Zdrojový kód wiki Algotrading
Naposledy upravil David Brazda 28.02.2023 16:44
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1.1 | 1 | = Resources = |
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1.2 | 3 | algo-trading basics [[https:~~/~~/algo-trading.readthedocs.io/en/latest/data-science-basics.html>>https://algo-trading.readthedocs.io/en/latest/data-science-basics.html]] a [[github>>https://github.com/awoo424/algotrading]] |
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1.1 | 4 | |
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14.1 | 5 | = Platformy = |
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1.3 | 6 | |
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14.1 | 7 | * Jednoduchá varianta Trading view + [[integrace s webhooks >>https://github.com/robswc/tradingview-webhooks-bot]]- python based, na vlastnim serveru. (pokud se osvedci traderspost, pak muzu nainstalovat toto, napriklad na forum.pgwiki.cz, kde je docker a ma domenu) |
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15.1 | 8 | * Backtrader + [[ALpaca backtrader API>>https://github.com/alpacahq/alpaca-backtrader-api]] (+pripadna ws [[proxy>>https://github.com/camelpac/alpaca-proxy-agent]]) |
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14.1 | 9 | * Blankly |
10 | * [[zvt AI trading ML python tradng platforma >>https://github.com/zvtvz/zvt]]on github - modular quant framework - [[docs>>https://zvt.readthedocs.io/en/latest/]] | ||
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16.1 | 11 | * [[LumiBot>>https://github.com/Lumiwealth/lumibot]] - hodně simple |
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18.1 | 12 | * [[https:~~/~~/github.com/Finned-Digital-Solutions/hft-ext>>https://github.com/Finned-Digital-Solutions/hft-ext]] - zkouknout |
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14.1 | 13 | |
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4.2 | 14 | = Python and stocks = |
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16 | [[https:~~/~~/github.com/LastAncientOne/SimpleStockAnalysisPython>>https://github.com/LastAncientOne/SimpleStockAnalysisPython]] | ||
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17.1 | 18 | = AI predictors = |
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4.2 | 19 | |
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19.1 | 20 | reinforced learning platforma - na toto se určitě podívat [[https:~~/~~/github.com/AI4Finance-Foundation/FinRL>>https://github.com/AI4Finance-Foundation/FinRL]] |
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12.1 | 22 | [[python AI knihovna na předpověď ceny- pandas market predictor on GITHUB>>https://github.com/somkietacode/Pandas_Market_Predictor]] |
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10.1 | 23 | |
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17.1 | 24 | [[Crypto predictions AI stock prediction platform>>https://github.com/alimohammadiamirhossein/CryptoPredictions]] on github - vypadá dobře |
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12.1 | 25 | |
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1.3 | 26 | = Zajimavé indikátory = |
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28 | Podívat se na Prior SAR: The SAR value for previous period. | ||
29 | Extreme Point (EP): The highest high of the current uptrend. | ||
30 | Acceleration Factor (AF): Starting at 0.02, increases by 0.02 each time the extreme point makes a new high. AF can only reach a maximum of 0.2, no matter how long the uptrend extends. | ||
31 | \\Dále se podívat na Commodity Channel Index (CCI) | ||
32 | The Commodity Channel Index (CCI) helps identify price reversals, price extremes, and trend strength. | ||
33 | Developed by Donald Lambert, CCI is a momentum-based oscillator used to help determine when an investment vehicle is reaching a condition of being overbought or oversold. Popis zde - vyzkouset | ||
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1.4 | 34 | |
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1.7 | 35 | A také [[ROC>>https://algo-trading.readthedocs.io/en/latest/technical-analysis.html#rate-of-change-roc]] |
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1.4 | 36 | |
37 | Popis základních indikátorů a jak na ně v pythonu je zde (projít!!) | ||
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1.3 | 38 | [[https:~~/~~/algo-trading.readthedocs.io/en/latest/technical-analysis.html>>url:https://algo-trading.readthedocs.io/en/latest/technical-analysis.html]] |
39 | \\a dale | ||
40 | Rsi divergence | ||
41 | [[https:~~/~~/github.com/SpiralDevelopment/RSI-divergence-detector>>url:https://github.com/SpiralDevelopment/RSI-divergence-detector]] | ||
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2.1 | 42 | |
43 | |||
44 | = AI = | ||
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17.1 | 46 | |
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9.1 | 48 | Základní myšlenka: Vstup (buď trade data nebo nějaký sec rt bar) + základní hodnoty indikátorů(ma, rsi, momentum..). Model dostane sušenku, když v aktuálním bodě predikuje, že půjde o malou hodnotu nahoru (např. 5 ticků). Za to dostane odměnu. A pustit na to třeba měsíční data. A vidělo by se. To by nemuselo být složité na interpretaci. |
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8.1 | 49 | |
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9.1 | 50 | A pak vytrénovaný model pustit na online data. |
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7.1 | 53 | LSTM in stock - příklad [[https:~~/~~/www.kaggle.com/code/faressayah/stock-market-analysis-prediction-using-lstm/notebook>>https://www.kaggle.com/code/faressayah/stock-market-analysis-prediction-using-lstm/notebook]] |
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8.1 | 55 | podívat se na keras a LTSM |
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3.2 | 57 | Zajimavý článek [[základy Recurrent Neural Networks>>http://karpathy.github.io/2015/05/21/rnn-effectiveness/]] a [[https:~~/~~/towardsdatascience.com/recurrent-neural-networks-rnns-3f06d7653a85>>https://towardsdatascience.com/recurrent-neural-networks-rnns-3f06d7653a85]] |
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3.1 | 58 | |
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3.3 | 59 | Příklad - [[singlefeature LSTM model in pytorch>>https://algo-trading.readthedocs.io/en/latest/integrated-strategy.html#single-feature-lstm-model]]. |
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3.1 | 60 | |
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5.2 | 61 | [[Stock Machine learning algorithms on github>>https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock]] ([[LSTM>>https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock/blob/master/Stock_Algorithms/LSTM_RNN_Part2.ipynb]])- projít |
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2.1 | 62 | |
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4.1 | 63 | Zadání: predikční modely (HFT, 15s dt, střednědobý) |
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2.1 | 65 | * - learning data |
66 | ** vývoj ceny - timeseries relevantní frekvence (trades, 15s ohlc a třeba 1h(1d) ohlc) | ||
67 | ** dopočítané/doplněné sloupce k timeseries (indikátory, calendar data a další time related data) | ||
68 | ** další doplňující atributy - jako premarket, fair price, trend z minulých období, odhad dnešního dne(dopočítávaný), celkový sentiment(může doplňovat jiný [[model>>https://algo-trading.readthedocs.io/en/latest/sentiment-analysis.html]] z news) | ||
69 | * | ||
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