Community Alpha of QuantConnect – Part 2: Social Trading Factor Strategies

13.August 2021

This blog post is the continuation of series about Quantconnect´s Alpha market strategies. This part is related to the factor strategies notoriously known from the majority of asset classes.

Overall, the factors on alpha strategies provide insightful results that could be utilized. The results particularly point to excluding the most extreme strategies based on various past distribution’s characteristics.

Stay tuned for the 3rd and 4th part of this series, where we will explore factor meta-strategies built on top of the QuantConnect’s Alpha Market.

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Market Sentiment and an Overnight Anomaly

19.April 2021

Various research papers show that market sentiment, also called investor sentiment, plays a role in market returns. Market sentiment refers to the general mood on the financial markets and investors’ overall tendency to trade. The mood on the market is divided into two main types, bullish and bearish. Naturally, rising prices indicate bullish sentiment. On the other hand, falling prices indicate bearish sentiment. This paper shows various ways to measure market sentiment and its influence on returns.

Additionally, we take a look at an overnight anomaly in combination with three market sentiment indicators. We analyse the Brain Market sentiment indicator in addition to VIX and the short-term trend in SPY ETF. Our aim is not to build a trading system. Instead, it is to analyze financial markets behaviour. Overall the transaction costs of this kind of strategy would be high. However, more appropriate than using this system on its own would be to use it as an overlay when deciding when to make trades.

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The Effectivity of Selected Crisis Hedge Strategies

30.July 2020

During past months we made a set of articles analyzing the performance of equity factors and selected systematic strategies during coronavirus crisis. These articles were short-ranged with data only from the start of the year 2020, which is enough for the purpose of the quick blog posts, but very short-sighted to see the nature of these strategies. Therefore, we expanded the time range by 20 years. For a better understanding of hedge possibilities of these strategies, we have added a comparison to essential safe-haven assets, not only to equities.

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YTD Performance of Crisis Hedge Strategies

25.June 2020

After a month, we are back with a year-to-date performance analysis of a few selected trading strategies. In the previous article, we were writing about the performance of equity factors during the coronavirus crisis. Several readers asked us to take a look also on different types of trading strategies, so we are now expanding to other asset classes. We picked a subset of strategies that can be used as a hedge at the times of market stress (at least, that’s what the source academic research papers indicate) and checked how they fared.

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Trend Breaks in Trend-Following Strategies

9.June 2020

Trend-following strategies are very effective when markets are cleanly trending, but they suffer when trends end too soon. How markets behaved during the last few years, were they prone to last-longing trends? Are we able to immunize trend-following to endure the negative impact of trend breaks better? A research paper written by Garg, Goulding, Harvey, and Mazzoleni finds a negative relationship between the number of turning points (a month in which slow 12-month and faster 2-month momentum signals differ in their indications to buy or sell) and risk-adjusted performance of a 12-month trend-following strategy. The average number of turning points experienced across assets has increased in recent years. But we can implement a “dynamic” trend-following strategy that adjusts the weight it assigns to slow and fast time-series momentum signals after observing market breaks to recover much of the losses experienced by static-window trend following…

Authors: Garg, Goulding, Harvey, Mazzoleni

Title: Breaking Bad Trends

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