Author(s): Jeffrey Ng CFA
+Chapter02
+2A_Seasonality
2A_trade seasonality.py
Average_cost_of_fossil_fuels_for_electricity_generation_natural_gas_California_electric_power_(total)_monthly.csv
Average_cost_of_fossil_fuels_for_electricity_generation_petroleum_coke_California_electric_power_(total)_monthly.csv
Average_cost_of_fossil_fuels_for_electricity_generation_petroleum_liquids_California_electric_power_(total)_monthly.csv
Import_file_names.txt
output_dataset.txt
Revenue_from_retail_sales_of_electricity_California_all_sectors_monthly.csv
Revenue_from_retail_sales_of_electricity_California_commercial_monthly.csv
Revenue_from_retail_sales_of_electricity_California_industrial_monthly.csv
Revenue_from_retail_sales_of_electricity_California_other_monthly.csv
Revenue_from_retail_sales_of_electricity_California_residential_monthly.csv
Revenue_from_retail_sales_of_electricity_California_transportation_monthly.csv
Total_consumption_coal_California_electric_power_(total)_monthly.csv
Total_consumption_natural_gas_California_electric_power_(total)_monthly.csv
Total_consumption_petroleum_coke_California_electric_power_(total)_monthly.csv
Total_consumption_petroleum_liquids_California_electric_power_(total)_monthly.csv
+2B_Procurement
2B_trade_mth_predictor.py
consumption_ng_exp.csv
demand_model.h5
+Chapter03
+3A_credit_model
3A_1_1_arffToCsv.py
3A_1_2_run_model.py
3A_1_credit_model.py
5year.arff
5year.csv
attrib.txt
corr.txt
decision_tree
decision_tree.pdf
log_reg.pkl
logreg_cols.txt
logreg_scaler.pkl
nn_clf.pkl
nn_scaler.pkl
tree_clf.pkl
tree_scaler.pkl
+3B_ALM
+.ipynb_checkpoints
Untitled2-checkpoint.ipynb
3B_2_ALM_Optimization_RLv4.py
deposit_list.csv
loan_list.csv
Untitled2.ipynb
+Chapter04
+4A_WACC
4A_WACC_Optimization_for_Corp.py
corr.csv
fields_selected.xlsx
FinancialProjection.xlsx
log.txt
log_reg.pkl
logreg_cols.txt
logreg_scaler.pkl
SampleAccountData.ods
ticker_list.csv
+4B_MarcoForecast
+weather
4B_Marco_forecast.py
industry_tickers_list.csv
industry_tickers_list_selected.csv
tmp.csv
+Chapter05
+5A_Syndication
+data
.csv
BANK OF NEW YORK MELLON CORP.csv
BLACKROCK INC.csv
BLACKROCK INSTITUTIONAL TRUST COMPANY NA.csv
FMR LLC.csv
JPMORGAN CHASE CO.csv
PRICE T ROWE ASSOCIATES INC.csv
STATE STREET CORP.csv
VANGUARD GROUP INC.csv
5A_S1_1a_instutional_holdering.py
5A_S1_1b1c1d_investor_similarity.py
5A_S1_2_stocks_similarity.py
5A_S2S3_run_similarity_models.py
industry_tickers_list.csv
industry_tickers_list_select.csv
investors.txt
investors_select.txt
+5B_MnA
5B_MnAPrediction.py
industry_tickers_list.csv
+Chapter06
+6A_BlackOptimizer
6A_1_cal_assetpara.py
6A_2_treynor_black.py
ETF_Para.db
r.txt
+6B_TrendFollowings
6B_1_trendFollowing.py
6B_2_TrainCNN.py
6B_3_flasksample.py
6B_3_RunCNN.py
+Chapter07
+7A_Sentiment
+__pycache__
+lexicon
+search
7A_1_run_download_tweets.py
7A_2_run_parse_tweets.py
7A_3_run_sentiment_analysis.py
7A_Ref_run_blackScholesMerton.py
7A_Ref_run_download_google_search.py
7A_Ref_run_parse_search.py
lib_cnt_sentiment.py
lib_parse_google_search.py
model.bin
parsed_AR.db
parsed_search.db
parsed_tweets.db
parsed_tweets.db-journal
peer.csv
peer_ticker.csv
ticker_companyname.csv
tweets.db
twitter key setup.docx
+7B_IndustryNetwork
+annualrpt
+lexicon
7B_1_run_parse_pdf.py
7B_2_run_generate_network.py
7B_ref_run_DownloadBankslist.py
lib_entitiesExtraction.py
lib_parser_pdf.py
+Chapter08
+8A_OpenBankAPI
+__pycache__
+json
8A_1_hello_obp.py
8A_2_run_store_json.py
8A_3_convert_json_sql.py
8A_4A_run_server.py
8A_4B_run_client.py
CQL_script
Mongo_script
nn_clf.pkl
nn_scaler.pkl
ofx.csv
oneTran.json
parsed_obp.db
requirements.txt
transactions.json
transactions_formatted.json
+8B_ReceiptsRecognition
8B_DocumentEntityRecognition.py
estatementfile.pdf.hocr
nn_clf.pkl
nn_scaler.pkl
OCR.txt
SH_run_pdftotif_file.txt
SH_run_tesseract_file.txt
statement.hocr
X_np.npy
Y_np.npy
+Chapter09
+9A_CampaignManagement
+dataset
.~lock.age_map.ods#
9A_CampaignMgt.py
age_map.ods
CENSUS_DATA.csv
CENSUS_DATA.ods
+9B_Chatbot
.~lock.drawings.odp#
9B_build_knowledge.py
customer.csv
edge.csv
graph.png
product.csv
Hands-On Artificial Intelligence for Banking_ A practical guide to building intelligent financial applications using machine.pdf
README.txt
Software Hardware List.pdf
Code, etc.zip
(39.23 MB, 需要: RMB 29 元)


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