The terms “smart money” and “dumb money” are used to describe different groups of market participants. Institutional investors and market insiders are labeled “smart money”, on the other hand, small retail traders and short-term speculators are labeled “dumb money”. Dumb money tends to buy and sell at the worst possible time, and it is wise to trade against it.

What is smart and dumb money?

There are many ways to define smart and dumb money in the global financial markets. Generally speaking, smart money refers to investments made by people with expert knowledge of the market. These experts may be successful hedge fund managers, wealthy individuals, or even insiders who have access to illegal inside information. On the other hand, dumb money mainly refers to retail investors who have limited knowledge of the market. Dumb money tends to follow exhausted market trends by applying high capital leverage. In many cases, small speculators and leveraged traders are usually referred to as ‘dumb money’.

According to statistics in a two-decade period, the average retail investor performed 2.75% less than the general market (each year). The following analysis focuses on several tools that can help traders identify the movements of smart and dumb money.

• The goal is to position in line with Smart Money (hedge funds, institutional investors, market gurus, insiders) and contrarian to Dumb Money (retail traders, leveraged traders, small speculators)

(1) Monitoring the weekly COT Report (All Financial Asset Classes)

An easy and practical way to monitor the positions of smart and dumb money is through the COT report. The COT or Commitments of Traders report is a weekly analysis that depicts the total positions of different players in the US derivatives market. The report includes all major asset classes: commodities, Forex currencies, stock indices, and even cryptocurrencies.

Major changes in the positions of specific categories of participants can signal upcoming trend reversals. These are three key categories of players involved in the COT report:

(a) Asset Managers

‘Asset Managers’ include institutional investors such as mutual funds, pension funds, and insurance companies, but also portfolio managers whose clients are mainly institutional investors. A major change in the positions of ‘Asset Managers’ can be an interesting clue in the COT report.

(b) Dealers

This category is the 'sell side' of the futures market and includes participants such as major banks and stockbrokers. Dealers use the futures market to hedge their portfolio risk, therefore, their role in the market is quite complex.

(c) Leveraged Funds (Dumb Money)

‘Leveraged Funds’ include players who seek capital leverage on their behalf or on behalf of some of their speculative clients. This category is usually wrong and may be seen as the ‘Dumb Money’ of the COT report.

Tip:

You want to trade contrarian to ‘Leveraged Funds’, especially when the positions of the other two participants coincide in the opposite direction.

Links:

• More about the COT report on TradingCenter.org

• CME Group -Commitment of Traders

• CFTC.gov -COT Reports Description

(2) Smart Money Flow Index (Equities)

The ‘Smart Money Flow Index’ or SMFI aims to record the market behavior of smart and dumb money. The SMFI was developed in 1997 by R. Koch (WallStreetCourier) and it is based on the Don Hays’ ‘Smart Money Index’. In 2003, Bloomberg published the SMFI indicator on their terminals.

Calculations

The ‘Smart Money Flow Index’ focuses on Dow Jones industrial and calculates two key trading periods:

• Opening (shortly after the Dow opening)

• Closing (within the last hour of trading)

As mentioned before, the SMFI is based on the ‘Smart Money Index’. The SMFI formula is not publicly available, however, the Don Hays SMI formula is as follows:

(a) Dow Jones Industrial gain or loss (in points) after the first half hour (9:30 a.m. - 10 a.m. EST)

(b) Dow Jones Industrial gain or loss (in points) during the last hour (3:00 p.m. - 4:00 p.m. EST)

(c) SMI = yesterday’s Smart Money Index - today’s gain/loss in the first half hour + today’s gain/loss in the last hour

Utility (on DJIA)

1. Recognize and confirm strong market trends

2. Identify major support and resistance levels

3. Identify divergences between the slope of SMFI and the slope of Dow Jones Industrial (can be used as an early sign of a trend reversal)

Chart: SMI on Dow Jones Industrial (weekly)

Tip:

The ‘Smart Money Flow Index’ can prove an interesting tool when investigating the possibilities of a DJIA trend reversal. Focus on potential slope divergences in high timeframes.

□ Link (SMI on TradingView): https://www.tradingview.com/script/PQEvcezt-Smart-Money-Index-SMI/

(3) Dumb Money Confidence (Equities)

‘Dumb Money Confidence’ incorporates several indicators showing a record of cycling to extremes. These indicators calculate the activity of retail traders and other participants who tend to follow the trend. As the developer states, a more accurate description for the tool would be "trend-following money’ and not “dumb money”.

These are some conclusions when using the ‘Dumb Money Confidence’:

• When the sentiment is pessimistic and starts to recover, it is time to buy the market

• When the sentiment is too optimistic and starts to fall, it is time to sell the market

Explaining why trend-following money is labeled as dumb money

Trend followers tend to wait for several confirmations before entering the market. They are waiting to follow well-established trends. But these trends become well-established just before they become exhausted. In other words, the model assumes that "trend-following" money enters the market near the top and exits near the bottom of major market movements.

Tip:

The ‘Dumb Money Confidence’ can be a useful tool near extreme readings, especially when a highly optimistic or pessimistic reading starts to reverse.

□ Link: https://sentimentrader.com/dumb-money

(4) Monitoring the Fear/Greed Indicators (Equities and Cryptocurrencies)

The ‘Fear & Greed’ indicators are useful tools for understanding the sentiment and the expectations of retail investors, who in most cases lose money.

• There are different indicators for different financial asset classes

• It is useful to think against what retail traders expect, as most of the time, small investors open the wrong positions in the market

• In the case of a liquidity crisis, don't trade against the retail sentiment

Overbought Area (a sign of greed)

A reading near 80 signals the excessive greed of retail traders. In this case, smart money will probably sell the market, with the ultimate goal of buying back at lower prices.

Oversold Area (a sign of fear)

Conversely, a reading near 10 signals the dominance of retail fear. In this case, smart money will probably buy the market, with the ultimate goal of selling at higher prices.

Tip:

Smart money always moves against the expectations of retail traders. Therefore, ‘Fear and Greed’ is an indicator that should be taken seriously when approaching extreme values. However, in the rare case of a ‘black swan event’ or even a simple liquidity crisis, don’t trade against the ‘Fear and Greed Index’.

□ Links:

• Crypto Fear and Greed Index (Crypto Fear & Greed Index)

• CNN Stocks Fear and Greed Index

■ Dumb Money vs Smart Money (Key Indicators)

G. P. for TradingCenter.org (c)

October, 26th 2023

Jesse Livermore Trading Method

Jesse Livermore is a legendary stock-market trader who made a fortune by short-selling during the American stock market crashes of 1907 and 1929. Jesse Livermore became world-known through the book written by journalist Edwin Lefèvre “Reminiscences of a Stock Operator (1923)”.

Jesse Livermore Rules

Livermore used to say: "Whatever happens in the stock market today has happened before and will happen again”

Here are some key rules by Jesse Livermore:

1. Markets are never wrong opinions often are. Back your judgment and don't trust your opinion, until the action of the market itself confirms your opinion
2. Few people ever make money on tips, beware of inside information. If there was easy money lying around, no one would be forcing it into your pocket
3. Money is made by sitting, not trading. It takes time to make money. Don't give me timing; give me time
4. Buy right, sit tight. Big movements take time to develop. Men who can both be right and sit tight are uncommon
5. Money cannot consistently be made by trading every day or every week during the year
6. Nothing new ever occurs in the business of speculating or investing in securities and commodities
7. Never average losses
8. The human side of every person is the greatest enemy of the average investor or speculator. Wishful thinking must be banished

Read more: Jesse Livermore Method and Rules

Gann's Law of Vibration

William Delbert Gann (1878 -1955) claimed he had discovered a repeating pattern of time and price that allowed him to predict market tops and bottoms. Collective behavior creates cycles through time, and that is what Mr. Gann called the “Law of Vibration”.

Vibration’s Theory in Financial Trading

If group behavior creates a repeating pattern, by calculating where the pattern appears next, you can make precise predictions regarding where the general market is heading. However, no one has ever precisely explained how Mr. Gann's law of vibration actually works. In this article, we are going to investigate the Vibration theory and its implications in financial trading.

From Pythagoras to Gann -The Ancient Origins of the Vibration’s theory

Vibration theory’s origins go back to the fifth century BC. The school of Pythagoras (570 BC –490 BC) thoroughly examined the natural frequencies of several fundamental systems (strings, vessels, etc.) and concluded that the natural vibration of a system is a pure property. A key feature that appears independently from any excitation. According to Pythagoreanism, everything in nature is connected. The movement of one thing generates harmonic associations (vibrations) to all other things in the system. The key to revealing the truth behind these natural associations is observation and mathematics.

Later, the legendary analyst William Delbert Gann developed the “Law of Vibration” and use it to predict the broad movements of equity and commodity markets. WD Gann was a very successful trader that used mathematics and astrology to investigate key patterns and time cycles due to certain market events.

Natural associations create patterns: “The pattern is said to emerge as a result of discontinuities in the perpetual processes of expansion and contraction within the cosmos. According to Mr. Gurdjieff, the discontinuities are a function of the Law of Seven, and the forces of expansion and contraction are a function of the Law of Three.” {Tony Plummer (2013)}

Read more: A Modern Trading Approach to the Law of Vibration (W.D. Gann)

High Trading Cost and Risk as your Worst Enemies

These two factors are responsible for traders who lose money in the long-run and they will be analyzed below.

The Trading Cost and Trading Risk Becomes Greater in Short Periods of Time

The Trading Cost when trading common stocks or other non-leveraged financial assets is limited. But when comes to derivatives, the trading cost can be really significant.

An Example on EUR/USD

Measuring the Cost in terms of the Spread Charged

The cost of derivative trading includes mainly the spread between the Ask/Bid and trading commissions based on volume. In our following analysis, we will assume the trading cost includes only the spread and no trading commissions.

When trading the most popular Forex pair, EUR/USD, the trading spread is between 0.5 and 4.0 pips maximum. You may find even narrower spreads but remember that we assumed no-trading commissions.

In other words, the spread on EUR/USD is from 0.00005 to 0.0004 of the actual value of the trade.

■ The spread counts about 0.00005 to 0.0004 of the value of the Trade

To show up our case we will assume an average spread of 1.5 pip on EURUSD without commissions or other fees charged.

A trader opens a Forex / CFD account by depositing $1,000.

Now if this trader opens a position of one micro lot ($1,000), he will pay:

■ $1,000 X 0.00015 = 15 cents USD

But no derivative trader opens an account worth $1,000 to open positions worth $1,000. So if we assume a deposit of $1,000 and that an average trader uses leverage 100:1 he will open an average position of 1 standard lot ($100,000) then the trading cost in a EURUSD trade of 1 lot will be:

■ $100,000 X 0.00015 = 15 USD

It seems like a reasonable cost given the profit potential. But the thing is that this is the cost of a single trade. Usually, day-traders and especially beginners are executing tens of trades each day. Let's assume 5 EURUSD trades per day.

■ 5 trades X 15 USD = 75 USD

In just a trading week (5 days) this trader will have pay:

■ 5 days X 75 USD = 375 USD

In overall, the trading cost for a trading week will count of 37.5% of the total value of this trader’s account.

It is obvious that even in the most competitive trading asset (EURUSD) the trading cost can be disastrous when executing a lot of trades. We assume no profits and no losses. Why? Because in the short-term you are exposed to what is called the “Market Noise”. Market noise cannot be forecasted and thus cannot be traded profitable, especially as concerns non-professional traders.

Read more: Market Noise and Earthquake Comparison