Trading strategy
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
Is trading indicator performance robust? Evidence from scenario building
This paper challenges widely applied trading indicators with regard to their ability to generate a robust performance.
Podcast: Lipton and de Prado on Covid and trading strategies
Top quants discuss collaboration and their worries about the economic recovery
A closed-form solution for optimal mean-reverting strategies
The heat potentials method is used to find the optimal profit-taking and stop-loss levels
What quants can learn from the Covid crisis
More nowcasting, less backtesting, and strategies that adapt to new regimes: a manifesto from Lipton and López de Prado
Traders flee Vix futures
Short interest of asset managers down 80% on 12-month peak
Opening the buy-side liquidity pool
Vikash Rughani, business manager at triReduce and triBalance, outlines a new approach enabling buy- and sell-side participants to optimise the transition of legacy Libor over-the-counter swaps contracts to alternative reference rates
Value: ‘Trade of the decade,’ says QMA
Quant firm predicts big revival for out-of-favour strategy
Trading revenues top $1bn at Wells Fargo in Q3
Net gains on trading activities up 75% on Q3 2018
Risk premia strategies – Lessons learned for the future
After a difficult 2018, investors are increasingly wary of risk premia, concerned that factors leading to underperformance might be a recurring problem. Imene Moussa, executive director at UBS, clarifies this issue
Beta hedging: performance measures, momentum weighting and rebalancing effects
In this paper, the authors discuss the various performance measures of beta hedging and offer a new synthetic criterion that accounts for both risk-adjusted returns and losses of trading strategy.
Winning investment strategies based on financial crisis indicators
The aim of this paper is to create systematic trading strategies built around several financial crisis indicators, which are based on the spectral properties of market dynamics.
To Hull and back: a 20-year hiatus in bank e-trading plans
In the 1990s, banks tried to buy automated trading expertise; now, after a long break, they’re trying to build it
Machine earning: how tech is shaking up bank market-making
As banks get serious about e-trading, humans are being asked to give up their secrets to the machines that could replace them
Risk averse fractional trading using the current drawdown
In this paper, the fractional trading ansatz of money management, also called growth optimal trading, is reconsidered. Special attention is paid to the chance and risk parts of the goal function for the related optimization problem.
Speed and dimensions of trading
In this paper, two new portfolio statistics are introduced: ENT, which measures trading speed, and ENTD, which measures trading diversity. Together with vectors representing major trading directions, these provide new insight into the intrinsic…
Machine learning for trading
Gordon Ritter applies reinforcement learning to dynamic trading strategies with market impact
An uncertainty quantification framework for the achievability of backtesting results of trading strategies
In this paper, the authors propose a framework for implementing and backtesting trading strategies.
New execution algos show complexity is not to be feared
Quants develop method to include both market impact and limit orders in optimal trade execution
Optimal trading with linear and (small) non-linear costs
Bouchaud et al find the optimal trading strategy for a family of predictive signals in the presence of transaction costs