Managing the Cash Position of a Firm

One of the most important activities in a business is to manage its day to day cash position. The goal is to ensure that the net cash position is not negative and at the same time there is not too much excess idle cash.

Ideally, a business would want its cash inflows and outflows to be equal but that is hardly the case. Since, it's difficult to match daily cash inflows and outflows, the companies have to take additional steps to match their cash position.

The companies generally want to avoid negative cash balances because the cost of borrowing funds for daily needs immediately is very expensive. Compared to this, having some additional funds invested in short-term investments is still an acceptable cost. Even while borrowing, the firms will generally borrow a little more than the immediate requirements to be safe, and invest the excess funds in short-term instruments.

The treasurer, who is responsible for managing company's cash, will depend on information from various sources and make decisions based on this information.

Based on regular patterns of how the company collects from its customers, how it pays to its vendors, and many other factors, a company can establish an effective cash flow system. This will involve identifying typical cash flows, the minimum cash requirements, buffer, cash flow forecast, monitoring the usage of capital, short-term investment options, and so on.

The cash flow management system will also be able to help the business in these aspects:

1. Cash flow forecasting

2. Managing the cash flows

3. Maintaining optimal levels of cash

4. Decisions to borrow/invest based on the needs

The short-term investment options include: Treasury bills, short-term agency securities, certificates of deposit, banker's acceptances, time deposits, repos, commercial paper, money-market mutual funds, tax-advantaged securities, etc.

Short-term borrowing options include borrowing from banks, issuing commercial paper, etc.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.