Recent Quantitative Finance Research Across Volatility, Factors, and Hedging
Summary
The document collects recommendations for quantitative finance papers and research areas, spanning rough volatility, option-implied recovery of future distributions, asset pricing factors, rates options, behavioral finance, and reinforcement learning for hedging and execution. It gives brief descriptions of selected contributions: rough volatility models use irregular volatility paths and fractional processes; recovery theory seeks to infer physical distributions from option prices; and factor research proposes competing models while examining whether return anomalies replicate robustly. Other entries point readers toward volatility option pricing, joint S&P and VIX calibration, and investment-based asset pricing.
This is a curated discussion rather than a systematic literature review. The recommendations mix papers from different publication years, and at least one cited rates-options paper is acknowledged as only narrowly meeting the question’s recency criterion. The summaries are too brief to establish comparative performance or consensus. Readers should verify publication details and use the references as starting points, selecting material that matches their subfield and research question.
Key ideas
- The recommendations cover rough volatility models and their use in option pricing.
- Recovery theory investigates whether option prices can reveal physical return distributions.
- The factor-model discussion includes competing asset pricing approaches and concerns about replicable anomalies.
- Other suggested topics include rates options, investment-based pricing, behavioral finance, and reinforcement learning for hedging and execution.
- The list is an informal reading guide, not a systematic or uniformly recent review.
Tags
Full text
# What are the recent quantitative finance papers we should all read?
# What are the recent quantitative finance papers we should all read?
Which papers released in the last five years should all quants read to keep up to date on recent developments?
See this question for the best must-read papers of all time. The bar for inclusion for an answer to this question is a bit lower. I'm more interested in papers that start new trends or give a very good overview of a new subfield.
Another older question with good answers is this one.
## Answer by Kevin (score 19)
https://quant.stackexchange.com/a/61158
### Rough Volatility
Gatheral, Jaisson and Rosenbaum (2018, QF) further popularise a stream of the literature which emphasises the non-smoothness of volatility paths. These models build on a fractional Brownian motion, with Gatheral et al. proposing a Hurst parameter $H<\frac{1}{2}$ and demonstrating the model's ability to match volatility time series. Fractional volatility models trace back at least as far back as Comte and Renault (1998, MF).
An extensive list of papers in the area is given here. Recent contributions include, for example, El Euch and Rosenbaum (2019, MF) deriving the corresponding characteristic function for the rough Heston model (at least numerically) and Horvath, Jacquier and Tankov (2020, SIAM JFM) studying how rough volatility models apply to the pricing of volatility options.
### Recovery Theory
In one of his last published papers, Steve Ross tried the impossible to recover the physical distribution of future stock prices from observed option prices, see his 2015 JF publication.
Jackwerth and Menner (2020, JFE) cast doubt whether the recovery theorem is compatible with future realised returns and variances. Peter Carr answers this question here on Quant.SE and gives an online lecture about the topic here.
### Factor Models
Fama and French (2015, JFE) add two new factors to their seminal three factors model (namely RMW and CMA, capturing risk associated to profitability and investment). Hou, Xue and Zhang (2015, RFS) provide an alternative four factor model based on $q$-theory.
Barillas and Shanken (2018, JF) and Stambaug and Yuan (2017, RFS) propose alternative factors. Hou, Mo, Xue, Zhang (2017, RF) show that their $q$-theory model seems to dominate others using spanning regressions.
### Other Good Reads
- Guyon (2020, Risk) proposes a solution for the joint calibration problem of S&P and VIX options.
- Grasselli (2017, MF) presents his 4/2 stochastic volatility model which neatly unifies the Heston model and the 3/2 model.
- Zhang (2017, EFM) summarises a large body of research on investment-based asset pricing, culminating in the investment CAPM, which is as simple as the standard (consumption) CAPM yet empirically more successful in explaining the cross-section of stock returns.
- Cochrane (2017, RF) gives a recent survey about popular asset pricing models.
- RFS editor Itay Goldstein invited leading researchers to share their opinions about which questions will invoke interesting research in asset pricing for the years to come, see the 2021 paper here.
- Harvey, Liu and Zhu (2016, RFS) and Hou, Xue and Zhang (2020, RFS) cast doubt over the ever growing ''factor zoo'' in finance by questioning how many ''anomalies'' can robustly be replicated.
- J.P. Morgan (2019, SFI) present their extension of Deep hedging using Reinforcement Learning with optimal execution which challenges complete markets and perfect hedging. RL is the new wave in finance industry (trading, execution and portfolio optimisation) and is here to stay, must read
## Answer by Jan Stuller (score 7)
https://quant.stackexchange.com/a/61170
## Rates options
Lognormal vs Normal Volatilities and Sensitivities in Practice: this is the best paper on pricing Rates Options in negative rates environment that I have read recently (disclaimer: I don't read many papers, so when I say the "best I read recently" does not necessarily raise the bar very high :).
It was published in March 2016, so just meets the "last 5 years" criteria.
If anyone has any good recent papers on pricing rates optional products, particularly when it comes to IBOR cessation / SOFR discounting, I would very much be interested: please do post these if you know of any.
## Answer by BCCapital (score 3)
https://quant.stackexchange.com/a/61258
Behavioral Finance
I'm cutting it close with McLean and Pontiff (2016, JF) but it's a great read and a personal favorite. Does Academic Research Destroy Stock Return Predictably - funny enough it's gone on to become one of the most cited papers around. I can't wait to check out what's already been shared.
## Answer by Sergei Rodionov (score -6)
https://quant.stackexchange.com/a/61164
I recommend SSRN, where you can search for most recent papers on topics of interest, or by author. The published papers are not always research per se, but can be interesting nonetheless. Here are a few ways to navigate it:
- Publications by AuthorShown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.