Discussion Topics

Market Making:

Understanding that a market maker does not have unlimited capital and cannot effectively implement a martingale - she must be sensitive to inventory risks. This (and the derivative exploration of computational efficiency/ timeliness of the input drivers) has increasingly been an area of research.

Seminal closed mathematical market making model: Avellaneda and Stoikov: https://www.math.nyu.edu/faculty/avellane/HighFrequencyTrading.pdf

Prudue phd paper that wraps up the state of things pretty well (and tried to introduce new thoughts):

https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1401&context=open_access_dissertations

Indepth discussion on self exciting point processes (and potentially how to speed it up):

https://arxiv.org/pdf/1308.6756

Improvements/ further exploration:

1. Fodra, Labadie https://arxiv.org/pdf/1206.4810

2. Gueant, Lehalle, Tapia https://arxiv.org/pdf/1105.3115

3. Cartea, Jaimungal https://pdfs.semanticscholar.org/325c/980a17bfa4af18fd33f7e38f20cacf01699f.pdf

Further works on some of the drivers and potential estimating variables:

Hewlett http://users.iems.northwestern.edu/~armbruster/2007msande444/Hewlett2006%20price%20impact.pdf

Fonseca and Zaatour https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2294112

Explaining one area of exploration: Hawkes processes: https://stmorse.github.io/journal/Hawkes-python.html

Python model of Avellaneda and Stoikov vs. a symmetrical model with simulated intensity and fills:

https://github.com/ragoragino/avellaneda-stoikov

Volitility pumping/ Rebalancing / Universal Algos

Cover, 1991 is a seminal paper with a premise that is thought to be one the starting points for one of the most secretive (and successful) Hedge funds, Renaissance Technologies. Since its release, additional works have tried to improve both on the investment performance and on the computational efficacy. Often the primary driver of returns for these strategies is volatility, and the inter-relationships of the constituents to the portfolio. One way to artificially increase volatility is leverage. Listed futures are a good product of choice to achieve increased leverage, and offer a breadth of correlation relationships.

Cover, Universal Portfolio:
https://stuff.mit.edu/afs/athena.mit.edu/course/6/6.962/www/www_fall_2001/shaas/universal_portfolios.pdf

additional paper often mentioned in the same context: Borodin, A., El-Yaniv, R., & Gogan, V. (2004). Can we learn to beat the best stock. http://papers.nips.cc/paper/2453-can-we-learn-to-beat-the-best-stock.pdf

recent paper discussing shortfalls and potential improvement: https://www.researchgate.net/publication/221346006_Algorithms_for_portfolio_management_based_on_the_Newton_method

github link to a library with a breadth of rebalancing Algos:

https://github.com/Marigold/universal-portfolios

python workbook using above library:

https://nbviewer.jupyter.org/github/Marigold/universal-portfolios/blob/master/On-line%20portfolios.ipynb

Volitility/ VIX:

Understanding product volitility (or product volitility) has only increased in importance as volitility has increasingly become its own asset class.

S&P related:

Statistics of VIX Futures …. https://www.math.nyu.edu/faculty/avellane/SSRN-id3028910.pdf

Fed Paper (Zero beta VIX portfolio) Chen and Tindall … https://pdfs.semanticscholar.org/a514/dafadc0b9cdae1d5edbb996527089dd69d01.pdf

Cooper (overerly simple discussion of VIX strategies and impacts) https://www.ssrn.com/abstract=2255327

Oil / Nat gas:

Chevallier (oil vol as predictor) ..https://www.ssrn.com/abstract=2292496

Mu (nat gas, weather, storage) https://www.researchgate.net/profile/Xiaoyi_Mu2/publication/286354146_Mu_NGVol/links/5667fe9708aef42b57881858.pdf

Perifanis and Dagoumas (crude and nat gas vol spill over effect?) https://www.researchgate.net/publication/328293748_Price_and_Volatility_Spillovers_Between_the_US_Crude_Oil_and_Natural_Gas_Wholesale_Markets

Pindyck (oil and nat gas vol) https://dspace.mit.edu/bitstream/handle/1721.1/45005/2003-012.pdf%3Bjsessionid%3D9F0DFFF8029E50DC43A56FBDB7FA8C03?sequence%3D1

Zamikau, woo, Zhu, Tsai (texas power volitility) http://www.frontierassoc.com/wp-content/uploads/2018/09/Market-price-behavior-of-wholesale-electricity-products-TX.pdf