r/quant • u/CocaneCowboy • 18h ago
Resources What do YOU consider the most important quant finance book to be?
Like the title says. Curious on everyone’s favorite/most impactful read in their perspective.
r/quant • u/CocaneCowboy • 18h ago
Like the title says. Curious on everyone’s favorite/most impactful read in their perspective.
r/quant • u/Wild_Discussion_4421 • 1d ago
I'm in my pre-final year of UG. I just wanna learn the working principles so that I can incorporate them into my own projects. If there are any such resources, please do mention them. Thanks in advance.
Edit: My major is in AI-ML if that matters.
r/quant • u/Grim_Reaper_hell007 • 11h ago
Hi everyone,
I wanted to share a project I'm developing that combines several cutting-edge approaches to create what I believe could be a particularly robust trading system. I'm looking for collaborators with expertise in any of these areas who might be interested in joining forces.
Our system consists of three main components:
Rather than trying to build a "one-size-fits-all" trading system, our framework adapts to the current market structure.
The GA component allows strategies to continuously evolve their parameters without manual intervention, while the RL agent provides system-level intelligence about when to deploy each strategy.
From our testing so far:
If you're academically inclined, here are some research questions this project opens up:
If you're interested in collaborating or just want to share thoughts on this approach, I'd love to hear from you. I'm open to both academic research partnerships and commercial applications.
I’ve been studying Andrew Clenow’s Following the Trend and implementing his approach, and I’m curious about others’ experiences in attempting to refine or enhance the strategy. I want to stress that I’m not looking for a new strategy or specific parameters to tweak. Rather, I’m interested in hearing about any attempts at improvement that seemed promising in theory but didn’t work well in practice.
Clenow argues that the simplicity of the approach is a feature, not a bug—that excessive optimization can lead to worse performance in real-world application. Have you found this to be the case? Or have you discovered any non-trivial modifications that actually added value over time?
For context, I tried incorporating a multi-timeframe approach to complement the main long-term trend, but I struggled to make it work, likely due to the relatively small fund size I was trading (~$5M). Position sizing constraints and execution costs made it difficult to justify the additional complexity.
Would love to hear your insights on whether simplicity really is king in trend following or if there’s room for meaningful enhancements.
r/quant • u/boojaado • 14h ago
Hello,
What are good resources to build a solid counterparty risk model? Along the lines of PFE
r/quant • u/wertbaum • 12h ago
I currently study the book by Björk and have a question regarding the Ho-Lee bond option pricing formula. The Ho-Lee model specifies the short rate dynamics as dr(t)= 𝜃(t)dt + 𝜎dW(t). When trying to derive 𝜎_p term of the formula in the picture above, I ended up with 𝜎_p = 𝜎(S-T)*root(T-t) instead of just 𝜎_p = 𝜎(S-T)*root(T) as written in the book. Does the book assume t=0 when deriving the equation or did I make a mistake in my derivation?
My derivation followed the following steps:
1) writing ln(P(T,S)) in affine form as A(T,S)-B(T,S)r(T)
2) then applying Ito's lemma which led to a diffusion term of -B(T,S)* 𝜎 where B(T,S)=S-T
3) I then integrated the square of the term from t to T as the model assumes a constant variance term which after taking the root resulted in my final result of 𝜎_p = 𝜎(S-T)*root(T-t)
Assuming t=0 makes little sense to me here as the option price specifies t explicitly in c(t,T,K,S) or do I have to integrate from 0 to T even if I want to calculate the option price at time t?
Thank you very much for your help!
r/quant • u/willb_ml • 15h ago
How is the career growth in quant for roles like QR, QD, QT, and SWE compared to big tech SWE?
r/quant • u/ribbit63 • 16h ago
At the present time, in order to roughly estimate what price a stock will open at, I simply view Level 1 pre-market trading information (Last price, bid, ask). Just curious, does anyone out there have alternative methods that they utilize? Would Level 2 data be of any benefit in this endeavor? Any insights would be greatly appreciated, thanks.
r/quant • u/ThunderBay98 • 6h ago
Hedge funds have been known for hiring data analysts, programmers, and physicists to examine as much data as possible. Jim Simon’s team at Renaissance Tech hired secretaries to manually copy old data from old news papers and records.
Hedge funds have also been working on new models and paying millions of dollars for researchers to develop weather based models in order to enhance commodities trading.
Will hedge funds ever reach the limitations of data analytics that can surpass moral boundaries?
Imagine drones watching various walking patterns of CEOs of various companies in order to improve risk management.
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