PYPL - Quick breakdown Using Mark Minervini's stage analysisThis is just a quick analysis that I did up using Mark Minervinni's stage analysis , Looks like a perfect example of a stock that achieved super performance that now is entering the final stage , which is stage 4.
If you have not read Marks books , I highly suggest picking them up , the best of the bunch in my opinion is his " How to trade like a stock market wizard " . Very valuable resource to any traders knowledge base .
One of the most important concepts from Marks book for me was the stage analysis. It's very useful and fairly easy to identify and asses if you know what you are looking for . The logic is that there are 4 stages of a stocks cycle , this is arguably true for most stocks. Even if stocks are not super-preformers, which Mark's book especially focuses on identifying, they will still often follow these 4 stages of movements.
The 4 stages are as follows :
Stage 1 is the neglect phase or "consolidation"
Stage 2 is the advancing stage or "accumulation"
Stage 3 is the Toping phase or "distribution"
Stage 4 is the declining phase or "capitulation"
The Stage 4 or Capitulation phase , which I believe PYPL is currently in , is always accompanied with massive selling volumes , this is very much because institution's have changed their view on the future of the company and decided to stop buying and supporting the share price's advancement . If you look at the monthly charts volumes, the last three months have been predominantly selling with a total volume around 580 Million , which is about half of the float . Obviously there is some brave bulls in this volume still buying but I think that there is a good possibly that around 70 % of that volume will be institution's selling .
Eventually , many stocks do recover from capitulation like this but there is often a second leg down and a longer term stage one will quite often be required to, once again, enter the advancing stage ( Stage 2) . Sometimes, this becomes year's and sometimes the stocks never do come back . I think that once we see a stage 4 setup like this , then we should wait for a stage one to form before considering a long and still a stage 2 or a breakout of a base is a much better setup .
It's important to recognize what stage a stock is currently exhibiting to increase the probability of your long setups and this is probably one to stay away from at this time , perhaps an ok day trader depending on your style but not a safe swing trade or investment at this time .
Just an opinion and the purpose of this posting is simply to share some of the basics of Mark's stage analysis .I want to mention also that Mark's stage analysis method is also very much in line with Stan Weinstein's book as well , which is titled "Secrets for profiting in bull and bear markets ". Stan's book is right up there with Mark's too, hard to pick a favorite of the two to be honest because they both are wonderful and have taught me very important lessons.
One last note , often after a large move up , stocks need some time to digest and thus will form a base , this is similar to a stage 3 much tighter . The best super-preformance stocks do not usually build more than 6 bases during its stage 2 cycle , 4-5 is more common though before stage 3 eventually sets in. Stage 3 has some similar traits to a base but is typically wider and looser price action . Also, although using stage analysis like this helps us to make assessment's of a stocks health anything can happen in the markets , as always . This is just a tiny part of what Mark's books have to offer and he has much more in depth explanation's of it too.
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Asset Classes - Part 1 and 2 - For beginnersAsset classes - Part 1 - Stocks, Bonds, Commodities and Currencies
There are several types of asset classes which group together investments with similar characteristics. However, each asset class also has its own particular features that it does not share with other asset classes. Most common asset classes are: equities, fixed income, real estate, commodities and currencies. Correlation between different asset classes within the same industry is common. However, asset classes in unrelated fields show very little correlation. Each asset class possesses a different level of liquidity; most liquid asset classes are equities, fixed-income securities, and commodities.
Sub-asset class
Asset classes can be subdivided into sub-asset classes; for example, commodities can be subdivided into lumber, metals, oil, etc. Sub-asset classes can be further subdivided into separate groups which show common characteristics while showing characteristics of the broad group at the same time. For example, metals can be subdivided into precious metals and industrial metals. Each group can be then divided even further to efficiently distinct between separate features of asset type. For example, precious metals can be divided into gold, silver and platinum.
Illustration 1.01
Illustration above shows a daily chart of continuous CFD on WTI oil. Price made a low of 33.67 USD on 2nd November 2020 and continued to rise until it reached a high of 85.39 USD on 25th October 2021.
Correlation
Some assets tend to show correlation. Such correlation can be positive or negative. Positive correlation means that two assets behave in a similar way. For example, when gold rises then mining stocks rise as well. Contrary to that, negative correlation describes such behavior in which assets move in the opposite direction to each other. For example, when USDEUR declines then WTI oil tends to rise.
Illustration 1.02
Illustration above shows the daily graph of Exxon Mobil Corporation which belongs to the oil mining and exploration sector. It made a low of 31.11 USD on 29th October 2020 and then continued to rise until 1st November 2021 when it reached a high of 66.08 USD. Positive correlation can be observed between CFD on WTI oil shown in Illustration 1.01 and Exxon Mobil Corporation stock.
Stocks
Stocks, also called equities, are normally issued by an eminent (company, state, etc.) as shares which give right of ownership to their holder. These shares are then sold by eminent (to investors) with the purpose to raise capital. Stocks are predominantly traded on stock exchanges and they can be either common stocks or preferred stocks. Common stocks entitle a shareholder to vote at shareholders´ meetings and to receive dividends being paid by a company. Preferred stocks differ from common stocks in that they usually come with limited or no voting rights at all. Though, preferred stocks have higher claims to dividends and distribution of assets by a company. This means that in case of liquidation of a company preferred stockholders have priority over common stockholders. In addition to that, preferred stocks can pay higher dividends than common stocks and because of that they are good for building passive income based on dividend payments which can be monthly or quarterly.
Bonds
Bonds are simply loans made by an eminent (borrower) which can be state, corporation, or any other legal entity. Bonds are considered fixed-income instruments because they come with interest payments being paid out to an investor. Owner of a bond is called debtholder while the issuer of a bond is called a creditor. Bonds are tradable assets and they have maturity. In addition to that, bonds come with risk of default. Because of that, higher yielding bonds usually come with higher risk of default. Bonds are great investment vehicles for building passive income, however, they generally underperform in terms of yield when compared to stocks, commodities and indices. Bond yield is negatively correlated to bond's price.
Commodities
Commodities are basic goods (such as gold, lumber, oil etc.) that are used in commerce. They are usually refined or used for production of other goods. Commodities can be traded on market exchanges where they must meet specified minimum standards like quality, weight, type, etc. Commodities are great speculative and anti-inflationary investment vehicles.
Illustration 1.03
Illustration 1.03 shows the daily chart of CFD on WTI oil. On 20th April 2020 due to the WTI oil crisis at Cushing, Oklahoma price plunged below negative 36 USD (-36 USD per barrel). Unfortunately, that is not depicted on the chart (chart depicts lowest value at 0.00 USD).
Currencies
Currency has the role of a medium of exchange for goods and services in almost all economies around the world. There are many different currencies worldwide, however, predominantly used currencies are U.S. dollar (USD), Euro (EUR), British pound (GBP), Yuan (CNY) Ruble (RUB), Yen (JPY). Relationships between currencies are highly intertwined making the currency market very complex and hard to predict. Central banks can influence currency rates through monetary policies such as interest rates and quantitative easing. Similarly, a government can impact currency rate by enacting fiscal policies. These policies can have an impact on spending, import, export, etc.; which will, in result, influence currency rate. In addition to all of that, some currencies exhibit positive or negative correlation with commodities such as gold, oil, etc.
Illustration 1.04
Illustration above shows the daily graph of EURUSD. It is observable that EURUSD made lows in March 2020 and then continued to rise towards November 2020. Only a month later in April 2020 oil bottomed out and then started to rise in tandem with EURUSD (depicted in Illustration 1.03).
Asset Classes - Part 2 - Cryptocurrencies, ETFs, CFDs
Modern technology along with financial evolution brought rise of new asset classes such as cryptocurrencies, exchange traded funds (ETFs), contracts for difference (CFDs) and options. These new financial instruments represent alternative investment to stocks, bonds, commodities and currencies. Additionally, some features within these products can help an investor to diversify portfolio, trade short and use leverage with ease of a few mouse button clicks.
Cryptocurrencies
Cryptocurrency is simply digital currency. Most cryptocurrencies are based on blockchain technology which acts as a distributed ledger that is run by a large number of computers that comprise decentralized structure. Normally, cryptocurrencies are not issued by central authorities (however, central banks around the world currently work on digital form of fiat currencies). Cryptocurrencies are encrypted by cryptographic methods which makes them very difficult to counterfeit and double-spend. These assets are considered to be more volatile when compared to stocks, bonds, commodities and fiat currencies. Another defining feature that sets cryptocurrencies apart from other assets is that they are traded non-stop (24 hours a day, including weekends). Most popular cryptocurrencies are Bitcoin (BTC), Ethereum (ETH), Cardano (ADA), Ripple (XRP), Dogecoin (DOGE).
Illustration 1.04
Picture above shows the monthly chart of BTCUSD (Bitcoin in USD). It is very easy to spot unbelievable growth of more than 862 000 % between August 2011 and November 2021.
Exchange traded fund (ETF)
Exchange traded fund is a type of security that is publicly traded on a stock market exchange and which tracks an index, stock, commodity, or other asset. Exchange traded funds can track either one asset or group of assets. This allows an ETF to be structured in such a way that it can reflect performance of a particular economic sector.
Illustration 1.05
Illustration above shows the daily graph of JETS ETF which is an airline exchange traded fund. It has exposure to airline manufacturers, airline operators, airports and terminal services.
Contract for difference (CFD)
Contract for difference is exchange traded security that is cash-settled and which does not include delivery of goods. It simply pays the difference between the opening price and closing price. CFDs copy the price of other securities and they can be traded short, and also on margin. However, usually higher fees are associated with CFDs when compared to stocks, bonds, currencies and commodities.
Illustration 1.06
Depiction above shows the monthly graph of CFD on USOIL.
DISCLAIMER: This content serves solely educational purposes.
Skill VS Luck - Becoming a Consistently Profitable TraderHi traders, here we are on another workshop. Today I'll be sharing some of the points on differentiating skill or luck trading. Majority of the traders have absolutely no clue on are they doing the right things or not? Here's a few key points:
Skill
1. Winners and Losers
- If you are a skilled trader, you're someone who understand the probable and possible in trading. There's no guarantee on any single trade whether it's a winner or loser. Remember, the short-term outcome in trading is completely random, what's more important is to come out being profitable in the long-term. Never judge your performance based on the short-term outcome, think long-term.
2. Good Risk Management
- Good traders always have effective risk management in place. Not any single trade is able cause damage on their capital, and they truly understand how to detach themselves from negative emotions.
3. Repeatable
- Good traders have a repeatable process, that allows them to tackle the market in the same way every single day.
4. Proper Planning
- Good traders rarely deviate from their initial plan, as they understand that a planned trade is a good trade regardless of the outcome. Any trade taken out of impulsive behaviour, is considered a bad trade regardless of the outcome.
5. Consistency
- Good traders have a set of routine and action plan. To achieve consistent results, you must have a consistent performance.
6. Execution
- Good traders have little to no hesitation when it comes to executing their trades. They execute their plan without second guessing or doubt.
Luck
1. No loser
- Most gurus' or lucky traders would promote themselves having 80% - 90% strike rates, which could never happen in reality. The only way you can achieve such a high win rate is to have a Profit Factor of less than 1. In fact, most of the best traders out there have a strike rate of 40-50%.
2. Excessive Risk Exposure
- Losing traders have no idea how to isolate themselves from a bad state of mind. They're constantly putting up a lot of risk on the table regardless of having no clue on what's going on in the markets. The sense of urgency is rushing them on taking unnecessary risk.
3. Unrepeatable
- Losing traders constantly take trades out of their trading plan, which is not duplicable. If you're taking trades that is unrepeatable, most likely it's a lucky trade and you shouldn't be happy about it even if it turns out to be a winning position.
4. Impulsive Behaviour
- Losing traders deviate from their initial plan due to uncontrolled emotion. They're taking trades they're not supposed to take, then regrets later on.
5. No routine
- Losing traders have no daily routine. They're always blind firing all over any 'seems' profitable position. Most of them possess of potential over-trading habits.
6. Hope & Praying
- Losing traders are constantly looking for the 'best trade' that'd give them an enormous return. Most of them have no trading plan and proper Risk Management in place, causing them to experience an emotional rollercoaster on any particular position when it gets out of hand.
"Chains of habit are too light to be felt until they are too heavy to be broken." - Warren Buffett
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Simplifying Order FlowThis chart analysis shows you the power of order flow using two main things:
OB - Order Blocks
BOS - Break of Structure
If you can determine a trend utilising impulse and correction, you can almost always ride the wave by scaling in positions using this method.
First, determine your trend and then wait for a break of structure of a low/high.
In this example, we are in a bearish market so we are anticipating a break of a low before we can draw up our order block.
Once we get a break we can mark the OB that created the break and then wait for demand at a later date for sells.
IF the price gets too far away from the OB and looks like it isn't going to return to that point, we can move on to the next BOS and OB.
Note: This does not always mean that price won't return but we can still capitalise on the short term moves.
I have left an example of what could potentially happen next, although I am doubtful because the trend looks like it is coming to an end.
Please take a moment to like and comment on this post!
Random walk vs Chaos Theory at AMC Theaters!For those who follow me for the past year, it is almost crystal clear that I do not believe in Random walk theory..!
However, It does not mean that I believe all market moves are predictable!
The stock market is a chaotic system, and follows the chaos theorem principles!
Now let's look at Chaos theory and its principles..!
What is Chaos Theory?
Chaos is the science of surprises, of the nonlinear and the unpredictable. It teaches us to expect the unexpected. While most traditional science deals with supposedly predictable phenomena like gravity, electricity, or chemical reactions, Chaos Theory deals with nonlinear things that are effectively impossible to predict or control, like turbulence, weather, the stock market, our brain states, and so on. These phenomena are often described by fractal mathematics, which captures the infinite complexity of nature. Many natural objects exhibit fractal properties, including landscapes, clouds, trees, organs, rivers, etc, and many of the systems in which we live exhibit complex, chaotic behavior. Recognizing the chaotic, fractal nature of our world can give us new insight, power, and wisdom. For example, by understanding the complex, chaotic dynamics of the atmosphere, a balloon pilot can “steer” a balloon to the desired location. By understanding that our ecosystems, our social systems, and our economic systems are interconnected, we can hope to avoid actions that may end up being detrimental to our long-term well-being.
Don't blame me!
Principles of Chaos
The Butterfly Effect: This effect grants the power to cause a hurricane in China to a butterfly flapping its wings in New Mexico. It may take a very long time, but the connection is real. If the butterfly had not flapped its wings at just the right point in space/time, the hurricane would not have happened. A more rigorous way to express this is that small changes in the initial conditions lead to drastic changes in the results. Our lives are an ongoing demonstration of this principle. Who knows what the long-term effects of teaching millions of kids about chaos and fractals will be?
Unpredictability: Because we can never know all the initial conditions of a complex system in sufficient (i.e. perfect) detail, we cannot hope to predict the ultimate fate of a complex system. Even slight errors in measuring the state of a system will be amplified dramatically, rendering any prediction useless. Since it is impossible to measure the effects of all the butterflies (etc) in the World, accurate long-range weather prediction will always remain impossible.
Order / Disorder Chaos is not simply disordered. Chaos explores the transitions between order and disorder, which often occur in surprising ways.
Mixing: Turbulence ensures that two adjacent points in a complex system will eventually end up in very different positions after some time has elapsed. Examples: Two neighboring water molecules may end up in different parts of the ocean or even in different oceans. A group of helium balloons that launch together will eventually land in drastically different places. Mixing is thorough because turbulence occurs at all scales. It is also nonlinear: fluids cannot be unmixed.
Feedback: Systems often become chaotic when there is feedback present. A good example is the behavior of the stock market. As the value of a stock rises or falls, people are inclined to buy or sell that stock. This in turn further affects the price of the stock, causing it to rise or fall chaotically.
Fractals: A fractal is a never-ending pattern. Fractals are infinitely complex patterns that are self-similar across different scales. They are created by repeating a simple process over and over in an ongoing feedback loop. Driven by recursion, fractals are images of dynamic systems – the pictures of Chaos. Geometrically, they exist in between our familiar dimensions. Fractal patterns are extremely familiar since nature is full of fractals. For instance: trees, rivers, coastlines, mountains, clouds, seashells, hurricanes, etc.
What Is the Random Walk Theory?
Random walk theory suggests that changes in stock prices have the same distribution and are independent of each other. Therefore, it assumes the past movement or trend of a stock price or market cannot be used to predict its future movement. In short, the random walk theory proclaims that stocks take a random and unpredictable path that makes all methods of predicting stock prices futile in the long run.(Investopedia)
Why it is important to know the difference between Randomness and chaotic behavior?
When the First 2 squeezes happened, I asked myself if there will be another squeeze in the future..!
By monitoring the pattern of the behavior of the Meme Stocks and Wall Street Bets, I noticed there are connections between these moves, such as:
-Most of them have relatively high short interest
Then I asked myself if there is a possible time that the squeeze phenomenon has a higher chance of happening?
I found this squeeze behavior has a higher chance of happening just a few weeks before the Quadruple witching phenomenon!!!
Dear Prof. Malkiel,
Your book A RANDOM WALK. DOWN WALL STREET is based on your observation of randomness in the markets, yet there is a transitory phase between these randomnesses that made tons of money to mathematicians like Jim Simons and Edward Thorp.
Jim Simons:
"Efficient market theory is correct in that there are no gross inefficiencies. But we look at anomalies that may be small in size and brief in time. We make our forecast. Then, shortly thereafter, we re-evaluate the situation and revise our forecast and our portfolio. We do this all day long. We're always in and out and out and in. So we're dependent on activity to make money."
Please, Check this watchlist I published on October 29th, and see how many of these 50 stocks have moved more than 10% in the past 3 days!
www.tradingview.com
just a few examples:
Best,
Moshkelgosha
Reference Articles:
fractalfoundation.org
www.investopedia.com
Term Structure Provides Fundamental CluesLast week, I wrote on processing spreads, a valuable tool that can provide clues about price direction. The price action in products that trade in the futures market like gasoline, heating oil, soybean meal, and soybean oil often tell us a lot about the path of least resistance for the crude oil and soybean futures contracts.
This week, I will turn my attention to term structure. Term structure is the price differential between one delivery period and another in the same commodity. Some traders call term structure time spreads, calendar spreads, front-to-back spreads, or switches. They are all the same, reflecting delivery or settlement premiums or discounts based only on time.
Backwardation- It’s what it sounds like
Contango- It’s not what it sounds like
A real-time supply and demand indicator
Commodities are unique- A mentor made a mint trading time spreads
Time spreads can enhance your commodity trading results- The cure for low and high commodity prices
The late Apple founder Steve Jobs once said, “My favorite things in life don’t cost any money. It’s really clear that the most precious resource we all have is time.” While Steve Jobs was referring to his mortality, time is a critical factor in commodities.
Close attention to term structure unlocks clues about fundamental supply and demand factors.
Backwardation- It’s what it sounds like
Backwardation is a condition where commodity prices for deferred delivery are lower than for nearby delivery. A backwardation suggests that supplies are tight, forcing nearby prices higher. The condition also indicates that producers will increase output in response to a market’s deficit, leading to lower future markets.
As of the end of last week, the NYMEX crude oil futures market was in backwardation.
The chart of NYMEX WTI crude oil for delivery in December 2022 minus the price for delivery in December 2021 was trading at over a $12 per barrel backwardation or discount. December 2021 futures settled at the $83.57 level on October 29, with the December 2022 futures at the $71.33 level. Robust demand, supply concerns, and other factors have driven the spread into the widest backwardation in years and NYMEX crude oil to the highest price since 2014. Higher crude oil prices tend to support a wider backwardation. Historically, the Middle East’s political volatility has caused supply concerns at higher prices as the region is home to over half the world’s petroleum reserves.
Crude oil is one example of a raw material market where the term structure reflects supply concerns. The trend towards a wider backwardation has been bullish for the energy commodity.
Contango- It’s not what it sounds like
While backwardation is a term that reflects the spread differentials, contango is another story. In the commodities lingo world, contango is backwardation’s opposite as it reflects a market where prices for deferred delivery are higher than for nearby delivery. Backwardation is a sign of supply concerns, whereas contango is present during periods of oversupply or equilibrium where supply and demand balance. The gold futures market is an example of a term structure in contango.
The daily chart highlights gold for delivery in December 2022 minus December 2021 is trading at a $10.30 contango or premium at the end of last week. The December 2021 futures were at the $1783.90 level, with the December 2022 contract at the $1794.20 level.
Central banks worldwide hold massive gold stocks as part of their foreign exchange reserves. Therefore, supply concerns tend to be low in the gold markets leading to a premium in its term structure. Moreover, gold has a long history as a means of exchange or money. Higher interest rates tend to push gold contangos higher.
Gold is one example of a commodity market in contango.
A real-time supply and demand indicator
A commodity’s term structure can be a helpful tool as it provides insight into supply and demand fundamentals. When a raw material price spikes higher because demand rises or supplies decline, the term structure tends to move into a widening backwardation. Producers respond by increasing output, creating the deferred discount.
When markets are in glut or oversupply conditions, producers often cut back on output, causing the chances for future deficits to develop. Thus, a steep contango can reflect the market’s perception that nearby oversupply will lead to eventual shortages.
Term structure is one of the puzzle pieces that comprise a market’s structure. The others are processing spreads, location and quality spreads, and substitution spreads.
Commodities are unique- A mentor made a mint trading time spreads
Commodities are essentials. Agricultural commodities feed and clothe the world and are increasingly providing alternative energy. Industrial commodities, including metals, energy, and minerals, are requirements for shelter, power, and infrastructure. Other raw materials have varying applications in daily life and even the financial system.
Shortages or gluts can have significant impacts on the global economy. The current inflationary pressures have roots in commodities, which had experienced price rises since the beginning of the worldwide pandemic when short-term lows gave way to bullish price action.
Supply chain bottlenecks and slowdowns or shutdowns at mines and processing facilities have put upward pressure on prices. Perhaps the most dramatic example came in the lumber futures market.
The quarterly lumber futures chart shows the price explosion to a record $1711.20 high in May 2021 on the back of slowdowns and shutdown at lumber mills and supply chain bottlenecks bringing wood to consumers during a period of rising demand. When lumber reached its May high, nearby January futures were far lower.
The chart shows January futures peaked at $1275 per 1,000 board feet, over $435 lower than the nearby contract at the May high.
When I worked at Phibro in the 1990s, my direct boss was Andy Hall, one of the most successful crude oil traders in history. While many market participants believe Mr. Hall churned out profits with long and short positions in the oil market, his greatest success came from what he called “structural risk positions.” He tended to buy the front months in the oil market and sell the deferred contracts when the market moved into contango. I remember the night when Saddam Hussein marched into Kuwait in 1990. The invasion caused the nearby price of crude oil to double in a matter of minutes.
Meanwhile, deferred oil prices declined, sending the spread to a massive backwardation. Mr. Hall pocketed hundreds of millions in profits on that night. His theory was that the risk of contango was limited over time, and the potential for spikes in backwardation increased the odds of success.
Time spreads can enhance your commodity trading results- The cure for low and high commodity prices
Commodity prices tend to rise to prices where producers increase output, consumers look for substitutes or limit buying, causing inventories to build. As supply rise to levels above demand, price find tops and reverse.
Conversely, prices tend to drop to levels where production becomes uneconomic. At low prices, consumers look to increase buying, and inventories decline, leading to price bottoms and upside reversals. The cure for high or low prices is those high or low prices in the world of commodities.
Meanwhile, highs or lows can be moving targets. As we learned in lumber and a host of other markets over the years, highs occur at levels that most analysts believe are illogical, irrational, and unreasonable. We learned the same holds on the downside as nearby NYMEX crude oil futures fell to a low of negative $40.32 per barrel in April 2020.
Time spreads can be real-time indicators of changes in a commodity’s supply and demand fundamentals. Understanding and monitoring term structure can only enhance the odds of success in the commodities asset class.
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Trading advice given in this communication, if any, is based on information taken from trades and statistical services and other sources that we believe are reliable. The author does not guarantee that such information is accurate or complete and it should not be relied upon as such. Trading advice reflects the author’s good faith judgment at a specific time and is subject to change without notice. There is no guarantee that the advice the author provides will result in profitable trades. There is risk of loss in all futures and options trading. Any investment involves substantial risks, including, but not limited to, pricing volatility, inadequate liquidity, and the potential complete loss of principal. This article does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein, or any security in any jurisdiction in which such an offer would be unlawful under the securities laws of such jurisdiction.
10 Rules for Every TraderI have on the wall next to my trading desk a list of 10 rules which I remind myself of every day. These are rules that I've come up with as a result of mistakes that I've made in the past. New traders often have misconceptions about what good trading looks like, or how a successful trader behaves. The barriers to getting into trading today are low, but the learning curve is still just as steep. You can save yourself considerable time and money by learning from others. I'm sharing this list mainly for new traders, but anyone can benefit. So, without further ado:
10 Rules For Every Trader
1. Price doesn't HAVE to do ANYTHING.
A common misconception among very new traders is that skilled traders are able to 'predict' the market. This is not true. This is not even possible. As a trader, your job is to deal in probabilities and risk-management.
2. Ranges are more common than breakouts.
In any given market, for every successful breakout and acceptance of new price, you will find 3-5 failed breakouts. New traders often prefer breakout trades because they happen fast, they're exciting, and there's a certain thrill to profiting off of a sudden move that you know caught a lot of other traders with their pants down. Remember that price action stays rangebound by default, until a demand imbalance pushes the auction process to a new range. Range bound trading is a boring grind, but it's also the easiest money you'll make.
3. You will be wrong at least 50% of the time. Keep your risk tight!
So, it's not necessarily true that you'll be wrong more than you are right, however as a new trader it's highly probable. This is however the mindset that I adopt when I am evaluating the risk of a potential trade. With any trade I take, I assume that I've got a greater chance of being wrong than being right. When you think about your trading this way, I guarantee that you'll tighten up your risk management game.
4. Check your ego at the door.
You're here to make money. That's all. The market is not here to offer you self-validation. The market doesn't care about your need to prove anything. Stay humble, and always keep the possibility of being wrong in the forefront of your mind.
5. Take what is offered.
This goes hand in hand with rule one and rule four. A common saying is 'follow the signals, not the cents'. I've let winners turn into losers in the past because I FELT (rule 4) like price action HAD (rule 1) to go farther before rolling over. Take what the market offers, and see the next rule.
6. There will ALWAYS be another opportunity.
FOMO (fear of missing out) is very real. It will also lead you to get cut to pieces in a leveraged market. If you missed your ideal entry, don't chase. You didn't just miss the last and only good trade in the world. Think of your risk capital like ammunition. Save it for tomorrow.
7. Winners add to winners. Losers add to losers.
What more can I say? If you're adding to a losing position with the intent to move your average entry price, you're already in trouble. Every time you think about adding to a position, I want you to hear this rule in your head. "Winners add to winners. Losers add to losers." Close that losing trade. Save your capital for the next opportunity.
8. Be greedy with your entries: fight for price.
If your trading thesis requires price to reach a certain level to validate your entry criteria, then wait for that level. Remember, don't FOMO into a trade. See rule six.
9. Be patient with your entries: Being early is the same as being wrong.
Similar to rule 8, no FOMO! Have you ever taken a trade and then been stopped out before the market makes the move you were expecting? You're trying to predict the market instead of reacting to what it is showing you. Slow down, and remember that acceptance of price is validated by both time and volume.
10. Hope is NOT a strategy!
This is the difference between trading and gambling. Good trading looks very boring. As a general rule of thumb, if it's exciting, you're probably gambling and not trading. If you don't have a solid 'if this, then that' thesis about the market you're looking to trade, then you don't have a trade to make.
These rules are meant to be guidelines for self-improvement as a trader. Write them down. Add your own personal rules. Print them out and put them where you will see them every day. Look at them before you trade and while you manage your positions. At the end of the day, evaluate how well you followed them and record your thoughts in a trading journal. I promise you that if you incorporate these rules into your trading plan, and make them a part of your thinking, you will find success as a trader.
Trade well everyone.
Bat Harmonic Pattern - Advanced AnalysisIn this series of chart patterns, we have taken a look at the more traditional ones. However, we have not yet discussed harmonic patterns.
Harmonic patterns form a part of the numerous chart patterns available for the identification of reversal points. The practice of trading using harmonic patterns is often defined as "Harmonic Trading".
We felt like it was an appropriate time to discuss the popular bat harmonic pattern, defined as "The most accurate pattern in the entire harmonic trading arsenal" by Scott M. Carney (1).
"Suspicions in thoughts are like bats among birds."
- Translated from Francis Bacon.
1. Introduction
Unlike most traditional chart patterns, these patterns do not require breakouts of the price to be traded and involve the usage of precise Fibonacci ratios (highlighted below) for the identification of harmonic patterns. This makes harmonic patterns less subjective and pretty spooky. Wow.
1.1 Fibonacci Ratios
Fibonacci ratios are key components of harmonic patterns.
Fibonacci ratios are obtained from the Fibonacci sequence, whose n th element is obtained by adding the two previous numbers of the sequence, that is:
Fib(n) = Fib(n-1) + Fib(n-2)
The sequence is as follows: 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233..., and exhibits various characteristics.
One characteristic of interest is given by the ratios between elements in the sequence. The ratio of one element in the sequence with the following one approximately equals 0.618, while the ratio of one element in the sequence with the previous one approximately equals 1.618. These two values are often defined as golden ratios, with 1.618 being denoted as "Phi" (upper-case P) and 0.618 as "phi" (lower-case p).
The ratio between elements separated by two positions returns 0.382 and 2.618 respectively, calculating the ratio using a higher separation would return the series of Fibonacci ratios. These ratios are also given by raising the golden number with specific exponents.
0.618^4 = 0.146
0.618^3 = 0.236
0.618^2 = 0.382
0.618^0.5 = 0.786
0.618^0.25 = 0.886
0.618^0 = 1
The rationale behind the usage of Fibonacci ratios with harmonic patterns (and other methodologies in general) is given by the presence of the Fibonacci Sequence in nature and certain organisms and structures, but more importantly in human behavior. If security prices reflect investor behaviors, it seems logical to find a connection with Fibonacci numbers. This is a common rationale used by technical analysts to justify the usage of Fibonacci ratios.
A few studies aimed to explain a potential connection between the Fibonacci sequence and financial markets and evidence obtained by Bhattacharya & Kumar provide further incisive research on this connection (2).
2. Harmonic Bat Patterns
The bat harmonic pattern is built from 4 segments connecting points X, A, B, C, and D, each one located at a local maxima/minima of the price. The relative distance between the segments is used to determine the validity of a bat pattern; these rules are defined as follows:
1 - Segment AB retraces within 38.2% and 50% of the XA segment (some less strict conditions only require a retracement within 38.2% and 61.8%).
2 - Segment BC retraces within 38.2% and 88.6% of the AB segment.
3 - Segment CD retraces within 161.8% and 261.8% of the segment BC.
4 - Segment AD is approximately equal to 88.6% of segment XA.
For the pattern to be valid, the vertex given by point C must be confirmed. It is also interesting to note that the bat pattern can possess an internal AB = CD pattern.
A reversal is more likely to occur within the "potential reversal zone" (PRZ). Traders can have different methods for identification however Fibonacci retracements are commonly used, with an extremity of the PRZ located at 88.6% of the internal retracement of XA and another at 161.8% of BC. Another method identifies the PRZ within 78.6% and 100% of the internal retracement of XA.
Some traders wait for additional confirmation before entering a position such as the occurrence of internal reversal patterns, oscillator divergences, or for the price to evolve outside the PRZ such that it implies that a reversal is occurring.
3. Stop Loss & Take Profits
Various techniques exist to set take profits and stop-loss levels during the formation of a bat pattern. Some traders place the stop loss at or a few ticks below X, which can lead to reduced risk but a higher risk of a premature trigger of the stop-loss. The usage of a very tight stop loss is mentioned by Scott M. Carney.
A take profit can be set at point A. Additional Fibonacci retracements might be used for partial exits.
4.Practical Examples
Bearish Bat pattern on USDJPY15, we apply Fibonacci retracements to the segment XA and use the levels 0.5, 0.382, 0.236 as partial take profits while level 0 exits the entirety of a position.
Bullish Bat pattern under completion on ERGOUSDT 4h, the price breaks the level situated at point B is a good sign for a potential of reach of the PRZ.
5. Observations
Oscillator divergences occurring when the price is within the PRZ can be an additional confirmation of a potential reversal occurring.
We found no studies proving data that the bat harmonic pattern is superior to other harmonic patterns.
One study by Krzysztof Bednarz highlights the profitability of the bat pattern in a trading period of 27 days (3).
Bulkowski shares statistics on how often price turns at point D (4). For Bullish Bats, the price reverses at point D 91% of the time, for Bearish Bat patterns the price reverses at point D 86% of the time. Super spooky...
References
(1) Carney, S. M. (2010). Harmonic Trading, Volume Two: Advanced Strategies for Profiting from the Natural Order of the Financial Markets. Pearson Education.
(2) Bhattacharya, S., & Kumar, K. (2006). A computational exploration of the efficacy of Fibonacci Sequences in technical analysis and trading. Annals of Economics and Finance, 7(1), 185.
(3) Bednarz, K. (2013). Taking investment decisions on the futures contracts market with the application of Bat harmonic pattern – the increased efficiency of investment.
(4) Bulkowski, T. N. (2021). Encyclopedia of chart patterns. John Wiley & Sons.
Market Structure Simplified It is easy to get confused with overflowing information about market structure in the trading world.
To simplify things we have come up with a way of analysing market structure simply by marking each high or low.
In this particular example, you can see that higher lows were being created all the way down the bearish trend, so we knew that it was a seller's market UNTIL we got our break of structure .
When the BOS became apparent, we began to shift our attention to the possibility of reversals and used our magic tool, the Fibonacci.
This technique can be used in any trend, try it for yourselves!
Please, support this post with a like and comment!
How To Create High Quality Trade IdeasThis week, we will be taking a look at the ingredients that go into creating and posting high quality trade ideas.
While many think that a good trade idea begins and ends with finding a high probability chart setup in a liquid, volatile asset, the *best* trade ideas often combine multiple disciplines - which could include macroeconomic analysis, fundamental analysis , and technical analysis , or some combination therein - into one cohesive unit. Getting in the habit of incorporating all of these factors into your thought process can lead to much higher quality setups, whether or not you choose to share them with the community.
Let’s jump in!
There are a couple questions that you should ask yourself when trying to come up with high quality ideas, and they boil down to the familiar five:
Who, What, Where, When, and Why.
Let's start with Who.
Who --
Who is this trade idea meant for? When posting a trade idea, don’t assume that the idea is one-size fits all. The most obvious way TradingView helps in this regard is by categorizing posts by asset class, so FX traders are looking mostly at FX ideas, and crypto investors aren’t constantly exposed to commodity futures spreads. However, there are more subtle ways this happens as well. Different traders and investors often have different styles of trading, and so even within a single asset class, a long term investment idea may not be applicable to a short term trader. When creating a trade idea, it may make sense to identify to readers (and yourself) who this idea is for, and within what strategy it might best fit.
What --
Most ideas do a great job at answering this question! It’s very simple: at its most core, what does this idea want to do? Whether that idea boils down to shorting the stock market or building a long/short cryptocurrency spread, make sure that your idea clearly identifies what the core thrust of the trade is.
Why --
This is the crux of any good trade idea. Why should someone commit capital and risk money according to your vision? It is common for traders, especially new traders, to think that answering this question comes down to building up a confluence of price patterns, indicators, and chart drawings until they line up and it is all systems go. In some cases, this serves as a reasonable answer to the “why” question - especially when assets have strong momentum.
However, oftentimes this approach may not go deep enough. What if the long technical setup on your chart is in a stock where the company’s business outlook is worsening? What if the descending triangle you’re looking at trading occurs within a larger bull market? This is where incorporating multiple disciplines, whether it’s fundamental analysis or macroeconomic understanding, can improve the quality of your trade ideas. Understanding some of the context surrounding the asset you’re trading can serve to layer probability in your favor.
Here’s the bottom line: the current price in any market is a reflection of the consensus view of the future. It’s important to illustrate *why* that pricing might be materially incorrect.
Where / When --
It’s important to illustrate why *right now* is the right time to act on the idea, and this is where technicals can come in very handy. Broadly speaking, fundamental data on most assets only comes out once every couple weeks, if that. It’s even longer between fundamental data releases for stocks. Because of this, utilizing price patterns, indicators, candlestick charting and other technical analysis can be extremely helpful in defining risk, pinpointing entries, and trading more efficiently overall.
This is also where clean charting comes in. It’s important to identify how trader positioning, supply and demand zones, and other factors (that technicals help illustrate) affect the timing and risk of the idea. In addition, when publishing an idea on TradingView, the chart is one of the most visible and prevalent ways of communicating this information. Making these items clearly defined can significantly improve the quality of a trading idea and ensure clear communication of the important information.
So there you have it - the key questions that are at the core of any good trading idea! We look forward to seeing how this framework is incorporated into future posts.
If you think you have what it takes to create a high quality trade idea, then post it below!
Additionally, if you’d like to submit your trade ideas for consideration by the editorial team for the Editor’s Picks section, simply post them in this chat: www.tradingview.com
Cheers!
-Team TradingView
PRICE ACTION TRADING | RISING WEDGE PATTERN 🔰
Hey traders,
Rising wedge pattern is one of the most accurate price action patterns.
Being relatively simple to recognize, it is applied in various trading strategies.
⭐️The pattern itself signifies the exhaustion of bulls.
Even though the asset keeps growing in value, the price action legs contract forming a narrowing channel.
Being stuck between two contracting trend lines, one serving as support and one serving as resistance, the price forms a wedge pattern.
🔔The trigger that we are looking for to sell the market is a bearish breakout of the support of the wedge (candle close below).
To not be caught by a false breakout, it is highly recommendable to wait for a bearish violation of the last higher low level as well.
Only then the wedge breakout is confirmed.
⚡️Trading the market aggressively, one opens a short position on spot just after the candle closes.
⚡️The conservative trader will wait for a retest of the broken support of the wedge though for a safer entry.
✔️Safest stop will lie strictly above the highest wick within the wedge.
✔️Initial target will be based on the closest key structure support.
Learn to recognize this pattern and be disciplined to wait for its confirmed breakout. Only then a high trading performance will be achieved.
What price action pattern do you want to learn in the next post?
❤️Please, support this idea with like and comment!❤️
Narrowing Wedges - Advanced AnalysisIn the last post in this series on chart patterns, we described the characteristics, rules, and causes of broadening wedges patterns (if you haven't seen it, see the related ideas below).
In this post, we shall perform an advanced analysis of a related pattern, narrowing wedges. We provide a description of each pattern and its implications.
That's the way it ends. The thin edge of the wedge.
- Bulkowski (1)
1. Narrowing Wedges
Narrowing Wedge patterns are reversal patterns that are characterized by price variations laying within one support and resistance and both having the same direction and narrowing over time. In a narrowing wedge, the apex is located at the end of the formation.
1.1 Rising Wedge
Rising wedges mostly occur during uptrends, with raising local maxima (higher highs) forming an upward sloping resistance and raising local minimas (higher lows) forming an upward slopping support. The slope of both the support and resistance should be significantly different from 0.
Bulkowski suggests the price should test the support and resistance 5 times.
Volume tends to decrease during the formation of such patterns.
Ascending wedges are bearish-biased, with breakouts mostly occurring downward. Downward breakouts are often followed by a decrease in price.
Example of rising wedge on Visa daily followed by a downward breakout.
1.2 Falling Wedges
Falling wedges mostly occur during downtrends, with declining local maxima (lower highs) forming a downward sloping resistance and declining local minima (lower lows) forming a downward slopping support. The slope of both the support and resistance should be significantly different from 0.
Like with rising wedges, Bulkowski suggests the price should test the support and resistance 5 times.
Volume tends to decrease during the formation of such pattern.
Descending wedges are bullish biased with breakouts mostly occurring upward. Upward breakouts are often followed by an increase in price.
Example of falling wedge on Trivago daily.
2. Measure Rule
The measure rule allows for the determination of where to set a take-profit/stop-loss after a breakout in a narrowing wedge formation. Rules differ from an upward to downward breakout of the formation.
When price breaks the support of a rising wedge, the take-profit is determined from the lowest low inside the formation. When the price breaks the resistance, the take-profit is determined by adding the height of the formation to the breakout point.
When price breaks the resistance of a falling wedge, the take-profit is determined from the highest high inside the formation. When the price breaks the support, the take-profit is determined by subtracting the height of the formation from the breakout point.
3. Some Observations
Technical analysts believe that narrowing wedges indicate a sentiment switch. The impulses within the formation have a decreasing amplitude over time, indicating a potential change in trend. The amplitude of the impulses decrease linearly over time.
The underlying trend in narrowing wedges formation is linear. Detrended prices within a narrowing wedge would highlight a damping effect.
Rising Wedges have been studied with climate time-series data (2)
References
(1) Bulkowski, T. N. (2021). Encyclopedia of chart patterns. John Wiley & Sons.
(2) Kaiser, J. (2017). Technical analysis of climate time series data.
The Squid Game Shows Why Most People Don’t Make Money TradingSquid game is the hottest series on Netflix ($NFLX) right now, in which 456 players join a game of death, where they have a chance to win 456 Billion Korean Won (KRW), or 38.5 Milllion US Dollars.
What’s interesting about this series is that it depicts human sentiment in a very realistic way. We could see how market participants think and act by looking at the participants of the squid game.
A random guy appears at the subway station, and offers to play card flip, where he’d slap the player if he wins, and pay $100 if he loses. He actually ends up paying the players, stimulating their curiosity. Later, players are taken to a remote island where they have no clue what game they’re playing, with hopes of potentially winning life-changing money.
Beginners Luck turns to Attribution Bias
People who join the stock market are not different. They don’t know what game they’re playing, and what rules there are. Just as the subway guy invokes curiosity from the players by paying them small amounts of actual money, people are dragged into the stock market through stories of their friends and acquaintances making life-changing money by trading.
You try to remember the name of the stock or cryptocurrency your friend mentioned, and buy it without doing any due dilligence. You participate in the game of the market with 0 understanding of the game and rules.
When the stock/crypto you bought goes up (by chance), you fall into the trap of beginner’s luck. Beginner’s luck refers to a phenomenon or situation in which a beginner experiences a disproportionate ferquency of success against even experts in a certain field or activity. It’s often used in gambling and sports. But beginner’s luck leads to overconfidence and attribution bias.
Overconfidence refers to one’s excessive trust in his decisions based on gut-feeling and his cognitive abilities. This often leads to overtrading, and the market participant ends up paying excessive trading fees. Overconfident traders also tend to neglect statistics, and put all their eggs in one basket. They hardly listen to other people, and tend to choose the stocks/crypto they invest in themselves.
Attribution bias, or cognitive bias, is when people find reasons for their own and others’ behaviors. So when they’re in profit, they think that it’s all thanks to their amazing prediction. When they’re at a loss, it’s because the market was in an unfavorable situation, or simply because they were unlucky. Essentially, they constantly come up with excuses for every situation.
We all know Isaac Newton as a genius physicist, but he was a failure as an investor. He made the wrong investment decision when he invested in South Sea stocks, which led him to lose 20,000 pounds (about $4M today). He lost most of his life savings and famously said that “you can calculate the motions of heavenly stars, but not the madness of people” - a classic example of someone with attribution bias.
Mob Psychology and the Bandwagon Effect
This is accurately reflected in Squid Game. When players play ‘Red Light Green Light’, they are shocked to see other players get massacred. After the game is over, they later vote whether they want to continue playing the game or not. The surviving players fall into the trap of overconfidence and attribution bias.
Only 1 person out or 456 will survive and win the prize money. Statistically, every player has a 0.22% chance of survival. While this is statistically low, they’re taken away by the pile of cash hanging from the ceiling, and start believing that they’re special, and that they can win. Lotteries and gambling work in the same way, in which people bet on a probable case that is close to impossible. Sadly, most people approach trading like gambling.
In Squid Game, right before they play tug of war, a riot breaks out, and players are split into different factions. So when they’re told to team up for tug of war, teams are formed based on the factions that were formed the day before. This shows us mob psychology and the bandwagon effect.
Mob psychology, or mob mentaility, is when people follow the actions and behaviors of their peers when in large groups. The bandwagon effect falls within the scope of mob mentaility, and is a phenomenon in which people do something primarily because others are doing it , regardless of their own beliefs.
The same psychological phenomena can be applied to investors and traders in the market. Instead of trading based on their own trading rules, strategies, and analyses, they simply follow the actions of other market participants. These are the people who end up panic buying or selling, and falling victim to pump and dump schemes.
Conclusion
These psychological phenomena prevents us from making the right decisions in the market, and making the wrong decisions indicates that we lose money. Just like how most people in the Squid Game end up dying, there are many other people who entered the market with dreams of becoming a millionaire, only to lose everything. But unlike the Squid Game, the financial markets isn’t a winner-takes-all. If you can understand the characteristics and rules of each market, and do your due diligence on different ways to beat the market, you can have a statistical edge. As a trader, I would say that technical knowledge accounts to less than 5% of what it takes to be successful. It’s more about understanding your cognitive bias and controlling your emotions and psychological state.
If you like this educational post, please make sure to like, and follow for more quality content!
If you have any questions or comments, feel free to comment below! :)
Tutorial: How SMAC can help find the Ideal Covered Call StrikeQ3 Earning season is approaching fast
Background: The earnings covered call volatility play
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one of the easy earning plays if you hold a portfolio of stocks (or if you're a fan of the wheeling strategy) is to sell Covered Call (CC) right before the earnings announcement - when the volatility is inflated and the premium price peaks - usually using weekly options - which then you can close immediately after the earnings have been announced, or just leave them to expire worthless if they end up out of the money (OTM).
When this play is done right, and depending on your position size, it can deliver few hundred (if not thousand) bucks literally overnight. When we design this play, we need to consider also the scenario that with the earnings announcement, the stock price may shoot over our selected strike, and we may end up getting assigned - and the stock is called away from us.
However, with the proper "design" of this trade play, you can set it up for a "no-lose" trade scenario
- if you don't get assigned, you keep all the call premium (not bad for a 2-day trade) - see example below - you still keep the stock.
- if you get assigned, you will earn the difference between the strike price and your breakeven *plus* the covered call premium -- so a winning trade in both scenarios.
if we can repeat this play for few stocks during earnings, the gain can accumulate and bring in a very "good month" for the trader who can master this play.
Using the SMAC to make this scenario easier
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One of the reasons i wrote the "Auto-stepping, Zero-lag Moving Average Channel - SMAC" script is to help me with trade scenarios like this. Let me share how.
- Assume i hold 1,000 AAPL shares in my portfolio.
- i just bought them couple of weeks ago - and i am planning to play the volatility and sell Covered Call into the upcoming earnings using the weekly options.
- my goal is either to collect the call premium and keep holding AAPL past the earnings - or to get assigned and sell the stock and realize a profit larger than what i would have got if i just bought then sold the stock direct
- my preferred strike "distance" is 5% Out of the Money (OTM) - which can give a reasonable value of premium while giving me room to still keep the stock if the price doesn't shoot that high due to the earnings.
- I plot my breakeven price on the chart - say for the example here, it's $143
- Add the SMAC to the chart and set the SMAC Percent Envelop to 5%
- This will immediately show what price range i should pick the Covered Call strike if i want a 5% OTM -- it's the $151 or the $152. Maybe i would pick the $152, cause if i get assigned, it would give me a larger gain on the underlying position.
Calculating the P&L for both CC scenarios is also easy now on the chart
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- Not Assigned: after the earnings, the stock still closes below our strike - we can even leave the call to expire worthless - no commission paid - i keep the premium
assume the CC premium is $1.3 by the time i sell the CC & assume i have 1,000 AAPL shares, that's $1,300 over-night! = 1% return and i still keep the stock
- We get assigned
with the same assumptions above, we keep $152 - $143 = $9 + the premium ( = $10 bucks per share -- that's $10,000 in 2 weeks. around 7% return) - we can buy AAPL again later on a dip.
*** Big Note here
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Another scenario is, if my breakeven for AAPL is above the 5% strike price level, in which case, i would not consider this trade at all - because if i sell the CC and i get assigned, i would basically close my position at a loss - again, once i set the SMAC and my BE of the chart, i can easily see if that's the case and make a fast trade decision - here's how this would look on the chart
if you hold 1 or 2 positions in your portfolio - this whole SMAC / Chart thing may not be worth it - maybe a quick mental calculation or simple spreadsheet is easier :) - but if you hold 15-20 positions in your portfolio / multiple accounts, doing this fast during the earnings days and visually on a chart can save a good amount of time and give more confidence.
i hope this can inspire some fellow traders to share how else they can use the Auto-stepping zero-lag Moving Average Channel
Please do not treat this post as a trade recommendation - or as trading education - i'm just sharing thoughts and some of my limited experience - Please trade safely.
Leave Your Ego At The DoorAl Pacino played John Milton in the 1997 film the Devil’s Advocate. Milton ran a hugely successful law firm as a front. The fictional character was really the devil. The final line of the movie is, “Vanity is definitely my favorite sin.”
Vanity is excessive pride in or admiration of one’s own abilities, appearance, or achievements. There is a fine line between vanity and ego. Ego is a person’s sense of self-esteem or self-importance. Vanity may be the devil’s favorite sin, but ego can be a trader or investor’s worst nightmare. Ego gets in the way of rational, logical, and reasonable conclusions because fear and greed can tug on our egos and cause us to make mistakes that are sins when growing our nest eggs.
The quest to buy at the low- Ego leads us to state the market is wrong
Looking to sell at the “high”- A recipe for disaster
Following trends requires no ego at all
Suppressing emotions is harder than you think
Never listen to that voice on your shoulder- It leads you to make mistakes
The quest to buy at the low- Ego leads us to state the market is wrong
Human nature is a powerful force, but it deludes us to believe our gut instincts. When the price of an asset falls to a level where an investor or trader believes is a logical, reasonable, and rational low, they perceive the price as a bargain.
After an initial purchase, if the price continues to fall, our emotions cause a dangerous impulse. The little voice in our heads declares that the market is wrong. The market price is never the wrong price. It is the level where buyers and sellers meet in a transparent environment, the marketplace. All of the fundamental analysis in the world can go out of the window when sellers overwhelm buyers. A perfect example occurred on April 20, 2020, in the crude oil futures arena. Who wouldn’t want to buy crude oil at zero? After all, what is the risk? Well, there turned out to be plenty of risk for those who purchased the nearby NYMEX crude oil futures on April 20, 2020, at zero, negative $10, negative $20, and even negative $30. Those with long positions on the expiring contract who could not store the energy commodity learned an expensive lesson.
As the chart shows, a purchase of the expiring futures contract at zero looked more than ugly at negative $40.32 per barrel, the April 20, 2020 low.
The oil example is dramatic. However, it is a reminder that the quest to buy the low in any market has everything to do with ego and little to do with making a profit.
Looking to sell at the “high”- A recipe for disaster
It is easier for most investors and traders to rationalize a long position as they assess the total risk from the current price level to zero. Oil was an exception to that assumption.
Meanwhile, shorting an asset has the same ego dynamics. Bull and bear markets can take prices to levels on the up and downside that defy logic, reason, and rational analysis. There are many instances where prices rise to levels that make no sense. The lumber market in May 2021 is the perfect example.
The annual chart of the illiquid lumber futures market shows the wood price never traded over the 1993 $493.50 per 1,000 board feet level before 2017. After falling to a low of $251.50 in early 2020 as the global pandemic gripped markets across all asset classes, the price took off on the upside. At $660 in August 2020, it reached a new record high. At $1,000 in September 2020, the price was irrational, and it more than halved in value, reaching a low of just over $490 in October 2020. In May 2021, the price exploded to $1711.20 per 1,000 board feet before collapsing.
Lumber is a dramatic example, but it reflects the potential for the ego to trigger impulses that lead traders and investors to financial ruin. Selling short at $1000 the second time up and ignoring the power of the trend was disastrous. Just because a market price rises to a high, does not mean it cannot go higher a lot higher.
Following trends requires no ego at all
Following trends requires a special skill, which is no skill at all. Following trends allows us to go with the flow, ignore expert advice, the news, and any other exogenous forces. The only tool necessary is a simple chart that displays the path of least resistance of the price. And, it does not matter what the asset is; it can be a stock, a commodity, a currency, a bond, or any other product with liquidity that allows for effective execution of buy and sell orders.
Following trends allow the markets to work for us instead of us slaving for the market. The process is entirely objective, while fundamental analysis is completely subjective. So many variables determine the path of least resistance of market prices, making it impossible to legislate for all potential outcomes. Experts may make a compelling case for buying or selling an asset, but they do not have a monopoly on the truth or offer any guaranty.
James Surowiecki wrote The Wisdom of Crowds in 2004, arguing that the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations. A price chart is the roadmap of the crowd’s wisdom.
Suppressing emotions is harder than you think
Tucking away your ego takes practice. Understanding that ego triggers the emotions that lead to pushing the buy or sell button is the first step.
Many investors wind up selling the lows and buying the highs in wild markets because they allow fear and greed to guide their behavior. Wild markets are the exception, not the norm. Training yourself to manage your ego objectively will reduce the odds of allowing it to destroy you when the you know what hits the fan in markets.
Eliminating ego from all investment and trading decisions starts with ignoring the news, experts, and any inputs other than the herd behavior in markets.
Since prices rise or fall to levels that many believe are not sustainable, following trends allows you to take advantage of their mistakes. Make a conscious decision that you will end the quest to pick a high or low in any market is a great place to start. Successful trend following will cause you to be long at the high and short at the low, but that is OK. It will also allow you to take the most significant percentage from a market move when trends emerge.
Moreover, following trends is an automatic exercise that reduces stress.
Never listen to that voice on your shoulder- It leads you to make mistakes
Eliminate any thoughts about picking lows or highs. When I first began trading in the early 1980s, a colleague in London offered sage advice, saying, “Andy, when you look to pick a bottom, all you will wind up with is a dirty finger.”
Ignore those voices in your head that appeal to your ego, trigger fear and greed, and lead you down a losing path. Never forget that your view has no relevance whatsoever. Vanity is definitely the devil’s favorite sin. Ego and vanity are dangerous. Follow those trends. Approach markets with a clear risk-reward plan where the rewards are equal to or greater than the capital at risk. Understand that you will be wrong all the time, but the market will never be wrong.
The most successful traders do not make money on all of their trades or investment positions. Many will tell you that losers far outnumber winners. However, success depends on catching that wave or substantial trend that yields the most significant profits.
Leave your ego at the door; it is your worst enemy, while the trend or the market’s wisdom is your only friend in the pursuit of profits.
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Trading advice given in this communication, if any, is based on information taken from trades and statistical services and other sources that we believe are reliable. The author does not guarantee that such information is accurate or complete and it should not be relied upon as such. Trading advice reflects the author’s good faith judgment at a specific time and is subject to change without notice. There is no guarantee that the advice the author provides will result in profitable trades. There is risk of loss in all futures and options trading. Any investment involves substantial risks, including, but not limited to, pricing volatility, inadequate liquidity, and the potential complete loss of principal. This article does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein, or any security in any jurisdiction in which such an offer would be unlawful under the securities laws of such jurisdiction.
Top 10 Cryptocurrencies & Their Real World UsesIn this video we explain the real world use cases of each of the top 10 cryptocurrencies. A lot of focus in crypto is focused on the price and the volatility of each coin without many people necessary understanding what their purposes are.
Bitcoin (BTC)
Digital Gold, a store of wealth and protection against inflation… this is because there’s a limited supply of BTC (21 Million) that will ever be mined. It’s supply cannot be inflated like FIAT currencies (Dollar, Pound, Euro etc) can simply be printed.
Collateral in DeFi, in many DeFi (Decentralised Finance) Bitcoin is used as collateral for you to borrow against the value of in return for a cryptocurrency loan for example. We will explain DeFi in a little more detail later.
Banking the unbanked, in many struggling economies (El Salvador for example) Bitcoin is a useful way for communities to gain access to banking facilities. While in many of those regions economies are still largely cash-driven and people cannot afford to pay for transportation to visit banks for registration, the number of those who have access to or own mobile phones is increasing. Thus, using digital wallets to transfer Bitcoin independent of traditional banks may provide a viable alternative for people without a bank account to participate in finance and to create a store of value.
Ethereum (ETH)
Smart contracts, In essence, smart contracts are created to automatically execute and complete processes, such as a payment process, in digitised form. This is the key to Ethereum’s success and its core use case. It enables developers to create complex applications powered by Ethereum’s platform.
DeFi applications, The largest category of smart contracts on Ethereum’s platform is in the form of Decentralised Finance applications.
With DeFi, you can do most of the things that banks support — earn interest, borrow, lend, buy insurance, trade derivatives, trade assets, and more — but it’s faster and doesn’t require paperwork or a third party. As with crypto generally, DeFi is global, peer-to-peer (meaning directly between two people, not routed through a centralized system), and open to all.
NFTs, an emerging use case for Ethereum is in the form of payment for NFTs… you will find that most NFT’s prices are denominated in ETH. NFTs for anyone that isn’t aware are essentially digital art that its authenticity is confirmed in blockchain data.
Think of it as a version of the Twitter blue tick for limited edition digital art.
Cardano (ADA)
Store of Value & Smart Contracts - The Cardano coin can be used as a transfer of value in a similar way that cash is currently used. This is not very different from other cryptocurrencies such as Ethereum and Bitcoin, but ADA has other uses as well.
One of the core principles of Cardano is its PoS blockchain protocol where ADA is staked to the blockchain to successfully verify transactions on the blockchain. This is where Cardano crypto comes in handy. Those who stake their ADA to the blockchain are rewarded for their efforts with more Cardano crypto in return. This staking system helps maintain security throughout the blockchain.
There is also the use of ADA in voting. In Cardano, unlike other blockchain projects, it is not miners who vote and decide on changes to the protocol, it is token holders. Therefore, when a new change or development is proposed to the Cardano blockchain, Cardano crypto holders use their ADA to vote on these proposals. This way, everyone who owns the cryptocurrency has a say in its development.
ADA also can be used to power the smart contract platform on the Cardano blockchain. Developers utilise ADA to create smart contracts and applications that run on the secure, decentralised Cardano blockchain.
In the case of running smart contracts it is cheaper in transaction fees than Ethereum.
Tether (USDT)
Stablecoin - Backed by US dollars and value is pegged to always be at-or very close to £1 per 1 USDT
Transferring Crypto - Lots of people will use Tether as a middleman when transferring money from one cryptocurrency to another without paying the fees associated either between each crypto or back and forth into Fiat currencies.
Generating a Yield - Some tether users also simply hold their funds in Tether because it generates a higher yield or interest rate than their money would in a bank for example.
Binance Coin (BNB)
Binance Coin is the cryptocurrency issued by the Binance exchange and trades with the BNB symbol.
BNB was initially based on the Ethereum network but is now the native currency of Binance's own blockchain, the Binance chain.
Every quarter, Binance uses one-fifth of its profits to repurchase and permanently destroy, or "burn," Binance coins held in its treasury.
Binance was created as a utility token for discounted trading fees in 2017, but its uses have expanded to numerous applications, including payments for transaction fees (on the Binance Chain), travel bookings, entertainment, online services, and financial services.
Ripple (XRP)
Very quick & cheap cross border payments
,
The primary use case for XRP is intended to be for transfer of other currencies (or indeed commodities or assets such as gold or oil) over the Ripple network. Each time a money (or asset) transferring organisation such as a bank uses the network to conduct a transfer and settlement, the cost is deducted in a small amount of XRP.
Cross-border payments between banks and organisations currently run on a system called SWIFT… a system created in 1973. This is essentially what Ripple and its coin XRP could replace with a much quicker and cheaper system.
Solana (SOL)
Smart Contracts platform.
Much in the same way that both Ethereum & Cardano is used on a day to day basis as developers who make applications on the Solana blockchain pay SOL coins for the processing / transaction fees.
Large numbers of NFTs are also available on the Solana blockchain.
Polkadot (DOT)
Interoperability - Allow different blockchains to talk to each other and share data / features between each other. This is useful for developers when making new blockchains, as they are able to use sections of features from different chains without the need to create them from scratch each time.
Unlimited Supply - Unlike most other cryptocurrencies, DOT isn’t limited in supply. This is designed to incentivise the network and dynamically adjust according to participation rates of users.
Dogecoin (DOGE)
Meme coin which was originally created as a joke or parody of the crypto world.
Now however has gained massive popularity and even is considered for payments as a real world use. This is still to be widely accepted however.
USDC (USDC)
Stablecoin, backed by US dollars and value is pegged to always be at-or very close to £1 per 1 USDT. Not as popular or widely used by the market than Tether.
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Education Excerpt: SMA, LWMA, GMA, TMA, EMAWe decided to publish second part of the paper on moving averages. The first part detailed Simple Moving Average. In the second part we decided to present: linearly weighted moving average (LWMA), geometric moving average (GMA), triangular moving average (TMA) and exponentially smoothed moving average (EMA).
The first part can be read by clicking on chart below:
Possible uses of the moving average
• Identification of trends
• Identification of price extremes
• Identification of support and resistance levels
• Identification of signals
Identification of trend
The moving average can be used as simple tool to determine prevailing trend. Simplest way to determine current trend using moving average is to compare current value of security to current value of moving average. If value of moving average is below price of the security, then trend is considered to be upward. Contrary to that when value of moving average is above price of the security then trend is considered to be downward. Another method of determining trend is to use two same moving averages but with different length (different number of hours or days, etc.). These two moving averages would be then plotted on graph as two simple lines occasionally crossing. Trend would be considered upward when shorter moving average would be above longer moving average. Opposite to that, if shorter moving average would be below longer moving average then trend would be regarded to be down.
Illustration 1.01
Picture above depicts daily chart of XAUUSD. It is observable that price continued to rise most of the time when it was above 10-day SMA. It is also observable that when price dropped below 10-day SMA then it continued to decline further.
Identification of price extremes
Analyst can find another utilization of moving average in finding the price extremes. This is possible due to natural tendency of price to move back towards its moving average after it deviated too far from it.
Illustration 1.02
Graph above depicts General Motors on daily time frame. It is visible that when price deviated too far from its 10-day SMA then retracement followed. However, it is not a rule that price will retrace full length back to moving average once it deviated too far from it.
Identification of support and resistance levels
Another possible use of moving averages lies in using them as specific support and resistance levels. In rising markets price has tendency to correct towards moving average before continuing to rise further. Similarly, in declining markets price tends to suddenly increase towards moving average and then drop and continue lower.
Identification of signals
Generally, when moving average with lower period interval crosses above moving average with longer period interval it is considered bullish signal. On the other hand, when moving average with longer period interval crosses above moving average with lower period interval it is considered bearish signal. These crossovers can serve as specific buy and sell signals in markets that are trending.
Illustration 1.03
Picture above shows same graph of General motors as is depicted in Illustration 1.02. However, instead of one 10-day SMA this graph also includes 20-day SMA. It is easily identifiable where these two moving averages cross each other and by doing so generate specific buy and sell signals. However, we have to note that in non-trending markets this method lacks utility since moving averages tend to produce a lot of false signals.
The Linearly Weighted Moving Average (LWMA)
The Linearly Weighted Moving Average (LWMA) is very similar to the Simple Moving Average (SMA) we introduced in our previous education excerpt. But while SMA gives each time period involved in the calculation same weight LWMA differentiates between the weight linked to each time interval. Normally, 10-day SMA calculation would be conducted by summing up each value per time period and then dividing this result by total number of time intervals (which would be 10 in this particular example). In this calculation each time period (each day) would have 10% weight. However, as mentioned before, LWMA gives each time interval different weight. This unequal redistribution of weight can be achieved in two simple steps. In the first step analyst multiplies each day's value and sums up resulting values together. Then in the second step analyst divides resulting value (from the first step) by the sum of all multipliers. For example, in 10-day LWMA first day's value would be multiplied by 10. Then second day's value would be multiplied by 9; and third day's value would be multiplied by 8 (continuing up to 10 days where last day's value would be multiplied by 1). Resulting value for each time interval would be then summed up and divided by 55 (multipliers: 10+9+8+7+6+5+4+3+2+1 = 55). This simple change in formula would result in giving 10th (most recent day) day in the calculation twice the weight of 5th day and ten times the weight of the 1st day. Calculation of 10-day LWMA for 11th day would then involve weighting data from 2nd day up to 11th day while dropping the 1st day's value from data set being used in the calculation. Assigning different weight to each time interval helps to give more relevance to the most recent days as opposed to giving less importance to days before that.
Formula
LWMA = / summation of W
P = price for the period
n = period
W = the assigned weight to each period (highest weight goes first and then it linearly declines)
Illustration 1.04
Chart above depicts two different moving averages. First is 10-day SMA (blue) and second is 10-day LWMA (yellow). While these two moving averages have same length they are different in shape. This is because of unequal redistribution of weight. This allows LWMA to act in advance of SMA.
Geometric Moving Average (GMA)
The Geometric Moving Average (GMA) is another form of moving average. But rather than using price in its calculation GMA uses percentage changes between the previous time period and the current time period. This type of moving average distributes weight equally as SMA. In addition to that it suffers from lag. When SMA and GMA (with same length) are plotted on same graph they are not different in shape or dimensions. Therefore they would overlay each other.
The Triangular Moving Average (TMA)
The Triangular Moving Average (TMA) is another type of moving average that is different from previous types of moving averages in that it is double smoothed. Its calculation begins with taking SMA with predetermined number of bars. After that these results are being used to take SMA of former SMA. However, length of second SMA is only half of that used in calculation of original SMA. For example, 20-day SMA would be smoothed through calculation of 10-day SMA that would use data from 20-day SMA. The result can be then plotted on graph and it is depicted as smoothed line. TMA represents the trend better since it is double smoothed, however, at cost of sensitivity to trend changes. When TMA and SMA (with same length) are plotted on same graph they are different in shape and dimensions.
Illustration 1.05
Picture above shows daily graph of PEP. Three moving averages are depicted: SMA, LWMA, TMA. They all observe same 10-days, however, each acts differently.
The Exponentially Smoothed Moving Average (EMA)
The Exponentially Smoothed Moving Average (EMA) is type of moving average that weights importance on the most recent data. Decrease in weight from one time interval (one day) to another is exponential; and unlike SMA and LWMA exponential moving average has ability to use information outside the length of the moving average. Result from calculation of EMA can be then plotted on graph similarly like result from SMA, LWMA or any other moving average. EMA is considered to be more responsive to trend changes and it can be used when analyst is concerned with effect of lag (which is stronger in SMA and LWMA).
Formula
EMA = Pricet x k + SMAy x (1-k)
t = today
k (multiplier) = 2/(number of days in period +1)
SMA = simple moving average of closing price
y = yesterday
Illustration 1.06
Picture above depicts daily graph of Raytheon. It also depicts 10-day SMA and 20-day EMA. It is visible that many fake signals took place once market started to trade sideways.
Disclaimer: This content is purely educational.
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Why Implied Volatility Is A Critical Tool For All TradersTraders and investors use different sets of tools when approaching markets. Some are fundamentalists, pouring through balance sheets, supply and demand data, and other macro and microeconomic information to predict the future prices of assets. Others have a strictly technical approach to markets, following trends and the path of least resistance of prices. Still, others combine the two to look for opportunities where fundamental and technical analysis merge to improve the chances of success.
The past is history; the present is all that matters for traders and investors
Historical volatility is a map of the past price variance for asset prices
Implied volatility is a real-time sentiment indicator
The primary variable determining put and call option prices
The three critical factors implied volatility reveals
Yogi Berra, the hall of fame catcher and armchair philosopher, once said, “The future ain’t what it used to be.” All market participants have the same goal, to increase their nest eggs. Projecting the future is the route to achieve their goal.
Implied volatility is a tool that all market participants need to embrace as it is a real-time indicator of market sentiment.
The past is history; the present is all that matters for traders and investors
History depends on interpretation. When it comes to markets, Napoleon Bonaparte may have said it best, “history is a set of lies agreed upon.” An asset’s price moved higher or lower in the past because of a collection of variables viewed through a prism that leads to a collective conclusion that has broad acceptance but may not be accurate. Taking a risk-based position on an inaccurate conclusion could lead to mistakes and losses.
When we consider buying or selling any asset, all that matters is the present. The current price of any asset is always the correct price because it is the level a seller is willing to accept and a buyer is willing to pay in a transparent environment, the market.
Historical volatility is a map of the past price variance for asset prices
Historical volatility is an objective statistical tool that defines the price variance of the past. Any disclosure document tells us that past performance is no guaranty of future performance. We must view historical volatility precisely the same way, with more than a grain of salt.
Historical volatility is a guide, but remember what Yogi said, “the future ain’t what it used to be!”
We calculate historical volatility by determining the average deviation from the average price over a given period. When it comes to math, the formulas are:
A simple explanation of the complicated formula comes in seven easy steps:
1. Collect the historical prices for the asset
2. Compute the expected price (mean) of the historical prices.
3. Work out the difference between the average price and each price in the series.
4. Square the differences from the previous step.
5. Determine the sum of the squared differences.
6. Divide the differences by the total number of prices (find variance).
7. Compute the square root of the variance computed in the previous step.
Implied volatility is a real-time sentiment indicator
While we can calculate historical volatility from historical data, implied volatility is a different story. Implied volatility is the expected or projected volatility or price variance of an asset over time.
We back into calculating implied volatility using an options pricing model. We can establish an implied volatility reading by entering the option value into the Black-Scholes options pricing formula or other formulas that determine options prices. If we have a put or call options price, we can solve for the implied volatility level. The Black-Scholes formula in mathematical notation is:
The primary variable determining put and call option prices
There are no option prices without implied volatility as it is the critical variable that determines put and call option values. Yogi also said, “You can observe a lot by watching.” The current implied volatility level is the market’s consensus perception of what volatility or price variance will be during the life of the put or call option.
Observing and watching reveals the constant changes in implied volatility levels, which can be highly volatile over time. Option traders call an option’s sensitivity to changes in implied volatility Vega, which measures the change in an option price for a one-point change in implied volatility.
Implied volatility is constantly changing. Yogi had another great saying, “If the world were perfect, it wouldn’t be,” which rings true for implied volatility which can change in the blink of an eye. Option traders pay lots of attention to their Vega risk as the volatility of implied volatility can be…highly volatile! How’s that for a tongue twister?
The three critical factors implied volatility reveals
Implied volatility is a valuable tool for all traders and investors for three significant reasons:
It is a real-time indicator of the market’s perception of the future price range of an asset.
It can change suddenly, and changes often occur before the price of an asset reacts, making implied volatility a leading indicator.
Implied volatility reflects the wisdom of the crowd, and crowds tend to make better decisions than individuals. Moreover, it is reading that reflects the present, not the past, and is a constantly changing measure of consensus forecasts for the future.
As traders and investors, we exist in the present. We attempt to increase our wealth with long and short risk positions that either add or subtract from our nest egg in the future. Implied volatility is a critical measure we should understand, utilize, and always keep in our toolbox. Any project requires the right tools. Implied volatility’s value is that it reflects a snapshot of the current market’s consensus.
Historical volatility depends on “Deja vu” happening “all over again.” Implied volatility is a measure that understands that the “future ain’t what it used to be.”
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Trading advice given in this communication, if any, is based on information taken from trades and statistical services and other sources that we believe are reliable. The author does not guarantee that such information is accurate or complete and it should not be relied upon as such. Trading advice reflects the author’s good faith judgment at a specific time and is subject to change without notice. There is no guarantee that the advice the author provides will result in profitable trades. There is risk of loss in all futures and options trading. Any investment involves substantial risks, including, but not limited to, pricing volatility, inadequate liquidity, and the potential complete loss of principal. This article does not in any way constitute an offer or solicitation of an offer to buy or sell any investment, security, or commodity discussed herein, or any security in any jurisdiction in which such an offer would be unlawful under the securities laws of such jurisdiction.