Forecasting

What is Forecasting?

Forecasting is a method of predicting the future through various algorithms and calculations to make appropriate business decisions or equity decisions.

Management inside a company use forecasts to make budget and expense adjustments, seeking future cash flows and calculating how much a firm can manage to expense for depreciation and amortization over a while.

Financial institutions use this method to decide whether a company's stock (or equity) is under or overvalued compared to its current price.

Doing this allows them to decide whether an investment can yield a profit in the future, given that the market will correct the underlying stock's value in a period by applying efficient market theory.

The efficient market theory says that an efficient market will correct the value of an asset to its appropriate value. Over or under-valued assets just describe the error in efficient markets creating an arbitrage.

Although history doesn't represent or replicate the future entirely, it is usually based on historical data such as a company's cash flow statements, asset historical stock prices, company net profits, etc. Creating an intrinsic or default error in the system, given that history doesn't accurately represent the future.

It also doesn't account for the beta factor of a given stock, which is a measure of how an asset's price reacts to the overall market. Hence, many financial institutions hedge their risks by entering both short and long positions of different assets, mitigating the beta value.

Forecasting Techniques

There are several ways a forecast can be created, but they can be divided mainly into qualitative and quantitative methods. 

The qualitative method describes models made manually with little to no automation. While on the other hand, the quantitative method describes models made using computing tools like machine learning, regression algorithms, data science, etc.

1. Qualitative Methods

Qualitative Methods include modeling or forecasting a company's stock or net present value via the company's quarterly or annual government filings, i.e., 8k, 10k, etc. Multiple investment firms' analysts use this modeling technique to spot an arbitrage for asset prices to yield profit from their investments.

Qualitative modeling or fundamental modeling predicts the future based on a company's history. A set of patterns is to be found in cash flows or net profits that conventionally will continue forward.

This method differs for different companies in assumptions such that the cash flows can be discounted in the sense that when adding future cash flows, the series is rather convergent than divergent to get a finite computable value.

In multiple models, a company's Net Present Value (NPV) is found wherein, when divided by total outstanding shares, they yield companies appropriate stock price with a margin of error in calculations and assumptions.

To calculate net present value, a set discount must be calculated alongside the maturity of a company after a certain period.

Note that qualitative modeling consists of fundamental research about a company and the company's management team and also has a very philosophical point of view about the product or services the company is providing and how the future might look. It has a rather long-term perspective on things.

Advantages of fundamental modeling

• The qualitative model can be used to find arbitrage in asset prices, given that default risk is accounted for. Many analysts in investment firms use fundament modeling for their respective investments to yield a profit.

Disadvantages of fundamental modeling 

• Fundamental modeling is subjective and can differ depending on the person or the analyst. Alongside that, the fundamental analysis doesn't account for a beta factor of an asset that relates the stock price to the overall market. 
• The beta factor is usually mitigated using hedging strategies. That is to hedge trades or trade in both directions negating the beta values. 

2. Quantitative Methods

Quantitative modeling is a mathematical approach to forecasting leading to more consistent results. Quantitative modeling deals with the computational analysis of charts to seek out patterns that could potentially repeat in the future.

For example, taking averages of prices throughout history or a given period of history seeking the value of a stock, wherein, if price deviated, could refer back to. Multiple complicated algorithms, such as regression algorithms, are used to find these patterns. 

Alongside that, various models from different fields of study are applied to quantitative forecastings, such as Brownian motion, entropy, etc., dealing with the disorder of stock prices and risk management. 

Advantages are:

• The quantitative approach is mathematical and systematic and provides consistent results throughout. Solving any subjective sensitivities that fundamental modeling has wherein results could differ based on the analyst.

Disadvantages are:

• Though the quantitative is a mathematical and probability-based approach, there isn't a fundamental reason for its working compared to the Qualitative approach, where the net present value of a business is calculated and divided through shares.

Quantitative Vs. Qualitative Modelling

Qualitative Modelling deals with manual forecasting based on income statements, balance sheets, cash flows, etc., and quantitative modeling deals with a mathematical approach to stock prices and forecasting. 

The main difference between these two is that while qualitative is a more fundamental approach, the time required to close a trade is often not defined, which in turn can take years to effectively turn in profits on the investments, while quantitative deals with micro-moments in the market-leading profits in short to mid-term timespans.

Quantitative modeling is mathematical and hence provides consistent results throughout, while qualitative or fundamental modeling, subjective in nature, varies according to the analysts forecasting it.

Let’s have a look at the table to better understand the differences:

Researched and Authored by Abhijeet Avhale | LinkedIn

Reviewed and Edited by Raghav Dharmarajan

Free Resources

To continue learning and advancing your career, check out these additional helpful WSO resources:

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• Break Even Point
• EBITDA