Investment Services: Institutional Clients, Trading and Research Departments

Institutional Client Division

Corporates, Insurance companies, large banks and pension funds also seek the services of investment banks. Usually a salesman handles one/few accounts. These client service professionals are the best in the team, as they are handling large high value clients. Excellent analytical, networking and communication skills are required for this profile.

Smaller but independently high net worth entities like trust funds, smaller banks and trust funds are often treated as mini-institutional clients.

Trading Department

Stock trading involves taking buy and sell orders from clients. There are two methods to execute a trade. This can be done on the trade floor or electronically.

For example, a broker on the floor takes a buy order from a client. The broker then sends the order to the floor clerk at the exchange. The floor clerk alerts one of the firm’s floor traders who finds another floor trader floor trader who knows which floor traders make markets in particular stocks.

The two agree on the price and complete the deal. The notification process goes back up the line and the broker calls the client with the final price. The process may take a few minutes or longer depending on the stock and the market. A few days later, an e-mail confirmation is sent.

Electronic trade uses technology to match buyers and sellers, rather than human brokers. Institutional traders prefer this method of trading.

Individual investor, use this method to get instant confirmations on trades. It gives the investor more control of online investing by putting   them closer to the market. The broker then accesses the electronic markets, and finds a buyer or seller depending on your order.

Research Department

This department consists of economists, equity market strategists, industry analysts, fixed income market analysts and credit analysts.

With the global nature of investment economists monitor and provide information about different world economies. They also try to forecast economic indicators such as interest rates, wage levels, unemployment levels, and growth levels and so on.

Equity market strategists take calls on the market as a whole. They analyze market sector growth levels and market performance. Industry analysts analyze specific industries and predict growth of the sector and companies within it.

Fixed Income Market Analysts asses the fixed income market (where securities like bonds-bills and preferred stock are traded) this market is characterized by low-risk and low return. These analysts help pick the best performers and provide information on the same.

Credit Analysts assess financial data of companies when it issues bonds. They assess credit quality using ratios, trend analysis as well as the creation of projections and a detailed analysis of cash flows.

Financial analysts in investment banking departments of securities or banking firms analyze the future prospects of companies that are going in for an initial public offering or IPO. They undertake compliance to regulation tasks. They also manage events to attract investors. Another key role is to work in mergers and acquisitions. They help pick prospective companies that can be acquired or undertake financial analysis in mergers. Some are buy-side analysts and some are sell-side analysts.

They also rate risk in some cases and are then called rating analysts__. Rating is often done to company or government bonds.

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 includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $29 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

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.