├── code ├── Readme.md ├── Process_data │ └── process_data.ipynb └── Query_data │ ├── cex_query.ipynb │ └── dex_query.ipynb ├── spotlight ├── Readme.md ├── figures │ ├── Readme.md │ ├── fee.png │ ├── user.png │ ├── cex_fee.png │ ├── dex_fee.png │ ├── volume.png │ ├── cex_volume.png │ ├── dex_volume.png │ ├── transaction.png │ ├── cex_volume_fee.png │ ├── dex_volume_fee.png │ ├── cex_fee_transaction.png │ └── dex_fee_transaction.png ├── 1.png ├── 2.png ├── 3.png ├── findings.png ├── mindmap.png └── decision_tree.png ├── data ├── Queried_Data │ ├── Readme.md │ ├── cex_inflow.csv │ ├── cex_outflow.csv │ ├── dex_inflow.csv │ ├── dex_outflow.csv │ ├── dex_to_cex_query.csv │ └── cex_to_dex_query.csv ├── Processed_Data │ ├── Readme.md │ ├── cex_process.csv │ └── dex_process.csv └── Readme.md ├── _config.yml ├── markdown_cheatsheet └── Readme.md ├── LICENSE ├── .github └── workflows │ └── jekyll-gh-pages.yml ├── .gitignore └── README.md /code/Readme.md: 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-------------------------------------------------------------------------------- 1 | Data Source: https://flipsidecrypto.xyz 2 | 3 | https://etherscan.io 4 | -------------------------------------------------------------------------------- /spotlight/1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SciEcon/SRS2023_cex_dex/main/spotlight/1.png -------------------------------------------------------------------------------- /spotlight/2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SciEcon/SRS2023_cex_dex/main/spotlight/2.png -------------------------------------------------------------------------------- /spotlight/3.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/SciEcon/SRS2023_cex_dex/main/spotlight/3.png 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-------------------------------------------------------------------------------- 1 | **References** 2 | - https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet#code 3 | - https://github.com/sunshineluyao/Readme-Cheatsheet 4 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2022 Luyao (Sunshine) Zhang 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /.github/workflows/jekyll-gh-pages.yml: -------------------------------------------------------------------------------- 1 | # Sample workflow for building and deploying a Jekyll site to GitHub Pages 2 | name: Deploy Jekyll with GitHub Pages dependencies preinstalled 3 | 4 | on: 5 | # Runs on pushes targeting the default branch 6 | push: 7 | branches: ["main"] 8 | 9 | # Allows you to run this workflow manually from the Actions tab 10 | workflow_dispatch: 11 | 12 | # Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages 13 | permissions: 14 | contents: read 15 | pages: write 16 | id-token: write 17 | 18 | # Allow one concurrent deployment 19 | concurrency: 20 | group: "pages" 21 | cancel-in-progress: true 22 | 23 | jobs: 24 | # Build job 25 | build: 26 | runs-on: ubuntu-latest 27 | steps: 28 | - name: Checkout 29 | uses: actions/checkout@v3 30 | - name: Setup Pages 31 | uses: actions/configure-pages@v2 32 | - name: Build with Jekyll 33 | uses: actions/jekyll-build-pages@v1 34 | with: 35 | source: ./ 36 | destination: ./_site 37 | - name: Upload artifact 38 | uses: actions/upload-pages-artifact@v1 39 | 40 | # Deployment job 41 | deploy: 42 | environment: 43 | name: github-pages 44 | url: ${{ steps.deployment.outputs.page_url }} 45 | runs-on: ubuntu-latest 46 | needs: build 47 | steps: 48 | - name: Deploy to GitHub Pages 49 | id: deployment 50 | uses: actions/deploy-pages@v1 51 | -------------------------------------------------------------------------------- /code/Process_data/process_data.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "provenance": [] 7 | }, 8 | "kernelspec": { 9 | "name": "python3", 10 | "display_name": "Python 3" 11 | }, 12 | "language_info": { 13 | "name": "python" 14 | } 15 | }, 16 | "cells": [ 17 | { 18 | "cell_type": "code", 19 | "execution_count": 1, 20 | "metadata": { 21 | "id": "01ZYq5l9A5lA" 22 | }, 23 | "outputs": [], 24 | "source": [ 25 | "# CEX\n", 26 | "import pandas as pd\n", 27 | "\n", 28 | "\n", 29 | "df1 = pd.read_csv('https://raw.githubusercontent.com/SciEcon/SRS2023_cex_dex/main/data/Queried_Data/cex_inflow.csv')\n", 30 | "df2 = pd.read_csv('https://raw.githubusercontent.com/SciEcon/SRS2023_cex_dex/main/data/Queried_Data/cex_outflow.csv')\n", 31 | "\n", 32 | "\n", 33 | "merged_df = df1.copy()\n", 34 | "merged_df['USD_VOLUMES'] += df2['USD_VOLUMES']\n", 35 | "merged_df['FEES'] += df2['FEES']\n", 36 | "merged_df['TOTAL_TRANSACTIONS'] += df2['TOTAL_TRANSACTIONS']\n", 37 | "\n", 38 | "\n", 39 | "merged_df.to_csv('cex_process.csv', index=False)" 40 | ] 41 | }, 42 | { 43 | "cell_type": "code", 44 | "source": [ 45 | "# DEX\n", 46 | "import pandas as pd\n", 47 | "\n", 48 | "\n", 49 | "df1 = pd.read_csv('https://raw.githubusercontent.com/SciEcon/SRS2023_cex_dex/main/data/Queried_Data/dex_inflow.csv')\n", 50 | "df2 = pd.read_csv('https://raw.githubusercontent.com/SciEcon/SRS2023_cex_dex/main/data/Queried_Data/dex_outflow.csv')\n", 51 | "\n", 52 | "\n", 53 | "merged_df = df1.copy()\n", 54 | "merged_df['USD_VOLUMES'] += df2['USD_VOLUMES']\n", 55 | "merged_df['FEES'] += df2['FEES']\n", 56 | "merged_df['TOTAL_TRANSACTIONS'] += df2['TOTAL_TRANSACTIONS']\n", 57 | "\n", 58 | "\n", 59 | "merged_df.to_csv('dex_process.csv', index=False)" 60 | ], 61 | "metadata": { 62 | "id": "0ngZAid8CNpz" 63 | }, 64 | "execution_count": 2, 65 | "outputs": [] 66 | } 67 | ] 68 | } -------------------------------------------------------------------------------- /data/Queried_Data/cex_inflow.csv: -------------------------------------------------------------------------------- 1 | Date,USD_VOLUMES,FEES,TOTAL_TRANSACTIONS 2 | 2022/10/11,1230659532,10605.78406,1353 3 | 2022/10/12,1152033499,6496.363214,1328 4 | 2022/10/13,3160832855,19795.42517,3620 5 | 2022/10/14,2718094160,12593.71613,2864 6 | 2022/10/15,1633592422,8346.377404,1691 7 | 2022/10/16,1206996221,11982.39131,2637 8 | 2022/10/17,2204855344,11098.16519,2080 9 | 2022/10/18,1724833720,11770.79487,1953 10 | 2022/10/19,1103223612,11376.25833,1757 11 | 2022/10/20,1028858730,10961.86891,1562 12 | 2022/10/21,1155963250,11935.05031,1598 13 | 2022/10/22,1818393051,10816.497,1715 14 | 2022/10/23,1999412988,7581.903374,1925 15 | 2022/10/24,2061188463,10509.38459,2069 16 | 2022/10/25,3234494848,23826.39532,3115 17 | 2022/10/26,3841069972,22238.73476,3834 18 | 2022/10/27,4000317872,13601.87014,2795 19 | 2022/10/28,3074269339,13418.91725,2503 20 | 2022/10/29,5064385783,24238.35076,4559 21 | 2022/10/30,4772267660,10908.18835,3472 22 | 2022/10/31,4203777230,15506.8204,2968 23 | 2022/11/1,2767178848,10577.16775,2492 24 | 2022/11/2,3883059341,13823.87187,2674 25 | 2022/11/3,2700307357,8562.08842,1508 26 | 2022/11/4,3608104182,14160.03886,2215 27 | 2022/11/5,3277646571,8058.477514,1914 28 | 2022/11/6,2686382820,7162.488256,1835 29 | 2022/11/7,2730910065,8970.951483,1732 30 | 2022/11/8,4199713506,58749.01111,3892 31 | 2022/11/9,2561978090,58269.97972,4991 32 | 2022/11/10,676562001.5,25030.30918,2709 33 | 2022/11/11,784397347.6,13074.10581,2234 34 | 2022/11/12,803364607,10322.49935,1852 35 | 2022/11/13,780603036.9,16354.70295,2027 36 | 2022/11/14,837419386.8,8413.118575,1909 37 | 2022/11/15,633502612.4,6170.083412,1151 38 | 2022/11/16,391609494.8,7145.439932,1573 39 | 2022/11/17,214976052.8,5787.888842,1458 40 | 2022/11/18,140622515.7,4036.857594,1251 41 | 2022/11/19,38215874.84,2639.610114,913 42 | 2022/11/20,105191521.8,5331.752644,1550 43 | 2022/11/21,627372868.6,6227.959002,2231 44 | 2022/11/22,1096931261,8286.333878,2117 45 | 2022/11/23,1114284714,5233.148636,1593 46 | 2022/11/24,1961552523,6180.020966,1874 47 | 2022/11/25,3202916674,7043.956752,2272 48 | 2022/11/26,3009549268,6748.111989,2460 49 | 2022/11/27,2478341030,5048.005947,1846 50 | 2022/11/28,2806237517,7414.849933,2200 51 | 2022/11/29,1733538828,6867.096877,2414 52 | 2022/11/30,3724806467,13589.02588,3337 53 | 2022/12/1,2242199800,6292.404525,1928 54 | 2022/12/2,1670078256,5830.136704,1751 55 | 2022/12/3,1914719911,5189.291744,1429 56 | 2022/12/4,913284287.9,4322.304846,1381 57 | 2022/12/5,1549076477,7766.406829,1756 58 | 2022/12/6,1222874781,5538.56474,1349 59 | 2022/12/7,1686730575,7192.973024,1648 60 | 2022/12/8,2048676824,8132.470061,1920 61 | 2022/12/9,1420074719,6346.870024,1069 62 | 2022/12/10,1555828724,4531.425504,1168 63 | 2022/12/11,1213605212,4770.016414,1194 64 | -------------------------------------------------------------------------------- /data/Queried_Data/cex_outflow.csv: -------------------------------------------------------------------------------- 1 | Date,USD_VOLUMES,FEES,TOTAL_TRANSACTIONS 2 | 2022/10/11,1229216867,10234.12545,1429 3 | 2022/10/12,1146793509,8076.461385,1135 4 | 2022/10/13,3160163786,19379.81886,3589 5 | 2022/10/14,2715596636,12356.40182,2830 6 | 2022/10/15,1631254542,13694.88992,2566 7 | 2022/10/16,1216018092,10829.22795,2677 8 | 2022/10/17,2201462967,12555.40145,2254 9 | 2022/10/18,1726684176,13002.59252,2180 10 | 2022/10/19,1100662274,12665.44682,1967 11 | 2022/10/20,1027239033,11911.90351,1552 12 | 2022/10/21,1159314979,11278.58779,1532 13 | 2022/10/22,1817817488,12229.74168,1553 14 | 2022/10/23,1998038793,6670.603913,1583 15 | 2022/10/24,2062667456,8692.528709,1787 16 | 2022/10/25,3234004017,17426.00453,2290 17 | 2022/10/26,3840749453,13655.66673,2622 18 | 2022/10/27,3997390887,16314.49008,3482 19 | 2022/10/28,3081063806,12490.05801,2500 20 | 2022/10/29,5059101430,22910.50488,3816 21 | 2022/10/30,4772840113,11258.10247,3898 22 | 2022/10/31,4205084473,15854.36372,3003 23 | 2022/11/1,2764911420,10894.54516,2326 24 | 2022/11/2,3888917945,13557.40515,2792 25 | 2022/11/3,2697360299,10417.45369,1804 26 | 2022/11/4,3604667651,13367.77369,2252 27 | 2022/11/5,3283233851,8046.333303,1951 28 | 2022/11/6,2685520681,7283.641057,1751 29 | 2022/11/7,2733268278,9297.347938,1772 30 | 2022/11/8,4203750914,63633.00982,4087 31 | 2022/11/9,2572039211,65591.84445,5798 32 | 2022/11/10,681303267.2,30312.71554,3166 33 | 2022/11/11,785516102.7,16726.17095,2557 34 | 2022/11/12,797582314.4,29013.00347,2321 35 | 2022/11/13,787034187.9,37828.4668,2422 36 | 2022/11/14,834256024.9,9969.514718,2194 37 | 2022/11/15,638650153.4,6350.471262,1349 38 | 2022/11/16,394497933.3,12432.61785,2539 39 | 2022/11/17,214516903.9,8123.245706,2020 40 | 2022/11/18,142342899.1,16375.44766,1223 41 | 2022/11/19,36933686.67,2948.894607,1006 42 | 2022/11/20,105927889.6,8487.57973,2232 43 | 2022/11/21,622683374.4,8802.537921,3085 44 | 2022/11/22,1096205930,8722.689757,2650 45 | 2022/11/23,1116115000,5591.455486,1783 46 | 2022/11/24,1959415079,7246.898923,1662 47 | 2022/11/25,3205940279,7122.523017,2435 48 | 2022/11/26,3009879455,5993.330239,2090 49 | 2022/11/27,2476393483,4951.529645,1754 50 | 2022/11/28,2808724717,9839.516307,2585 51 | 2022/11/29,1736904321,6614.208881,1985 52 | 2022/11/30,3722900031,14669.89556,3215 53 | 2022/12/1,2240892555,8139.678382,2112 54 | 2022/12/2,1670414697,6266.004458,1734 55 | 2022/12/3,1913450814,5115.810401,1578 56 | 2022/12/4,916147148.4,4891.037613,1214 57 | 2022/12/5,1547947975,9699.545325,1948 58 | 2022/12/6,1222256691,5725.620221,1471 59 | 2022/12/7,1687771719,8821.84223,2189 60 | 2022/12/8,2048717471,6844.863055,1690 61 | 2022/12/9,1417654208,5978.879672,1062 62 | 2022/12/10,1557863723,4730.062504,1263 63 | 2022/12/11,1214610893,5469.551522,1256 64 | -------------------------------------------------------------------------------- /data/Queried_Data/dex_inflow.csv: -------------------------------------------------------------------------------- 1 | Date,USD_VOLUMES,FEES,TOTAL_TRANSACTIONS 2 | 2022/10/11,847398225.2,868288.4929,96267 3 | 2022/10/12,734036707.5,604084.4583,85569 4 | 2022/10/13,2263703655,798058.4183,100318 5 | 2022/10/14,2026999110,591142.8267,88437 6 | 2022/10/15,891958012.3,515206.7024,86594 7 | 2022/10/16,862256837.4,509173.0455,93178 8 | 2022/10/17,1700578119,1107326.537,133529 9 | 2022/10/18,1418553776,980008.6659,122159 10 | 2022/10/19,973890536.7,1029311.062,115198 11 | 2022/10/20,934097670.2,1239949.864,109286 12 | 2022/10/21,879073235.7,1014985.832,100662 13 | 2022/10/22,715719902.7,549365.0304,81398 14 | 2022/10/23,1180199435,482885.8574,93946 15 | 2022/10/24,1829756076,622982.1934,89457 16 | 2022/10/25,2666171196,913471.138,100714 17 | 2022/10/26,3030558048,847429.1841,102582 18 | 2022/10/27,2391186700,704415.4262,96180 19 | 2022/10/28,2571308046,948208.2518,129823 20 | 2022/10/29,3185349537,935551.1362,140507 21 | 2022/10/30,2271204828,518966.9814,119776 22 | 2022/10/31,2452354337,1233654.282,121892 23 | 2022/11/1,2339582728,888525.565,129894 24 | 2022/11/2,3022075714,966551.181,126785 25 | 2022/11/3,1630169157,1007356.639,118044 26 | 2022/11/4,2735662696,1062895.71,122990 27 | 2022/11/5,1692547689,668786.1791,108206 28 | 2022/11/6,1409148474,652642.9137,106531 29 | 2022/11/7,2552115282,898537.5158,109677 30 | 2022/11/8,4548752013,2909174.758,139002 31 | 2022/11/9,4542292785,2496822.567,133279 32 | 2022/11/10,3749798907,1754574.018,126515 33 | 2022/11/11,2463118059,1133218.017,105328 34 | 2022/11/12,2791624551,630277.0639,86835 35 | 2022/11/13,1871006987,626964.9398,93361 36 | 2022/11/14,2472504543,763699.0448,105536 37 | 2022/11/15,1981615236,775507.8294,109428 38 | 2022/11/16,1292932585,657888.7457,107158 39 | 2022/11/17,1610477143,509735.6059,87377 40 | 2022/11/18,827562163.4,542202.9176,82286 41 | 2022/11/19,673114997.5,314221.8268,70382 42 | 2022/11/20,1212764507,426695.4611,88225 43 | 2022/11/21,1974973597,476545.1698,90478 44 | 2022/11/22,2015689618,516726.1903,85874 45 | 2022/11/23,2365197953,373854.0962,75572 46 | 2022/11/24,2433580209,339797.3907,68157 47 | 2022/11/25,2459226788,283516.3907,68201 48 | 2022/11/26,1928020691,285351.1929,69945 49 | 2022/11/27,1653149513,248463.3626,65962 50 | 2022/11/28,1933134099,411542.198,77063 51 | 2022/11/29,1688011615,343275.7781,79620 52 | 2022/11/30,2578939590,462287.4699,88157 53 | 2022/12/1,1523636023,381265.884,76458 54 | 2022/12/2,1622688227,340774.0566,69602 55 | 2022/12/3,1249819818,277635.5603,65297 56 | 2022/12/4,1043085963,263864.3912,63656 57 | 2022/12/5,1684595240,435638.1786,78496 58 | 2022/12/6,1549450773,372140.9506,73207 59 | 2022/12/7,1545481205,379285.281,70432 60 | 2022/12/8,1846665782,417585.7867,74174 61 | 2022/12/9,1340328348,548132.1456,62174 62 | 2022/12/10,862405436.3,327588.7405,60231 63 | 2022/12/11,1162871440,335947.7069,58862 64 | -------------------------------------------------------------------------------- /data/Queried_Data/dex_outflow.csv: -------------------------------------------------------------------------------- 1 | Date,USD_VOLUMES,FEES,TOTAL_TRANSACTIONS 2 | 2022/10/11,854179428.3,899104.7962,96467 3 | 2022/10/12,753219524.4,650889.8368,89402 4 | 2022/10/13,2258731502,825047.4871,99822 5 | 2022/10/14,2037980636,635730.0164,90635 6 | 2022/10/15,871682450.2,531799.1137,84312 7 | 2022/10/16,892407865.6,571139.1461,99751 8 | 2022/10/17,1686932780,1139495.338,135416 9 | 2022/10/18,1397849767,1061161.665,129569 10 | 2022/10/19,974505299.9,1087634.143,123074 11 | 2022/10/20,929280158.9,1317904.106,122478 12 | 2022/10/21,915324552.7,1127656.813,113943 13 | 2022/10/22,728283392.6,603738.2524,87749 14 | 2022/10/23,1221949842,558034.3905,105003 15 | 2022/10/24,1820376556,699707.5173,99630 16 | 2022/10/25,2724527241,1034674.693,111811 17 | 2022/10/26,3152513476,959862.211,114050 18 | 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2022/12/4,1829431436.3,9213.342459,2595 57 | 2022/12/5,3097024452.0,17465.952154,3704 58 | 2022/12/6,2445131472.0,11264.184960999999,2820 59 | 2022/12/7,3374502294.0,16014.815254000001,3837 60 | 2022/12/8,4097394295.0,14977.333116,3610 61 | 2022/12/9,2837728927.0,12325.749695999999,2131 62 | 2022/12/10,3113692447.0,9261.488008,2431 63 | 2022/12/11,2428216105.0,10239.567936,2450 64 | -------------------------------------------------------------------------------- /data/Queried_Data/dex_to_cex_query.csv: -------------------------------------------------------------------------------- 1 | Date,NUM_USERS,TOTAL_USD_VOLUMES,TOTAL_FEES,TOTAL_TRANSACTIONS 2 | 2022/10/11,148,449986401.6,7430.838899,976 3 | 2022/10/12,202,423429397.2,4472.620627,985 4 | 2022/10/13,349,1178587314,13829.15791,2830 5 | 2022/10/14,257,1184277390,8892.571753,2220 6 | 2022/10/15,225,503408676.2,6461.361843,1341 7 | 2022/10/16,229,519606723.2,10165.1138,2270 8 | 2022/10/17,265,1051765485,7707.579394,1610 9 | 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2022/10/11,139,9899131.453,6916.500439,1086 3 | 2022/10/12,154,4933868.676,5736.360538,858 4 | 2022/10/13,365,24258871.33,13435.40768,2861 5 | 2022/10/14,261,14206041.92,8409.007496,2150 6 | 2022/10/15,251,9945068.224,11798.36953,2209 7 | 2022/10/16,224,9663669.798,9174.612166,2317 8 | 2022/10/17,210,10858555.56,9285.832182,1800 9 | 2022/10/18,179,11308729.15,8416.623856,1675 10 | 2022/10/19,203,8343192.08,8493.192344,1445 11 | 2022/10/20,198,7704207.662,8815.558648,1205 12 | 2022/10/21,171,10810023.89,7908.111096,1178 13 | 2022/10/22,198,7801533.085,10184.87769,1263 14 | 2022/10/23,314,8113861.057,4540.095363,1205 15 | 2022/10/24,288,10910452.22,5475.516747,1282 16 | 2022/10/25,341,19455401.17,12135.60408,1672 17 | 2022/10/26,336,19014733.47,9180.755929,1923 18 | 2022/10/27,338,26958748.99,10605.07089,2537 19 | 2022/10/28,203,15362096.54,7746.553214,1718 20 | 2022/10/29,302,29688385.4,17982.15556,3012 21 | 2022/10/30,309,19445449.01,8413.880338,3219 22 | 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2022/12/10,326,3996423.648,2685.670588,815 63 | 2022/12/11,503,3265572.96,3375.158363,913 64 | -------------------------------------------------------------------------------- /data/Processed_Data/dex_process.csv: -------------------------------------------------------------------------------- 1 | Date,USD_VOLUMES,FEES,TOTAL_TRANSACTIONS 2 | 2022/10/11,1701577653.5,1767393.2891,192734 3 | 2022/10/12,1487256231.9,1254974.2951000002,174971 4 | 2022/10/13,4522435157.0,1623105.9054,200140 5 | 2022/10/14,4064979746.0,1226872.8431,179072 6 | 2022/10/15,1763640462.5,1047005.8160999999,170906 7 | 2022/10/16,1754664703.0,1080312.1916,192929 8 | 2022/10/17,3387510899.0,2246821.875,268945 9 | 2022/10/18,2816403543.0,2041170.3309,251728 10 | 2022/10/19,1948395836.6,2116945.205,238272 11 | 2022/10/20,1863377829.1,2557853.9699999997,231764 12 | 2022/10/21,1794397788.4,2142642.645,214605 13 | 2022/10/22,1444003295.3000002,1153103.2828000002,169147 14 | 2022/10/23,2402149277.0,1040920.2479,198949 15 | 2022/10/24,3650132632.0,1322689.7107,189087 16 | 2022/10/25,5390698437.0,1948145.831,212525 17 | 2022/10/26,6183071524.0,1807291.3950999998,216632 18 | 2022/10/27,4764488614.0,1460441.2951,197497 19 | 2022/10/28,5158923658.0,1974274.8828,257412 20 | 2022/10/29,6406260205.0,1977879.6392,282280 21 | 2022/10/30,4530826844.0,1097250.8198,238231 22 | 2022/10/31,4879497731.0,2538958.528,242399 23 | 2022/11/1,4697251216.0,1847807.4311,259125 24 | 2022/11/2,5976406480.0,2017993.0550000002,251728 25 | 2022/11/3,3272697075.0,2076065.711,234054 26 | 2022/11/4,5570615412.0,2272254.268,246199 27 | 2022/11/5,3353137566.0,1384984.2526,215247 28 | 2022/11/6,2783607370.0,1361325.87,212374 29 | 2022/11/7,5117618055.0,1863749.1579,218567 30 | 2022/11/8,8967736987.0,5889562.791999999,274321 31 | 2022/11/9,9026957011.0,5126801.427999999,263635 32 | 2022/11/10,7627373837.0,3768337.308,252066 33 | 2022/11/11,4981027918.0,2356196.836,211469 34 | 2022/11/12,5519068975.0,1279793.9788,172163 35 | 2022/11/13,3734220501.0,1315829.4908,185264 36 | 2022/11/14,4928015844.0,1601594.2065,209036 37 | 2022/11/15,3859702468.0,1593539.5917,215999 38 | 2022/11/16,2551287792.0,1380814.6538,211458 39 | 2022/11/17,3182690265.0,1052928.3935,176576 40 | 2022/11/18,1675083434.1999998,1095976.4283,167416 41 | 2022/11/19,1345277308.2,648923.9665,142476 42 | 2022/11/20,2363455022.0,881310.3859999999,177088 43 | 2022/11/21,3913498267.0,1050844.6099999999,180888 44 | 2022/11/22,4020612411.0,1110710.1230000001,173068 45 | 2022/11/23,4741751809.0,779692.6108,152944 46 | 2022/11/24,4869400823.0,729777.5501,140522 47 | 2022/11/25,4908624375.0,584879.1841,138075 48 | 2022/11/26,3854672462.0,599148.7617,141739 49 | 2022/11/27,3289017286.0,510828.148,133230 50 | 2022/11/28,3845919550.0,850837.0434999999,155763 51 | 2022/11/29,3416260938.0,736088.8558,164156 52 | 2022/11/30,5181152394.0,987476.6993,180473 53 | 2022/12/1,3038099190.0,800191.3958,155315 54 | 2022/12/2,3266337410.0,727139.1124,142621 55 | 2022/12/3,2448239943.0,557987.2472999999,132173 56 | 2022/12/4,2112327266.0,571600.1569000001,130686 57 | 2022/12/5,3335930534.0,887090.2649999999,159799 58 | 2022/12/6,3120024250.0,784209.9364,151498 59 | 2022/12/7,3048382673.0,800788.8285000001,145054 60 | 2022/12/8,3729400284.0,897599.4657000001,154356 61 | 2022/12/9,2656749572.0,1100574.6384,126697 62 | 2022/12/10,1732106383.3,671066.4873,123634 63 | 2022/12/11,2324910181.0,693203.5486999999,122364 64 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | Skip to content 2 | Search or jump to… 3 | Pull requests 4 | Issues 5 | Codespaces 6 | Marketplace 7 | Explore 8 | 9 | @sunshineluyao 10 | Rising-Stars-by-Sunshine 11 | / 12 | posters 13 | Public 14 | Code 15 | Issues 16 | Pull requests 17 | Actions 18 | Projects 19 | Wiki 20 | Security 21 | Insights 22 | Settings 23 | posters/.gitignore 24 | @sunshineluyao 25 | sunshineluyao Initial commit 26 | Latest commit 48fd45b on Nov 7 27 | History 28 | 1 contributor 29 | 129 lines (105 sloc) 1.76 KB 30 | 31 | # Byte-compiled / optimized / DLL files 32 | __pycache__/ 33 | *.py[cod] 34 | *$py.class 35 | 36 | # C extensions 37 | *.so 38 | 39 | # Distribution / packaging 40 | .Python 41 | build/ 42 | develop-eggs/ 43 | dist/ 44 | downloads/ 45 | eggs/ 46 | .eggs/ 47 | lib/ 48 | lib64/ 49 | parts/ 50 | sdist/ 51 | var/ 52 | wheels/ 53 | pip-wheel-metadata/ 54 | share/python-wheels/ 55 | *.egg-info/ 56 | .installed.cfg 57 | *.egg 58 | MANIFEST 59 | 60 | # PyInstaller 61 | # Usually these files are written by a python script from a template 62 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 63 | *.manifest 64 | *.spec 65 | 66 | # Installer logs 67 | pip-log.txt 68 | pip-delete-this-directory.txt 69 | 70 | # Unit test / coverage reports 71 | htmlcov/ 72 | .tox/ 73 | .nox/ 74 | .coverage 75 | .coverage.* 76 | .cache 77 | 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/code/Query_data/cex_query.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "id": "9b272b52-c295-4f04-916f-cbb56022e3b3", 7 | "metadata": {}, 8 | "outputs": [], 9 | "source": [ 10 | "# CEX INFLOW\n", 11 | "WITH eth_price AS (\n", 12 | " SELECT\n", 13 | " DATE_TRUNC('day', a.hour) AS day,\n", 14 | " AVG(a.price) AS price_usd\n", 15 | " FROM ethereum.core.fact_hourly_token_prices a\n", 16 | " WHERE a.symbol = 'WETH'\n", 17 | " GROUP BY 1\n", 18 | "),\n", 19 | "transfers AS (\n", 20 | " SELECT\n", 21 | " DATE_TRUNC('day', t.block_timestamp) AS date,\n", 22 | " t.origin_from_address,\n", 23 | " t.to_address,\n", 24 | " t.amount_usd,\n", 25 | " ft.tx_fee * ep.price_usd AS fee_usd\n", 26 | " FROM ethereum.core.ez_token_transfers t\n", 27 | " JOIN ethereum.core.fact_transactions ft ON t.tx_hash = ft.tx_hash\n", 28 | " JOIN ethereum.core.dim_labels l_to ON t.to_address = l_to.address\n", 29 | " JOIN eth_price ep ON DATE_TRUNC('day', t.block_timestamp) = ep.day\n", 30 | " WHERE t.symbol = 'WETH'\n", 31 | " AND t.amount_usd IS NOT NULL\n", 32 | " AND t.amount_usd > 0\n", 33 | " AND ft.status = 'SUCCESS'\n", 34 | " AND l_to.label_type = 'cex'\n", 35 | " AND t.block_timestamp >= '2022-10-11' AND t.block_timestamp <= '2022-12-12'\n", 36 | "),\n", 37 | "transfer_summary AS (\n", 38 | " SELECT\n", 39 | " date,\n", 40 | " SUM(amount_usd) AS total_usd_volumes,\n", 41 | " SUM(fee_usd) AS total_fees,\n", 42 | " COUNT(*) AS total_transactions\n", 43 | " FROM transfers\n", 44 | " GROUP BY date\n", 45 | ")\n", 46 | "SELECT\n", 47 | " date,\n", 48 | " SUM(total_usd_volumes) AS usd_volumes,\n", 49 | " SUM(total_fees) AS fees,\n", 50 | " SUM(total_transactions) AS total_transactions\n", 51 | "FROM transfer_summary\n", 52 | "GROUP BY date\n", 53 | "ORDER BY date;\n" 54 | ] 55 | }, 56 | { 57 | "cell_type": "code", 58 | "execution_count": null, 59 | "id": "35107104-f1ce-4557-98d4-a09966152e36", 60 | "metadata": {}, 61 | "outputs": [], 62 | "source": [ 63 | "# CEX OUTFLOW\n", 64 | "WITH eth_price AS (\n", 65 | " SELECT\n", 66 | " DATE_TRUNC('day', a.hour) AS day,\n", 67 | " AVG(a.price) AS price_usd\n", 68 | " FROM ethereum.core.fact_hourly_token_prices a\n", 69 | " WHERE a.symbol = 'WETH'\n", 70 | " GROUP BY 1\n", 71 | "),\n", 72 | "transfers AS (\n", 73 | " SELECT\n", 74 | " DATE_TRUNC('day', t.block_timestamp) AS date,\n", 75 | " t.origin_from_address,\n", 76 | " t.amount_usd,\n", 77 | " ft.tx_fee * ep.price_usd AS fee_usd\n", 78 | " FROM ethereum.core.ez_token_transfers t\n", 79 | " JOIN ethereum.core.fact_transactions ft ON t.tx_hash = ft.tx_hash\n", 80 | " JOIN ethereum.core.dim_labels l_from ON t.from_address = l_from.address\n", 81 | " JOIN eth_price ep ON DATE_TRUNC('day', t.block_timestamp) = ep.day\n", 82 | " WHERE t.symbol = 'WETH'\n", 83 | " AND t.amount_usd IS NOT NULL\n", 84 | " AND t.amount_usd > 0\n", 85 | " AND ft.status = 'SUCCESS'\n", 86 | " AND l_from.label_type = 'cex'\n", 87 | " AND t.block_timestamp >= '2022-10-11' AND t.block_timestamp <= '2022-12-12'\n", 88 | "),\n", 89 | "transfer_summary AS (\n", 90 | " SELECT\n", 91 | " date,\n", 92 | " origin_from_address,\n", 93 | " SUM(amount_usd) AS total_usd_volumes,\n", 94 | " SUM(fee_usd) AS total_fees,\n", 95 | " COUNT(*) AS total_transactions\n", 96 | " FROM transfers\n", 97 | " GROUP BY date, origin_from_address\n", 98 | ")\n", 99 | "SELECT\n", 100 | " date,\n", 101 | " SUM(total_usd_volumes) AS usd_volumes,\n", 102 | " SUM(total_fees) AS fees,\n", 103 | " SUM(total_transactions) AS total_transactions\n", 104 | "FROM transfer_summary\n", 105 | "GROUP BY date\n", 106 | "ORDER BY date;\n" 107 | ] 108 | } 109 | ], 110 | "metadata": { 111 | "kernelspec": { 112 | "display_name": "Python 3 (ipykernel)", 113 | "language": "python", 114 | "name": "python3" 115 | }, 116 | "language_info": { 117 | "codemirror_mode": { 118 | "name": "ipython", 119 | "version": 3 120 | }, 121 | "file_extension": ".py", 122 | "mimetype": "text/x-python", 123 | "name": "python", 124 | "nbconvert_exporter": "python", 125 | "pygments_lexer": "ipython3", 126 | "version": "3.9.7" 127 | } 128 | }, 129 | "nbformat": 4, 130 | "nbformat_minor": 5 131 | } 132 | -------------------------------------------------------------------------------- /code/Query_data/dex_query.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "id": "32b21a30-7320-4936-a852-491cb6b7c7d9", 7 | "metadata": {}, 8 | "outputs": [], 9 | "source": [ 10 | "# DEX INFLOW\n", 11 | "WITH eth_price AS (\n", 12 | " SELECT\n", 13 | " DATE_TRUNC('day', a.hour) AS day,\n", 14 | " AVG(a.price) AS price_usd\n", 15 | " FROM ethereum.core.fact_hourly_token_prices a\n", 16 | " WHERE a.symbol = 'WETH'\n", 17 | " GROUP BY 1\n", 18 | "),\n", 19 | "transfers AS (\n", 20 | " SELECT\n", 21 | " DATE_TRUNC('day', t.block_timestamp) AS date,\n", 22 | " t.origin_from_address,\n", 23 | " t.to_address,\n", 24 | " t.amount_usd,\n", 25 | " ft.tx_fee * ep.price_usd AS fee_usd\n", 26 | " FROM ethereum.core.ez_token_transfers t\n", 27 | " JOIN ethereum.core.fact_transactions ft ON t.tx_hash = ft.tx_hash\n", 28 | " JOIN ethereum.core.dim_labels l_to ON t.to_address = l_to.address\n", 29 | " JOIN eth_price ep ON DATE_TRUNC('day', t.block_timestamp) = ep.day\n", 30 | " WHERE t.symbol = 'WETH'\n", 31 | " AND t.amount_usd IS NOT NULL\n", 32 | " AND t.amount_usd > 0\n", 33 | " AND ft.status = 'SUCCESS'\n", 34 | " AND l_to.label_type = 'dex'\n", 35 | " AND t.block_timestamp >= '2022-10-11' AND t.block_timestamp <= '2022-12-12'\n", 36 | "),\n", 37 | "transfer_summary AS (\n", 38 | " SELECT\n", 39 | " date,\n", 40 | " SUM(amount_usd) AS total_usd_volumes,\n", 41 | " SUM(fee_usd) AS total_fees,\n", 42 | " COUNT(*) AS total_transactions\n", 43 | " FROM transfers\n", 44 | " GROUP BY date\n", 45 | ")\n", 46 | "SELECT\n", 47 | " date,\n", 48 | " SUM(total_usd_volumes) AS usd_volumes,\n", 49 | " SUM(total_fees) AS fees,\n", 50 | " SUM(total_transactions) AS total_transactions\n", 51 | "FROM transfer_summary\n", 52 | "GROUP BY date\n", 53 | "ORDER BY date;\n" 54 | ] 55 | }, 56 | { 57 | "cell_type": "code", 58 | "execution_count": null, 59 | "id": "4792990a-b362-4fd5-87b7-cc512fce7171", 60 | "metadata": {}, 61 | "outputs": [], 62 | "source": [ 63 | "# DEX OUTFLOW\n", 64 | "WITH eth_price AS (\n", 65 | " SELECT\n", 66 | " DATE_TRUNC('day', a.hour) AS day,\n", 67 | " AVG(a.price) AS price_usd\n", 68 | " FROM ethereum.core.fact_hourly_token_prices a\n", 69 | " WHERE a.symbol = 'WETH'\n", 70 | " GROUP BY 1\n", 71 | "),\n", 72 | "transfers AS (\n", 73 | " SELECT\n", 74 | " DATE_TRUNC('day', t.block_timestamp) AS date,\n", 75 | " t.origin_from_address,\n", 76 | " t.amount_usd,\n", 77 | " ft.tx_fee * ep.price_usd AS fee_usd\n", 78 | " FROM ethereum.core.ez_token_transfers t\n", 79 | " JOIN ethereum.core.fact_transactions ft ON t.tx_hash = ft.tx_hash\n", 80 | " JOIN ethereum.core.dim_labels l_from ON t.from_address = l_from.address\n", 81 | " JOIN eth_price ep ON DATE_TRUNC('day', t.block_timestamp) = ep.day\n", 82 | " WHERE t.symbol = 'WETH'\n", 83 | " AND t.amount_usd IS NOT NULL\n", 84 | " AND t.amount_usd > 0\n", 85 | " AND ft.status = 'SUCCESS'\n", 86 | " AND l_from.label_type = 'dex'\n", 87 | " AND t.block_timestamp >= '2022-10-11' AND t.block_timestamp <= '2022-12-12'\n", 88 | "),\n", 89 | "transfer_summary AS (\n", 90 | " SELECT\n", 91 | " date,\n", 92 | " origin_from_address,\n", 93 | " SUM(amount_usd) AS total_usd_volumes,\n", 94 | " SUM(fee_usd) AS total_fees,\n", 95 | " COUNT(*) AS total_transactions\n", 96 | " FROM transfers\n", 97 | " GROUP BY date, origin_from_address\n", 98 | ")\n", 99 | "SELECT\n", 100 | " date,\n", 101 | " SUM(total_usd_volumes) AS usd_volumes,\n", 102 | " SUM(total_fees) AS fees,\n", 103 | " SUM(total_transactions) AS total_transactions\n", 104 | "FROM transfer_summary\n", 105 | "GROUP BY date\n", 106 | "ORDER BY date;\n" 107 | ] 108 | } 109 | ], 110 | "metadata": { 111 | "kernelspec": { 112 | "display_name": "Python 3 (ipykernel)", 113 | "language": "python", 114 | "name": "python3" 115 | }, 116 | "language_info": { 117 | "codemirror_mode": { 118 | "name": "ipython", 119 | "version": 3 120 | }, 121 | "file_extension": ".py", 122 | "mimetype": "text/x-python", 123 | "name": "python", 124 | "nbconvert_exporter": "python", 125 | "pygments_lexer": "ipython3", 126 | "version": "3.9.7" 127 | } 128 | }, 129 | "nbformat": 4, 130 | "nbformat_minor": 5 131 | } 132 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Exploring Centralized and Decentralized Cryptocurrency Exchanges - Analyzing ETH Token Trading on Centralized and Decentralized Cryptocurrency Exchanges 2 | Disclaimer: This article is a final deliverable from Prof. Luyao Zhang’s project entitled “From ‘Code is Law’ to ‘Code and Law’: A Comparative Study on Blockchain Governance,” supported by the 2023 Summer Research Scholarship (SRS) program at Duke Kunshan University. SciEcon wholeheartedly supports DKU’s noble mission of advancing interdisciplinary research and fostering integrated talents. Our support is solely focused on promoting academic excellence and knowledge exchange. SciEcon does not seek any financial gains, property rights, or branding privileges from DKU. Moreover, individuals involved in this philanthropy event perform their roles independently at DKU and SciEcon. 3 | 4 | Read the article on Medium: [https://medium.com/sciecon-innovate/dynamics-of-centralized-and-decentralized-cryptocurrency-exchanges-83f777023609](https://medium.com/sciecon-innovate/dynamics-of-centralized-and-decentralized-cryptocurrency-exchanges-83f777023609) 5 | 6 | ## Project information 7 | - **Author**: Xintong Wu, Computation and Design, Class of 2025, Duke Kunshan University 8 | - **Instructor**: Prof. Luyao Zhang, Duke Kunshan University 9 | - **Acknowledgments**: My sincere appreciation to SciEcon Insights and its directors: Prof. Luyao Zhang, Xinyu Tian, Wanlin Deng, and Zesen Zhuang. Also thanks to Yutong Quan for the peer evaluation. 10 | - **Project Summary**: 11 | This project takes the ETH token as an example. It selects two months before and after the FTX collapse as the time nodes to analyze the transaction indicators such as transaction volume (in USD), transaction fees, and transactions in CEX and DEX, investigate the correlation between the indicators, explore users' preference for CEX and DEX, and provide the development direction for future cryptocurrency exchanges. First, this research analyzed the ETH token flow of CEX and DEX, considering the migration in both inflow and outflow directions, and presented the changes of each transaction indicator over time by drawing a graph. Then, it performed the correlation test and Granger causality test (Engle and C. W. J. Granger 1987) (Ante and Saggu 2023) for the data analysis of the trading indicators therein. Also, the analysis of liquid trading between CEX and DEX focused on the changes in trading indicators before and after the FTX collapse incident. Finally, it summarizes the above findings, provides a comprehensive overview of CEX and DEX transactions, and analyzes the future direction of cryptocurrency exchanges, thus proposing a possible collaborative system between centralized and decentralized finance. (Qin et al. 2021). This study helps users understand the cryptocurrency market better and supports informed decision-making by examining the trends between the CEX and DEX platforms and their distribution. 12 | 13 | ## Table of Contents 14 | - [Data](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/README.md#data) 15 | - [Code](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/README.md#code) 16 | - [Spotlight](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/README.md#spotlight) 17 | - [More about the Author](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/README.md#more-about-the-author) 18 | - [References](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/README.md#references) 19 | 20 | 21 | ## Data 22 | - Data Source: https://flipsidecrypto.xyz/ 23 | 24 | ### Meta Data Infomation 25 | 26 | | Data Files | Data Type | Data Content | 27 | | ------------- | ------------- | ------------- | 28 | | [cex_inflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/cex_inflow.csv) | Queried_Data | CEX inflow data | 29 | | [cex_outflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/cex_outflow.csv) | Queried_Data | CEX outflow data | 30 | | [dex_inflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/dex_inflow.csv) | Queried_Data | DEX inflow data | 31 | | [dex_outflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/dex_outflow.csv) | Queried_Data | DEX outflow data | 32 | | [cex_to_dex_query](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/cex_to_dex_query.csv) | Queried_Data | CEX to DEX flow data | 33 | | [dex_to_cex_query](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/dex_to_cex_query.csv) | Queried_Data | DEX to CEX flow data | 34 | | [cex_process](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Processed_Data/cex_process.csv) | Processed_Data | CEX's total transaction data | 35 | | [dex_process](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Processed_Data/dex_process.csv) | Processed_Data | DEX's total transaction data | 36 | 37 | ### Data Dictionary 38 | 39 | | File Name | Variable Name | Description | Frecuency | Unit | Type | 40 | | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | 41 | |[cex_inflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/cex_inflow.csv)| Date | date | daily | 1 day | int | 42 | | | USD_VOLUMES | transaction volumes | daily | USD | float | 43 | | | FEES | transaction fees | daily | USD | float | 44 | | | TOTAL_TRANSACTIONS | transaction | daily | 1 | int | 45 | |[cex_outflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/cex_outflow.csv)| Date | date | daily | 1 day | int | 46 | | | USD_VOLUMES | transaction volumes | daily | USD | float | 47 | | | FEES | transaction fees | daily | USD | float | 48 | | | TOTAL_TRANSACTIONS | transaction | daily | 1 | int | 49 | |[dex_inflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/dex_inflow.csv)| Date | date | daily | 1 day | int | 50 | | | USD_VOLUMES | transaction volumes | daily | USD | float | 51 | | | FEES | transaction fees | daily | USD | float | 52 | | | TOTAL_TRANSACTIONS | transaction | daily | 1 | int | 53 | |[dex_outflow](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/dex_outflow.csv)| Date | date | daily | 1 day | int | 54 | | | USD_VOLUMES | transaction volumes | daily | USD | float | 55 | | | FEES | transaction fees | daily | USD | float | 56 | | | TOTAL_TRANSACTIONS | transaction | daily | 1 | int | 57 | | [cex_to_dex_query](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/cex_to_dex_query.csv) |Date | date | daily | 1 day | int | 58 | | | NUM_USERS | the number of users | daily | 1 | int | 59 | | | TOTAL_USD_VOLUMES | total transaction volumes | daily | USD | float | 60 | | | TOTAL_FEES | total transaction fees | daily | USD | float | 61 | | | TOTAL_TRANSACTIONS | total transactions | daily | 1 | int | 62 | | [dex_to_cex_query](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Queried_Data/dex_to_cex_query.csv) |Date | date | daily | 1 day | int | 63 | | | NUM_USERS | the number of users | daily | 1 | int | 64 | | | TOTAL_USD_VOLUMES | total transaction volumes | daily | USD | float | 65 | | | TOTAL_FEES | total transaction fees | daily | USD | float | 66 | | | TOTAL_TRANSACTIONS | total transactions | daily | 1 | int | 67 | |[cex_process](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Processed_Data/cex_process.csv)| Date | date | daily | 1 day | int | 68 | | | USD_VOLUMES | transaction volumes | daily | USD | float | 69 | | | FEES | transaction fees | daily | USD | float | 70 | | | TOTAL_TRANSACTIONS | transaction | daily | 1 | int | 71 | |[dex_process](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/data/Processed_Data/dex_process.csv)| Date | date | daily | 1 day | int | 72 | | | USD_VOLUMES | transaction volumes | daily | USD | float | 73 | | | FEES | transaction fees | daily | USD | float | 74 | | | TOTAL_TRANSACTIONS | transaction | daily | 1 | int | 75 | 76 | 77 | 78 | ## Code 79 | - Query Code Source: https://flipsidecrypto.xyz/emi/uni-token-cex-dex-transactions-6nQXQJ 80 | 81 | ### Code Dictionary 82 | | File name | Type | 83 | | ------------- | ------------- | 84 | | [cex_query](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/code/Query_data/cex_query.ipynb) | Query_data | 85 | | [dex_query](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/code/Query_data/dex_query.ipynb) | Query_data| 86 | | [process_data](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/code/Process_data/process_data.ipynb) | Process_data | 87 | | [cex_analyze](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/code/Analyze_data/cex_analyze.ipynb) | Analyze_data | 88 | | [dex_analyze](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/code/Analyze_data/dex_analyze.ipynb) | Analyze_data | 89 | | [cex_dex_compare](https://github.com/SciEcon/SRS2023_cex_dex/blob/main/code/Analyze_data/cex_dex_compare.ipynb) | Analyze_data | 90 | 91 | 92 | ## Spotlight 93 | 94 | -Mind map 95 | ![image](spotlight/mindmap.png) 96 | #### Figure No.1 Mind map of the article 97 | 98 | - Decision tree 99 | ![image](spotlight/decision_tree.png) 100 | #### Figure No.2 Decision tree of the article 101 | 102 | - Finding 103 | ![image](spotlight/findings.png) 104 | #### Figure No.3 Findings of the article 105 | 106 | - Figures 107 | ![image](spotlight/1.png) 108 | #### Figure No.4 CEX Visulization 109 | 110 | ![image](spotlight/2.png) 111 | #### Figure No.5 DEX Visulization 112 | 113 | ![image](spotlight/3.png) 114 | #### Figure No.6 CEX and DEX flow 115 | 116 | 117 | ## More about the Author 118 | - **Bio** 119 | Xintong Wu is a student in the Class of 2025 at Duke Kunshan University, majoring in Computing and Design. Her interested research areas are digital design, digital market research, and metaverse. She hopes to delve into the dynamic interactions between technology and society in the future Web 3.0 era and explore the infinite possibilities that technology can bring. Through the research with Prof. Luyao Zhang, she hopes to create new digital virtual worlds that are decentered, interdisciplinary, and have infinite possibilities. 120 | 121 | 122 | 123 | ## References 124 | 125 | ### Data Source 126 | - https://flipsidecrypto.xyz/ 127 | ### Code Source 128 | - https://flipsidecrypto.xyz/emi/uni-token-cex-dex-transactions-6nQXQJ 129 | ### Literature 130 | - Ante, Lennart, and Aman Saggu. 2023. “Time-Varying Bidirectional Causal Relationships between Transaction Fees and Economic Activity of Subsystems Utilizing the Ethereum Blockchain Network.” SSRN Electronic Journal 29. https://doi.org/10.2139/ssrn.4400040. 131 | 132 | - Engle, Robert F., and C. W. J. Granger. 1987. “Co-Integration and Error Correction: Representation, Estimation, and Testing.” Econometrica 55 (2): 251–76. https://doi.org/10.2307/1913236. 133 | 134 | - Qin, Kaihua, Liyi Zhou, Yaroslav Afonin, Ludovico Lazzaretti, and Arthur Gervais. 2021. “CeFi vs. DeFi -- Comparing Centralized to Decentralized Finance.” ArXiv:2106.08157 [Cs, Q-Fin], June. https://arxiv.org/abs/2106.08157. 135 | ``` 136 | @article{ante2023time, 137 | title={Time-Varying Bidirectional Causal Relationships between Transaction Fees and Economic Activity of Subsystems Utilizing the Ethereum Blockchain Network}, 138 | author={Ante, Lennart and Saggu, Aman}, 139 | journal={Available at SSRN 4400040}, 140 | year={2023} 141 | } 142 | 143 | @article{engel1987cointegration, 144 | title={Cointegration and error correction: Representation, estimation and testing}, 145 | author={Engel, Robert F}, 146 | journal={Journal of econometrics}, 147 | volume={55}, 148 | pages={251--276}, 149 | year={1987} 150 | } 151 | 152 | @article{qin2021cefi, 153 | title={CeFi vs. DeFi--Comparing Centralized to Decentralized Finance}, 154 | author={Qin, Kaihua and Zhou, Liyi and Afonin, Yaroslav and Lazzaretti, Ludovico and Gervais, Arthur}, 155 | journal={arXiv preprint arXiv:2106.08157}, 156 | year={2021} 157 | } 158 | ``` 159 | 160 | --------------------------------------------------------------------------------