Book Summary: Expert Advisor Programming by Andrew Young

Expert Advisor Programming by Andrew Young: Book Review and What It Teaches

Last updated: 3 July 2026 · By Spencer Li, CFTe

“Expert Advisor Programming” by Andrew Young is a hands-on, beginner-friendly guide to building automated trading systems (expert advisors, or EAs) on the MetaTrader 4 platform using the MQL4 programming language. It walks you from the basics of the MetaEditor environment, through writing and testing a strategy, optimizing its parameters, and adding risk management, to debugging and forward-testing the finished robot. It is best suited to traders and programmers with a basic grounding in both, though a motivated beginner can follow it. Its core message is honest and worth repeating: an EA is only a tool, and it cannot rescue a strategy that has no real edge to begin with. Note one limitation up front: the book does not cover machine learning or AI, so treat it as a foundation in classic MQL4 automation, not a modern AI-trading text.

Here is what the book actually covers, who should read it, and where it stops.

What is an expert advisor (EA)?

An expert advisor (EA) is a program that runs inside MetaTrader 4 and trades automatically on your behalf. It reads price data, applies the rules you have coded, and then places, manages, and closes orders without you clicking anything. You write it in MQL4 (MetaQuotes Language 4, the platform’s built-in programming language) using the MetaEditor (the code editor bundled with MetaTrader 4).

In plain terms, an EA is your trading plan turned into software. That is the appeal, and also the trap. If your plan has an edge, the EA executes it tirelessly and without emotion. If your plan does not, the EA loses money faster and more consistently than you ever could by hand.

What is the book about?

The book is built in three parts, and the structure tells you the intended path.

Part	What it covers	What you walk away able to do
Part 1: Foundations	The MetaTrader 4 platform, the MQL4 language, and the MetaEditor environment	Read and write basic MQL4, find your way around the tools
Part 2: Building the EA	Creating and testing a strategy, optimizing parameters, implementing risk management	Turn a trading idea into a working, risk-managed robot
Part 3: Hardening it	Debugging, troubleshooting, backtesting, and forward testing	Find the bugs and pressure-test the system before it touches real money

The main message is the one most beginners skip past: EA programming is a powerful tool, but it rewards a solid understanding of both the markets and the language. The code is the easy half. The edge is the hard half.

About the author

Andrew Young is a professional trader and programmer with over a decade in the financial markets. He has a computer-science background and has worked as a software developer for large corporations, and he has built trading strategies and automated systems for various financial institutions. He has written several books on trading and programming and speaks regularly at industry conferences. So the book comes from someone who has actually shipped both code and strategies, not a pure theorist.

The 10 key ideas from the book

These are the points the book keeps returning to. Read them as a checklist for anyone thinking about automating a strategy.

Learn the platform first. A working knowledge of MetaTrader 4 and the MQL4 language is the price of entry for building any EA.
The strategy comes before the code. A profitable trading strategy is the first step. The EA is just the delivery mechanism.
Optimize with caution. Over-optimization (overfitting) tunes a system so tightly to past data that it falls apart on new data. More optimization is not more profit.
Bake in risk management. Risk control is not a bolt-on. It belongs inside the system from the start.
Backtest and forward-test. Backtesting (running the EA over historical data) and forward testing (running it live on small or demo capital) are both needed to judge whether it actually works.
Budget time for debugging. Debugging and troubleshooting are slow, unglamorous, and necessary. This is most of the real work.
Use functions and libraries. Reusable functions and libraries make an EA more efficient and far easier to maintain.
Pull in external data where it helps. External data sources can extend what an EA reacts to.
Add custom indicators. Custom indicators can sharpen the signals an EA trades on.
Optimization techniques have a ceiling. Methods like parameter optimization (and, in principle, neural networks) can improve performance, but only on top of a strategy that already has an edge.

How do you apply the book to your own trading?

The book pairs each idea with a practical move. Here is the applied version, in the order you would actually do them.

Define a real edge by hand first. Analyze the markets, find the pattern or trend you can trade, and prove it works manually before you write a line of code.
Optimize parameters, but lightly. Test combinations and pick a robust one, not the single best-fit curve.
Code in your risk rules. Stop loss and take profit are not optional features. They are what keep one bad run from ending the account.
Backtest, then forward-test. Use both to surface problems the other one hides.
Debug systematically. Expect errors, and fix them methodically rather than guessing.
Write maintainable code. Use functions and libraries so the next change does not break three other things.
Layer in external data where it genuinely adds signal, not noise.
Add custom indicators to refine entries and exits.
Apply optimization to squeeze the system, knowing it cannot manufacture an edge that was never there.
Monitor and adjust continuously. A live EA is not “set and forget”. Markets change, and the robot needs minding.

What the book does not cover

A few honest boundaries, so you buy it for the right reasons.

It is built around MetaTrader 4 specifically, though the concepts carry over to other platforms.
It mostly uses forex examples, but the methods apply to other markets too.
It assumes a basic grounding in trading and programming. A complete beginner can follow it with effort, not effortlessly.
It does not cover machine learning or AI. If you came for an AI-trading book, this is not it. It is a classic-automation foundation.

Where the human edge comes in

Here is the part the book is quietly honest about, and the part I want to underline. An EA will execute your rules flawlessly, around the clock, with no fear and no greed. What it will never do is supply the edge. It cannot tell you that your strategy is curve-fit, that your backtest is lying to you, or that the market regime that made it work has quietly ended. Automation removes the emotion and the manual labor. It does not remove the need for judgment. The code is the cheap half now. Knowing whether the strategy underneath it is real, and pulling the plug when it stops being real, is the human edge, and it is the first of the Five Edges no robot can trade for you.

FAQ

Is “Expert Advisor Programming” by Andrew Young good for beginners?
It is suitable for traders and programmers who have a basic understanding of both. A complete beginner can follow it with effort, but it is not a no-prerequisites book. The willingness to learn matters more than prior expertise.

What is an expert advisor in MetaTrader 4?
An expert advisor (EA) is a program that runs inside MetaTrader 4 and trades automatically using rules you code in the MQL4 language. It places, manages, and closes orders without manual input.

Does the book cover AI or machine learning for trading?
No. The book covers classic MQL4 automation, strategy testing, optimization, risk management, and debugging. It does not cover machine learning or AI.

What programming language do you need to build an EA?
MQL4 (MetaQuotes Language 4), the built-in language of MetaTrader 4. You write it in the MetaEditor environment that ships with the platform.

Can an expert advisor make a losing strategy profitable?
No. An EA only executes the rules you give it. If the underlying strategy has no edge, automating it usually loses money faster and more consistently. The strategy has to work first.

Now that you have the map of what this book teaches, would you add it to your reading list? And if you have already built an EA, what tripped you up most: the code, or proving the strategy actually worked? Let me know in the comments.

For the wider reading list, see the pillar: Best Investing and Trading Books of All Time.

Want a system you can run by hand before you ever automate it? Grab the free 15-Minute Swing Trading Starter Kit. It is the exact routine I use to scan once a day and trade any market in 15 minutes, and it is the kind of edge worth proving manually before you hand it to a robot.

About the author. Spencer Li is the founder of Synapse Trading and a Certified Financial Technician (CFTe) with 15 years of trading across stocks, forex, crypto, commodities, and bonds. His trade log is public, 404 trades, losses left in. He teaches low-risk swing trading in 15 minutes a day, one system for any market.

Education, not financial advice. Synapse Trading is not licensed by MAS to advise on investment products. Trading carries risk of loss; past performance is not indicative of future results.

Best Investing and Trading Books of All Time (pillar) · Algorithmic and automated trading guide · Backtesting a trading strategy · Risk management for traders

0 Comments/by Spencer Li

Book Summary: Evidence-Based Technical Analysis by David Aronson

Book Summaries

thumbnail Book Summary Evidence Based Technical Analysis Applying the Scientific Method and Statistical Inference to Trading Signals by David Aronson

Evidence-Based Technical Analysis by David Aronson: Summary and Key Lessons

Last updated: 3 July 2026 · By Spencer Li, CFTe

Evidence-Based Technical Analysis by David Aronson is a 2006 book that applies the scientific method and statistical inference to chart-based trading signals, arguing that most traditional technical analysis is subjective interpretation that has never been properly tested. Aronson’s core claim is simple: a pattern or indicator only earns a place in your trading if it survives a rigorous statistical test, not because it looks good on a hand-picked chart. The book teaches you how to run those tests yourself, using hypothesis testing, Monte Carlo simulation (running thousands of randomised what-if scenarios to see if a result could be luck), and Bayesian inference (updating your probability estimate as new data arrives). It is worth reading if you want to stop trading on stories and start trading on evidence. Do note that it is dense, stats-heavy, and aimed at short-term traders working mostly with stocks, so it is not a casual beach read.

Here is what the book actually argues, the ideas worth keeping, and how to apply them without a statistics degree.

Who is David Aronson?

David Aronson is a statistician and quantitative analyst who spent over twenty years in finance. He holds a PhD in statistics and has written several books on quantitative methods in markets, including this one and a follow-up on Bayesian inference in finance.

That background matters, because it tells you the lens. Aronson is not a chart guru selling you a pattern. He is a statistician asking an uncomfortable question: can you prove any of this works? Most technical analysis books never ask it. This one is built around it.

What is Evidence-Based Technical Analysis about?

The book is about using scientific methods to separate the technical analysis that works from the technical analysis that only looks like it works.

Aronson’s argument runs like this. Traditional technical analysis leans on subjective reading of charts and patterns. Two analysts look at the same chart and see two different things. That subjectivity produces inconsistent, unreliable results, and worse, it is unfalsifiable: if the pattern fails, you can always say you read it wrong rather than admit the pattern itself is useless.

His fix is to treat every trading rule as a hypothesis to be tested against data. Run the rule across a large historical sample. Measure whether its returns are genuinely better than random. If they are not, throw the rule out, no matter how convincing the chart looked. He walks through the statistical machinery to do this honestly, including how to avoid fooling yourself with data mining (testing so many rules that one looks good by pure chance).

Personally, this is the part I value most. It is not the specific tests. It is the mindset shift from “this pattern feels right” to “show me the numbers, then show me they are not luck.”

The 10 key ideas, and how to actually use each one

The book gives you ideas and a method. Most readers absorb the ideas and never apply them. So here is each core idea paired with the one practical move that turns it into something you do, not just something you nodded at.

Key idea from the book	How to apply it
Traditional technical analysis is subjective and often unreliable	Stop trusting a pattern because it “looks good”; demand a tested edge before you risk money
Statistical methods raise the accuracy of your predictions	Treat every trading rule as a hypothesis and test it on data before you trade it
Use data to test your trading ideas	Keep a historical sample and run your rule across all of it, not three flattering charts
Hypothesis testing and Monte Carlo simulation evaluate strategies	Use Monte Carlo (thousands of randomised runs) to check whether a result could just be luck
Indicators like moving averages and RSI are tools, not magic	Know what each indicator actually measures, then test if it adds edge in your market
Bayesian inference updates probabilities as new data arrives	Adjust your confidence in a setup as fresh results come in, do not anchor to the first read
Risk management and stop-loss orders limit losses	Define your stop and position size before entry, every time, no exceptions
Combine technical with fundamental and news analysis	Use chart signals alongside context, not as the only input
Backtesting evaluates a strategy on historical data	Backtest honestly, and reserve fresh data the rule has never seen to confirm it
Excel and software tools implement the methods	You do not need to code; a spreadsheet is enough to start testing rules properly

The thread running through every row is the same: test before you trust.

The trap the book is really warning you about

Here is the quiet danger Aronson keeps circling, and it is the most useful thing in the book.

If you test enough rules against enough data, some of them will look profitable by pure chance. Test a thousand random rules and a handful will have a great-looking equity curve that means absolutely nothing. This is data mining, and it has wrecked more “backtested” systems than bad luck ever has.

The cure is statistical discipline. You account for how many rules you tested. You use methods like Monte Carlo to ask, “could this result have happened by random chance?” And you keep a slice of data the rule has never touched, so a strategy that only memorised the past gets caught before it costs you real money.

Most traders skip this and wonder why their amazing backtest dies in live trading. The book exists to stop that.

Where the human edge comes in

Aronson hands you the toolkit to test signals, and that toolkit gets cheaper and faster every year. A modern scanner or AI can backtest a thousand rules before you finish your coffee. That part is close to free now.

What it will not do is keep you honest. It will not stop you from running the test a hundred ways until one version looks good. It will not tell you that your beautiful backtest curve is overfit nonsense, or that you cherry-picked the sample, or that you should walk away from a system that “works” only on data it has already seen. The statistics catch the luck; the discipline to accept what the statistics say is yours. That judgment, the willingness to kill your own good-looking idea because the evidence says so, is the first of the Five Edges no machine can trade for you.

Who should read this book?

Read it if you are a short-term trader who wants to stop guessing and start testing, and you are comfortable with a book that takes statistics seriously. It includes an introductory chapter for readers new to the stats, so you do not need to arrive fluent, but you do need patience.

Skip it, or save it for later, if you want quick setups you can trade tomorrow morning. This book changes how you think, not what you trade on Monday. It is focused on short-term trading, mostly in stocks, though the testing mindset travels to any market. And it explains the statistical methods clearly without giving you step-by-step software instructions, so you bring the implementation.

Personally, I would put it on the list of any serious trader who has ever lost money on a pattern that “always works.” It is the book that explains why it did not.

FAQ

What is Evidence-Based Technical Analysis about?
It argues that most traditional technical analysis is subjective and untested, and shows how to use statistical methods, hypothesis testing, Monte Carlo simulation, and Bayesian inference, to test whether a trading signal genuinely works or only looks good on a chart.

Is Evidence-Based Technical Analysis worth reading?
Yes, if you are a short-term trader who wants to test your ideas rigorously and you are comfortable with statistics. It is dense and stats-heavy, so it is less suited to beginners wanting ready-made setups.

Who is David Aronson?
David Aronson is a statistician and quantitative analyst with over twenty years in finance and a PhD in statistics. He wrote Evidence-Based Technical Analysis and a follow-up book on Bayesian inference in finance.

Do I need to know statistics to read it?
Some basic statistics helps, but the book includes an introductory chapter for newcomers. You do not need to code; a spreadsheet is enough to start applying the methods.

What is the main lesson of the book?
Do not trust a pattern or indicator because it looks good. Treat every trading rule as a hypothesis, test it against data, and use statistical discipline (especially guarding against data mining) to make sure the result is not just luck.

So, would you add Evidence-Based Technical Analysis to your reading list? And if you have already read it, what stuck with you? Let me know in the comments.

If you want the wider map of which trading books are worth your time, read the pillar: Best Investing and Trading Books of All Time.

Want the system behind the testing? Grab the free 15-Minute Swing Trading Starter Kit, the exact routine I use to scan once a day and trade any market in 15 minutes, built on rules I have actually tested.

Education, not financial advice. Synapse Trading is not licensed by MAS to advise on investment products. Trading carries risk of loss; past performance is not indicative of future results.

Best Investing and Trading Books of All Time (pillar) · Trading in the Zone by Mark Douglas · Reminiscences of a Stock Operator · How to start backtesting a trading strategy

0 Comments/by Spencer Li

What is the FOMC (Federal Open Market Committee) Meeting and How to Trade it?

Economics & News Trading

What is the FOMC, and Why Does It Move the Market?

Last updated: 3 July 2026 · By Spencer Li, CFTe

The FOMC (Federal Open Market Committee) is the branch of the U.S. Federal Reserve that sets monetary policy, mainly the federal funds rate (the interest rate at which banks lend to each other overnight). It meets eight times a year, about every six weeks, and after each meeting it releases a statement, economic projections, and forward guidance (its signal about where policy is headed). Markets move on these meetings because interest rates set the price of money: when the Fed raises rates, bond yields tend to rise and bond prices fall, and riskier assets like stocks often come under pressure; when it cuts, the reverse tends to happen. So when traders ask “why does the FOMC matter,” the short answer is that it is one of the few scheduled events that can re-price stocks, bonds, and currencies all at once, on a known date and time. That last part is the useful bit. You always know when it is coming.

Here is what the FOMC is, what it actually decides, and how traders read it without getting run over.

What is the FOMC and where did it come from?

The FOMC is part of the Federal Reserve System, the central bank of the United States. It was created by the Banking Act of 1935, the same act that reshaped the Fed itself. Its job is monetary policy: setting interest rates and using other tools to influence the economy.

It has 12 voting members:

The seven members of the Board of Governors (appointed by the U.S. President, confirmed by the Senate, serving 14-year terms).
Five of the 12 Federal Reserve Bank presidents (chosen by their own Reserve Banks, serving one-year terms on the committee).

So it is not one person turning a dial. It is a committee, and committees disagree, which is why the dissents in a vote are worth reading.

How does the FOMC operate?

The committee meets eight times a year, roughly every six weeks, on a schedule set well in advance and published on the Federal Reserve’s website. Meetings are held in Washington, D.C., and usually run two days.

The “set well in advance” part is the trader’s gift here. Unlike most market-moving news, an FOMC meeting is on the calendar months ahead. You can plan around it.

What comes out of an FOMC meeting?

After each meeting, the FOMC publishes a statement. It covers current economic conditions, the policy decision, and anything else the committee wants on the record. It is one of the most closely read documents in finance because it shows the committee’s thinking, not just its action.

Here is what the statement and its companion releases actually contain, and why each line matters to a trader:

What is released	What it tells you	Why a trader watches it
Federal funds target range	The current overnight interest rate band	Direct driver of bond yields and the cost of money
The vote (and any dissents)	How united the committee is	Dissents hint at where policy could swing next
Economic projections	Expected path of rates, GDP, unemployment, inflation	Shapes the outlook for stocks and riskier assets
Assessment and balance of risks	The committee’s read on the economy	Frames whether the bias is toward tightening or easing
Forward guidance / language changes	Signal about future policy	Often moves markets more than the rate decision itself

Two more timing notes worth knowing. The data in the statement is not revised after the meeting, but the committee issues fresh projections and may tweak the statement language at every meeting. And the minutes, the detailed account of the discussion and reasoning, come out three weeks later. The statement is the headline; the minutes are the footnotes, and the footnotes sometimes move the market a second time.

How do traders and investors actually use FOMC data?

The statement and projections shape the direction of interest rates, and through rates, the value of stocks, bonds, and currencies. Most traders watch a few specific things:

The rate decision itself. A hike tends to push bond yields up and bond prices down; a cut tends to do the opposite. Fixed-income positions react first.
The economic projections. If the committee expects strong growth, traders may lean toward stocks. If it expects weakness, money often rotates toward the relative stability of bonds.
The forward guidance. If the Fed signals rates will stay low for a while, that can support stocks in the short term. If it signals hikes are coming, traders may tilt defensive.
The language changes. A few changed words on inflation or the balance of risks can tell you which way the committee is leaning before the numbers do.

Notice the pattern. None of this is about predicting the decision. It is about reading the committee’s bias and positioning for the direction of travel.

News trading on FOMC data

“News trading” means trading the reaction to a scheduled release, in this case the FOMC. A few ways traders approach it:

Interest rate decisions. A surprise hike can knock bond prices down as yields jump; a surprise cut can lift them. Traders adjust positions around the gap between what was expected and what was delivered.
Economic projections. Stronger-than-expected growth projections can support stocks; weaker ones can weigh on them.
Forward guidance. A shift in guidance changes expectations for future policy. A signal of near-term hikes, for instance, can pressure bond prices ahead of the actual move.
Statement language changes. A change in tone on inflation or risk can reset expectations for rates, GDP, unemployment, and inflation all at once.

Personally, I am cautious with trading the FOMC release itself. The first move is often a head-fake: price spikes one way on the headline, then reverses once traders finish reading the detail. The spread widens, the volatility is brutal, and the algorithms are faster than you are. For most swing traders, the better edge is not guessing the number. It is knowing a high-volatility event is on the calendar and managing risk around it, sizing down, or simply standing aside until the dust settles.

Where the human edge comes in

A news calendar will flag the FOMC date for you. A model can even forecast the rate decision. Neither will tell you to size down into the event, to ignore the first 15-minute whipsaw, or to skip the trade entirely on a day when the edge is just noise. The calendar is the easy part. Knowing when not to trade an event this volatile is judgment, the first of the Five Edges that no algorithm trades for you.

FAQ

What does FOMC stand for?
FOMC stands for the Federal Open Market Committee, the branch of the U.S. Federal Reserve that sets monetary policy, mainly the federal funds interest rate.

How often does the FOMC meet?
The FOMC meets eight times a year, about every six weeks, on a schedule published in advance on the Federal Reserve’s website. Each meeting usually runs two days in Washington, D.C.

Why does the stock market move on FOMC days?
Because the FOMC sets interest rates, which set the price of money. A rate change or a shift in forward guidance can re-price bonds, stocks, and currencies at once, so traders react fast to even small surprises.

What is the difference between the FOMC statement and the minutes?
The statement comes out right after the meeting and gives the decision and the committee’s headline thinking. The minutes come out three weeks later and give the detailed discussion and reasoning behind the decision.

Should beginners trade the FOMC announcement?
For most beginners, no. The first move after the release is often a head-fake that reverses once the detail is read, and the volatility is hard to manage. It is usually safer to size down or stand aside around the event than to trade the headline.

Now that you know what the FOMC is and how its decisions ripple through the market, is it something you will add to your trading toolbox? Let me know in the comments.

And if you want the bigger picture on trading scheduled news without getting whipsawed, read the pillar: The Complete Guide to News Trading and Economic Events.

Want a calmer way to trade? Grab the free 15-Minute Swing Trading Starter Kit. It’s the exact routine I use to scan once a day and trade any market in 15 minutes, FOMC week included.

Education, not financial advice. Synapse Trading is not licensed by MAS to advise on investment products. Trading carries risk of loss; past performance is not indicative of future results.

The Complete Guide to News Trading and Economic Events (pillar) · How interest rates affect the stock market · How to trade economic news releases · What is the federal funds rate

0 Comments/by Spencer Li

Weekly Market Wrap: Is this Finally a New Bull Market?

Market Analysis

Investors’ views on inflation, recession risk, and monetary policy were fickle throughout much of 2022.

Recently, a positive bias has emerged, reflected in the downward shift in interest rate expectations and upward move in securities prices since mid-October.

Investors appear to be interpreting economic data as evidence that a dovish pivot (Fed stopping interest rate hikes and possibly cutting them) is imminent.

Bad news (slowing job growth, dismal economic survey data, falling property values, negative real wage growth) is seen as good news when viewed through the lens of inflation and monetary policy.

But what is missing in this discussion is the real economy and what may have to happen to it for this market narrative to play out.

The dovish pivot narrative is driven by the expectation that U.S. inflation will continue to decline at a fairly rapid rate.

However, it’s also noteworthy that the Fed’s success in slowing inflation thus far has occurred while China, the world’s second-largest economy, has been hampered by pandemic-related restrictions.

The Fed is typically prone to keeping policy either too tight or too loose for too long.

Fed officials only have to look back at “the great inflation” of 1965 to 1982 to see what can happen when policy is loosened too quickly.

The market’s optimism could make it more likely that the Fed keeps tightening policy.

So, all things considered, the risk of over-tightening seems to be higher than the likelihood of a premature pivot.

What would cause the Fed to make a significant shift in policy?

Most likely a meaningful recession or market crisis – risks that aren’t being reflected in today’s earnings expectations or credit spreads.

Investors are focusing far more on what negative economic data means for interest rates than the potential implications for the real economy.

Join our “Daily Trading Signals” for real-time trading opportunities!

[Photo: Lake Aydarkul, Uzbekistan – See my full travel photo log!]

For our weekly market wrap, we go through some of the trade calls and analysis from last week, which gives us valuable insights for the week ahead.

We cover 3 main markets with a total of 200+ counters, so we will never run out of trading opportunities:

Forex, CFDs, commodities, bonds
US stocks, ETFs, global stock indices
Cryptocurrencies, crypto indices

By covering a broad range of markets, we can focus our attention (and capital) on whichever market currently gives the best returns.

Click here to receive all these signals in real-time for only $67 a month! You will get several signals a day, and even taking just 1 trade the whole month can easily cover the fee, so what are you waiting for?

Weekly Market Outlook Video

Weekly Market Outlook (22 January 2023)

CNY week will see slow markets
Watch out for tech layoffs and earnings

Portfolio Highlights

Weekly Portfolio Updates (22 January 2023)

Not much changes, since the market has not moved much.

Forex & Commodities Market Highlights

AUDCHF – Excellent short entry, and trade is now in the money. Can consider trailing SL to breakeven to reduce risk.

EURAUD – Great entry near the support level, and the trade is now in the money. Can continue to hold for more profits since the trend is still bullish.

EURCHF – Excellent entry near support, after pulling back from an ascending triangle breakout.

USDJPY (H4 chart) – Congrats to those who managed catch this short!

Gold (XAUUSD) – Still going strong, after some small profit-taking. I have circled the previous buying/consolidation points.

Probably heading up to test the previous swing highs.

The Periodic Table of Commodities Returns 2022

Stock & Bond Market Highlights

S&P 500 (US500) – The major trendline is back in play, after the recent rally failed to break past it.

If it takes out the previous swing low (~3750), then the bears will start stepping in full force and we will probably see new lows.

Now that we are more or less certain that inflation is coming down, the next major concern is slowing growth and worse company earnings.

S&P 500 Calendar Year Returns: 1928-2022

200,000+ laid off in tech since the beginning of 2022. And for no reason other than “everyone else is doing it”.

Tech workers need a union.

Crypto Market Highlights

Bitcoin (BTCUSD) – After an impressive rally the last few weeks, prices are now consolidating.

If prices can break out of the small bull flag, this could spark more buyers coming in and start an uptrend.

However, if volumes falter, then traders could end up taking the chance to dump their holdings on this rally.

Click here to receive all these signals in real-time for only $67 a month! You will get several signals a day, and even taking just 1 trade the whole month can easily cover the fee, so what are you waiting for?

Good luck, and may next week bring more excellent profits!

0 Comments/by Spencer Li

Weekly Market Wrap: Slowing Growth & Earnings in the US?

Market Analysis

US nominal growth is experiencing a significant deceleration, as evidenced by declining services PMI and lower momentum of Non-Farm Payrolls, with a negative rate of change for real growth and moderating wage growth indicating negative inflationary pressures.

Inflation in the US is currently affecting services the most, which is where nearly two-thirds of consumer spending goes.

Services include housing, insurance, healthcare, education, travel and hotel bookings, subscriptions, streaming, telecommunication, haircuts and more.

Inflation in the Eurozone is increasing due to excessive printing of real-economy money and a relatively inelastic basket of goods and services.

European core inflation may lag US core inflation by 6 months but it is expected to continue to increase over the next 3-6 months, which will force the ECB to be hawkish.

The Chinese economy is experiencing a significant reopening, which is expected to boost growth and force Emerging Markets fund managers to reallocate to China and other countries.

This push from the Chinese reopening is offset by the pull of a deteriorating global growth and inflation picture.

In light of these mixed news, has the stock market bottomed, or was the recent rally a bull trap?

Stayed tuned in our “Daily Trading Signals” private Telegram channel!

[Photo: Cappadocia, Turkey – See my full travel photo log!]

For our weekly market wrap, we go through some of the trade calls and analysis from last week, which gives us valuable insights for the week ahead.

We cover 3 main markets with a total of 200+ counters, so we will never run out of trading opportunities:

Forex, CFDs, commodities, bonds
US stocks, ETFs, global stock indices
Cryptocurrencies, crypto indices

By covering a broad range of markets, we can focus our attention (and capital) on whichever market currently gives the best returns.

Click here to receive all these signals in real-time for only $67 a month! You will get several signals a day, and even taking just 1 trade the whole month can easily cover the fee, so what are you waiting for?

Weekly Market Outlook Video

Weekly Market Outlook (15 January 2023)

1. Bearishness of USD – might be oversold
2. No clear direction of US stock market
3. Bullishness of China stock market
4. Watch for TLT as early indicator
5. Crypto market reversing?
6. CNY market slowdown
7. Soft landing or recession?

Portfolio Highlights

Weekly Portfolio Updates (15 January 2023)

Not much changes, but this week I could be doing some rebalancing, which I will update when it happens.

Stay tuned!

Forex & Commodities Market Highlights

USDJPY – Congrats to those who followed the trade, prices have hit the first TP!

Gold (XAUUSD) – This trade has also hit the TP, congrats to all those who followed!

USDSGD – As predicted, prices have fallen to the major support level. Congrats!

Since prices are quite oversold and the support is strong, this will be a good level to have a price rebound.

USDSGD is near the 5 year low, and is at the bottom of a wide trading range. Weekly RSI is in the oversold region.

Good chance of a rebound from these levels, which means if you are looking to buy US dollars, now is a good time to get it cheaper.

And if you are planning to fund your trading accounts in USD, you can also take advantage of the good conversion rates now.

AUDJPY – Continuation of the downtrend

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What if don’t get a recession this year?
What happens if we get a soft landing?

Click here to receive all these signals in real-time for only $67 a month! You will get several signals a day, and even taking just 1 trade the whole month can easily cover the fee, so what are you waiting for?

Good luck, and may next week bring more excellent profits!

0 Comments/by Spencer Li

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