Have you ever wondered how prices on the stock markets are derived and if they are based on the real economy? Do stock prices truly represent economic conditions?  Are the valuation models used by analysts to make bullish or bearish calls accurate? Are there any flaws? Can they be impacted by human behavior or other outside factors?

In this article we are going to touch on some of the processes used in pricing and creating valuations to better understand complexities that we as traders must deal with day in day out.

First let’s start by looking at the Valuation Models

Valuation models are commonly used by market participants and are the main contributor to the current market dynamics. The main reason why valuation models are important to the markets is they give an idea of expected returns which is what traders and Investors alike are trying to determine (what the actual value is now and what it will be in the future).

Many traders that we speak to believe that prices go up because there are more buyers than sellers. This is wrong. For every transaction, there should be an equal number of units of a financial security (i.e. Shares, FX and or Futures contracts etc. ) that change hands between buyers and sellers. The number of buyers and sellers doesn’t really matter.

Prices tend to go up when the buyers are more eager to buy and are happy to pay up to make the desired investment or trade. In other words, prices go higher as long as traders have positive expectations towards the market. Of course for the prices to keep on increasing, buyers’ bullish expectations must be stronger than the sellers’ bearish expectations.

Since expectations tend to influence trends by the use of valuations models; it is important to have a fair understanding about valuation mechanisms and their potential shortfalls in order to better validate or question the quality of a given trend.

Valuations models are designed to capture the current information of the underlying fundamentals and produce what’s believed to be the intrinsic (real value) of a given stock (market). In doing so, all valuation models have to make a series of assumptions, that’s where it get’s tricky.

For example, to determine the intrinsic value (real value) of stocks, the usual process is to look at the history of earnings growth for the past few years (usually up to 5 years) and then make assumptions  to extrapolate these earnings up to 5 years into the future.

So for the models to work, they have to  make  assumptions  and use perceived information (as opposed to factual information )  to arrive at a price forecast and accordingly form a view towards the market. The quality of these assumptions play a significant role in the accuracy of these models. History has shown that  assumptions tend to lose quality as analysts try to estimate further out.

Adding to this there are technical difficulties that you will have to overcome when dealing with the reported earnings (fact or fiction). In this area we have found that management have incentives to try and engineer the financial statements so that earnings look good and the company is growing. Management  have repeatedly been caught trying to hide or delay expenses, artificially inflating operating income, use off-balance sheet transactions to hide the true assets and liabilities and many more creative accounting techniques to manipulate the market expectations.

One of the more recent examples of an accounting scandal is the case of Olympus Corporation. Olympus Corporation is a Japan-based manufacturer of optics and reprography products. In 2011, it’s newly appointed CEO discovered series of accounting frauds where the prior management team had been able to secretly liquidate hundreds of millions of dollars of Olympus investments over six years and then lied to auditors by certifying that the investments still existed. This resulted in a 50% drop in the value of the company in 2011. Olympus Scandal.

Another notable accounting error/scandal includes Enron.

There are a number of research houses who look for anomalies in company reports, one well known research company is Muddy Waters:

We believe that current market conditions are somewhat distorted as we have seen central banks trying to stimulate the markets by providing record cheap capital (liquidity). Such loose monetary policies have helped many blue chip companies raise large quantities of cash at very cheap rates.This money, among other uses,can be used for share buybacks. Share buyback is a process in which a company buys  it’s own shares. Share buybacks usually result in price increase which may not necessarily be supported by the underlying fundamentals. For example, against declining earnings, IBM shares have been in part supported by a large scale buyback scheme which has been in place in the recent years.

According to figures by FactSet Research Systems the total share buybacks within the S&P 500 reached $447.6 billion in 2013 which was up by 23.6% over the 2012 levels and the highest since 2008.

If a Trader/Investor was to misunderstand the above point and mistook it for actual growth based on better economic prospects, he/she may form an unwarranted opinion about the markets and will likely get engaged in trades which may not be all they seem.

Another factor that can significantly affect market prices is our own biases. For example, ‘Herding’ bias is when traders trade in the same direction or in the same Instrument (security) even if the information available may not be supportive of the trading decision.

Herding is usually associated with the ‘Availability Bias’ which occurs when investors sacrifice quality for availability and follow  less comprehensive sources of information such as mass media.

Another phenomenon that co exists with Herding is ‘Regret Aversion’. This happens when you look back thinking you should have bought or sold a particular investment at a particular time in the past (after the fact). Regret Aversion can lead traders to buy products they wish they had purchased earlier fueling the prevailing trends. This is also known as the FOMO rally (Fear of Missing Out). However this trend may not be created because of the economic reality, but is just a by-production of human emotions.

Such biases can help explain why some stocks in the US are now trading around 1000 Price to Earning ratio in the face of no real economic value. For example Move Inc is an US listed online real estate company. The company has experienced a huge decline in earnings with extremely low margins, but yet is trading at a P/E ratio of 1062 (02 May 2014)!

Now you may be asking yourselves how can I correctly make investment/trading decisions when prices and trends can be severely affected by factors that don’t necessarily reflect the true economic reality. The simple answer is that we don’t live in an ideal world and we can only use information we have.

Unfortunately valuations will never be perfect and prices will always be impacted by human emotions and an overwhelming issue of the supply and demand matrix. The best strategy is to create multiple diverse systems across a range of markets. One thing we look to do as a professional trading firm is to react to price action accordingly.

When the numbers start to look a little unrealistic then at the very least we will look to move stops right up against the markets on our winning positions, this allows us to manage any sharp reversals when the markets move in the opposite direction.

At the same time we try to be on top of the outcome of dominant valuations and use them as tools to avoid being trapped in trades where there is no real economic value.

Remember the markets always adjust. It might take it a little bit of time but it will adjust.

Most retail traders are now automating their trading models to build a systematic and disciplined approach in achieving their goals.

Build your very own automated trading system and receive a new model or concept straight from our Trading Desk every week.

Get access to our Online Systems Building PLUS program now!