麝香市场价格预测数据

本数据基于供需-成本双因子建模与市场动量校准，能够为林麝和麝香产业链参与者提供动态决策支持，其核心价值在于通过量化分析供给压力、成本传导及市场趋势，形成对短期价格波动的科学预判。本数据对于林麝养殖和麝香生产基地而言，在生产计划动态调整、库存风险精细化管理和养殖成本优化决策等方面具有实际的应用价值；对于制药企业等下游采购商而言，本数据能为其优化采购策略、促进价格谈判等提供重要依据；林业部门可依据价格预测数据监测麝香市场异常波动，并为制定养殖补贴政策提供量化参考。1.数据采集：按每日采集公司与麝香产量、库存、成本、市场售价相关的数据，包括采集日期、基地编号、本日产量、近30日累计产量、本日库存量、历史库存安全阈值、每克麝香本日综合成本/（元/克）、近30日每克麝香每日综合成本均值/（元/克）、近10日麝香市场均价/（元/克）、近30日麝香市场均价/（元/克）。
2.供需-成本双因子建模：供给压力系数=0.6×(本日产量/近30日累计产量×30)+0.4×(历史库存安全阈值/本日库存量)；成本传导强度=1+(每克麝香本日综合成本/近30日每克麝香每日综合成本均值-1)×0.6。
3.市场动量校准：趋势惯性系数=近10日麝香市场均价/近30日麝香市场均价。
4.价格预测模型：下月预测价格=近30日麝香市场均价×（供给压力系数×0.7+成本传导强度×0.3）×趋势惯性系数。

This dataset is developed based on supply-demand and cost dual-factor modeling and market momentum calibration, providing dynamic decision-making support for participants in the forest musk deer and musk industry chain. Its core value lies in generating scientific forecasts of short-term price fluctuations through quantitative analysis of supply pressure, cost transmission and market trends.

This dataset has practical application value for forest musk deer breeding and musk production bases, including dynamic adjustment of production plans, refined management of inventory risks and optimized decision-making for breeding costs. For downstream purchasers such as pharmaceutical enterprises, this dataset can provide important basis for optimizing procurement strategies and facilitating price negotiations. Forestry departments can use the price forecast data to monitor abnormal fluctuations in the musk market and offer quantitative references for formulating breeding subsidy policies.

1. Data Collection
Data related to musk production, inventory, cost and market selling price of each enterprise/base are collected daily, including collection date, base number, today's production volume, 30-day cumulative production volume, today's inventory volume, historical inventory safety threshold, today's comprehensive cost per gram of musk (unit: yuan/gram), 30-day average daily comprehensive cost per gram of musk (unit: yuan/gram), 10-day average market price of musk (unit: yuan/gram), 30-day average market price of musk (unit: yuan/gram).

2. Supply-demand and Cost Dual-factor Modeling
Supply Pressure Coefficient = 0.6 × (Today's Production Volume / 30-day Cumulative Production Volume × 30) + 0.4 × (Historical Inventory Safety Threshold / Today's Inventory Volume);
Cost Transmission Intensity = 1 + (Today's Comprehensive Cost per Gram of Musk / 30-day Average Daily Comprehensive Cost per Gram of Musk - 1) × 0.6.

3. Market Momentum Calibration
Trend Inertia Coefficient = 10-day Average Market Price of Musk / 30-day Average Market Price of Musk.

4. Price Forecasting Model
Next-month Forecast Price = 30-day Average Market Price of Musk × (Supply Pressure Coefficient × 0.7 + Cost Transmission Intensity × 0.3) × Trend Inertia Coefficient.

搜集汇总

背景与挑战

背景概述

该数据集专注于麝香市场价格预测，通过每日更新的产量、库存、成本及市场均价等14个字段，基于供需-成本双因子建模与市场动量校准算法，生成短期价格预测。它为林麝养殖基地、制药企业等产业链参与者提供动态决策支持，应用于生产计划调整、库存风险管理、采购策略优化及政策制定参考。