dorsal/arxiv
View SchemaPredictability of Shanghai Stock Market by Agent-based Mix-game Model
| Authors | Chengling Gou |
|---|---|
| Categories | |
| ArXiv ID | physics/0505180 |
| URL | https://arxiv.org/abs/physics/0505180 |
Abstract
This paper reports the effort of using agent-based mix-game model to predict financial time series. It introduces simple generic algorithm into the prediction methodology, and gives an example of its application to forecasting Shanghai Index. The results show that this prediction methodology is effective and agent-based mix-game model is a potential good model to predict time series of financial markets
{
"annotation_id": "7da50424-6c3e-43a9-b844-99be83908ded",
"date_created": "2026-03-02T18:00:56.879000Z",
"date_modified": "2026-03-02T18:00:56.879000Z",
"file_hash": "dda9239cb7e4d9628c934d9d5816a2059e2140fc78a9ef0264b9782720310003",
"private": false,
"record": {
"abstract": "This paper reports the effort of using agent-based mix-game model to predict\nfinancial time series. It introduces simple generic algorithm into the\nprediction methodology, and gives an example of its application to forecasting\nShanghai Index. The results show that this prediction methodology is effective\nand agent-based mix-game model is a potential good model to predict time series\nof financial markets",
"arxiv_id": "physics/0505180",
"authors": [
"Chengling Gou"
],
"categories": [
"physics.soc-ph"
],
"title": "Predictability of Shanghai Stock Market by Agent-based Mix-game Model",
"url": "https://arxiv.org/abs/physics/0505180"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "6a63b296-4471-403a-87b5-0ace29c0cd0b",
"id": "arXiv Dataset IDs",
"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
},
"user_id": 1000002
}