One technique that has helped me create 6-figure trading strategies:

Monte Carlo Simulations.

But what is it? and how do you do the same?

Here's everything you need to know (explained simply): What are Monte Carlo Simulations?

It is a powerful statistical technique to model the probability of different outcomes.

At its core, it performs a risk analysis by resequencing the historical trades of a backtest.

It keeps doing this for 100s of iterations.

I just finished backtesting 3 of the most popular volume trading indicators over the past 24 years.

The results were surprising...

Here is what I found summarized in 3 minutes: Context:

Each one of these indicators solve different problems when implementing them into a strategy.

I will discuss their basic implementation and provide a simple historical backtest,

But further testing techniques are necessary for more thorough validation of the results.

9 books that explain how algorithmic trading works and how to get started:

1. Building Winning Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading 2. Quantitative Trading: How to Build Your Own Algorithmic Trading Business

Look at this guy.

He built Renaissance Technologies, a hedge fund that returned 66%, per year for 30 years.

Dubbed the "Quant King", I watched 10+ hours of his public talks to learn everything I could about him.

Here are his most powerful lessons that made him $30 billion: The importance of large sample sizes to be able to tell the statistical significance of an "anomaly," e.g., a potential predictive signal.

Over the past 5 years, I've read over 100 research papers on trading strategies.

And the truth is, 95% of them held absolutely no alpha.

So, I've created a list of 11 that would be worth your time (bookmark this thread): Context:

Most published ideas require refinement rather than immediate application;

Their true value lies in fostering creativity. I absorb as much information as possible to enhance my ability to build/find strategies.

So here are the 10 I found quite useful:

Tim Grittani turned $1,500 into $13,000,000.

He has priceless insights into being a consistent trader as he has been so for over a decade.

Here are 6 takeaways on how he did it: 1. Focusing on one setup.

Concentrating on mastering a single setup before expanding can lead to faster profitability and development as a trader.

In the beginning, there is a lot of ignorance and debt you have to overcome to really understand a setup.

This is Thomas Peterffy.

He's worth an estimated $38.3 billion.

He is the founder of one of the biggest brokerages in the world and was one of the first electronic traders.

Here's his story from 100 dollars to billions: Peterffy was born in Budapest on September 30, 1944.

In 1965, Peterffy emigrated to the United States with his father, but with no room for him he gave Thomas $100 and told him to "make something of himself".

He is now the 57th richest man.

3 techniques to optimize any trading strategy that you need to know.

1. Grid Search Context:

Be careful with the optimization of strategies, as they can often lead to overfitting if done aggressively.

Make sure to combine your testing with robustness tests as well.

With that out of the way, here are three optimization techniques explained simply:

This is Shigeru Fujimoto.

An 87-year-old investor who has made over $12,000,000.

He is often referred to as "Japan's Buffett".

Here's his investing lessons: Context:

Shigeru Fujimoto was born in 1936 in Hyogo prefecture.

Despite his family's agricultural background, Fujimoto chose a different path and began working in a pet shop.

After leaving the pet store at age 19, Fujimoto started a Mahjong parlor in Kobe.

Parameter Sensitivity is one of the best tools in quantitative trading.

But 99% of traders don't understand it.

Here's how it works explained simply so you can build better strategies: What is Parameter Sensitivity?

It measures how changes in input parameters affect a trading strategy's output or performance metrics.

These metrics could be:
• Total return
• Sharpe ratio
• Max drawdown

The primary objective is to tell how sensitive the strategy is.

6 books that explain how the market works.

1. Market Microstructure in Practice 2. Algorithmic Trading and DMA: An introduction to direct access trading strategies

5 statistical illusions that uncover why your backtests are misleading.

1. Data snooping. This occurs from overfitting a strategy to noise in the data by commonly testing too many parameters with your optimization.

Such as using 50 parameters on 2 years of data.

A good way to avoid this is to focus on simplicity, use out-of-sample testing and logical parameters.

7 cheat codes I now know 1,988 days into trading I wish I knew day 1.

1. Leverage the power of the "holy grail" in trading. The "Holy Grail" in trading isn't one strategy,

But a collection of uncorrelated ones.

Billionaire hedge fund managers like Ray Dalio and the late Jim Simons have highlighted this.

Building such a portfolio takes time and effort, but understanding this offers a clearer path.

The 28-year-old who destroyed a whole bank.

Nick Leeson.

He lost over $1 billion with almost a single trade.

Leaving a note "I'm sorry".

Here's the crazy story of Nick Leeson, who inspired the movie Rogue Trader: Nick Leeson was born in Watford, Hertfordshire, to working-class parents.

After finishing sixth form in 1985 with six O Levels and two A Levels, he started work at Coutts Bank.

In 1989, he later joined Barings Bank, one of England's oldest banks.

Which he would later bankrupt.

This guy was an institutional trader at a firm with over $161 billion in AUM.

And was one of the most impactful traders in my journey.

Steal these 6 lessons from him on building systematic trading systems to beat the market: 1. Simplicity in trading systems.

Rob Carver emphasizes keeping trading rules and strategies as simple as possible, avoiding over-complication for marginal improvements in backtests.

Simple systems tend to be more robust.

Machine learning can be one of the most powerful tools in quantitative trading.

But 99% of traders use it in the wrong way.

Here are 6 must-read books on how professionals use it (so you can too): 1. Machine Learning in Finance: From Theory to Practice

I've been able to scale my trading to over 6 figures,

All because of data.

Here are all the data sources I have used (pros and cons of each): Polygon

Pros:
• Perfect for equities data
• Amazing endpoints
• Affordable
• Great documentation

Cons:
• Options data is a bit lackluster

I have backtested 100s of strategies.

Here are 6 indicators that have made me the most: Indicators are mathematical calculations used to analyze markets.

Each indicator normally falls into one of these categories:
• Trend
• Volatility
• Oscillator
• Breadth
• Fundamental

There are no magical indicators, but some do work better than others.

The single most important thing to do when trading:

Survive.

Sadly, 99% of traders neglect this core principle.

Here's the formula that professional traders use to make and keep millions: There are countless ways to fail at trading, like emotions, overtrading, etc

But one of the most common, even for those who've made millions:

Placing bets too large for their account size.

This concept is called Risk of Ruin, a formula every trader needs to know.

I just finished re-reading The Laws Of Trading by Agustin Lebron.

It's one of the best books for trading I've read.

Here are the 6 laws you need to know: Before we jump into the laws that helped re-shape my trading,

Why did Agustin Lebron call them laws?

7 Books that serve as a crash course on automated trading (full of strategies).

1. Professional Automated Trading: Theory and Practice 2. Quantitative Momentum: A Practitioner's Guide to Building a Momentum-Based Stock Selection System

By Jack Vogel, Wesley Gray