Trading strategy
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.
The future of equity derivatives: perspectives for UK equities and dividends
Managing equity and dividend risk today requires new trading strategies and products. In a webinar convened by Risk.net and hosted by Eurex, three experts discuss what’s next for the UK and European markets.
Forecasting volatility and market returns using the CBOE Volatility Index and its options
This paper examines the CBOE VIX, the VIX options’ implied volatility and the smirks associated with these options.
The value-at-risk of time-series momentum and contrarian trading strategies
This paper not only provides a theoretical model for the value-at-risk of active and passive trading strategies but also discusses the substantial implications relevant to risk management.
A new metric for liquidity add-ons: easy as ADV, but better
Proposed measure allows brokers to calculate stable, stock-specific liquidity add-ons
A principled approach to clean-up costs in algo trading
The opportunity cost associated with the cancelled portion of an order is quantified
Time to act – Smart transitions to UMR compliance
Firms face many challenges as deadlines loom for phases five and six of the uncleared margin rules (UMR), including getting their average aggregate notional amount calculations right to determine which phase they are in. With only three months to prepare…
Options to mitigate the challenges of index cessation fallbacks and conversion
This has so far been a defining year for index cessation, Isda’s fallbacks protocol and central counterparty conversions. TriOptima insists that now is the time for firms to get their interest rate swap portfolios in order before year-end
Invesco bets on new tech to refine its FX trading
Home-grown tool will improve order routing and execution strategies, asset manager believes
Rising stars in quant finance: Iuliia Manziuk and Bastien Baldacci
Risk Awards 2021: new research tackles ‘fundamental’ but largely ignored smart order routing problem
FCMs fret over S&P 500 options settlement changes
Dealers say CME, Cboe settlement time shift for S&P 500-linked options causes risk management headache
What’s so special about time series momentum?
We find that the buy-and-hold (B&H) strategy for the S&P 500 index (^GSPC) for January 1950–April 2019 had a significantly higher return than that produced by time series momentum (TSM). However, TSM was superior in terms of the Sharpe ratio due to its…
Credit Suisse traded most with top Pimco funds in 2019
Bank’s US securities arm conducted trades worth $639 billion over 12 months to end-March 2020
Optimal dynamic strategies on Gaussian returns
It is hoped that this paper will form a foundational approach to the study of dynamic strategies and how to optimize them. We make efforts to understand their properties without claiming to understand why they work (ie, why there are stable…
Delivering certainty in uncertain times
TriOptima explains how it combines the reduction of gross notional exposure and the conversion of net risk exposure to deliver outsized results, partnering its portfolio compression network with core net ICE Libor over-the-counter swap portfolios