Our mathematicians, statisticians, engineers and computer scientists perform fundamental research and advanced quantitative analysis, and utilize cutting–edge technology to identify and create new strategies in the investment arena.
Our organization and our people are diligent students of several of the best schools of statistical learning (in the tradition of Hastie, Tibshirani and Friedman at Stanford.) We deploy state-of-the-art software, including many packages from the R statistical language such as caret and mlr along with their underlying boosting, bagging and tree-based classification and regression methods.
It is this core belief in the academic foundation and principles of our work that inform our approach to investing.
As our researchers develop new strategies they write and share published papers to explain their findings.
The Risk-Reversal Premium
- Published in The Journal of Investment Strategies
We study the risk-reversal premium, where out-of-the-money puts are over-priced relative to out-of-the-money calls. This effect is driven by investors’ utility preferences which lead them to over-pay for the risk reduction benefits of long puts instead of valuing options on the basis of expected returns. Investors can exploit this implied skewness premium by trading standard, exchange-traded index options. We also show that including risk-reversals in an equity portfolio creates a better portfolio (as measured by Sharpe ratio) compared to a pure index position.
A Practitioner’s Defense of Return Predictability
- Published in The Journal of Portfolio Management
Our first paper is authored by Blair Hull and Xiao Qiao and explores the issues and opportunities of market timing and return predictability.
It is this core belief in the academic foundation and principles of our work that inform our approach to investing. In “A Practitioner’s Defense of Return Predictability,” a paper authored by Blair Hull and Xiao Qiao, the issues and opportunities of market timing and return predictability are explored.
The paper discusses a six-month horizon model that leverages correlation screening to combine a constantly changing collection of twenty academically referenced variables in order to demonstrate forecasting efficacy. Using a walk forward simulation in which positions in SPY are taken proportional to the model forecast equity risk premium, this approach indicates simulated strategy yields of more than twice the annual returns of a buy-and-hold strategy and a corresponding Sharpe ratio four times that of buy-and-hold.
Return Predictability and Market-Timing: A One-Month Model
- Published in The Journal of Investment Management
In 2017, the Hull team released the results of its current research in a paper called “Return Predictability and Market-Timing: A One-Month Model”. We believe the paper is unique in that it provides a link to the model’s forecasts. To our knowledge, no other research paper gives access to real time predictions of the equity risk premium.
Seasonal Effects and Other Anomalies
The most recent paper revisits a series of popular anomalies: seasonal, announcement and momentum. The Hull team investigates the creation of a seasonal anomaly and trend model composed of the Sell in May (SIM), Turn of the Month (TOM), Federal Open Market Committee pre-announcement drift (FOMC) and State Dependent Momentum (SDM). Similar to the previous two papers, model conclusions and recommendations are included in the Daily Report.
These documents are provided by Hull Tactical for academic and informational purposes only, are not intended for Retail Investors, and may not be reproduced, distributed or published without the written consent of Hull Tactical. This document does not constitute an offer or a solicitation to buy or to sell any security, product or service in any jurisdiction; nor is it intended to provide investment, financial, legal, accounting, tax, or other advice and such information should not be relied or acted upon for providing such advice. This document is not available for distribution to investors in jurisdictions where such distribution would be prohibited.
There are risks associated with investing, including possible loss of principal. Commodities contain heightened risk including market, political, regulatory, and natural conditions, and may not be appropriate for all investors.
Derivatives may involve certain costs and risks such as liquidity, interest rate, market, credit, management and the risk that a position could not be closed when most advantageous. In addition, commodity-linked derivative instruments may involve additional costs and risks such as changes in commodity index volatility or factors affecting a particular industry or commodity, such as drought, floods, weather, livestock disease, embargoes, tariffs and international economic, political and regulatory developments. Investing in derivatives could lose more than the amount invested.
Trading security futures contracts may not be suitable for all investors. You may lose a substantial amount of money in a very short period of time. The amount you may lose is potentially unlimited and can exceed the amount you originally deposit with your broker. This is because futures trading is highly leveraged, with a relatively small amount of money used to establish a position in assets having a much greater value.
Any investment and economic outlook information contained in this document has been compiled by Hull Tactical from various sources. Information obtained from third parties is believed to be reliable, but no representation or warranty, express or implied, is made by Hull Tactical, or any other person as to its accuracy, completeness or correctness. Hull Tactical assumes no responsibility for any errors or omissions in such information.
Opinions contained herein reflect the judgment and thought leadership of Hull Tactical and are subject to change at any time. Such opinions are for informational purposes only and are not intended to be investment or financial advice and should not be relied or acted upon for providing such advice. Hull Tactical does not undertake any obligation or responsibility to update such opinions.