Using Expectation Analysis On Expected Stock Returns

Investors monitor the markets within a rational expectations’ framework in which they seek to capitalize on currently available information to predict future returns. Taking into consideration valuation metrics, such as price to earnings (P/E), price to book (P/B), and price to cash flow (P/CF), but also the firm size, trading volume, and market returns, expectation analysis seeks to best estimate the future direction of stock prices under the prism of investor expectations.

Defining Expectation Analysis

Expectation analysis enables financial analysts to forecast the economy’s future direction based on current trends. Given that analysts cannot measure the accuracy of their estimates at the time they produce them, economic forecasts have to be scientific, i.e. formulated by verifiable predictions based on an explicitly stated statistical method that can be checked or reproduced. Otherwise, the validity of the forecasts is debatable, and the forecast reliability cannot serve as a basis for further scientific progress.

Considering the fluctuations in the current financial environment and the assumptions that practically produce the estimates, expectation analysis monitors the data produced in the form of information available to investors to identify changes in the financial environment or violation of the analyst’s assumptions.

Determinants of Investor Expectations

Investors shape their expectations based on certain ratios and fundamentals of the firms, which indicate their operational competence and expected profitability. One of the key determinants of investor expectations is the dividend ratio. Companies that consistently deliver a cash dividend to their shareholders are widely considered as solvent and financially strong as opposed to those that deliver a dividend once in a while. The dividend represents a firm’s operational performance in relation to certain macroeconomic variables such as the GDP growth, industrial production, and the unemployment rate.

Although macroeconomic variables have statistically significant correlations with investor expectations, they are nearly always eliminated when analysts input market-related variables. For instance, in the case of earnings growth, macroeconomic variables consistently play a role in explaining investor return expectations. When the price level and the past stock market return are both included, these variables become insignificant.

The Stages of Expectation Analysis

Expectation analysis involves four stages:

(1) In the first stage, expectation analysis forecasts the broader economic, political and demographic trends. Stage 1 includes assumptions about monetary and fiscal policy, political conditions and initiatives, trade partnerships and others.

(2) In the second stage, expectation analysis aims to identify how GDP components, such as government spending, consumption, investment, and net exports, may change over time and how they may affect certain sectors of the economy.

(3) In the third stage, expectation analysis estimates price elasticity, competitive positioning, and other micro and macro trends that are particularly relevant to the industry in which a firm operates.

(4) In the fourth stage, expectation analysis performs economic and industry analysis to the individual firm using the Porter’s 5 Forces Model. The model determines competition, the power of suppliers, the power of buyers, the threat of new entrants and the threat of substitute products in the industry that the firm operates.

The Market is not Efficient

The completion of each stage of the analysis produces relevant variables, which track the relationship between the analysts’ estimates and the expected industry performance. In the end, expectation analysis weighs the implications of new information on industry analysis and economic outlook. In this stage, analyst consensus, i.e. the combined estimates of analysts for a given company, may change, proving that analyst estimates cannot be 100% accurate since they depend on future events. At the same time, analysts’ estimates drive the market efficiency. Stocks adjust to new information provided by a company’s quarterly earnings, expansion into new markets or any other event that may cause the stock price to change. Analyst estimates drive the market further up or further down. In the case of bias, analysts review their estimates to adjust to market realities so that investors can rebuild their rational expectations for future stock market performance based on more accurate estimates, i.e. relevant to the current market state.

 

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