The Journal of Investment Strategies is dedicated to the rigorous treatment of modern investment strategies; going well beyond the “classical” approaches in both its subject instruments and methodologies. In providing a balanced representation of academic, buy-side and sell-side research, the Journal promotes the cross-pollination of ideas amongst researchers and practitioners, achieving a unique nexus of academia and industry on one hand, and theoretical and applied models on the other.
The Journal contains in-depth research papers as well as discussion articles on technical and market subjects, and aims to equip the global investment community with practical and cutting-edge research in order to understand and implement modern investment strategies.
With a focus on important contemporary investment strategies, techniques and management, the journal considers papers on the following areas:
- Fundamental Strategies: including fundamental macro, fundamental equity or credit selection
- Relative Value Strategies: estimation of and investing in the relative valuation of related securities, both vanilla and derivatives
- Tactical Strategies: strategies based on forecasting of, and investing in, patterns of market behavior, such as momentum or mean reversion, and tactical asset allocation strategies.
- Event-Driven Strategies: strategies based on the forecast of likelihood of market-moving events or market reactions to such events
- Algorithmic Trading Strategies: models of market microstructure, liquidity and market impact and algorithmic trade execution and market-making strategies
- Principal Investment Strategies: investment strategies for illiquid securities and principal ownership or funding of real assets and businesses
- Portfolio Management and Asset Allocation: models for portfolio optimization, risk control, performance attribution and asset allocation
- Econometric and Statistical Methods: with applications to investment strategies
The Journal of Investment Strategies has been selected for coverage in the Clarivate Analytics Emerging Sources Citation Index.
In this paper, the authors study the dynamics of Chicago Board Options Exchange volatility index (VIX) futures and exchange-traded notes (ETNs)/exchange-traded funds (ETFs).
In this paper, the authors introduce an approach to cluster asset classes by correlation distance and then outline how these results can be used to design portfolios that are optimal in a group risk parity (GRP) framework.
In this paper, the authors show that single-asset trend strategies have built-in convexity, provided their returns are aggregated over the right time scale, ie, that of the trend filter.
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…
This paper determines life-cycle trading strategies for portfolios subject to the US tax system.
Portfolio concentration and equity market contagion: evidence on the “flight to familiarity” across indexing methods
This paper sheds light on the entanglement of index weighting schemes.
By extending the Kelly criterion to a simple probabilistic model with an additional tail risk outcome associated with uncertainty, this paper looks beyond risk and evaluates how uncertainty constrains optimal leverage.
Lifecycle investing with the profitable dividend yield strategy: simulations and nonparametric analysis
Using simulations, the author shows that life-cycle investing implemented on highly profitable and high dividend yield stocks (the profitable dividend yield strategy) provides a compelling solution to the suboptimality problem by leveraging on the…
This paper considers the problem of enhancing an investment activity by regularly adding an option trade to the portfolio mix and presented results for the single underlier of the S&P 500 index, with the underlying activity being either long the index or…
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.
This paper examines the performance of three DeMark indicators over twenty-one commodity futures markets and ten years of daily data.
In this paper, the authors provide tools to test the correctness of backtest engines for setups with at most one entry and one exit.
This paper brings Black–Litterman optimization, exotic betas and varying starting portfolios together into one complete, symbiotic framework.
This paper offers a new perspective on portfolio allocation, which avoids any explicit optimization and instead takes the point of view of symmetry.
This paper studies centrality (interconnectedness risk) measures and their added value in an active portfolio optimization framework.
In this paper the authors investigate how fixed-fee transaction costs affect portfolio rebalancing.
The authors propose an analytical framework to measure investment opportunities and allocate risk across time based on the Mahalanobis distance.
In this paper, the authors give complete algorithms and source code for constructing statistical risk models.
This paper proposes using an optimization mechanism in the currency overlay portfolio construction process.
The authors of this paper derive an optimal trading strategy that benchmarks the closing price in a mean–variance optimization framework.