Abstract

Abstract

This abstract discusses the impact of the 2020 US presidential election on healthcare stocks. It highlights the potential effects of Biden's proposed policies, such as reversing corporate tax cuts and expanding Medicare, on the stock market. The abstract also mentions the availability of consolidated betting data from RealClearPolitics, which shows the likelihood of each candidate winning based on betting averages. The abstract describes the process of incorporating this data into a trading algorithm and monitoring the percentage change in the likelihood of Biden winning. The abstract ends abruptly, possibly due to a character limit.

Abstract

In this QuantConnect discussion, the authors analyze the reasons behind the recent surge in gold prices. They examine the claims made by different sources regarding the relationship between gold prices, expected inflation, and bond yields. To investigate this, they gather data from the Federal Reserve Economic Data (FRED) website, including the 10-year breakeven inflation rate and the 10-year treasury inflation-indexed bond yield data. The authors then conduct a backtest using this data and find that the strategy produces impressive results, but caution that further testing during different market conditions is needed before deploying it live.

Abstract

In this QuantConnect discussion, the focus is on reducing portfolio political risk using "Trump Beta". The idea is to construct a portfolio of securities that have a low correlation with Donald Trump's tweets and public actions. The Trump beta values are obtained from the Political Beta data set, which provides a daily time series of Trump beta values for a collection of securities. The values range between -1 and 1, with 1 indicating perfect correlation and -1 indicating perfect anti-correlation with Trump's betting odds. The portfolio construction model gives equal weight to the selected securities for 7 days. Two backtests were conducted, one with securities closest to zero Trump beta values and the other with securities furthest from zero. The results showed that the portfolio targeting high Trump beta values had a higher return of 8.83% compared to 5.08% for the low Trump beta portfolio.

Abstract

In this episode of Idea Streams, the focus is on buying Bitcoin and testing different strategies for entering a market at all-time highs with high volatility. The strategy employed is dollar-cost averaging, which involves investing a fixed amount over a period of time to minimize volatility. Two different strategies were created: one that buys $10 worth of Bitcoin every week and another that deposits money into the portfolio each week. The backtests were set to start on January 1, 2017, and the results showed an equity curve that gradually increased over time. The value of the portfolio increased as the price of Bitcoin rose. This discussion provides insights into trading crypto, incorporating dollar-cost averaging, and simulating money deposits. The source code of the project can be cloned for further reference.

Abstract

In Idea Streams #12, the relationship between rising bond yields and market shocks is investigated. The strategy aims to capitalize on this relationship by staying invested in the S&P 500 but exiting when there is a large increase in bond yields. To quantify a "large increase," a threshold of 2.5 standard deviations above the 90-day average is used. The strategy was tested using a custom data set for the S&P 500 index since 1970 and bond yield data from the Federal Reserve Economic Data website. Two backtests were conducted, one with the strategy and one without. The results of the strategy backtest were observed and compared to the benchmark.