: XLF dtype: int64 - name: XLE dtype: int64 - name: XLI dtype: int64 - name: XLK dtype: int64 - name: XLY dtype: int64 - name: XLP dtype: int64 - name: XLB dtype: int64 - name: XLRE dtype: int64 - name: XLU dtype: int64 - name: XLC dtype: int64 - name: XBI dtype: int64 - name: XME dtype: int64 - name: XHB dtype: int64 - name: XSD dtype: int64 - name: XRT dtype: int64 - name: XAR dtype: int64 - name: XNTK dtype: int64 splits: - name: train num_bytes: 1184592 num_examples: 5336 download_size: 55278 dataset_size: 1184592 - config_name: equity_latest_optimal features: - name: optimal_period dtype: int64 - name: optimal_n dtype: int64 - name: best_ann_return dtype: float64 - name: holdings dtype: string - name: as_of dtype: string splits: - name: train num_bytes: 58 num_examples: 1 download_size: 3397 dataset_size: 58 - config_name: equity_latest_weights features: - name: ticker dtype: string - name: weight dtype: float64 splits: - name: train num_bytes: 304 num_examples: 3 download_size: 5140 dataset_size: 304 - config_name: equity_optimal_params features: - name: date dtype: string - name: optimal_period dtype: int64 - name: optimal_n dtype: int64 - name: best_ann_return dtype: float64 splits: - name: train num_bytes: 93225 num_examples: 1695 download_size: 28531 dataset_size: 93225 - config_name: equity_returns features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: portfolio_net dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 203435 num_examples: 5336 download_size: 184391 dataset_size: 203435 - config_name: equity_rolling features: - name: date dtype: string - name: rolling_1y dtype: float64 - name: rolling_3y dtype: float64 - name: rolling_5y dtype: float64 splits: - name: train num_bytes: 204769 num_examples: 5336 download_size: 175235 dataset_size: 204769 - config_name: equity_summary features: - name: Period dtype: string - name: Composite Gross Return dtype: float64 - name: Composite Net Return dtype: float64 - name: Index Return dtype: float64 - name: Excess Return (gross) dtype: float64 - name: Excess Return (net) dtype: float64 - name: Composite Std Dev dtype: float64 - name: Index Std Dev dtype: float64 - name: Composite Sharpe dtype: float64 - name: Index Sharpe dtype: float64 - name: Tracking Error dtype: float64 - name: Information Ratio dtype: float64 - name: Max Drawdown dtype: float64 splits: - name: train num_bytes: 540 num_examples: 5 download_size: 6978 dataset_size: 540 - config_name: equity_weights features: - name: date dtype: string - name: IWD dtype: float64 - name: IWF dtype: float64 - name: IWN dtype: float64 - name: IWO dtype: float64 - name: EFA dtype: float64 - name: EEM dtype: float64 - name: EWZ dtype: float64 - name: QQQ dtype: float64 - name: XLV dtype: float64 - name: XLF dtype: float64 - name: XLE dtype: float64 - name: XLI dtype: float64 - name: XLK dtype: float64 - name: XLY dtype: float64 - name: XLP dtype: float64 - name: XLB dtype: float64 - name: XLRE dtype: float64 - name: XLU dtype: float64 - name: XLC dtype: float64 - name: XBI dtype: float64 - name: XME dtype: float64 - name: XHB dtype: float64 - name: XSD dtype: float64 - name: XRT dtype: float64 - name: XAR dtype: float64 - name: XNTK dtype: float64 splits: - name: train num_bytes: 1184592 num_examples: 5336 download_size: 53441 dataset_size: 1184592 - config_name: fixed_income_a_calendar features: - name: Year dtype: int32 - name: Strategy (Gross) dtype: float64 - name: Strategy (Net) dtype: float64 - name: Benchmark dtype: float64 - name: Excess Return (Gross) dtype: float64 - name: Excess Return (Net) dtype: float64 splits: - name: train num_bytes: 880 num_examples: 20 download_size: 4126 dataset_size: 880 - config_name: fixed_income_a_growth features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 165438 num_examples: 4848 download_size: 118953 dataset_size: 165438 - config_name: fixed_income_a_inclusion features: - name: date dtype: string - name: TIP dtype: int64 - name: SHY dtype: int64 - name: TLT dtype: int64 - name: LQD dtype: int64 - name: HYG dtype: int64 - name: PFF dtype: int64 - name: MBB dtype: int64 - name: SLV dtype: int64 - name: GLD dtype: int64 - name: VNQ dtype: int64 splits: - name: train num_bytes: 475104 num_examples: 4848 download_size: 37053 dataset_size: 475104 - config_name: fixed_income_a_returns features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: portfolio_net dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 204222 num_examples: 4848 download_size: 165909 dataset_size: 204222 - config_name: fixed_income_a_rolling features: - name: date dtype: string - name: rolling_1y dtype: float64 - name: rolling_3y dtype: float64 - name: rolling_5y dtype: float64 splits: - name: train num_bytes: 205434 num_examples: 4848 download_size: 158329 dataset_size: 205434 - config_name: fixed_income_a_summary features: - name: Period dtype: string - name: Composite Gross Return dtype: float64 - name: Composite Net Return dtype: float64 - name: Index Return dtype: float64 - name: Excess Return (gross) dtype: float64 - name: Excess Return (net) dtype: float64 - name: Composite Std Dev dtype: float64 - name: Index Std Dev dtype: float64 - name: Composite Sharpe dtype: float64 - name: Index Sharpe dtype: float64 - name: Tracking Error dtype: float64 - name: Information Ratio dtype: float64 - name: Max Drawdown dtype: float64 splits: - name: train num_bytes: 560 num_examples: 5 download_size: 6988 dataset_size: 560 - config_name: fixed_income_a_weights features: - name: date dtype: string - name: TIP dtype: float64 - name: SHY dtype: float64 - name: TLT dtype: float64 - name: LQD dtype: float64 - name: HYG dtype: float64 - name: PFF dtype: float64 - name: MBB dtype: float64 - name: SLV dtype: float64 - name: GLD dtype: float64 - name: VNQ dtype: float64 splits: - name: train num_bytes: 475104 num_examples: 4848 download_size: 38936 dataset_size: 475104 - config_name: fixed_income_b_calendar features: - name: Year dtype: int32 - name: Strategy (Gross) dtype: float64 - name: Strategy (Net) dtype: float64 - name: Benchmark dtype: float64 - name: Excess Return (Gross) dtype: float64 - name: Excess Return (Net) dtype: float64 splits: - name: train num_bytes: 880 num_examples: 20 download_size: 4126 dataset_size: 880 - config_name: fixed_income_b_growth features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 165438 num_examples: 4848 download_size: 106496 dataset_size: 165438 - config_name: fixed_income_b_inclusion features: - name: date dtype: string - name: TIP dtype: int64 - name: SHY dtype: int64 - name: TLT dtype: int64 - name: LQD dtype: int64 - name: HYG dtype: int64 - name: PFF dtype: int64 - name: MBB dtype: int64 - name: SLV dtype: int64 - name: GLD dtype: int64 - name: VNQ dtype: int64 splits: - name: train num_bytes: 475104 num_examples: 4848 download_size: 35986 dataset_size: 475104 - config_name: fixed_income_b_returns features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: portfolio_net dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 204222 num_examples: 4848 download_size: 140877 dataset_size: 204222 - config_name: fixed_income_b_rolling features: - name: date dtype: string - name: rolling_1y dtype: float64 - name: rolling_3y dtype: float64 - name: rolling_5y dtype: float64 splits: - name: train num_bytes: 205434 num_examples: 4848 download_size: 158321 dataset_size: 205434 - config_name: fixed_income_b_summary features: - name: Period dtype: string - name: Composite Gross Return dtype: float64 - name: Composite Net Return dtype: float64 - name: Index Return dtype: float64 - name: Excess Return (gross) dtype: float64 - name: Excess Return (net) dtype: float64 - name: Composite Std Dev dtype: float64 - name: Index Std Dev dtype: float64 - name: Composite Sharpe dtype: float64 - name: Index Sharpe dtype: float64 - name: Tracking Error dtype: float64 - name: Information Ratio dtype: float64 - name: Max Drawdown dtype: float64 splits: - name: train num_bytes: 560 num_examples: 5 download_size: 6979 dataset_size: 560 - config_name: fixed_income_b_weights features: - name: date dtype: string - name: TIP dtype: float64 - name: SHY dtype: float64 - name: TLT dtype: float64 - name: LQD dtype: float64 - name: HYG dtype: float64 - name: PFF dtype: float64 - name: MBB dtype: float64 - name: SLV dtype: float64 - name: GLD dtype: float64 - name: VNQ dtype: float64 splits: - name: train num_bytes: 475104 num_examples: 4848 download_size: 45567 dataset_size: 475104 - config_name: fixed_income_calendar features: - name: Year dtype: int32 - name: Strategy (Gross) dtype: float64 - name: Strategy (Net) dtype: float64 - name: Benchmark dtype: float64 - name: Excess Return (Gross) dtype: float64 - name: Excess Return (Net) dtype: float64 splits: - name: train num_bytes: 880 num_examples: 20 download_size: 4126 dataset_size: 880 - config_name: fixed_income_growth features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 145595 num_examples: 4833 download_size: 118518 dataset_size: 145595 - config_name: fixed_income_inclusion features: - name: date dtype: string - name: TIP dtype: int64 - name: SHY dtype: int64 - name: TLT dtype: int64 - name: LQD dtype: int64 - name: HYG dtype: int64 - name: PFF dtype: int64 - name: MBB dtype: int64 - name: SLV dtype: int64 - name: GLD dtype: int64 - name: VNQ dtype: int64 splits: - name: train num_bytes: 454302 num_examples: 4833 download_size: 36951 dataset_size: 454302 - config_name: fixed_income_latest_optimal features: - name: optimal_period dtype: int64 - name: optimal_n dtype: int64 - name: best_ann_return dtype: float64 - name: holdings dtype: string - name: as_of dtype: string splits: - name: train num_bytes: 54 num_examples: 1 download_size: 3377 dataset_size: 54 - config_name: fixed_income_latest_weights features: - name: ticker dtype: string - name: weight dtype: float64 splits: - name: train num_bytes: 274 num_examples: 3 download_size: 5089 dataset_size: 274 - config_name: fixed_income_optimal_params features: - name: date dtype: string - name: optimal_period dtype: int64 - name: optimal_n dtype: int64 - name: best_ann_return dtype: float64 splits: - name: train num_bytes: 83985 num_examples: 1527 download_size: 26230 dataset_size: 83985 - config_name: fixed_income_returns features: - name: date dtype: string - name: portfolio_gross dtype: float64 - name: portfolio_net dtype: float64 - name: benchmark dtype: float64 splits: - name: train num_bytes: 184259 num_examples: 4833 download_size: 165401 dataset_size: 184259 - config_name: fixed_income_rolling features: - name: date dtype: string - name: rolling_1y dtype: float64 - name: rolling_3y dtype: float64 - name: rolling_5y dtype: float64 splits: - name: train num_bytes: 185469 num_examples: 4833 download_size: 157801 dataset_size: 185469 - config_name: fixed_income_summary features: - name: Period dtype: string - name: Composite Gross Return dtype: float64 - name: Composite Net Return dtype: float64 - name: Index Return dtype: float64 - name: Excess Return (gross) dtype: float64 - name: Excess Return (net) dtype: float64 - name: Composite Std Dev dtype: float64 - name: Index Std Dev dtype: float64 - name: Composite Sharpe dtype: float64 - name: Index Sharpe dtype: float64 - name: Tracking Error dtype: float64 - name: Information Ratio dtype: float64 - name: Max Drawdown dtype: float64 splits: - name: train num_bytes: 540 num_examples: 5 download_size: 6974 dataset_size: 540 - config_name: fixed_income_weights features: - name: date dtype: string - name: TIP dtype: float64 - name: SHY dtype: float64 - name: TLT dtype: float64 - name: LQD dtype: float64 - name: HYG dtype: float64 - name: PFF dtype: float64 - name: MBB dtype: float64 - name: SLV dtype: float64 - name: GLD dtype: float64 - name: VNQ dtype: float64 splits: - name: train num_bytes: 454302 num_examples: 4833 download_size: 38821 dataset_size: 454302 - config_name: metadata features: - name: ticker dtype: string - name: universe dtype: string - name: role dtype: string splits: - name: train num_bytes: 1172 num_examples: 38 download_size: 1889 dataset_size: 1172 - config_name: ohlcv features: - name: date dtype: large_string - name: ticker dtype: large_string - name: open dtype: float64 - name: high dtype: float64 - name: low dtype: float64 - name: close dtype: float64 - name: volume dtype: float64 splits: - name: train num_bytes: 15215460 num_examples: 219587 download_size: 17914460 dataset_size: 15215460 - config_name: prices features: - name: date dtype: large_string - name: AGG dtype: float64 - name: EEM dtype: float64 - name: EFA dtype: float64 - name: EWZ dtype: float64 - name: GLD dtype: float64 - name: HYG dtype: float64 - name: IWD dtype: float64 - name: IWF dtype: float64 - name: IWN dtype: float64 - name: IWO dtype: float64 - name: LQD dtype: float64 - name: MBB dtype: float64 - name: PFF dtype: float64 - name: QQQ dtype: float64 - name: SHY dtype: float64 - name: SLV dtype: float64 - name: SPY dtype: float64 - name: TIP dtype: float64 - name: TLT dtype: float64 - name: VNQ dtype: float64 - name: XAR dtype: float64 - name: XBI dtype: float64 - name: XHB dtype: float64 - name: XLB dtype: float64 - name: XLC dtype: float64 - name: XLE dtype: float64 - name: XLF dtype: float64 - name: XLI dtype: float64 - name: XLK dtype: float64 - name: XLP dtype: float64 - name: XLRE dtype: float64 - name: XLU dtype: float64 - name: XLV dtype: float64 - name: XLY dtype: float64 - name: XME dtype: float64 - name: XNTK dtype: float64 - name: XRT dtype: float64 - name: XSD dtype: float64 splits: - name: train num_bytes: 2405285 num_examples: 7364 download_size: 1560146 dataset_size: 2405285 configs: - config_name: equity_a_calendar data_files: - split: train path: equity_a_calendar/train-* - config_name: equity_a_growth data_files: - split: train path: equity_a_growth/train-* - config_name: equity_a_inclusion data_files: - split: train path: equity_a_inclusion/train-* - config_name: equity_a_returns data_files: - split: train path: equity_a_returns/train-* - config_name: equity_a_rolling data_files: - split: train path: equity_a_rolling/train-* - config_name: equity_a_summary data_files: - split: train path: equity_a_summary/train-* - config_name: equity_a_weights data_files: - split: train path: equity_a_weights/train-* - config_name: equity_b_calendar data_files: - split: train path: equity_b_calendar/train-* - config_name: equity_b_growth data_files: - split: train path: equity_b_growth/train-* - config_name: equity_b_inclusion data_files: - split: train path: equity_b_inclusion/train-* - config_name: equity_b_returns data_files: - split: train path: equity_b_returns/train-* - config_name: equity_b_rolling data_files: - split: train path: equity_b_rolling/train-* - config_name: equity_b_summary data_files: - split: train path: equity_b_summary/train-* - config_name: equity_b_weights data_files: - split: train path: equity_b_weights/train-* - config_name: equity_calendar data_files: - split: train path: equity_calendar/train-* - config_name: equity_growth data_files: - split: train path: equity_growth/train-* - config_name: equity_inclusion data_files: - split: train path: equity_inclusion/train-* - config_name: equity_latest_optimal data_files: - split: train path: equity_latest_optimal/train-* - config_name: equity_latest_weights data_files: - split: train path: equity_latest_weights/train-* - config_name: equity_optimal_params data_files: - split: train path: equity_optimal_params/train-* - config_name: equity_returns data_files: - split: train path: equity_returns/train-* - config_name: equity_rolling data_files: - split: train path: equity_rolling/train-* - config_name: equity_summary data_files: - split: train path: equity_summary/train-* - config_name: equity_weights data_files: - split: train path: equity_weights/train-* - config_name: fixed_income_a_calendar data_files: - split: train path: fixed_income_a_calendar/train-* - config_name: fixed_income_a_growth data_files: - split: train path: fixed_income_a_growth/train-* - config_name: fixed_income_a_inclusion data_files: - split: train path: fixed_income_a_inclusion/train-* - config_name: fixed_income_a_returns data_files: - split: train path: fixed_income_a_returns/train-* - config_name: fixed_income_a_rolling data_files: - split: train path: fixed_income_a_rolling/train-* - config_name: fixed_income_a_summary data_files: - split: train path: fixed_income_a_summary/train-* - config_name: fixed_income_a_weights data_files: - split: train path: fixed_income_a_weights/train-* - config_name: fixed_income_b_calendar data_files: - split: train path: fixed_income_b_calendar/train-* - config_name: fixed_income_b_growth data_files: - split: train path: fixed_income_b_growth/train-* - config_name: fixed_income_b_inclusion data_files: - split: train path: fixed_income_b_inclusion/train-* - config_name: fixed_income_b_returns data_files: - split: train path: fixed_income_b_returns/train-* - config_name: fixed_income_b_rolling data_files: - split: train path: fixed_income_b_rolling/train-* - config_name: fixed_income_b_summary data_files: - split: train path: fixed_income_b_summary/train-* - config_name: fixed_income_b_weights data_files: - split: train path: fixed_income_b_weights/train-* - config_name: fixed_income_calendar data_files: - split: train path: fixed_income_calendar/train-* - config_name: fixed_income_growth data_files: - split: train path: fixed_income_growth/train-* - config_name: fixed_income_inclusion data_files: - split: train path: fixed_income_inclusion/train-* - config_name: fixed_income_latest_optimal data_files: - split: train path: fixed_income_latest_optimal/train-* - config_name: fixed_income_latest_weights data_files: - split: train path: fixed_income_latest_weights/train-* - config_name: fixed_income_optimal_params data_files: - split: train path: fixed_income_optimal_params/train-* - config_name: fixed_income_returns data_files: - split: train path: fixed_income_returns/train-* - config_name: fixed_income_rolling data_files: - split: train path: fixed_income_rolling/train-* - config_name: fixed_income_summary data_files: - split: train path: fixed_income_summary/train-* - config_name: fixed_income_weights data_files: - split: train path: fixed_income_weights/train-* - config_name: metadata data_files: - split: train path: metadata/train-* - config_name: ohlcv data_files: - split: train path: ohlcv/train-* - config_name: prices data_files: - split: train path: prices/train-* ---

搜集汇总

数据集介绍

构建方式

在量化金融领域，追踪投资组合表现的数据集对于策略验证至关重要。该数据集通过系统化地收集并整合多个资产类别的历史交易数据构建而成，涵盖了股票和固定收益两大类资产。具体而言，数据集从公开市场数据源提取了包括IWD、IWF等广泛使用的交易所交易基金（ETF）的每日价格、权重分配及收益信息，并依据预设的投资策略逻辑计算了投资组合的净值增长、超额收益以及风险调整后指标。数据构建过程注重时间序列的连续性与完整性，确保每个配置项均包含详尽的日期标记和对应的财务指标，从而为后续的量化分析提供了坚实的数据基础。

使用方法

针对量化金融研究与实践，该数据集为策略开发与绩效评估提供了直接的应用路径。使用者可通过加载特定的配置名称（如`equity_returns`或`fixed_income_a_weights`）来获取相应资产类别和策略版本的历史数据。典型应用场景包括：基于历史权重和收益数据回测动态资产配置策略的有效性；利用滚动收益和摘要统计量进行策略的稳健性检验；通过比较不同策略版本（A/B）或与基准的对比，进行绩效归因分析。数据集以标准数据框格式组织，可直接与Pandas、NumPy等数据分析库集成，或用于训练机器学习模型以预测资产收益。其结构化设计确保了从数据提取到模型验证流程的顺畅衔接。

背景与挑战

背景概述

在量化金融领域，交易型开放式指数基金（ETF）的动态资产配置策略研究一直是学术界与业界关注的焦点。p2-etf-trendfolios-replication-data数据集由相关研究团队构建，旨在为基于趋势跟踪（Trend Following）的ETF投资组合策略提供可复现的实证数据。该数据集涵盖了股票与固定收益两大类资产，通过多维度指标如收益、权重、滚动回报及风险调整后绩效，系统性地记录了策略在历史周期内的表现。其核心研究问题聚焦于探究动量效应在跨资产配置中的稳健性与经济价值，为检验自适应投资模型的可行性提供了关键数据基础，对推动算法交易与智能投顾领域的发展具有显著影响力。

当前挑战

该数据集致力于解决量化资产配置中趋势策略的绩效评估与优化问题，其面临的挑战体现在多个层面。在领域问题层面，挑战主要源于金融市场的非平稳性与结构性断点，这可能导致基于历史数据的趋势信号失效，使得策略在样本外测试中表现不稳定。同时，多资产间的相关性时变与交易成本的精确实证，对超额收益的准确度量构成严峻考验。在构建过程中，挑战涉及原始ETF数据的清洗与对齐，需处理大量缺失值、分红调整及代码变更，并确保不同数据源间频率与口径的一致性。此外，动态权重与净值序列的生成需严谨遵循策略规则，任何计算偏差都可能影响结论的可信度。

常用场景

经典使用场景

在量化金融领域，趋势跟踪策略的评估与优化是核心研究课题。该数据集通过提供多资产类别（如股票与固定收益）的详细投资组合回报、权重及风险指标，为研究人员构建和验证基于动量的投资策略提供了实证基础。经典使用场景包括利用历史回报数据回测趋势跟踪模型，分析不同时间窗口下策略的滚动表现，并比较净收益与基准指数的差异，从而揭示市场趋势的持续性与反转特征。

解决学术问题

该数据集有效解决了量化金融中关于趋势策略稳健性与可复现性的学术争议。通过提供经费用调整后的净收益数据，它允许学者精确评估交易成本对策略绩效的影响，克服了以往研究中忽略实际摩擦的局限。数据集涵盖多个市场周期，支持对策略在不同经济环境下的适应性检验，为理解动量效应的跨资产普适性提供了关键证据，推动了资产定价理论与实证研究的深度融合。

实际应用

在实际投资管理中，该数据集被广泛应用于智能投顾系统与ETF组合构建。投资机构利用其权重配置数据动态调整资产分配，实现基于趋势信号的自动化再平衡。风险管理部门则借助滚动回报与最大回撤指标监控策略下行风险，优化组合的夏普比率。此外，数据集中的最新最优参数为实时交易系统提供了决策依据，助力开发低延迟、高适应性的趋势跟踪产品。

数据集最近研究

最新研究方向

在量化投资领域，ETF趋势投资组合的构建与优化正成为研究热点。该数据集通过提供多类资产配置的详细历史数据，包括股票与固定收益ETF的权重、收益及风险指标，为动态资产配置策略的实证研究奠定了坚实基础。当前前沿探索聚焦于利用机器学习算法，如强化学习与时间序列预测模型，对数据集中的滚动收益与最优参数进行深度挖掘，旨在捕捉市场趋势并实现自适应调仓。随着被动投资规模持续扩张与智能投顾兴起，此类研究不仅推动了因子投资与风险平价策略的演进，也为开发低波动、高夏普比率的组合提供了关键实证支持，对资产管理行业的数字化转型具有深远影响。