UNIT B| Analytical Tools

4. Sentiment Indicators

Random Walk and Efficient Market Hypothesis

If fundamental analysis would, by itself, determine the intrinsic value of money and therefore of financial assets, then there would be no bubbles, no depressions and no financial crises. While fundamental factors do contribute to the confidence and pessimism of market participants about the economy, why does price action often diverge so much from what a rational fundamental model is forecasting? The answer is in the emotions and feelings of the market participants, in one word: sentiment.

Price action can be seen as the expression of collective psychology oscillating between optimism and pessimism. As with any oscillator, there will be peaks of both emotional extremes driving prices up and down. These extremes explain the many inconsistencies in economical reports being favorable to a certain currency and the market reacting in the opposite direction.

Market sentiment is often presented as a characteristic of crowd behavior. Humans behave under the influence of other humans and show a tendency to conform to the crowd - even if the crowd is wrong. Crowds typically think and act differently than individuals act when uninfluenced by others. In financial markets, this results in market participants not taking objective trading decisions based on rational conclusions, but rather emotional decisions based on feelings.

With subjectivity and uncertainty gaining so much importance in price action, models such as random walk hypothesis has evolved around the idea that markets are absolutely unpredictable and impossible to outperform in the long run. This is also the basic premise of its close relative, the efficient market hypothesis model, which states that markets consist of many rational participants who are constantly reacting to new information and reflecting the new information in the price. The information includes not only what is currently known about the market but also any future expectation. It is surely true that information in financial markets 150 years ago was not so rapidly digested as it is today, but does the speed of information processing and the participant's rationality make the market really efficient?

But if markets are efficient, then why do we witness deviations of exchange rates from their fundamentals? Why do market participants express more demand and finally buy after a substantial rise in price? This reality runs contrary to the conventional supply and demand equations we have learned so far, namely, that investors buy low and sell high. The market efficiency model attributes this fact to the excessive speculation in the markets, although it views speculation positively as it enhances market efficiency and liquidity, even if exacerbating volatility.

Let's have a look back to price action for a moment. If we simplify the mechanics of a common retail shop transaction we could say that in a retail environment, the seller sets the price and the purchaser measures his need for the item against the price asked and makes a decision to buy or not.
In a market transaction, it gets a bit more dynamic because both the seller and the buyer continually adjust their price expectations depending on the available information. Note that information can be anything coming from the market and/or from external sources.
A potential seller who believes that the price may be higher in the future may choose to stay out of the market hoping to get a higher rate. If enough sellers do the same, the deal price will rise to the next available supply level. Conversely, if traders think the price may fall from now on, then they may lower their own offers until they find a buyer, in effect driving the market price lower.

We can derive from the example that price movements are the combined reactions from market participants to changing information. You will often hear that “the market reacted this or that way to news”, but in reality what moved price was a mass decision, being price its representation. The common use of this market personification tends to obscure what is the most important psychological aspect in market behavior: the “market” is a conglomerate of the minds of its participants.

What produces market movement is the difference between what most of the participants expect or believe to happen and a newly arrived information that changes that general expectation or belief.
When we hear that a certain economical report is already 'priced into the market', it means that the new released economic report is at or close to the general opinion of what the result would be. This general opinion does not correspond to any rational fundamental model, because it is largely made of beliefs. It seems to dominate exchange rate moves above analytical models.

The efficient market hypothesis states that market participants have rational expectations and it also states that the participants, on average, are correct. It also sustains that all new relevant information makes the participants update their expectations appropriately. In this sense, the model accepts that investors' reactions will be random but the overall effect from all the participants reactions, that is, the “market”, will be always right.

Arguing that future prices cannot be predicted by analyzing historical prices or other historical data, it sustains that it is not possible to profit from the market in the long run. This implies that neither fundamental analysis nor technical analysis techniques are able to reliably produce profits.

But even after several decades of empirical and theoretical disputes, economists have not yet reached a consensus about whether financial markets are efficient or not. One of the reasons for this state of affairs is the fact that the efficient markets hypothesis, by itself, is not a well-defined and empirically refutable hypothesis. In order to make it operational, too many variables and auxiliary hypotheses would have to be taken into account such as investors’ goals, their level of information, their risk preferences, their capitalization levels, all of these aspects influencing their beliefs.

Behavioral Finance

Here is where a multidisciplinary ramification of economical studies emerged: behavioral finance. Behavioral finance is an area of financial research that explores the psychological factors affecting investment decisions. Behavioral economists attribute what they call "anomalies" in financial markets to psychological factors, or behavioral biases, which affect investors and limit and distort their information resulting in incorrect conclusions- even if the information is correct.

A market extreme such as a speculative bubble is an obvious anomaly: in that market participants seem to be trading on irrational exuberance, overlooking the underlying value of the assets traded. Few investors profit from such irrational bubbles because, as John Maynard Keynes commented, "Markets can remain irrational longer than you can remain solvent." A long-term trend, for instance, is also seen as an anomaly. For us though, what matters is that market trends are not a logical result of the macro-economical circumstances, but rather a collective reaction of market participants to those circumstances as reported in the news.

In order to understand market behavior and price action, behavioral researchers look at several human and social cognitive and emotional biases such as:

• overconfidence in the own abilities as trader or investor
• overreaction to newly arrived information
• a biased market view (meaning the persistence of one's trading strategy even when such strategy is failing or ignoring new information that may contradict one's trading decisions)
• loss aversion (it's empirically proved that people prefer to avoid losses than acquire gains)
• money illusion (refers to the fact that people do not think of currency in real terms but in nominal terms)
• fear of regret (which causes investors to hold losing positions too long in the hope that they will become profitable, or liquidate winners too soon to lock in profits before they turn into losses)
• marginal utility of money (where the seed capital is more valuable than additional gains)
• inability to use complex rather than linear reasoning (meaning a rational attribution of market reaction to specific causes)
• and various other predictable human errors in reasoning and information processing.

A good example of the rational attribution to specific causes is seen in the daily reporting of news. The mainstream financial media tends to explain what happened rather then what is about to happen. In any case, price action is always reported as being due to some sound and reasonable cause. If the market is up, reasons as to why it is up are selected, and if it is down, then different reasons are also found to explain it. The media tells the crowd what they want to hear, because it is made by reporters, not traders. So the obsessions of the reporters are mirroring those of the crowd.

The main limitation in behavioral finance research is the same as with the more rational models, that is, linking cause to effect. But apart from its limitations, we can use its fundamentals to treat the price action as a crowd behavior, and use it as a contrarian indicator to make money in the markets.

Contrarian Approaches with Sentiment Indicators

It is the study of crowd behavior that forms the basis of contrarian investing: selling when optimism has peaked or buying when pessimism has peaked and the market has bottomed out. Such an approach could not really exist if the efficient market hypothesis were true, since price action would constantly be determined by the logical of fundamentals. A contrarian approach can only exist because prices are mostly determined by market sentiment.

Crowd behavior is a composite of many types of biased thinking and therefore it is virtually impossible to quantify. But yet, there are some tools that fall under the category of market sentiment indicators which we will use to determine bullish sentiment and bearish market sentiment.
There are many sentiment indicators, and an almost infinite variety of ways of interpreting them. In any case they should be used with other indicators and even with the fundamental analysis as we have described it so far.

There is a general perception that a sentiment indicator is like a technical indicator based on past price data over a period of time. It is somehow displayed like a technical indicator, but with some differences. First of all it is not based on price action in the way a technical indicator is. Moreover they don't lag as technical indicators do. Sentiment indicators are most often used together with technical indicators in order to generate buy and sell signals. But perhaps the most important is their usefulness as risk control indicators assessing if markets are reaching a sentiment extreme and therefore a change of bias is possible, or if there is still room for a trend extreme to develop.

There are many attempts to accurately measure market sentiment and so there are several different kinds of sentiment indicators—only a few are presented here. One good thing about sentiment indicators is the fact that they are transparent and in many cases freely accessible. Let's look at some of these indicators which can be extremely helpful to spot market turns.

Commitment of Traders Report (COT)

The COT provides up-to-date information about the trend and the strength of the commitment traders have towards that trend by detailing the positioning of speculative and commercial traders in the various futures markets. Remember that the spot Forex is an over-the-counter market, therefore the futures market is used here as a proxy for the spot market. The Commodity Futures Trading Commission (CFTC) releases a new COT report each Friday.

The COT report contains a lot of information, but the meat of the report is the data which shows the net long or short positions for each available futures contract for commercials and non-commercial traders. There are COT reports for equity traders (stock futures), commodity traders (including oil and gold) and currency traders (currency futures).

Commercial traders represent companies and institutions that use the futures market to hedge risk in the cash or spot market. These participants have a preference to buying on weakness and selling into strength (negative-feedback or counter-trend trading). They are trading without emotion, as they are hedging risk, long-term, and only change positions when the price deviates a lot from what theiy consider fair value. The typical commercial trading pattern is to average down in a bearish market (or up, in the case of an up-trending market). There seems to be uniform agreement that the commercials (hedgers) are the group that determines the direction of prices.

These market participants have very deep pockets, in the sense that they can endure positions against market trends for a long time. The COT report gives us an idea about the trend for a particular asset class and tells us what the big money is doing.
In order to spot for market turns we shall pay attention to this category because commercials are typically most bullish at market bottoms and most bearish at market tops. They don't do this because of a contrarian approach but rather because they are hedging.

Non-commercial traders, on the other hand, are considered speculators. This category includes large institutional investors, hedge funds and other entities that are trading in the futures market for capital gains. These participants are usually trend followers, buying when prices increase and selling when prices decrease. They behave like positive feedback traders: they enter late when the trend is underway, suffer through any pullbacks, and exit late when their algorythms are convinced the trend is over causing them to lose heavily at major trend changes especially when considering they usually have highly leveraged positions. But don't misunderstand: they are not losers, they simply do poorly as a group compared with more optimized possibilities. Large speculators may be associated with superior forecasting ability, therefore you want to know if they are net long or net short and avoid trading against them.

Trends of non-commercial futures traders tend to follow the trends very well. But it's worth noticing that in the futures market all foreign currency exchange futures use the U.S. dollar as the base currency. This means that net-short open interest in the futures market for the Swiss franc (CHF) shows bullish sentiment for USD/CHF. In other words, the futures market for CHF represents futures for CHF/USD, on which long and short positions will be the exact opposite of long and short positions on USD/CHF.

Knowing what the commercial and non-commercial traders are doing through the COT report gives us some idea about the market extremes for a particular currency. Jamie Saettele, in his book “Sentiment in the Forex Market” resumes the idea by explaining:

The author dwells much deeper in the combined used of the COT data and offers the trader community an analytical tool to understand what actually affects price action and what is just temporary noise. As he says: "every market top is accompanied by a sentiment extreme, but not every sentiment extreme leads to a market top."

VIX

The VIX (Volatility Index) has a fair amount of popularity and usefulness for Forex traders as a market sentiment indicator to measure implied volatility. Remember, volatility is the magnitude of movement that a price deviates from the mean price over a specified time period. Specifically, the VIX measures the implied volatility, rather than the historical volatility, of the options bough and sold on the S&P 500 index. If we consider options as a protective measure against a corrective price move against a major trend, then we understand that the greater the implied volatility is, the greater is the fear among the trend following traders that the market is reaching an extreme (a bottom or a top).

There are some currencies which are sensitive to equity markets and that is the reason why this indicator also serves to build a Forex trading methodology.
As with other sentiment indicators, traders look at extremes in the VIX. If the VIX shows a downtrend this means that traders are buying fewer options, which in turn means they are complacent with the underlying prices. When the VIX hits an extreme bottom, then traders prepare for a reversal in the VIX which implies a higher risk trading environment coming soon.
Pairs such as the USD/JPY or EUR/JPY are sensitive to equity prices and can thus find a reliable tool in this indicator. A bottom in the VIX can be seen as a reversal from a top extreme in those pairs as traders have reached a top of confidence and optimism towards the trend.

In order to properly use sentiment indicators and specially the VIX, the trader shall first of all find out what is the current theme in the market. Secondly, if the VIX is reversing from a bottom showing increased risk aversion, the trader has to find out what markets are currently showing more optimism, in order to enter on a contrarian move.