New strategies:
#364 – Trading the Crude Oil Term Structure
Period of rebalancing: Weekly
Markets traded: commodities
Instruments used for trading: futures, ETFs
Complexity: Complex strategy
Bactest period: 2011-2016
Indicative performance: 5.40%
Estimated volatility: 7.10%
Source paper:
Donninger, Chrilly: Modeling, Forecasting and Trading the Crude Oil Term Structure
https://ssrn.com/abstract=2874869
Abstract:
Barunik and Malinska apply the bond term-structure forecasting model of Diebold and Li to
crude oil Futures. But they report only statistical results and do not apply the model to trading calendar spreads. This paper addresses this logical next step. The performance is compared to strategies which are based on different rolling-strategies. Basically one shorts a less efficient rolling-strategy and goes a more efficient long. Both methods boil down to similar trading behavior and have hence also a comparable performance. The performance is in the time range from 2011-01-01 till 2016-11-18 quite reasonable.
#365 – Timing S&P500 Using a Large Set of Forecasting Variables
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: ETFs, futures, CFDs
Complexity: Complex strategy
Bactest period: 2003-2017
Indicative performance: 16.60%
Estimated volatility: 16.60%
Source paper:
Hull, Blair and Qiao, Xiao and Bakosova, Petra: Return Predictability and Market-Timing: A One-Month Model
https://ssrn.com/abstract=3050254
Abstract:
We propose a one-month market-timing model constructed from 15 diverse variables. We use weighted least squares with stepwise variable selection to build a predictive model for the one-month-ahead market excess returns. From our statistical model, we transform our forecasts into investable positions to build a market-timing strategy. From 2003 to 2017, our strategy results in 16.6% annual returns with a 0.92 Sharpe ratio and a 20.3% maximum drawdown, whereas the S&P 500 has annual returns of 10%, a 0.46 Sharpe ratio, and a maximum drawdown of 55.2%. When our one-month model is used in conjunction with Hull and Qiao’s (2017) six-month model, the Sharpe ratio of the combined strategy exceeds the individual model Sharpe ratios. The combined model has 15% annual returns, a Sharpe ratio of 1.12, and a maximum drawdown of 14%. We publish forecasts from our one-month model in our Daily Report.
#366 – Daily Box Office Earnings and Aggregate Stock Returns
Period of rebalancing: Daily
Markets traded: equities
Instruments used for trading: ETFs, futures, CFDs
Complexity: Simple strategy
Bactest period: 2002-2016
Indicative performance: 24.93%
Estimated volatility: not stated
Source paper:
Oz, Seda and Fortin, Steve, Is it Time for Popcorn? Daily Box Office Earnings and Aggregate Stock Returns
https://ssrn.com/abstract=3026910
Abstract:
We quantitatively measure the interactions between the discretionary consumption and the stock market. We demonstrate daily theatrical box office earnings as a proxy for the discretionary consumption and document a statistically significant positive association between changes in box office earnings and daily aggregate stock returns. Our results suggest that changes in box office earnings can predict stock returns up to 4 days. We also demonstrate a hypothetical trading strategy using changes in box office earnings that yields nontrivial excess returns with little risk. These findings suggest that box office effect is an economically important factor for equities. To the extent that box office earnings capture discretionary consumption, the framework implies that deviations from investors’ discretionary consumption trends summarize agents' expectations of future returns on the market portfolio.
New research papers related to existing strategies:
#1 – Asset Class Trend Following
#118 – Time Series Momentum Effect
#137 – Trendfollowing in Futures Markets
Jusselin, Lezmi, Malongo, Masselin, Roncalli, Dao: Understanding the Momentum Risk Premium: An In-Depth Journey Through Trend-Following Strategies
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3042173
Abstract:
Momentum risk premium is one of the most important alternative risk premia. Since it is considered a market anomaly, it is not always well understood. Many publications on this topic are therefore based on backtesting and empirical results. However, some academic studies have developed a theoretical framework that allows us to understand the behavior of such strategies. In this paper, we extend the model of Bruder and Gaussel (2011) to the multivariate case. We can find the main properties found in academic literature, and obtain new theoretical findings on the momentum risk premium. In particular, we revisit the payoff of trend-following strategies, and analyze the impact of the asset universe on the risk/return profile. We also compare empirical stylized facts with the theoretical results obtained from our model. Finally, we study the hedging properties of trend-following strategies.
One additional related research paper has been included into existing free strategy reviews during last 2 weeks:
All of us at Quantpedia are history freaks, thefore we absolutely LOVE papers like this:
Schmelzing: Eight Centuries of the Risk-Free Rate: Bond Market Reversals from the Venetians to the ‘VaR Shock’
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3062498
Abstract:
This paper presents a new dataset for the annual risk-free rate in both nominal and real terms going back to the 13th century. On this basis, we establish for the first time a long-term comparative investigation of ‘bond bull markets’. It is shown that the global risk-free rate in July 2016 reached its lowest nominal level ever recorded. The current bond bull market in US Treasuries which originated in 1981 is currently the third longest on record, and the second most intense. The second part of this paper presents three case studies for the 20th century, to typify modern forms of bond market reversals. It is found that fundamental, inflation-led bond market reversals have inflicted the longest and most intense losses upon investors, as exemplified by the 1960s market in US Treasuries. However, central bank (mis-) communication has played a key role in the 1994 ‘Bond massacre’. The 2003 Japanese ‘VaR shock’ demonstrates how curve steepening dynamics can create positive externalities for the banking system in periods of monetary policy and financial uncertainty. The paper finally argues that the inflation dynamics underlying the 1965–70 bond market sell-off in US Treasuries could hold particular relevance for the current market environment.
