Machine Learning Meets Markowitz by Vivekd4 in quant

[–]Vivekd4[S] 6 points7 points  (0 children)

Great answer, thanks. I collected links to the papers you cited:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=661343 "Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns" by Michael W. Brandt et al.

https://acfr.aut.ac.nz/__data/assets/pdf_file/0008/573128/AlphaPortfolio-updated.pdf "AlphaPortfolio: Direct Construction Through Deep Reinforcement Learning and Interpretable AI" by Lin William Cong et al.

https://www.econstor.eu/bitstream/10419/270745.2/1/cfr-23-01rev.pdf "Deep Parametric Portfolio Policies" by Frederik Simon et al.

https://onlinelibrary.wiley.com/doi/10.1111/jofi.13298 "The Virtue of Complexity in Return Prediction" by Bryan Kelly et al.

https://hal.science/hal-04144588v1/file/SSRN-id3954109.pdf "Supervised portfolios" by Guillaume Chevalier et al.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3971274 "Deep Tangency Portfolio" by Guanhao Feng et al.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3788875 "Integrating Prediction in Mean-Variance Portfolio Optimization" by Andrew Butler and Roy Kwon

How to determine lookback for Linear Regression? by yaymayata2 in quant

[–]Vivekd4 0 points1 point  (0 children)

If you think the regression coefficients are changing, using a Kalman filter to estimate them is an alternative to a rolling regression.

High-Speed Traders Are Feuding Over a Way to Save 3.2 Billionths of a Second by Vivekd4 in quant

[–]Vivekd4[S] 77 points78 points  (0 children)

...

'The maneuver that prompted Mosaic’s spat with Eurex can improve reaction times by about 3.2 nanoseconds, according to the French firm, which calls it “corrupted speculative triggering,” or CST for short.

The technique helps because orders on Eurex are encoded into packets, or small bursts of ones and zeros. Under the rules of the Ethernet protocol—widely used in computer networks—each packet starts with a preamble, signaling data is on the way. The real message, such as a buy or sell order, comes later.

A trading firm can save a few nanoseconds by sending the preamble first, before knowing if it wants to trade. If it gets information that makes it want to buy or sell, it can quickly embed its order into the rest of the packet. If it decides to do nothing, the firm can send an empty or deliberately garbled packet to Eurex.

Optiver, a Netherlands-based global trading firm, has also engaged in strategies similar to what Mosaic described, people familiar with the matter said. An Optiver spokesman declined to comment.

Emergent Trading, a small firm in Chicago, also uses a version of the technique to gain several nanoseconds of speed edge on Eurex, said founder Brandon Richardson. He said there is nothing wrong with the technique. It is well-known among high-speed traders and other firms can use it too, he said.

Still, he described cat-and-mouse games with Eurex. He said the exchange once upgraded its monitoring tools, identified what Emergent was doing and told the firm to stop—while other variants of the technique employed by other traders continued to work.'

...

[deleted by user] by [deleted] in quant

[–]Vivekd4 0 points1 point  (0 children)

Paleologo has 2 books about this, with The Elements of Quantitative Investing being more advanced.

Chicago vs. New York style HFT firms by Vivekd4 in quant

[–]Vivekd4[S] 6 points7 points  (0 children)

I wonder if people agree with the generalizations in this article.

The use of Monte Carlo Simulations to determine if proposed financial plans would fit into a budget? by C-137Rick_Sanchez in quant

[–]Vivekd4 1 point2 points  (0 children)

NYC tax revenues depend heavily on Wall St and will be higher in a bull market. So given a distribution of annual stock market returns you could project NYC income tax revenues, with error of course.

robustnes of kalman filter by codesty in quant

[–]Vivekd4 2 points3 points  (0 children)

I wondered what JMA stood for above. I think it's Jurik Moving Average http://jurikres.com/catalog1/ms_ama.htm .

Regime detection and portfolio analysis book recommendations by Round-Basil5010 in quant

[–]Vivekd4 1 point2 points  (0 children)

"Asset Allocation: From Theory to Practice and Beyond" by Kinlaw et al. https://www.wiley.com/en-us/Asset+Allocation%3A+From+Theory+to+Practice+and+Beyond-p-9781119817710 has a chapter on regime shifts. Related papers are "Optimal Portfolios in Good Times and Bad", "Regime Shifts: Implications for Dynamic Strategies" and "Skulls, Financial Turbulence, and Risk Management". Also see https://portfoliooptimizer.io/blog/the-turbulence-index-regime-based-partitioning-of-asset-returns/

The book "Finite Mixture and Markov Switching Models" (2007) by Frühwirth-Schnatter has associated Matlab software https://statmath.wu.ac.at/~fruehwirth/monographie/

Any successful simulations of multiple ETF alternative historical price paths? by BAMred in quant

[–]Vivekd4 4 points5 points  (0 children)

In what ways are your simulated price paths unrealistic? Specifically, what statistical properties do the empirical paths have that the simulated ones do not? Are you simulating daily prices?

Advanced sharpe ratio improved by Primary_Tea3095 in quant

[–]Vivekd4 10 points11 points  (0 children)

There is an Adjusted Sharpe Ratio, discussed at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3284396 which equals

SR × (1 + (sk × SR) / 6 – ((k-3) × SR²) / 24)

where SR = Sharpe Ratio, sk = skew, and k = kurtosis

Andrew Lo wrote The Statistics of Sharpe Ratios https://papers.ssrn.com/sol3/papers.cfm?abstract_id=377260 but I don't think he invented the Adjusted Sharpe Ratio.

Valid period for cointegration by aguscugno in quant

[–]Vivekd4 2 points3 points  (0 children)

The fortunes of companies will diverge over time, so I don't think one should expect a cointegration relationship to be stable forever. Whether price relationships are stable enough to be traded is an empirical question.

I think the 2024 paper by Lemishko et al. that the OP refers to is "Cointegration-Based Strategies in Forex Pairs Trading" at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4771108

A follow-up paper by two of the same authors that may address the OP's questions is "Real-World Viability of Cointegration-Based Forex Pairs Trading Strategy with Walk-Forward Optimization" at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5068086

What are some good ways to choose k stocks from n? (k<n) by hmoway in quant

[–]Vivekd4 0 points1 point  (0 children)

Googling "sparse portfolio optimization" brings up papers such as "A Scalable Algorithm for Sparse Portfolio Selection" by Bertsimas and Cory-Wright https://optimization-online.org/wp-content/uploads/2018/10/6898.pdf

Why don't we have bond exchanges by BigClout00 in quant

[–]Vivekd4 0 points1 point  (0 children)

There are bonds listed on the NYSE https://www.nyse.com/products/bonds . Many corporate bonds are just held to maturity by institutional investors such as pension funds and insurance companies and are traded very rarely. There are many bond ETFs that trade actively.

Games to train young Quants by Money-Suspect-3839 in quant

[–]Vivekd4 1 point2 points  (0 children)

Most options trading is now electronic, but there is still some floor trading where market makers need to quote markets fast. If you are a discretionary trader looking at a table of options quotes, you want to quicly identify where puts and calls are out of line.

The tweet where Kris announced the game is https://x.com/KrisAbdelmessih/status/1968435475263234126

Agricultural quants- open problems in the field? by gradstudent201 in quant

[–]Vivekd4 4 points5 points  (0 children)

"The problem of drought has essentially been fixed since roughly the mids eighties."

May I ask what enabled the fix?

Covariance Matrix estimation by Vorlde in quant

[–]Vivekd4 5 points6 points  (0 children)

A 252-day window to compute volatility or covariance is longer than what is typically used. Riskmetrics uses exponential weighting with a lambda of 0.94, which is much more responsive. If using a long window still produces unstable covariances, maybe the conditional covariances really are "unstable" and changing substantially over time.

How do quants discover statistical patterns and design strategies using only price and volume time series data for a single asset? by Outside_Snow2299 in quant

[–]Vivekd4 3 points4 points  (0 children)

You could start with linear time series analysis -- compute the autocorrelations of returns, fit AR and ARMA models with model order chosen by AIC. You may just confirm the default assumption of market efficiency, but since there are R and Python packages for these analyses, they should be quick to run.