Trading strategy
Quantum two-sample test for investment strategies
Quantum algorithms display high discriminatory power in the classification of probability distributions
Podcast: Lorenzo Ravagli on why the skew is for the many
JP Morgan quant proposes a unified framework for trading the volatility skew premium
Form an orderly QIS: hedge funds spur quant products to new heights
Rise of multi-strategy vehicles triggers demand for indexes once seen as competitors
Securities and Exchange Commission Form 13F Holdings Report: statistical investigation of trading imbalances and profitability analysis
The authors argue that trading against SEC Form 13F-HR imbalances can prove a profitable strategy due to the inflation of related asset prices.
Rethinking P&L attribution for options
A buy-side perspective on how to decompose the P&L of index options is presented
Zero-day options: unique market dynamics and risk considerations
In a recent Risk.net webinar, experts discussed the growth and usage of 0DTE options, challenges in modelling their prices and risks, practical risk management issues and whether they pose systemic risks to the market.
Japan’s interest rate derivatives trading and clearing on the rise
Japan Exchange Group and OpenGamma chart Japan’s journey towards a flourishing derivatives trading and clearing ecosystem
Dynamic margining long/short equity trading strategies
A repo haircut model extends a previous solution for long-only strategies
Are cryptocurrencies cryptic or a source of arbitrage? A genetic algorithm approach
The authors identify triangular arbitrage trading opportunities through genetic algorithms in order to find insights into the volatility of cryptocurrencies and stablecoins with the largest market cap.
How AI can give banks an edge in bond trading
Machine learning expert Terry Benzschawel explains that bots are available to help dealers manage inventory and model markets
The cost of mis-specifying price impact
Expected returns can be significantly affected by the wrong use of impact models
Getting more for less: better A / B testing via causal regularisation
A causal machine learning algorithm is used to estimate trades’ price impact
HFT activity increases periodic auctions costs
Eightfold jump in market impact as more trades head to once-benign execution format
Momentum transformer: an interpretable deep learning trading model
An attention-based deep learning model for trading is presented
Trading the vol-of-vol risk premium
Applications of the vol-of-vol parameter for cross-asset derivatives are presented
The quant investor harnessing the power of ants
Swarm Technology designs network of trading algorithms that mimics hive mind of insects
Role of the dice: how Susquehanna puts game theory to work
One of the world’s largest options traders uses game theory – and poker practice – to get results
Optimal trade execution with uncertain volume target
This paper demonstrates that risk-averse traders can benefit from delaying trades using a model that accounts for volume uncertainty.
Linking performance of vanilla options to the volatility premium
A framework to account for vanilla options' performance in trading strategies is presented
‘Corrective’ algo tells quant firm when it’s wrong
QTS has built a machine to show whether a strategy is likely to succeed or flop
Abnormal returns and stock price movements: some evidence from developed and emerging markets
This paper investigates the impact of abnormal returns on stock prices by using daily and hourly data for developed and emerging markets from 2010 up until 2020.