We’ve already analyzed tens of thousands of financial research papers and identified more than 700 attractive trading systems together with hundreds of related academic papers.
Browse Strategies- Unlocked Screener & 300+ Advanced Charts
- 700+ uncommon trading strategy ideas
- New strategies on a bi-weekly basis
- 2000+ links to academic research papers
- 500+ out-of-sample backtests
- Design multi-factor multi-asset portfolios
Upgrade subscription
Several research papers show that investor sentiment, also known as market sentiment, plays a part in market returns. Market sentiment refers to the general mood on the financial markets and investors’ overall tendency to trade. There are two types of mood on the market: bullish and bearish. Rising prices indicate bullish sentiment, while falling prices indicate bearish sentiment.
There are numerous ways to measure sentiment in the financial markets. Traditional sentiment indicators include the CBOE Volatility Index (VIX), High-Low Index or Bullish Percent Index (BPI). Another way to measure sentiment is by using various news sources, social media or other market sentiment indicators. This paper shows various ways to measure market sentiment and its influence on returns.
Additionally, traders have noticed that the US stocks have significantly higher return during the night sessioncompared to the daily session. Multiple academic studies have confirmed this suspicion and found that the US equity premium is mostly due to overnight returns. This paper looks at an overnight anomaly combined with three market sentiment indicators, including Brain Market sentiment indicator, VIX and the short-term trend in SPY ETF.
Fundamental reason
There are numerous possible reasons, which can explain an overnight anomaly. Academic studies show that part of the reason for an overnight anomaly is the high opening prices derived from the accumulation of market orders from market participants, which subsequently decline in the first hour of trading. Some portion of positive overnight returns can be expected due to an illiquidity premium, but liquidity can explain only a small part of the night and day return difference.
Additionally, the explanation for market sentiment is pretty simple. When the sentiment is bullish the general mood on the market is good which means the investors tend to buy more, which makes the mood even better. On the other hand, when the sentiment is bearish the general mood on the market is not so good which means the investors tend to buy less, which makes the mood even worse.
- Unlocked Screener & 300+ Advanced Charts
- 700+ uncommon trading strategy ideas
- New strategies on a bi-weekly basis
- 2000+ links to academic research papers
- 500+ out-of-sample backtests
- Design multi-factor multi-asset portfolios
Backtest period from source paper
2018-2021
Confidence in anomaly's validity
Strong
Indicative Performance
15.58%
Notes to Confidence in Anomaly's Validity
Notes to Indicative Performance
Table on page 5, Equally-Weighted Portfolio, 20-day MA
Period of Rebalancing
Daily
Estimated Volatility
7.33%
Notes to Period of Rebalancing
Notes to Estimated Volatility
Table on page 5, Equally-Weighted Portfolio, 20-day MA
Number of Traded Instruments
1
Notes to Number of Traded Instruments
Notes to Maximum drawdown
Table on page 5, Equally-Weighted Portfolio, 20-day MA
Complexity Evaluation
Moderately complex strategy
Notes to Complexity Evaluation
Financial instruments
ETFs
Simple trading strategy
The investment universe consists of SPY ETF, and the price of SPY, price of VIX and Brain Market Sentiment (BMS) indicator are used to identify the market sentiment. The investor buys SPY ETF and holds it overnight; when the price of SPY is above its 20-day moving average, the price of VIX is below its moving average, and the value of the BMS indicator is greater than its 20-day moving average.
Note that the authors suggest using this strategy as an overlay when deciding whether to make a trade rather than using this system on its own.
Hedge for stocks during bear markets
Partially - Strategy’s goal is to hold equity portfolio only in positive times (low risk and low volatility times) and otherwise be out of equities. So, it could be expected that the strategy would not suffer significant drawdowns since it would not be invested at all.
Out-of-sample strategy's implementation/validation in QuantConnect's framework
(chart+statistics+code)