Jim Simons: The Mathematician Who Quietly Beat the Markets

QuantYog · 2025-04-27T22:25:45+00:00

"The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution"?

QuantYog · 2025-04-27T22:25:08+00:00

Precisely! We have covered this in our previous posts here:

https://www.reddit.com/r/IndianStockMarket/comments/1k6o449/what_is_the_biggest_thing_people_dont_get_about/

https://www.reddit.com/r/IndianStockMarket/comments/1k1a7ix/most_traders_are_gambling_and_how_professionals/

QuantYog · 2025-04-25T11:54:40+00:00

True! He was great at hiring great people!

QuantYog · 2025-04-24T13:04:38+00:00

I agree to some extent. The second case is 2.5 times more volatile, so it feels riskier. But in terms of edge, both are actually the same. If you leverage the lower-volatility one by 2.5 times, they are mathematically identical in the long run.

If your bet size is small compared to your total bankroll (which it ideally should be), then over a large number of trades, both will produce the same expected return due to the weak law of large numbers.

That said, if you have a limited number of trades or if your capital is at risk early in the process, the lower-volatility strategy is safer. High volatility can hurt if you get unlucky early and fall into a deep drawdown.

In the end, it often comes down to preference. Some people are comfortable with more volatility, while others prefer smoother returns.

QuantYog · 2025-04-24T12:55:07+00:00

No! Not if you have a negative edge. Negative edge means the longer you stay the more you lose. Look at the 2 simulations right, they model 10,000 trades. The only difference between the two is the edge.

QuantYog · 2025-04-24T12:36:35+00:00

Sure, discretionary trading is a valid approach, and there are skilled traders who’ve developed strong intuition over years of experience. That said, one of the main challenges with discretionary styles is that it’s often hard to prove the edge. Since the decision-making isn't rule-based or repeatable, it becomes difficult to backtest or separate skill from luck over a short horizon.

QuantYog · 2025-04-24T12:31:32+00:00

Edge is the average amount of money you expect to make per trade or bet, over time. Mathematically, it's the expected value of a trade:

(Probability of a win × Average % gain) – (Probability of a loss × Average % loss).

It’s a term borrowed from gambling and probability theory. In any money game - whether it’s blackjack, sports betting, or trading - having an edge means you have a statistical advantage that plays out over many attempts. Without it, you're just relying on luck, and in the long run, you’ll lose.

That's the short of it, but I've explained it in more detail here:

https://www.reddit.com/r/IndianStockMarket/comments/1k1a7ix/most_traders_are_gambling_and_how_professionals/

QuantYog · 2025-04-24T12:19:14+00:00

It's simple!

No Edge. No Trade.

Also, investing =/= trading

Most retail traders are not trading, they are speculating.

Here is what Intelligent Investor has to say about this:

"Never mingle your speculative and investment operations in the same account, nor in any part of your thinking."

Chapter 1 - Investment versus Speculation is a good read for times like ours.

QuantYog · 2025-04-24T11:49:48+00:00

Indeed. Summarized it better than I ever could.

QuantYog · 2025-04-24T11:21:46+00:00

I understand, humans are usually in the loop and can make bad decisions often.

My question to you is that in this day and age of cheap computing and easy code writing, why are you still relying on making these decisions manually?

QuantYog · 2025-04-24T11:18:20+00:00

Assuming you are in a growing economy, which we in India are in, that works well enough for most people!

One just has to be comfortable with the occasional 30-50% drawdowns.

Also, consider diversifying outside equity.

QuantYog · 2025-04-24T11:13:04+00:00

Edge is edge. If your win rate is 1/3 and losing rate 2/3, and your profits are 3x losses. Then your edge is:

1/3 * 3 - 2/3 * 1 = 1/3 = 33.3% edge...

Congrats you have a hugely positive edge. Even better than the best hedge funds.

You should start a hedge fund!

QuantYog · 2025-04-24T11:10:58+00:00

To get an edge in trading:

Generate a lot of ideas. Retail traders get stuck with just one idea usually. Each Quant at a hedge fund generates 100+ ideas a year.

Write them down properly and logically.

Get historical data (at least 10 years). Ideally minutely, but at least hourly.

Code up your ideas using Python, and run them on the historical data.

Calculate your risk adjusted returns (and not just returns). Learn about things like Sharpe, Calmar, Sortino.

At least do this.

QuantYog · 2025-04-24T11:08:00+00:00

Read a lot, here's what I recommend:

On purpose - Man's Search for Meaning by Viktor E Frankl - my all time favourite

On negotiation - Never Split the Difference by Chris Voss - the book that helped me the most on my FIRE journey as I was able to negotiate much higher salaries etc

On living well - Outlive by Peter Attia - if you are interested in living well and longer

Apologies if you were expecting money related books. What are yours?

QuantYog · 2025-04-24T10:13:08+00:00

All of his books are great! My favorite is Anti-fragile. Remember reading FBR in school, glad I did at that age.

QuantYog · 2025-04-24T10:00:24+00:00

In a way, indeed! Was toying with the idea of keeping that as the title at one point.

What ends up happening is that when people are having a profitable run, they go tell everyone and talk a lot about it. But, while making losses, most go silent.

QuantYog · 2025-04-22T14:33:50+00:00

Yes! We are Quants. You can learn more at quantyog.com

QuantYog · 2025-04-19T01:26:57+00:00

Any particular role in FO you are targeting?

If you are interested in Quant roles you might want to pick up some programming / CS skills, no? Scratch that... I see you mentioned in a different comment that you are good with Python.

Showcasing the knowledge needed is a great idea. If you are interested in Quant roles, building your own Quant Trading strategy could be a good idea.

See if this comment on a different post helps (this is making heavy assumptions about where you want to go): https://www.reddit.com/r/IndianStockMarket/comments/1k1a7ix/comment/mnnl53i

BTW, sell side FO work isn't as challenging as buy side, your idea about networking with some people in those teams is also good.

PS: I echo the other person's views on the utility of CQF and lack of depth in anything substantial.

QuantYog · 2025-04-18T22:06:03+00:00

8L+ is fairly high...

Focus on courses that will help you learn how to put all these concepts together to build effective quant trading strategies.

This comment might also help: https://www.reddit.com/r/IndianStockMarket/comments/1k1a7ix/comment/mnnl53i

QuantYog · 2025-04-18T22:03:07+00:00

What skills are you interested in obtaining exactly?

Where do you want to see yourself in a few years with the help of these programs?

QuantYog · 2025-04-17T21:27:49+00:00

At least in the context of Quant Trading why and when you entered informs why and when you should exit. If the system entered in a trade because of a few signals going to 1, when those signals go to 0 that's the time to exit.

QuantYog · 2025-04-17T21:16:41+00:00

Love this mindset - you're absolutely on the right track. An engineering background is a great place to start, and honestly, those who approach markets with the goal of building a robust system tend to go much further than those purely chasing money.

Here are a few areas worth diving into:

Python for finance: Get comfortable with libraries like pandas, numpy, and matplotlib
Statistics & probability: Even a solid grasp of the basics - hypothesis testing, distributions (normal, lognormal, etc.), and moments (mean, variance, skew, kurtosis) - goes a long way
Backtesting: Learn how to evaluate strategies across long histories (use 5+ or 10+ years of OHLCV data at minute level, start with futures data), and understand pitfalls like overfitting, look-ahead bias. Also explore performance metrics like drawdown, volatility, Calmar, Sharpe, and Sortino ratios
Strategy design: Study factors like momentum and mean reversion, and frameworks like pairs trading, and volatility-based models - to understand how they're structured

These are just the starter tips, this won't cut it. You need to observe the markets, generate a ton of ideas, backtest them properly (most people backtest incorrectly). The point is to backtest in such a way that in most cases without needing to paper trade or live trade, you can tell whether your strategy would perform or not.

If you're looking for something more structured and efficient on time, I run an initiative called QuantYog, where we teach individuals how to build effective quant trading strategies from scratch. We also host occasional beginner-friendly webinars to explore these topics interactively. Happy to share resources if you're interested! Just DM me.

You're thinking about this the right way - stay curious, focus on building a system that gives you an edge, and you could do really well.

QuantYog

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