Technical paper/S&P 500
Neural networks unleashed: joint SPX/VIX calibration has never been faster
SPX and VIX options can be jointly calibrated in real time with deep neural networks
Investment decisions driven by fine-tuned large language models and uniform manifold approximation and projection-supported clustering and hierarchical density-based spatial clustering
Luxury watches: a viable alternative investment or mere speculative trend? An analysis of two decades before the pandemic
Neural joint S&P 500/VIX smile calibration
Optimal transport for model calibration
Volatility models and SPX/VIX joint dynamics are calibrated using optimal transport theory
Option pricing using high-frequency futures prices
The authors examine two potential routes to improve the outcome of option pricing: extracting the variance from futures prices instead of the underlying asset prices, and calculating the variance in different frequencies with intraday data instead of…
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…
Can shorting leveraged exchange-traded fund pairs be a profitable trade?
In this paper, the authors examine if investors can profit from the underperformance of leveraged exchange-traded funds (ETFs) in long holding periods.
Rating migrations of US financial institutions: are different outcomes equivalent?
This study employs a competing risks approach to examine the rating migrations of US financial institutions (FIs) during the period 1984–2006.
Tail-risk mitigation with managed volatility strategies
This paper examines strategy performance from an investment practitioner perspective. Using long-term data from the Standard & Poor’s 500, the authors show that these strategies offer an improvement in risk-adjusted return compared with a buy-and-hold…
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.
Dilated convolutional neural networks for time series forecasting
In this paper, the authors present a method for conditional time series forecasting based on an adaptation of the recent deep convolutional WaveNet architecture.
Covering the world: global evidence on covered calls
Typical covered call strategies may be decomposed, using a risk and performance attribution methodology, into three components: equity exposure, short volatility exposure and equity timing. This paper applies that attribution methodology to covered calls…
News-sentiment networks as a company risk indicator
This paper defines an algorithm for measuring sentiment-based network risk, to understand the relationship between news sentiment and company stock price movements, and to better understand connectivity among companies.
Cutting Edge introduction: Hedging dependence
Hedging dependence