cash-flow-forecast

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

Cash Flow Forecast

现金流预测

Overview

概述

Project future cash inflows and outflows using a 3-month moving average methodology. Identifies recurring revenue and expenses, detects seasonal patterns, and produces a monthly projection table.

利用3个月移动平均法预测未来现金流入和流出。识别经常性收入和支出，检测季节性模式，并生成月度预测表格。

Wilson Tools Used

使用的Wilson工具

```
spending_summary
```
— get monthly expense totals and category breakdowns for trend analysis
```
anomaly_detect
```
— identify recurring transactions (subscriptions, regular payments, payroll) that form the predictable baseline
```
transaction_search
```
— pull historical cash position and transaction data

```
spending_summary
```
— 获取月度支出总额和分类明细，用于趋势分析
```
anomaly_detect
```
— 识别构成可预测基线的经常性交易（订阅、定期付款、薪资）
```
transaction_search
```
— 获取历史现金头寸和交易数据

Workflow

工作流程

Ask for the forecast horizon (default: 3 months) and current cash balance.
Use
```
transaction_search
```
to pull the last 6-12 months of transactions.
Use
```
spending_summary
```
for each of the past 6 months to get income and expense totals.
Use
```
anomaly_detect
```
to identify recurring transactions (subscriptions, payroll, rent, retainers).
Calculate the 3-month moving average for income and expenses:
- Moving Avg Income = (Month-1 + Month-2 + Month-3) / 3
- Moving Avg Expenses = (Month-1 + Month-2 + Month-3) / 3
Separate recurring (predictable) from variable (estimated) cash flows.
Generate the projection:

CASH FLOW FORECAST — [Start Month] to [End Month]
══════════════════════════════════════════════════════════
                      Month 1     Month 2     Month 3
──────────────────────────────────────────────────────────
Opening Balance       $XX,XXX     $XX,XXX     $XX,XXX

INFLOWS
  Recurring Revenue    $X,XXX      $X,XXX      $X,XXX
  Variable Revenue     $X,XXX      $X,XXX      $X,XXX
  Total Inflows        $X,XXX      $X,XXX      $X,XXX

OUTFLOWS
  Payroll             ($X,XXX)    ($X,XXX)    ($X,XXX)
  Rent                ($X,XXX)    ($X,XXX)    ($X,XXX)
  Subscriptions         ($XXX)      ($XXX)      ($XXX)
  Variable Expenses   ($X,XXX)    ($X,XXX)    ($X,XXX)
  Total Outflows      ($X,XXX)    ($X,XXX)    ($X,XXX)

NET CASH FLOW          $X,XXX      $X,XXX      $X,XXX
Closing Balance       $XX,XXX     $XX,XXX     $XX,XXX
══════════════════════════════════════════════════════════

Flag any month where projected closing balance drops below a safety threshold (suggest 2 months of expenses as minimum).

询问预测期限（默认：3个月）和当前现金余额。
使用
```
transaction_search
```
获取过去6-12个月的交易记录。
对过去6个月的每个月使用
```
spending_summary
```
获取收入和支出总额。
使用
```
anomaly_detect
```
识别经常性交易（订阅、薪资、租金、定金）。
计算收入和支出的3个月移动平均值：
- 移动平均收入 = （第-1月 + 第-2月 + 第-3月）/ 3
- 移动平均支出 = （第-1月 + 第-2月 + 第-3月）/ 3
将经常性（可预测）现金流与可变（估算）现金流分开。
生成预测表：

CASH FLOW FORECAST — [Start Month] to [End Month]
══════════════════════════════════════════════════════════
                      Month 1     Month 2     Month 3
──────────────────────────────────────────────────────────
Opening Balance       $XX,XXX     $XX,XXX     $XX,XXX

INFLOWS
  Recurring Revenue    $X,XXX      $X,XXX      $X,XXX
  Variable Revenue     $X,XXX      $X,XXX      $X,XXX
  Total Inflows        $X,XXX      $X,XXX      $X,XXX

OUTFLOWS
  Payroll             ($X,XXX)    ($X,XXX)    ($X,XXX)
  Rent                ($X,XXX)    ($X,XXX)    ($X,XXX)
  Subscriptions         ($XXX)      ($XXX)      ($XXX)
  Variable Expenses   ($X,XXX)    ($X,XXX)    ($X,XXX)
  Total Outflows      ($X,XXX)    ($X,XXX)    ($X,XXX)

NET CASH FLOW          $X,XXX      $X,XXX      $X,XXX
Closing Balance       $XX,XXX     $XX,XXX     $XX,XXX
══════════════════════════════════════════════════════════

标记任何预计期末余额低于安全阈值的月份（建议以2个月的支出为最低标准）。

Without Wilson

不使用Wilson的操作步骤

Export the last 12 months of transactions from your bank as CSV.
In Google Sheets, add a
```
Month
```
column:
```
=TEXT(Date,"YYYY-MM")
```
.
Create two pivot tables: one for income by month, one for expenses by month.
For the 3-month moving average, use:
```
=AVERAGE(B2:B4)
```
sliding across the monthly totals.
For recurring items, sort by description and look for entries that repeat monthly. Sum these separately.
Build the projection manually: Opening Balance + Avg Income - Avg Expenses = Closing Balance. Closing Balance of Month N = Opening Balance of Month N+1.
For a more accurate forecast, use Excel's
```
=FORECAST.ETS()
```
function on monthly totals, which handles seasonality automatically.

Google Sheets alternative:

=FORECAST(target_date, known_values, known_dates)

从银行导出过去12个月的交易记录为CSV格式。
在Google Sheets中添加
```
Month
```
列：
```
=TEXT(Date,"YYYY-MM")
```
。
创建两个数据透视表：一个按月份统计收入，一个按月份统计支出。
计算3个月移动平均值，使用公式：
```
=AVERAGE(B2:B4)
```
并在月度总额中滑动计算。
对于经常性项目，按描述排序并查找每月重复的条目，单独汇总这些条目。
手动构建预测表：期初余额 + 平均收入 - 平均支出 = 期末余额。第N个月的期末余额 = 第N+1个月的期初余额。
如需更准确的预测，对月度总额使用Excel的
```
=FORECAST.ETS()
```
函数，该函数可自动处理季节性因素。

Google Sheets替代方案：

=FORECAST(target_date, known_values, known_dates)

。

Important Notes

重要说明

The 3-month moving average smooths volatility but lags behind trend changes. If your business is growing or shrinking rapidly, weight recent months more heavily.
Forecasts are estimates. Build in a 10-20% buffer on expenses for unexpected costs.
Seasonal businesses should use 12-month data minimum to capture full cycles. A 3-month average in retail would badly miss holiday spikes.
This is cash-basis forecasting. Outstanding invoices and unpaid bills are not reflected until money moves.

3个月移动平均法可平滑波动，但会滞后于趋势变化。如果您的业务增长或萎缩迅速，请加大近期月份的权重。
预测仅为估算值。应为意外成本预留10-20%的支出缓冲。
季节性企业应至少使用12个月的数据以捕捉完整周期。零售业使用3个月平均值会严重遗漏假日高峰。
这是基于收付实现制的预测。未结清发票和未付账单在资金流动前不会被反映。