New strategies:
#371 – Supply Chain Based Equity Strategy
Period of rebalancing: Daily
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Bactest period: 1989 – 2014
Indicative performance: 34.84%
Estimated volatility: 58.68%
Source paper:
Qiu, Buhui and Xu, Fangming and Zeng, Cheng, Contagious Stock Price Crashes
https://ssrn.com/abstract=3069993
Abstract:
This paper examines the contagion effects of stock price crashes along the supply chain. We find that stock price crashes can be transmitted from major customers to suppliers with a delay of up to two weeks. Moreover, this delay is moderated by the information transparency of the affected suppliers, but there is only limited evidence on the impact of investor inattention. A long-short trading strategy based on the delayed crash transmission generates significantly positive abnormal returns of 40% per year. In addition, major customers’ stock price crashes can significantly predict supplier firms being delisted from stock markets in the near future. The results are robust to a battery of sensitivity tests. Overall, our findings shed new light on the capital market consequences of stock price crashes.
#372 – Trading Based on Levered ETFs Speculation Sentiment
Period of rebalancing: Monthly
Markets traded: equities
Instruments used for trading: stocks
Complexity: Very complex strategy
Bactest period: 2010 – 2016
Indicative performance: 17.98%
Estimated volatility: 18.51%
Source paper:
Davies, Shaun William: Speculation Sentiment
https://ssrn.com/abstract=3063551
Abstract:
I provide a novel and direct test that shows sp eculative trades push asset prices away from fundamentals. I form the Speculation Sentiment Index using observable arbitrage trades in levered exchange traded funds (ETFs). Arbitrage activity originates from demand shocks that create relative mispricing between an ETF and its underlying. Because levered ETFs are used by novice traders to speculate on the market, the implicit demand shock is related to speculation. The index captures the direction and magnitude of market-wide speculation sentiment and it predicts aggregate asset return reversals. Furthermore, a trading strategy based on the index earns substantial excess returns.
New research papers related to existing strategies:
#370 – Value-Growth Timing
Asness, Liew, Pedersen, Thapar: Deep Value
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3076181
Abstract:
We define “deep value” as episodes where the valuation spread between cheap and expensive securities is wide relative to its history. Examining deep value across global individual equities, equity index futures, currencies, and global bonds provides new evidence on competing theories for the value premium.
Following these episodes, the value strategy has:
(1) high average returns;
(2) low market betas, but high betas to a global value factor;
(3) deteriorating fundamentals;
(4) negative news sentiment;
(5) selling pressure;
(6) increased limits to arbitrage; and
(7) increased arbitrage activity.
Lastly, we find that deep value episodes tend to cluster and a deep value trading strategy generates excess returns not explained by traditional risk factors.
Two additional related research papers have been included into existing free strategy reviews during last 2 weeks:
A new financial research paper related to:
#5 – FX Carry Trade
Accominotti, Cen, Chambers, Marsh: Currency Regimes and the Carry Trade
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3077029
Abstract:
Carry trade returns vary across fixed and floating currency regimes. Over the last century, outsized carry returns occur exclusively in the floating regime, being zero in the fixed regime. The absence of skewness in floating carry returns rules out a skewness-based explanation for this result. Fixed-to-floating regime shifts deliver negative return shocks to the floating carry strategy, even when controlling for volatility risk. This result explains average excess returns to the floating and therefore the unconditional carry trades over the long-run. We rationalize these findings with a model allowing risk compensation in currency markets to depend on regime.
Cryptocurrencies are at the moment very popular, therefore we decided to point on a short research paper showing interesting cryptos' characteristic – persistance:
Caporale, Gil-Alana, Plastun: Persistence in the Cryptocurrency Market
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3084023
Abstract:
This paper examines persistence in the cryptocurrency market. Two different longmemory methods (R/S analysis and fractional integration) are used to analyse it in the case of the four main cryptocurrencies (BitCoin, LiteCoin, Ripple, Dash) over the sample period 2013-2017. The findings indicate that this market exhibits persistence (there is a positive correlation between its past and future values), and that its degree changes over time. Such predictability represents evidence of market inefficiency: trend trading strategies can be used to generate abnormal profits in the cryptocurrency market.
