Scenarios vs. Certainties: The Shift Serious Traders MakeWhy Certainty Destroys Traders
Every losing trader I’ve ever met had one thing in common: they wanted certainty.
“This setup will definitely work.”
“This pair must go up.”
But markets don’t work like that. They don’t reward certainty — they reward adaptability. The difference between amateurs and professionals? Amateurs bet on one fixed outcome. Professionals prepare for scenarios.
________________________________________
The Trap of Certainty
When you lock your mind on just one outcome, two things happen:
• You become emotionally tied to it — when it fails, you spiral.
• You ignore new information — even when the chart screams something changed.
That’s how a manageable trade turns into a disaster.
________________________________________
Building Scenarios Instead of Certainty
A professional trader prepares a mental map of outcomes before taking a position:
1. Worst Case
• Market goes directly against your entry
• Hits stop-loss
• ✅ Response: Accept loss calmly, move on
2. Base Case
• Price fluctuates, stays inside a range
• No clear follow-through yet
• ✅ Response: Observe, adapt, maybe scale out, close all or adjust stop
3. Optimistic Case
• Price moves steadily toward target
• Smooth momentum, plan unfolds
• ✅ Response: Let the trade run, stick to plan
4. Best Case
• Trend accelerates, profit exceeds expectations
• Move continues further than projected
• ✅ Response: Move take profit further, trail stop, lock in gains, maximize opportunity
________________________________________
Why This Works
• You’re emotionally prepared: no outcome shocks you.
• You stay flexible: adapting without panic.
• You build consistency: no more swinging between overconfidence and despair.
________________________________________
How to Apply This Today
1. Before entry, write down at least 3–4 scenarios (worst, base, optimistic, best).
2. Decide in advance: what will you do in each case? Close early, adjust, or let it run?
3. After the trade: review which scenario played out and how you reacted.
Do this for 10 trades, and you’ll notice less stress, more clarity, and better discipline.
________________________________________
Conclusion – From Gambler to Strategist
Amateurs crave certainty. Professionals build scenarios.
The market will always surprise you — but if you’ve already prepared for multiple paths, you’ll never be caught off guard. That’s how you stay disciplined, calm, and profitable.
________________________________________
👉 Challenge for you: On your next trade, write down at least three scenarios before you enter. Track which one unfolds. This habit alone can transform your trading mindset. 🚀
Trading Plan
Best Lot Size for Gold Trading (XAUUSD) Explained
If you trade Gold with fix lot, I prepared for you a simple manual how to calculate the best lot size for your XAUUSD trading account.
Step 1
Find at least the last 10 trades that you took on Gold.
Step 2
Measure stop losses of all these trades in pips
Step 3
Find the trade with the biggest stop loss
In our example, the biggest stop loss is 680 pips
Step 4
Open position size calculator for XAUUSD
Step 5
Input your account size, 1,5% as the risk ratio.
In "stop loss in pips" field, write down the pip value of your biggest stop loss - 680 pips in our example.
Press, calculate.
For our example, the best lot size for Gold will be 0.22.
The idea is that your maximum loss should not exceed 1,5% of your account balance, while the average loss will be around 1%.
❤️Please, support my work with like, thank you!❤️
I am part of Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis.
Forget the USD–Gold Correlation: Trade What MattersI took my first steps in the markets back in 2002 with stock investments. Real trading, however—the kind involving leverage, speculation, and active decision-making—began for me in 2004.
Like any responsible beginner, I started by taking courses and reading the classic trading books. One of the first lessons drilled into me was the inverse correlation between the US dollar and gold.
Fast forward more than 20 years, and for the past 15, XAUUSD has been my primary focus. And here’s the truth: I’m here to tell you that relying on USD–gold correlation is a mistake.
In this article, I’ll explain why you should avoid it, and more importantly, I’ll show you how to think like a “sophisticated” trader—especially if you can’t resist looking at the DXY .
Let’s Dissect the Myth
And for those who will say: “How on earth can you call this a mistake? Everyone knows gold moves opposite to the dollar!” — let’s dissect this step by step.
There couldn’t be a better example than 2025. We’re in the middle of a clear bullish trend in gold. Prices are climbing steadily, but not only against USD.
If gold were truly just the inverse of DXY, this overall rally wouldn’t exist. But it does. Why? Because the real driver isn’t the dollar falling — it’s demand for gold itself . Central banks are buying, funds are reallocating, and investors see gold as a store of value.
The Simple Logic That Breaks the Correlation
If it were truly a mirror correlation, then XAU/EUR would have been flat for years. Think about it: if gold only moved as the “inverse of the dollar,” then against other currencies it should show no trend at all. But the charts tell a completely different story.
Gold has been rising not just in USD terms, but also in EUR, GBP, and JPY. That means the move is not about the dollar being weak — it’s about gold being in demand.
This simple observation destroys the illusion of a strict USD–gold inverse correlation. If gold climbs across multiple currencies at the same time, the driver can’t be the dollar. The driver must be gold itself.
Why Correlation Thinking Creates Frustration
This is exactly why I tell you to ignore the so-called correlation: because it distracts you. You end up staring at the DXY when in reality, you’re trading the price of gold.
And that’s where frustration kicks in. You’re sitting on a position, watching the dollar index going higher, and you start yelling at the screen: “DXY is going up, so why isn’t gold falling? Why is my short position bleeding instead of working?”
I’ve been there many years ago, I know that feeling. But here’s the truth: gold doesn’t care about your correlation. It doesn’t care that DXY is green, red or pink. It moves on its own flows. And when you finally accept that, your trading becomes much cleaner. You stop being trapped by illusions and start focusing on the only thing that matters: the demand and supply of gold itself.
Where the Confusion Comes From
So where does all this confusion come from? Let’s take an example: imagine we get a very bad NFP number. That translates into a weaker USD. What happens? XAUUSD ticks higher.
Now, most traders immediately scream: “See? Inverse correlation!” But that’s not what’s really happening. The move you’re seeing is just a re-alignment of gold’s price in dollar terms. It’s noise, not a fundamental shift in gold’s trend.
If gold is in a downtrend overall, this kind of move doesn’t suddenly make it bullish. It’s just a temporary adjustment because the denominator (USD) weakened. On the other hand, if gold itself is already strong, such an event can act as an accelerator, pushing the trend even stronger.
The key is this: the dollar can influence the short-term pricing of XauUsd, but it doesn’t define the trend of gold. That trend is driven by demand for gold as an asset.
A Recent Example That Says It All
Let’s take a very recent example. Over the past month, DXY has been stuck in a range — no breakout, no major trend. Yet gold hasn’t just pushed higher in USD terms, it has made new all-time highs in XAU/EUR, XAU/GBP, and other currencies as well.
Why? Because gold rose. Not because the dollar fell, not because of some neat inverse chart overlay. Gold as an asset was in demand — globally, across currencies.
This is the ultimate proof that gold trades on its own flows. When buyers want gold, they don’t care whether DXY is flat, rising, or falling. They buy gold, and the charts across multiple currencies show it.
What Sophistication Really Looks Like
If you really want to be sophisticated, here’s what you do:
You see a clear bullish trend in XAUUSD. At the same time, you notice a clear bearish trend in EURUSD — which means the dollar is strong. Most traders get stuck here. Their brain short-circuits: “Wait, how can gold rise if the dollar is also strong?”
But the sophisticated trader doesn’t waste time arguing with a textbook correlation. Instead, they look for the trade that makes sense: buy XAU/EUR.
Because if gold is strong and the euro is weak, the real opportunity isn’t in fighting with DXY — it’s in positioning yourself where you can earn more. That’s not correlation thinking. That’s flow thinking.
Final Thoughts
The dollar–gold inverse correlation is a myth that refuses to die. Traders cling to it because it feels simple and safe. But real trading requires letting go of illusions and facing complexity head-on.
Gold is an independent asset. It rises and falls because of demand, not because the dollar happens to be moving the other way. Once you stop staring at DXY and start trading the flows that actually drive gold, you’ll leave frustration behind and step into sophistication.
🚀 If you still need DXY to tell you where gold is going, you’re not trading gold — you’re trading your own illusions.
Diversification in Practice: My Approach to MarketsThe big project for me at the moment is finding ways to diversify.
Ray Dalio calls diversification the holy grail of investing, and I tend to agree.
If you put the numbers in a volatility formula you will find that going from 1 investment to 8 ones with 20% correlation divides volatility by 2, and going from 1 to 20 with 5% correlation divides volatility by 3.
So diversification could in theory double to triple risk-adjusted returns. To help visualise what this means:
Starting with 10k and making 15% a year for 10 years results in having 40k;
Starting with 10k and making 45% a year for 10 years results in having 410k.
Of course in practice it is not realistic to expect to find that many profit sources with such low correlation.
💰 Asset classes I am focussing on
Even though I am looking to diversify, I will, at least for the time being, only focus on Forex, commodities and a little bit indices.
Forex and Commodities: They have their differences, FX retraces much more than commodities, but in many ways they are similar. They are great for speculating over a few weeks, something I personally favor.
Indices: I rarely trade them, but I did spend a lot of time studying them, and feel comfortable trading them the same way I trade the EUR/USD or gold.
The reasons for ignoring Bonds, cryptos and shares:
- Cryptos and shares behave significantly differently,
- The timeframes are different,
- Stocks gap so much and anyway are highly correlated to the S&P500
- I do not think it would add much to my portfolio, volatility would be the same
💰 Improvements I have made to my diversification
I was able to add some instruments and reduce my exposure to the USD from 33% to 25% on average.
Keep in mind that over small periods exposure can go above the average as I get so many signals.
I went through a period of 1-2 months where 50% of my activity was on the USD, with intraday swings wiping out weeks of progress (it can get close to target then do a 70% retrace to entry in a few hours).
I improved my diversification but it is still not enough. The Euro still amounts to 22% of my activity, and the Yen 18%, everything else is below 12% which is acceptable.
I added several east asian currencies to the watchlist. I had not thought of it but Yen, Yuan and SGD pairs are actually not that expensive, liquid, and trend just like the rest.
I also increased exposure to commodities I already invest in, I added gold and silver quoted in currencies other than USD, as well as Brent Oil (on top of CL1! I have been trading for years).
💰 Other instruments I might consider later on
I could look at extra commodities, ag ones I don't already trade, something like Lumber, Rice or Orange Juice; as well as metals traded on the London Metal Exchange, such as Nickel, Zinc, Aluminum and Lead.
I do not think there is much more I can do with Forex, there is no point trading ultra exotic pairs such as PLN/CZK where the spread is going to be huge, and who knows what could go wrong.
Other than those few examples I mentionned I do not have any other ideas.
If I could reduce my expose to the USD to 20% that would be great. I do not think I can push it further than this.
Do you think I am wrong to ignore some asset classes? Do you know about LME metals and think they are great/terrible? Please let me know dear colleagues.
Win in Trading by Mastering 7 Key Processes (Beyond Strategy)🔷 Lesson 1: Focus on Processes, Not Just Strategy
Every trader starts by chasing the perfect strategy. Testing system after system, hoping the next one would be “the one.” I spent years stuck in this cycle.
Here’s the truth: Even a mediocre strategy can gee increneratdible results if your trade management, risk control, and process discipline are solid.
Takeaway: Stop chasing shiny objects. Start building reliable trading processes.
🔷 Lesson 2: Risk Management Is Your Lifeline
Blowing up an account is like a rite of passage. If you don’t respect risk, the market will humble you fast.
I’ve seen traders risk 1% per trade—but take 50 trades a day. That’s not a smart risk; that’s emotional chaos.
And if you're overleveraging to “hit it big,” you’re gambling, not trading.
Discipline > Emotion. It doesn’t matter how good your setup is—if your risk management is trash, your career won’t last.
🔷 Lesson 3: Patience Pays (Literally)
If you can't sit on your hands, trading will chew you up.
Impatience costs a lot of trades in early exits, poor re-entries, and over-managing winning trades. Your turning point? Practicing patience like a muscle.
Challenge for You:
Plan 25 trades. Partial at 2R, stop to break-even, let the rest run. No early exits. No fiddling. Just patience.
If you squirm waiting for 2R, you’ve got work to do.
🔷 Lesson 4: Overconfidence Can Kill Your Account
Ever had a winning streak, then sized up on one “can’t lose” trade, only to lose it all?
Been there.
The market doesn’t care how smart you are. If you're trading to prove something, you’re playing a dangerous game.
Set table limits. Stick to fixed risk. If the trade setup doesn’t fit your risk parameters, skip it.
Discipline beats ego. Every time.
🔷 Lesson 5: Take Breaks. Often.
Trading burnout is real.
There are 250 trading days in a year. You’re not a robot. If athletes have off-seasons, why don’t traders?
Mental fatigue leads to poor decisions. Poor decisions hurt your account.
Reminder: The market will still be here tomorrow. Your sanity comes first.
🔷 Lesson 6: Know Yourself Better Than the Market
The market is the ultimate mirror. It’ll expose your fear, greed, impulsiveness, and every flaw you try to ignore.
Success in trading isn’t just about charts—it’s about self-awareness.
Start journaling. Note your habits, triggers, and reactions. The more you understand yourself, the fewer self-sabotaging thoughts you’ll have.
Your edge isn’t just in the market—it’s in your mind.
🔷 Lesson 7: Zoom Out and Think Long-Term
Too many traders put all their hopes into one trade or one day. That’s not how wealth is built.
Why? Because a profitable trader is focused on the long game. When you stop trading like every moment is life or death, you finally give yourself the space to perform.
You’ll stop forcing trades. You’ll stop overtrading. You’ll start enjoying the process.
🔷 Final Thoughts: You Can Do This—But Only If You Do It Right
These seven lessons weren’t just “helpful tips”—they were lifelines. They helped me transition from being lost and frustrated to being profitable and confident.
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Every Boost helps another trader find clarity in this noisy space. 🚀
What was your "aha!" moment from this guide? Share it below — let’s learn together. 💬
Follow me to grow your edge, one trade at a time.
Thank You...
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How Many Indicators Are Too Many?
I have been trading for around 5 years and in that time, I lost money and hope more often than I can count. A common coping strategy I use when in a time of loss is to strip all the "completely useless" indicators from my charts. And 6 months later, I have more than I had before.
Recently, I have actually started to earn small amounts of money from the markets consistently but my indicator problem persists. The picture above is an example of just some of the indicators I use. So now I ask the question,
-How many indicators are too many?
There really is not an answer despite what those on reddit might tell you. I seem to always have this fantasy that I will find the perfect chart set-up with all my indicators telling me just what I want to know. And of course TradingView has Pinscript which only makes my habit worse by allowing me to create exactly what I want.
As I was thinking about chart layouts this morning I came to a conclusion that my trading will always be evolving and the way in which I view the visual output of markets will change as well. There will most likely never be a chart set-up that I will use for the next 20 years. Even when I find my edge, the process of trading will still evolve. My "edge" will never be an indicator or a set of indicators .
So I wrote this to try and help those that are experiencing the same dilemma. Just know that you are not alone in your obsession with finding that perfect layout. Add 100 indicators to your chart and then delete them all when you feel they don't belong. You will never find that perfect indicator but but neither will you stop looking. It may seems like it is all a waste of time but I assure you that everything you experience in trading is worth it and progress does happen .
Safe Trading, Frank
Its Non-Farm: How much will ES Move?Hi all - Happy Non-Farm Friday!
I haven't done this in a while and thought it might be helpful to share my process for estimating the size of the move that we may get on ES after the Non-Farm Payrolls data is released.
I'm not trying to make a prediction on direction here - but more understand where the boundaries could be so I can determine how to trade this (what trading tool I can pull out of my box) once the announcement comes out.
Hope it helps and please let me know if you find it useful and I'll create more posts .
Cheers,
Jeff
Moving Stops - The Illusion of ControlA trader frames an idea:
BTC Daily Uptrend
Looking for reasons to frame a low risk idea for a long, wanting to get into uptrend resumption
Drops down to the 4hr
Notices buyers coming back … or at the minimum the sellers pause
Enters with a tight stop for a healthy return to risk ratio
Stop set. Risk defined. Plan in place.
Price goes against
Trader shifts the stop down
What is going on here?
It’s all too easy to do.
Many of us have been here before.
Stop in place. Target set. Everything mapped.
Then the market nudges against you …
You might tell yourself “this is just ‘noise’”.
You convince yourself that ‘they’ are just going to pick you off.
and suddenly you’re “adjusting.”
Move the stop just a little.
Pull the target closer.
Bend the rules you swore you’d follow.
And it feels ‘right’ in the moment. Like you’re managing risk.
But what’s happening here is that
You are attempting to control your own discomfort.
And in so doing - you enter the slippery slide of losing self control.
It’s subtle but it starts like this.
If the trade works out - you might feel justified in having moved your stop and therein starts a pattern of rule breaking.
If the trade does not work out - you might beat yourself up and undermine confidence in yourself and your process
🧠 A simple thing that might help guard against this:
Before the trade, write down the one level you will respect.
Write it in a journal.
Annotate it on the chart.
Use the TradingView long position / short position tool.
Even saying it out loud locks it in.
That tiny ritual makes it much harder to justify shifting things mid-trade.
The market will do what it does.
The only thing you truly control is whether you keep your word to yourself.
Commit to the stop when you commit to the trade
Live to trade another day.
The Two Pillars That Changed My TradingAfter years of trial and error, I shifted my focus from searching for signals to building a foundation. For me, that foundation rests on two pillars:
Pillar 1: Risk Management
Risk per trade: Fixed % of account. Currently, mine is 0.5%
Minimum Risk/Reward: 1:2. I try as much as possible to make this minimum a rare occasion; I try to aim for higher, but it all depends on other factors of the setup.
Position sizing: Calculated precisely before every entry. I base it on three factors: the current account balance, risk per trade, SL distance.
Pillar 2: The Trading Plan
A written, unambiguous set of rules for every action.
Based on price action and market structure.
Designed to be followed without emotion or deviation.
These pillars work together. The plan gives me confidence, and the risk management gives me the longevity to be wrong. This mindset shift made all the difference. I document my journey applying these principles in detail elsewhere.
What's one rule in your trading plan you won't break?
Trade Against the Crowd | Skeptic’s Night Byte Ep.3Welcome to Episode 3 of Skeptic’s Night Byte! 🔮
Today we break down a comment and share practical tips on how to act on triggers in crypto and stocks — even when the world seems against you. Learn how to:
Follow your strategy without being swayed by news
Manage risk with smart stop-loss rules
Keep your trades disciplined and avoid FOMO
💡 Keep it simple, manage your capital, and trade with confidence.
Trading Imbalances: How to Use Fair Value GapsDifficulty: 🐳🐳🐋🐋🐋 (Novice+)
This article is designed for traders who want to understand Fair Value Gaps (FVGs) in a simple, practical way — without drowning in complex Smart Money Concepts terminology.
🔵 INTRODUCTION
If you’ve studied Smart Money Concepts (SMC), you’ve likely come across Fair Value Gaps (FVGs). For many, the concept feels overcomplicated. In reality, an FVG is just an imbalance in price — a spot where the market moved so fast that it didn’t fully trade both sides.
🔑When price leaves a gap behind, it often comes back later to “rebalance.” This gives traders powerful zones for entries, exits, and target setting.
🔵 WHAT IS A FAIR VALUE GAP?
A Fair Value Gap is formed over three candles :
Candle 1: The first move (anchor).
Candle 2: The big impulsive candle (the imbalance).
Candle 3: The follow-up candle.
The gap exists when the high of Candle 1 is below the low of Candle 3 (in a bullish case). This leaves an “untraded zone” inside Candle 2.
Think of it as a skipped step. Price rushed through so quickly, there wasn’t enough time to trade at fair value.
🔵 WHY DOES PRICE RETURN TO FVGs?
Markets seek balance. When an imbalance forms, algorithms and institutional flows often revisit the gap to collect liquidity and rebalance orders.
This doesn’t mean every FVG gets filled instantly — some remain open for days or even weeks. But many serve as magnets for price.
🔑Key point: An FVG is not a magic level. It’s a clue about where inefficiency sits.
🔵 HOW TO TRADE FVGS SIMPLY
1️⃣ Mark the Zone
Identify the three-candle imbalance. Highlight the gap inside Candle 2.
2️⃣ Wait for Return
Don’t chase the impulsive candle. Instead, wait for price to retrace into the FVG zone.
3️⃣ Trade the Reaction
Bullish FVG → wait for price to dip into the zone and show bullish reaction
Bearish FVG → wait for price to retest zone and reject downward
Stops are usually placed beyond the gap, targets set toward the next liquidity pool or swing level.
🔵 EXAMPLE SCENARIO
A strong bullish candle leaves an imbalance.
Price continues higher, but a day later revisits the gap.
At bullish rejection candles form with increasing volume.
Entry taken, stop below gap, target at next swing high.
🔵 TIPS FOR ADVANCED TRADERS
Higher timeframe FVGs are stronger and attract price longer.
Not every gap fills — filter with trend direction.
Combine with OBs (Order Blocks) or liquidity zones for more precision.
Ignore small random gaps in low-volume markets.
🔵 CONCLUSION
Fair Value Gaps don’t need to be mysterious. They’re simply imbalances in the auction process. By waiting for price to return and react, traders can build structured entries with defined risk.
🔑Instead of overcomplicating SMC concepts, think of FVGs as footprints of urgency — and opportunities for balance.
Do you already trade FVGs, or is this your first time hearing about them? Share your setups below!
CM - The Best Method I’ve Found For Finding - Stocks That MOVE!!Today I want to show you The Best Method I’ve Found to Create a list of Stocks to find the most profitable stocks to TRADE consistently.
Please leave a comment below if:
You find this video useful.
You have any questions.
You want me to do a video on how I built the screeners shown in the video.
You want me to continue providing the up to date watchlists.
The link to import the watchlist from the video:
www.tradingview.com
Thanks...
Why Is Crypto Tumbling? A Trader's Guide to the Recent Sell-OffWhy Is Crypto Tumbling? A Trader's Guide to the Recent Sell-Off 📉
🚨 If you're watching the markets today, you've seen the sea of red. Bitcoin, Ethereum, and major altcoins have experienced a significant pullback, leaving many to wonder about the cause.
While sharp drops can be unsettling, for the strategic trader, they are critical moments to analyze, not to panic. The current downturn isn't random; it's driven by a convergence of clear geopolitical, technical, and macroeconomic factors.
Here’s a breakdown of what’s happening behind the charts:
1. Geopolitical Uncertainty 🌐
High-stakes diplomatic meetings are underway involving the US, EU, and Ukrainian leaders to discuss the Russia-Ukraine peace deal. Markets inherently dislike uncertainty. As traders await a clear outcome, many are de-risking their portfolios, leading to selling pressure on assets like cryptocurrencies.
2. A Healthy Market Reset 📊
The crypto market just came off a powerful rally where many assets saw gains of 50-100%. This rapid rise led to a buildup of high-leverage positions. Today's dip is forcing a "leverage flush," liquidating over-extended traders. While painful for some, this is a standard market mechanism that washes out speculative excess and often creates a more stable foundation for future growth.
3. Shifting Macroeconomic Tides 📉
Just a week ago, a September interest rate cut was seen as a certainty. Now, recent economic data has slightly lowered those odds. Financial markets, including crypto, are incredibly sensitive to central bank policy. The market is now pricing in this small but significant shift in expectations, contributing to the downward pressure.
The Trader's Perspective: Opportunity in Volatility 💡
So, what does this all mean? It underscores a core principle of successful trading: volatility has a source.
For the prepared trader, this isn't a signal to abandon ship. It's a signal to consult your strategy. This is precisely the kind of environment where a clear, data-driven forecast becomes invaluable.
By understanding the root causes of the sell-off, you can better anticipate market structure, manage risk, and identify potential zones of support where "smart money" may begin to re-accumulate.
This is where the difference between a professional and a novice trader becomes clear. Experienced traders welcome every correction or pullback in the market, seeing it as an opportunity to re-enter and profit from the next upward wave. 📈
Therefore, instead of worry and stress, shift your focus to finding key reversal points and defining new entry zones (Watchboxes) for future trades at more attractive prices. View this price correction as a strategic opportunity, not a threat. 🚀
What are your thoughts on this pullback? Are you seeing it as a risk or an opportunity? Let's discuss in the comments. 👇
Trade Smart!
Navid Jafarian
Investing vs. Speculating in Crypto: Stop Mixing the TwoThe crypto market is in a correction, and every time this happens, I see the same pattern repeat: traders and investors talking about the moon — expecting 10x or 100x — but the moment their coin drops by 10%, they panic. They ask “What’s wrong?” or panic that the project is failing.
This is a misunderstanding of what it means to invest versus what it means to speculate. Let’s clear that up.
🚀 The Investor’s Perspective
If you believe Bitcoin is going to 500,000 USD, do you really care if it dips under 100k before reversing?
If you bought Solana with the vision of 1,000 USD, why should a retest of 150 USD make you nervous?
Investors understand:
Markets never move in a straight line.
Patience is essential — big returns require time.
Short-term corrections don’t change a solid long-term thesis.
If you’re aiming for 5x or 10x, you must accept that it takes months or years, not days.
⚡ The Speculator’s Perspective
Speculators play a different game:
They focus on short-term setups.
They use technical analysis and momentum.
They might even short-sell when the conditions align.
Both are fine — but the problem begins when people think they’re “investors” while acting like speculators every time the market moves against them.
🎯 Targets, Plans, and Patience
Here’s what most forget:
The market isn’t a straight line up designed for your convenience or for your dream Lambo
You need to set a clear target and be patient.
Want 5x on BTC? Or 10x on a strong altcoin? Then you’ll have to wait for it.
If you expect daily gains and can’t handle normal corrections, you’re not investing — you’re speculating without realizing it.
🤡 The Quick 10x Illusion
Yes, you can chase 10x in a day or two with meme coins on DEXes. Sometimes it works, most times it ends with rugs or sudden collapses. That’s not investing. That’s just gambling, and you can’t complain when it goes wrong.
✅ Final Thoughts
Decide who you are:
As an investor, set your targets, trust your thesis, and don’t panic on corrections.
As a speculator, play the short-term moves but accept the inherent risks and use discipline.
Crypto can deliver very big returns — but only if you stop mixing long-term conviction with short-term panic.
Patience and discipline will always beat hype. 🚀
P.S.
Let’s take a concrete example: since April, ETH tripled in value in a nearly straight line. What do you expect — for it to keep rising like that to 25k by the end of the year?
Do you look at your portfolio daily expecting more money every single day?
Think also of those who bought ETH with 10 million dollars, not just 3 ETH for 5k.
Maybe they want to mark profits.
Maybe they need a new yacht:)
Their selling affects the market too — and corrections are part of the bull runs.
“Little Entry Ticket” Scam: Why $50 Can Ruin Your Trading CareerI don’t think there’s a single reader here who hasn’t come across this type of scam.
You know the story: “The next BTC! The next ETH! Entry only $50.”
At first sight, it doesn’t even feel dangerous. So what if you lose $50? That’s a few beers on a terrace.
But here’s the problem: it’s not about the money — it’s about your mindset.
________________________________________
How It Works
1. The promise: “Early entry into the next big coin.”
2. The hook: the price of admission is low — $50 or $100, something anyone can afford to lose
3. The thought trap: “I can’t lose much… but what if it moons?”
4. The harvest: thousands of people fall for it, and the scammer collects a fortune.
5. The ending: the token dies, liquidity vanishes, and your “lottery ticket” is worthless.
________________________________________
Why It’s Dangerous
It’s not dangerous because you’ll lose $50.
It’s dangerous because it sets your brain on the wrong track.
• Instead of thinking in terms of probabilities and risk management, you start thinking in terms of what if .
• Instead of trading or investing, you’re gambling.
• And once your mindset shifts that way, you’ll chase “cheap tickets” over and over, until the small losses pile up — or worse, you start adding bigger amounts hoping for that one lucky hit.
________________________________________
Final Note
Trading or investing isn’t about lottery tickets. It’s about discipline, probabilities, and outcomes.
If you find yourself drawn into a “little entry” scam, remember: the real danger is not losing $50 — it’s losing your focus, your discipline, and eventually your trading career.
Intraday or Swing - Ichimoku, SMA, RSI and Fractal - Full SetupA very simple and effective setup for Swing and Intraday and can be applied to any stocks, crypto, or Forex.
Simplified –
If the Ichimoku Lag Span is ABOVE the price, then the upcoming momentum is Bullish and Trending Upwards.
If the Ichimoku Lag Span is BELOW the price, then the upcoming momentum is Bearish and Trending Downwards.
# Full Setup for Swing, Positional, Intraday and applicable on any scripts: -
• Monthly Ichimoku Lag span must be above Current price
• Price must be above 9SMA
• RSI 60>
• Same setup in Daily as monthly
• You will take entry at fractals which is green and red bar. Green bar is Resistance and Red is support. You will enter near Support for better Risk Management
Note – Example of TVS motors for you all. Now back test with any stocks.
6 Best Tips for Small Trading Accounts (Forex, Gold)
This useful trading tips will help you to efficiently start trading with a small trading account.
A quick note: by a small account, I mean an account size from 10$ - 2000$.
1 - Trade less often
Small account implies a limited amount of money for trading. It means that among dozens of trading opportunities that you spot during a trading day, you should carefully pick only the most promising ones.
I recommend opening maximum 3 trades per day.
2 - Stick to one strategy
One of the ways to trade less frequently is to stick to one single trading strategy. Most of the traders do completely opposite: instead of focusing on one approach, they prefer to trade multiple ones simultaneously.
Trading various strategies requires a lot of capital. The more strategies you follow, the more margin is needed.
With a small trading account, you are risking being left without a free margin for all the trading opportunities that the strategies provide.
3 - Trade liquid instruments with low spreads
When you are picking the financial instruments for your trading, make sure that you select the most liquid ones. You can assess the liquidity of the instrument by a spread. The bigger is the spread, the less liquid is the asset.
Take a look at a spread difference between EURUSD and CHFJPY.
The spread on EURUSD is 0.1 pip.
While the spread on CHFJPY is 2.7 pips.
Spreads directly affect the costs of trading. Bigger spreads reduce the potential profits and increase the risks.
Make sure that you choose the assets with the lowest spreads possible.
4 - Shorten the list of trading instruments
One more option to trade less often is to narrow down the list of your trading instruments. I recommend choosing the maximum of 7 instruments.
7 USD Major Forex Pairs:
EURUSD,
GBPUSD,
USDJPY,
USDCAD
NZDUSD
AUDUSD
USDCHF
is a perfect watch list for a small account trader.
5 - Don't trade higher time frames
Be careful when deciding a time frame to trade.
Remember that the higher is the time frame, the bigger are the stop losses for your traders.
On the left chart is the swing trade that I took with my students on EURUSD chart on a daily. While on the right is the scalping trade taken on 30 minutes time frame.
A stop loss for swing trade is 90 pips and a stop loss of scalping position is 19 pips.
Big stop losses require more free margin and limit the amount of the trades that you can take simultaneously.
For that reason, prioritize lower time frame trading with a small trading account.
6 - Don't risk more than 2% per trade
When traders trade with a small trading account, they often risk a huge portion of their trading account per a single trade.
If you have 100$ trading account, and you risk 20$ per trade, the nominal value of that risk does not look huge. But from a percentage standpoint, it is 20% of the total balance.
Just a 5 trades losing streak will blow such an account.
Make sure that you apply a position size calculator and risk no more than 2% of your account per trade.
Following these recommendations, you will be able to build an effective trading plan that will help you to grow your capital quickly.
❤️Please, support my work with like, thank you!❤️
I am part of Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis.
Stop Chasing Results – Start Building a Winning ProcessIn trading, it’s easy to get caught up in goals like “I’m going to make X amount per month” or “I’m going to have X winning trades each week.”
The problem is that outcomes are something we have very little control over. When we fail to hit these targets, we risk overtrading, taking unnecessary risks, or abandoning our plan – which often leads to even worse results.
The truth is that uncertainty is a constant in trading. Even the most well-developed and “bulletproof” strategy will have losing periods.
Yet many traders interpret a winning trade as proof that the strategy works, and a losing trade as evidence that it’s flawed. This allows single outcomes to dictate confidence and decision-making, creating an emotional rollercoaster that makes us more impulsive and less disciplined.
Shifting the focus to the process means putting your energy into the things you can actually control:
✅ following your strategy
✅ sticking to your risk parameters
✅ completing your analysis before each trade
✅ reviewing how you executed – regardless of the result.
This shift helps maintain discipline during drawdowns, measure success by behavior rather than outcome, and develop the knowledge, skills, and mental tools needed for long-term success.
🎯A first step toward process focus is to set goals based on your actions, not on the market’s results. At the end of each trading day, ask yourself: ”Did I follow my process today?” If the answer is yes, that’s a win – even if the day’s P/L is negative.
🎯When a loss occurs, the next step is to analyze why it happened. Was it a natural result of market movement, or a deviation from your strategy? By consistently identifying these patterns, you build psychological tolerance for losses and learn to see them as a normal part of trading rather than as failures.
When you measure success by your process rather than by single outcomes, you reduce emotional highs and lows and create the conditions for stable performance over time.
💡Pro tip:
So next time you take a loss, pause before judging the result.
Ask yourself:
How well did I follow my process today?
Over the long run, your answer to that question will determine the kind of trader you become.
Happy compassionate trading! 💙
/ Tina the Tradingpsychologist
WHY TRADING IS HARD – EVEN FOR GOD!THE BRUTAL TRUTH ABOUT PERFECT PORTFOLIOS AND IMPERFECT HUMANS
Imagine having access to the same portfolio strategy that made Ray Dalio one of the world's wealthiest hedge fund managers. Picture yourself armed with Nobel Prize-winning research, billion-dollar backtesting results, and a mathematical framework so elegant it seems divinely inspired. Now imagine watching that same strategy torture you psychologically for years while delivering precisely the returns it promised.
Welcome to the God Portfolio paradox: even divine wisdom cannot save us from ourselves.
Ray Dalio's All Weather strategy has generated approximately 12% annual returns with maximum drawdowns of just 4% since its inception in 1996. Compare this to the S&P 500's 10% annual returns with gut-wrenching drawdowns exceeding 50% during major crashes. On paper, the choice seems obvious. In practice, it becomes a psychological nightmare that breaks even sophisticated investors.
Let us examine what this means in concrete terms. Consider two hypothetical investors, each starting with one million dollars in January 2000. Investor A puts everything into an S&P 500 index fund. Investor B implements a simplified All Weather approach: 30% stocks, 40% long-term bonds, 15% intermediate-term bonds, 7.5% commodities, and 7.5% inflation-protected securities, rebalanced quarterly. Both strategies are mathematically sound, historically proven, and widely recommended by financial experts.
The foundation of this cruel reality lies in the inherent conflict between what markets reward and what human nature compels us to do. Markets reward patience, discipline, and contrarian thinking. Human nature drives us toward impatience, emotional decision-making, and herd behavior. Even the most elegant portfolio construction cannot bridge this gap without addressing the psychological challenges that make trading extraordinarily difficult, even when armed with theoretically perfect strategies.
Historical Development and Theoretical Foundations
The intellectual origins of systematic portfolio construction trace back to Harry Markowitz's groundbreaking work on portfolio selection in 1952. Markowitz demonstrated that rational investors should focus on maximizing expected returns for a given level of risk, leading to the development of the efficient frontier concept (Markowitz, 1952). This work established the mathematical foundation for understanding how diversification can reduce portfolio risk without necessarily reducing expected returns.
Building upon Markowitz's framework, William Sharpe introduced the Capital Asset Pricing Model in 1964, which provided a theoretical basis for understanding how individual securities should be priced relative to market risk (Sharpe, 1964). These developments laid the groundwork for more sophisticated approaches to portfolio construction that would emerge in subsequent decades.
The evolution toward all-weather strategies gained momentum in the 1980s and 1990s as institutional investors began to recognize the limitations of traditional 60/40 stock-bond portfolios. Research by Swensen (2000) at Yale University demonstrated how institutional endowments could achieve superior risk-adjusted returns through alternative asset allocation approaches that emphasized diversification across risk factors rather than asset classes.
The modern conception of the "God Portfolio" crystallized with Ray Dalio's development of the All Weather strategy at Bridgewater Associates. Dalio's approach, first implemented in 1996, was based on the premise that economic environments can be characterized by two primary variables: growth (rising or falling) and inflation (rising or falling). By constructing portfolios that perform well in each of these four potential economic scenarios, investors could theoretically achieve more consistent returns (Dalio, 2017).
Risk Parity and Factor-Based Approaches
The theoretical underpinning of modern all-weather strategies relies heavily on risk parity principles. Unlike traditional portfolio construction methods that focus on dollar allocation weights, risk parity approaches seek to equalize the risk contribution of different portfolio components. This methodology was formalized by Qian (2005), who demonstrated that portfolios constructed using risk budgeting techniques could achieve superior risk-adjusted returns compared to market capitalization-weighted approaches.
Academic research has consistently supported the theoretical advantages of risk parity strategies. Maillard et al. (2010) showed that equally weighted risk contribution portfolios tend to be located in the efficient region of the mean-variance frontier, particularly during periods of market stress. Their analysis demonstrated that risk parity portfolios exhibited lower volatility and better downside protection compared to traditional asset allocation approaches.
The factor-based investment framework provides another lens through which to understand all-weather portfolio construction. Fama and French (1993) expanded the understanding of systematic risk factors beyond market beta to include size and value factors, while subsequent research has identified additional factors such as momentum, quality, and low volatility that contribute to long-term returns (Fama and French, 2015).
Contemporary research by Asness et al. (2012) demonstrated that factor diversification across asset classes could provide similar benefits to traditional asset class diversification, but with potentially superior risk-adjusted returns. This insight has led to the development of factor-based all-weather strategies that seek to maintain balanced exposure to different return drivers rather than asset classes per se.
Portfolio Construction Methodology
The construction of an effective all-weather portfolio requires careful consideration of several key principles. First, the portfolio must maintain diversification across different economic scenarios. This typically involves allocating to assets that perform well during periods of economic growth (stocks, corporate bonds, commodities), economic contraction (government bonds, gold), rising inflation (commodities, inflation-protected securities), and falling inflation (nominal bonds, growth stocks).
Second, the portfolio construction process must account for the volatility differences between asset classes. Traditional approaches that allocate equal dollar amounts to stocks and bonds effectively give stocks much greater influence on portfolio performance due to their higher volatility. Risk parity approaches address this by adjusting position sizes to equalize risk contributions, typically resulting in larger allocations to lower-volatility assets such as government bonds.
Third, effective all-weather portfolios often incorporate leverage to achieve target return levels while maintaining risk balance. This concept, popularized by Dalio, recognizes that a truly diversified portfolio may have lower expected returns than a concentrated equity portfolio, but can use modest leverage to enhance returns while maintaining superior risk characteristics (Dalio, 2017).
Academic research has provided empirical support for these construction principles. Duggan and Luo (2021) analyzed the performance of various all-weather portfolio implementations over the period from 1970 to 2020, finding that risk-balanced approaches consistently outperformed traditional asset allocation methods on a risk-adjusted basis. Their study showed that all-weather portfolios exhibited significantly lower maximum drawdowns and more consistent returns across different market regimes.
Implementation Considerations for Retail Traders
While the theoretical foundations of all-weather investing are compelling, retail traders face several practical challenges in implementation. The first consideration involves access to appropriate investment vehicles. Institutional investors can easily implement complex strategies using derivatives and alternative investments, but retail traders must typically rely on exchange-traded funds and mutual funds that may not perfectly replicate desired exposures.
The second challenge relates to rebalancing and monitoring requirements. Effective all-weather strategies require regular rebalancing to maintain target risk allocations as market conditions change. Research by Cesarone et al. (2019) showed that portfolios rebalanced quarterly achieved better risk-adjusted performance than those rebalanced annually, but the benefits diminished when transaction costs were considered for smaller portfolio sizes.
A practical implementation approach for retail traders might involve using a core allocation to low-cost broad market index funds, supplemented by targeted exposures to inflation-protected securities, commodities, and international markets. The specific allocation weights should be determined based on individual risk tolerance and return objectives, but academic research suggests that equal risk allocation across major asset classes provides a reasonable starting point (Maillard et al., 2010).
Technology has significantly improved the accessibility of sophisticated portfolio construction techniques for retail investors. Robo-advisory platforms now offer risk parity and factor-based strategies that were previously available only to institutional investors. Research by D'Acunto et al. (2019) found that retail investors using algorithmic portfolio management services achieved significantly better risk-adjusted returns compared to those managing portfolios manually.
Performance Analysis: When Mathematics Meets Messy Reality
Let us return to our two million-dollar investors and see how their journeys unfolded over 23 years. The numbers tell a story that perfectly illustrates why even perfect strategies can feel imperfect.
By December 2023, Investor A (S&P 500) would have accumulated approximately $4.2 million, representing an 8.1% annual return despite enduring three major crashes. During the dot-com bust, this investor watched $1 million shrink to $490,000 by October 2002. In 2008, the portfolio plummeted from $1.1 million to $550,000 in just six months. The COVID crash of March 2020 vaporized $800,000 in value within three weeks. Each recovery took years of psychological endurance.
Investor B (All Weather approach) would have reached approximately $3.8 million by the same date, representing a 7.6% annual return. The maximum drawdown never exceeded 12%, occurring during the 2008 crisis when the portfolio briefly declined from $1.3 million to $1.14 million. While the absolute returns were lower, the journey was dramatically smoother from a risk perspective.
Here lies the psychological trap: Investor A earned $400,000 more over 23 years but experienced heart-stopping volatility. Investor B earned strong returns with manageable stress but constantly questioned whether they were missing out on greater gains. Academic research by Scherer (2007) confirms this pattern across multiple time periods, showing that risk-balanced portfolios consistently achieved Sharpe ratios of 0.65-0.85 compared to 0.45-0.65 for market capitalization-weighted approaches.
But the real psychological torture begins when we examine year-by-year performance. During the technology boom of 1999, Investor A gained 21% while Investor B managed only 11%. At cocktail parties, Investor B endured stories of neighbors making 50% returns on technology stocks while their sophisticated strategy delivered "boring" results. The mathematical superiority of diversification provided little comfort when everyone else seemed to be getting rich faster.
The 2008 financial crisis reversed this dynamic. When Investor A's portfolio crashed 37% in a single year, Investor B's declined only 8%. Suddenly, the All Weather approach looked brilliant. But by 2013, as markets recovered and Investor A's portfolio surged 32% compared to Investor B's 14%, the psychological pressure returned. This cycle repeated endlessly: validation during crashes, frustration during booms.
Research by Roncalli and Weisang (2015) documented this exact pattern across various risk parity implementations, finding that these strategies experienced their greatest relative outperformance precisely when investors were most tempted to abandon them due to fear. Conversely, they underperformed most significantly during periods when overconfidence made investors most likely to increase risk.
The Psychological Paradox: Why Perfect Strategies Fail Imperfect Humans
Picture this scenario: You have constructed the perfect portfolio based on decades of academic research. Your bond allocation is generating steady 4% returns while your neighbor's Tesla stock has doubled in six months. Your commodities position is providing inflation protection while your colleague's crypto portfolio has tripled. Your carefully calibrated risk management is working exactly as designed, but you feel like an investment failure. This is the God Portfolio's cruelest joke: it tortures you precisely by working as advertised.
Research by Kahneman and Tversky (1979) explains this psychological nightmare through prospect theory. Humans feel the pain of losses approximately twice as intensely as the pleasure of equivalent gains. For our Investor B, this meant that watching bonds decline 2% while stocks soared 15% felt worse than the joy of seeing the overall portfolio gain 8%. The mathematics were favorable, but the psychology was brutal.
Consider a specific example from our All Weather investor during 2017. That year, the S&P 500 delivered a remarkable 21.8% return while the All Weather approach managed 12.3%. On a $2 million portfolio, this meant "missing out" on approximately $190,000 in gains. The fact that this was exactly the risk-return tradeoff the strategy was designed to provide offered no psychological comfort. Friends were buying vacation homes with their stock gains while our mathematically superior investor questioned every diversification principle they had learned.
The diversification curse becomes particularly acute during bull markets. When Bitcoin was reaching $60,000, gold was stagnating. When growth stocks were doubling, value stocks were treading water. When real estate was booming, bonds were declining. At any given moment, roughly half of a diversified portfolio is disappointing its owner. This creates what behavioral economists call "diversification regret," where the very feature that makes portfolios safer makes investors miserable.
Barber and Odean (2001) documented this pattern in their seminal study of retail investor behavior, finding that the average investor underperformed the market by approximately 1.5% annually due to behavioral mistakes. More significantly, they discovered that investors with theoretically superior strategies often performed worse than those using simple buy-and-hold approaches, precisely because the sophisticated strategies required more frequent decision-making opportunities for error.
The timing of psychological stress compounds these challenges. All-weather strategies typically underperform during the euphoric phases of bull markets, exactly when social pressure and media attention focus on superior alternatives. Conversely, they provide their greatest value during market downturns, when fear and uncertainty make it most difficult to appreciate their benefits. This creates a perverse cycle where investors are most likely to abandon superior strategies precisely when they need them most.
Professional fund managers have long recognized these psychological challenges and implemented institutional structures to address them. Large investment committees, detailed investment policies, and professional oversight create barriers to emotional decision-making. Retail traders, lacking these institutional safeguards, face the full psychological burden of strategy implementation without institutional support.
The Implementation Gap: Where Theory Meets Brutal Reality
Let us examine exactly what happened to our All Weather investor during the critical rebalancing moment of March 2020. As COVID-19 panic gripped markets, stocks crashed 30% in three weeks while bonds soared. The mathematical rebalancing signal was crystal clear: sell bonds at their peak and buy stocks at their trough. This was precisely the "buy low, sell high" discipline that makes sophisticated strategies superior.
On March 23, 2020, our investor faced a decision. Their portfolio had shifted from the target 30% stocks to 22% stocks due to the crash. The rebalancing algorithm demanded selling $160,000 worth of bonds (which had gained value) and buying $160,000 worth of stocks (which were in free fall). Every financial media outlet was predicting economic apocalypse. Friends were withdrawing money from markets entirely. The VIX had spiked to levels not seen since 2008.
Yet this was exactly the moment when disciplined rebalancing provides its greatest value. Institutional studies by Choi et al. (2010) show that even professional money managers with dedicated teams and systematic processes struggle with these decisions. Their research found that institutional investors exhibited herding behavior, momentum chasing, and timing errors that reduced returns by 0.5-1.5% annually compared to their own stated strategies.
Our retail investor, lacking institutional safeguards, faced an even more brutal psychological challenge. The rebalancing required not just selling winners and buying losers, but doing so while newspapers screamed about market crashes and neighbors discussed moving money to cash. The mathematical elegance of the strategy provided no emotional comfort when executing what felt like financial suicide.
Consider the specific dollar amounts involved. On that March day, our $2.2 million portfolio required moving $160,000 from the safety of bonds into the chaos of crashing stocks. The transaction felt like throwing money into a financial volcano. Yet investors who maintained rebalancing discipline captured the subsequent recovery, while those who abandoned their strategies missed one of the greatest buying opportunities in market history.
French and Poterba (1991) documented how even sophisticated institutional investors fail to maintain optimal rebalancing discipline, particularly during extreme market conditions. Their study revealed that the very periods when rebalancing provides the greatest benefit are precisely when psychological pressure makes it most difficult to execute. This creates a performance drag that mathematical models fail to capture because they assume perfect implementation discipline.
Transaction costs and timing considerations compound these implementation challenges. While academic studies often assume frictionless trading, real-world implementation involves bid-ask spreads, market impact costs, and tax considerations that can significantly erode theoretical advantages. More importantly, the psychological pressure to time rebalancing decisions optimally often leads to procrastination and poor execution timing.
The technology paradox further complicates implementation. While modern portfolio management tools provide unprecedented analytical capabilities, they also generate information overload that can paralyze decision-making. Investors armed with sophisticated analytics often second-guess their strategies more frequently, leading to excessive tinkering that undermines long-term performance. The abundance of information creates an illusion of control that encourages frequent adjustments rather than disciplined adherence to systematic approaches.
Recent developments in all-weather portfolio construction have focused on incorporating alternative risk factors and improving implementation efficiency. Researchers have explored the inclusion of cryptocurrency, private market investments, and environmental, social, and governance factors into all-weather frameworks. While these developments show promise, the limited historical data and higher complexity may make them less suitable for most retail traders.
Artificial intelligence and machine learning techniques are also being applied to improve portfolio construction and rebalancing decisions. Studies by Gu et al. (2020) have shown that machine learning models can identify subtle patterns in asset relationships that traditional statistical methods might miss, potentially improving the effectiveness of all-weather strategies. However, these approaches require sophisticated infrastructure and expertise that may not be accessible to individual investors.
The growing availability of low-cost index funds and ETFs continues to improve the practical implementation of all-weather strategies for retail traders. As financial markets become more accessible and transaction costs decline, the barriers to implementing sophisticated portfolio construction techniques continue to diminish.
Limitations and Risk Considerations
Despite their theoretical advantages, all-weather portfolios are not without risks and limitations. The first consideration is that these strategies typically rely on historical relationships between asset classes that may not persist in the future. Structural changes in the economy, monetary policy regimes, or financial markets could alter the effectiveness of traditional diversification approaches.
Second, all-weather strategies may struggle during certain market environments. Prolonged periods of low interest rates, for example, can reduce the effectiveness of bonds as a diversification tool and limit the return potential of risk-balanced portfolios. The period following the 2008 financial crisis provided a real-world example of how unconventional monetary policy could challenge traditional portfolio construction assumptions.
Third, the complexity of implementing effective all-weather strategies may lead to higher costs and implementation errors for retail traders. Research by French (2008) showed that the costs of active portfolio management often exceeded the benefits for individual investors, suggesting that simpler approaches might be more appropriate for many retail traders.
Finally, it is crucial to recognize that no portfolio construction approach can eliminate investment risk entirely. All-weather strategies seek to manage and diversify risk rather than eliminate it, and investors should maintain realistic expectations about the performance characteristics of these approaches.
Conclusion: The Humbling Truth About Perfect Strategies
After following our two investors through 23 years of market history, the verdict is both clear and painful: the God Portfolio exists, it works exactly as promised, and it will likely drive you insane in the process. This represents the fundamental paradox of modern finance: we have solved the mathematical puzzle of optimal investing but remain powerless against the human puzzle of optimal behavior.
Our All Weather investor ended with $3.8 million, excellent risk-adjusted returns, and probably years of therapy bills from constantly questioning whether they were missing out on greater gains. Our S&P 500 investor reached $4.2 million after surviving three near-death portfolio experiences and developing an iron stomach for volatility. Both strategies worked. Both investors suffered. Both questioned their decisions countless times.
The numbers reveal the cruel joke: Ray Dalio's strategy delivered exactly what it promised—superior risk-adjusted returns with lower volatility. The 7.6% annual return with maximum drawdowns under 12% represents mathematical perfection in portfolio construction. Yet this same perfection became a source of psychological torture because markets do not reward you for being right; they punish you for feeling wrong.
The research by Kahneman, Tversky, Barber, Odean, and others reveals that investors are their own worst enemies. Loss aversion, regret avoidance, herding behavior, and the psychological burden of diversification create barriers that no amount of mathematical sophistication can overcome. Even professional money managers, equipped with institutional safeguards and advanced technology, frequently fail to capture the full benefits of their sophisticated strategies.
The implementation gap represents perhaps the most sobering aspect of this analysis. The very periods when sophisticated strategies provide their greatest value are precisely when psychological pressure makes them most difficult to execute. Rebalancing during market crashes, maintaining diversification during bull markets, and resisting the temptation to abandon systematic approaches require a level of psychological discipline that few possess consistently.
Consider what this means for ordinary investors. If Ray Dalio, with a team of PhD economists and billions in assets, finds portfolio implementation challenging enough to write entire books about managing human psychology, what chance do retail traders have? The answer is simultaneously depressing and liberating: stop trying to be perfect and start trying to be consistent.
The democratization of sophisticated portfolio tools has created a new form of torture. Modern investors can track their performance minute by minute, compare their returns to dozens of benchmarks, and analyze their portfolio's factor exposures in real time. Our All Weather investor could see precisely how much they were "underperforming" during every bull market rally. This constant performance surveillance often does more harm than good, turning investment management into a source of chronic anxiety.
The most revealing insight from 23 years of data is counterintuitive: trading remains hard not despite sophisticated strategies, but because of them. The S&P 500 investor had one decision to make—buy and hold. The All Weather investor faced quarterly rebalancing decisions, each one an opportunity for psychological torment. Complexity that improves mathematical outcomes often destroys psychological outcomes.
Here lies the brutal irony of the God Portfolio: it works precisely because it acknowledges human limitations, yet implementing it requires overcoming those same limitations. Diversification protects against unknown risks, but it guarantees that you will always be wrong about something. Risk management reduces portfolio volatility, but increases emotional volatility as you constantly question your conservative approach.
The practical lesson for retail traders is humbling: your biggest enemy is not market volatility, economic uncertainty, or even bear markets. Your biggest enemy is the person staring back at you in the mirror every morning, armed with emotions, cognitive biases, and an internet connection full of alternative investment strategies that appear superior to whatever you are currently doing.
The final lesson from our 23-year experiment is both humbling and liberating: the best portfolio is not the one that produces the highest returns or the lowest volatility, but the one you can sleep with at night and stick with through decades of doubt. Our All Weather investor earned $3.8 million and maintained their sanity. Our S&P 500 investor earned $4.2 million and probably aged a decade from stress. Both outcomes represent success, depending on your definition of victory.
Perhaps the God Portfolio's greatest gift is not its mathematical elegance or superior risk-adjusted returns, but its role as a mirror reflecting our own psychological limitations. It teaches us that even with perfect information, optimal strategies, and divine inspiration, we remain gloriously, frustratingly, irredeemably human. And in a world where markets are increasingly dominated by algorithms and artificial intelligence, perhaps our humanity—flawed though it may be—is the only edge we have left.
The God Portfolio exists. It works. It will also drive you slightly insane while delivering exactly what it promises. This is not a bug in the system; it is the system. Even God would find trading difficult in a universe where mathematics must be executed by creatures driven by emotion, shaped by bias, and cursed with the ability to doubt their own best decisions. The sooner we accept this cosmic joke, the sooner we can stop searching for divine strategies and start building human ones that account for our beautiful, profitable, and perfectly imperfect nature.
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Skeptic's Night Byte: 3 Hacks to Beat a Losing StreakHey, it’s Skeptic 👋
We’ve all been there — losing streaks suck, but they don’t have to wipe you out.
In under 60 seconds, I’ll show you 3 quick hacks that make a huge difference:
Build friction into your trading decisions
Stop letting news events wreck your win rate
Use higher time frames to avoid the noise
Simple moves. Massive impact.
If this helped, hit that boost so I know to drop more tips like this.
Swing Trading Setup - RSI and SMA 9 & 200🔍 Step-by-Step Monthly Chart Analysis
1. Start with the Monthly Chart – The Bigger Picture
9 SMA (Simple Moving Average)
→ Check if the current monthly candle is closing above the 9 SMA.
This indicates a bullish trend and acts as confirmation for strength in the longer term.
RSI (Relative Strength Index)
→ RSI should be above 50.
This suggests momentum is on the bullish side.
2. Align Daily Chart with Monthly
On the daily chart, confirm the following:
Price is also closing above the 9 SMA
RSI is also above 50 and crossing upward
✅ When both monthly and daily charts are aligned with these indicators, this is a strong confirmation for entry.
3. Stop-Loss Strategy
Use the most recent swing low on the daily chart as your Stop Loss.
This keeps your risk defined and close to your entry level.
4. Exit or Red Flag Condition
If the monthly candle closes below the 9 SMA, this is your major signal to:
Watch out for a trend reversal
Expect that the daily chart might cross below the 200 SMA
Also, watch for monthly RSI potentially crossing below 60, indicating waning momentum
📌 This acts as a signal to either exit the trade or tighten your stop loss.
The Illusion of ControlThere comes a point in every trader’s journey when you do everything right, and it still goes wrong.
You plan the trade meticulously, plot the levels, define your risk, wait patiently for the setup, and enter with the kind of discipline that would make any textbook proud. You follow your rules. You trust your process. And yet, the market does what it does!
It breaks through your stop as if your risk management was never there. Sometimes it gaps hard against you, leaving no room to act. Sometimes it simply meanders sideways, wearing down your conviction until, exhausted and uncertain, you exit - only to watch the market finally rally the moment you’re out.
This experience is frustrating and discouraging. Yet, for those with enough experience, it's a familiar scenario.
It's not just about losing money, though that definitely stings. This kind of hit really messes with your confidence, throws off your game, and makes you feel disconnected from your work. Before you know it, those sneaky little doubts creep in: Did I miss something? Could I have stopped this? Am I just not good enough at this yet?
So you go back to the charts, really digging into every detail. You watch replays, try out new filters, and pile on more indicators, scrutinizing the trade from every possible angle. You tell yourself this super careful process makes you better, a crucial part of being a professional. But if you're real with yourself, it's more than just getting better. Underneath all this striving for improvement is often a deeper reason: you really want to be in control.
We often discuss risk management, patience, and emotional discipline, yet we seldom acknowledge our deep-seated desire to control the market. We invest countless hours in learning, testing, and refining, expecting our efforts to yield tangible results. When the market doesn't respond as we anticipate, it's disheartening. This is because, at our core, we not only aspire to be skilled traders but also crave the belief that we are truly in command.
The market just does its thing, plain and simple. It doesn't care how much work you put in or how carefully you prepare. It's not about rewarding effort; it just moves. Trying to find a reason for every little change is pointless, like trying to argue with the ocean. You can't outsmart randomness; you can only learn to coexist with it.
The best traders do prepare with care. They’re thoughtful, meticulous, and dedicated. But many cross a subtle line, often unknowingly - the line where preparation morphs into obsession, where working harder becomes an emotional shield, and where we start to believe that if we can just control every input, we can guarantee the output.
This is where it all becomes dangerous. Not financially, necessarily, but psychologically. When your self-worth becomes intertwined with your performance, every loss starts to feel personal. Every drawdown feels like an indictment. You tell yourself you’re striving for excellence, but what you’re really chasing is certainty; and in a domain governed by uncertainty, that’s a recipe for chronic frustration.
The truth is, trading isn't about being right all the time, or even most of the time. The real skill is staying cool when you mess up and not freaking out when things go sideways. You don't have to be perfect; you just need to handle the unknown without needing to control it. You won't pick up this tough lesson from courses, forums, or even tons of practice, unless you're truly reflecting on what you're doing. You learn it by watching winning trades go bad, by handling losses without freaking out, and by being able to stay cool when things get uncomfortable.
You know that annoying feeling we sometimes get? It's usually just fear, popping up as worries about messing things up, looking foolish, or not being quite good enough. When you're trading, these fears can seriously mess with your mind. You might jump into trades too quickly, fiddle with your stop-loss, settle for smaller gains, or just abandon your whole strategy when things get tough. We might try to convince ourselves we're being clever, but typically, we're just trying to escape feeling uncomfortable.
Trying too hard to control the market often hurts your edge. Trading systems usually don't fail because of math errors; they fail because traders don't have the patience to stick with them through tough times and let them do their job.
Every trader eventually faces a fundamental, liberating truth: you are not in control. Once you accept this, you can stop trying to control the uncontrollable and instead concentrate on what you can manage: your risk, routine, discipline, and behavior.
Detaching from the outcome isn't about indifference or a lack of concern; it's about embracing trust. Trust in your preparation. Trust in your edge. Trust in the law of large numbers — that over time, if you execute consistently, the results will follow. Not perfectly, not smoothly, but faithfully.
You build trust over time, often without even realizing it. It's about sticking to your plan even when things aren't going your way, taking losses in stride, and not messing with something that's working, just because it hasn't paid off yet.
Over time, your trading approach transforms. You no longer dwell on every loss or micromanage winning trades. The urge to constantly adjust your system after a bad week/month subsides. Your perspective broadens; you begin to think in terms of years, not just days. This shift cultivates a deeper, process-driven confidence, untethered from mere numbers. You stop striving for absolute control, and in doing so, discover a sense of peace.
True mastery isn't about dominating the market, but rather relinquishing the illusion that you ever could.
The Hidden Cost of ActivityHow Trading Frequency Undermines Retail Investor Profitability
In the age of commission-free trading and social media-driven hype cycles, the line between investment and entertainment has blurred. Retail traders now execute millions of trades a day across global markets, empowered by sleek mobile apps and real-time alerts. Yet beneath this democratization of access lies a sobering truth: higher trading frequency among retail investors is consistently linked with lower profitability.
This article explores the academic research surrounding this paradox. Drawing from large-scale studies in Colombia, the UK, China, and India, it demonstrates that the more frequently retail investors trade, the less likely they are to outperform the market—or even earn positive returns. But this is more than a statistical quirk; it reveals deep behavioral biases, structural disadvantages, and misunderstood costs that plague the average individual investor.
Colombian Evidence: The More You Trade, the Less You Keep
One of the most comprehensive investigations into retail trading behavior comes from Colombia. Over a ten-year period, researchers analyzed more than 5.3 million trades made by over 42,000 individual investors on the Colombian Stock Exchange. The results were stark: retail investors lost between 4.0% and 4.4% annually in gross abnormal returns, depending on the asset pricing model used (CAPM, Fama-French, Carhart) (Villatoro & González, 2021). These losses persisted even before commissions and taxes were deducted.
However, the more striking pattern emerged when the researchers categorized traders by activity level. The most active traders consistently underperformed their less active counterparts. This performance gap remained even after controlling for other variables such as portfolio size, trading experience, and market conditions. In short: trading more often almost guaranteed worse outcomes.
Interestingly, when controlling for how long traders had been active in the market, a new nuance emerged. Those with longer tenure and moderate trading frequencies tended to perform better, suggesting that experience and discipline can partially offset the costs of frequent trading. But for most retail investors, especially newcomers, a high frequency of trades was a losing game.
Behavioral Pitfalls and the Illusion of Control
Why do so many retail traders engage in self-defeating behavior? Behavioral finance offers compelling answers. Overconfidence, a hallmark of retail trading behavior, leads individuals to overestimate their ability to time the market (Barber & Odean, 2001). Many traders fall victim to what’s known as the “illusion of control”—the belief that more activity translates into better outcomes. In reality, each trade introduces friction, often in the form of bid-ask spreads, slippage, and execution delays, not to mention mental fatigue and stress.
A revealing study from the UK examined 7,200 individual trading accounts. It found that the top 10% of traders accounted for over half of all trading activity. These individuals placed an average of 69 trades per year, compared to just six trades annually for the bottom 80% (Feng & Seasholes, 2005). And yet, the frequent traders substantially underperformed. Most of the losses were not due to bad stock picks, but rather to cumulative trading costs and poorly timed entries and exits.
Another study from an experimental setting demonstrated that even in a zero-commission environment with rational expectations, excessive trading reduced final wealth. Participants who traded most actively were consistently those who took the greatest risks and made the least profit (Kirchler et al., 2012). Activity, it seemed, was a poor substitute for strategy.
The Amplifying Effect of Social Trading Platforms
In China, where social trading platforms allow users to follow and copy the trades of so-called investment leaders, the relationship between frequency and performance takes an even more complex turn. A 2022 study found that when traders received more comments or likes on their trades, their trading frequency increased significantly. But rather than improving outcomes, this social reinforcement led to deteriorating performance (Wu et al., 2022).
The mechanism here is subtle but powerful. Social validation creates a feedback loop that encourages more trades, not necessarily better ones. The result is a dangerous mix of herding behavior and overconfidence, both of which are well-documented causes of underperformance in financial markets. And since these platforms often gamify trading with leaderboards and rewards, they unintentionally promote high-frequency trading behaviors that are detrimental to most participants.
India’s Derivatives Market: A Harsh Lesson in Leverage
The consequences of high-frequency trading become especially severe in leveraged markets. India’s derivatives market offers a cautionary tale. Between 2021 and 2024, retail traders lost an estimated ₹1.81 trillion (around USD 21.7 billion) trading futures and options. A staggering 93% of retail traders incurred net losses, and the median loss per participant ranged between ₹100,000 and ₹200,000 (SEBI, 2024).
These losses were not random. Regulatory analysis showed that retail traders often entered and exited positions too quickly, misjudging volatility and price momentum. Many strategies were reactive rather than analytical, driven by short-term news or social media chatter. The vast majority of losses were concentrated among high-frequency traders who overestimated their ability to anticipate market movements.
In contrast, institutional players and algorithmic trading firms profited handsomely during the same period. With better access to information, faster execution systems, and rigorous risk management, they capitalized on the very inefficiencies created by retail traders.
The Free Lunch Illusion: The True Cost of “Zero Commission” Platforms
Much of the rise in trading frequency among retail investors can be traced to platforms like Robinhood, eToro, or Trade Republic, which advertise commission-free trading. While these platforms have lowered the barrier to entry, they often obscure the true costs embedded in trade execution.
Commission-free brokers typically rely on a business model called payment for order flow (PFOF). In this setup, the broker routes retail orders to market makers or high-frequency trading firms, which pay the broker for the opportunity to execute the trade. These market makers profit from the bid-ask spread, often at the expense of retail traders. Although legal in the U.S., PFOF is banned in countries like the UK and Canada due to conflict-of-interest concerns (The Economist, 2021).
Critics argue that PFOF incentivizes brokers to maximize volume rather than execution quality. This can result in poorer price execution for the trader, even if no explicit commission is charged. A 2020 SEC report on the GameStop-Robinhood episode found that retail investors may be disadvantaged by a few cents per share—minor per trade, but substantial over thousands of trades (SEC, 2020).
The ease of access, gamified interfaces, and perceived lack of cost encourage frequent, impulsive trading—especially among young and inexperienced investors. Robinhood users, for example, were found to trade options 88 times more than Charles Schwab users, and equities 40 times more often (Barber et al., 2021). Such behavior has been linked with higher loss probabilities, particularly in volatile markets.
From Reddit to Real Life: A Personal Turnaround
On trading forums such as Reddit, anecdotal stories often mirror these empirical patterns. One day trader shared a telling experience: after months of executing 10 or more trades per day, his results were consistently negative. However, after shifting to a more selective approach—averaging around three trades per day—his performance dramatically improved. He reported a win rate of 48.8%, an average reward-to-risk ratio of 2.17, and a monthly return exceeding 20R (i.e., twenty times the risk unit per trade). While anecdotal, stories like this are common. They suggest that reducing frequency allows for better decision-making, more stringent trade selection, and improved emotional control—all of which contribute to higher profitability.
The Core Problem: Frequency Without Edge
The critical difference between successful high-frequency strategies (like those used by hedge funds) and retail trading lies in the presence of a quantifiable edge. Professional firms use complex models, co-location servers, and massive datasets to gain millisecond advantages. Retail traders, by contrast, often increase frequency without any corresponding informational edge. The result is a compounding of noise, cost, and error.
Academic consensus is clear: unless trading frequency is backed by superior information, strategy, and execution, it is more likely to erode returns than enhance them. The average retail trader is better served by thoughtful, low-frequency strategies that minimize costs, reduce emotional friction, and allow performance to compound over time (Lo et al., 2004).
Less Is More
The allure of high-frequency trading for retail investors is understandable. It promises engagement, excitement, and the illusion of control. But the data tells a more sobering story: more trades almost invariably lead to worse outcomes. From Colombia to India, from Reddit anecdotes to formal econometric studies, the verdict is consistent. The path to profitability is paved not with activity, but with restraint.
For retail traders seeking long-term success, the prescription is clear: trade less, think more, and remember that in markets, patience is often more profitable than precision timing.
References
Barber, B.M. and Odean, T., 2001. Trading is hazardous to your wealth: The common stock investment performance of individual investors. Journal of Finance, 55(2), pp.773–806. Available at: faculty.haas.berkeley.edu
Barber, B.M., Huang, X., Odean, T. and Schwarz, C., 2021. Attention induced trading and returns: Evidence from Robinhood users. NBER Working Paper No. 28906. National Bureau of Economic Research. Available at: www.nber.org
Feng, L. and Seasholes, M.S., 2005. Do investor sophistication and trading experience reduce behavioral biases?. Review of Finance, 9(3), pp.305–351. Available at: faculty.haas.berkeley.edu
Kirchler, M., Lindner, F. and Weitzel, U., 2012. Markets, bubbles, and crashes: Laboratory results on the effectiveness of circuit breakers. Journal of Economic Behavior & Organization, 83(1), pp.179–189. Available at: pubmed.ncbi.nlm.nih.gov
Lo, A.W., Repin, D.V. and Steenbarger, B.N., 2004. Fear and greed in financial markets: A clinical study of day-traders. American Economic Review, 94(2), pp.352–356. Available at: web.mit.edu
Securities and Exchange Commission (SEC), 2020. Staff Report on Equity and Options Market Structure Conditions in Early 2021. U.S. Securities and Exchange Commission. Available at: www.sec.gov
SEBI (Securities and Exchange Board of India), 2024. Retail derivatives trading losses total ₹1.81 trillion over three years. Reuters, 23 Sep. Available at: www.reuters.com
The Economist, 2021. The future of retail broking: Zero-commission trading has a hidden cost. The Economist, 4 Feb. Available at: www.economist.com
Villatoro, D.I. and González, M.A., 2021. Retail investors’ behavior and performance: Evidence from the Colombian stock market. Heliyon, 7(12), p.e08535. Available at: www.sciencedirect.com
Wu, Y., Duan, Y., Xu, G. and Shen, H., 2022. The impact of social interaction on retail investors’ trading behavior in social trading platforms. Financial Innovation, 8(1), Article 39. Available at: link.springer.com