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“US Venture Exit Value Achieved $290 Billion in 2020 Alongside Record Years for Investment and Fundraising Activity,” - the National Venture Capital Association, January 2021.
A recent Greenwich Associates survey identified five groups of trading algorithms that accounted for three-quarters of the algo executions in US equity markets. This article considers the types of buy-side trading strategies and the required execution outcomes that drive the selection of the algorithm.
As the S&P 500 steadily trended upward throughout April, I noticed again that the financial news media were neglecting algorithmic trading. I can guarantee though, that the effects of algorithms on market moves will become a hot topic again as soon as we experience a strong downward trend.
Deutsche Bank recently published their list of market risks for 2019. Topping that list is “Algo-driven, risk-parity driven fire sale in equities and credit continues.” In a previous article (insert reference) I discussed the impacts of algorithmic trading, but this article is focused specifically on risk-parity strategies.
As the US equity markets closed on Tuesday December 5, 2018, with the Dow Jones Industrial Average down nearly 800 points and broader markets off more than 3%, CNBC’s Fast Money panel engaged in a spirited discussion regarding the impact of algorithmic trading on the market moves. The consensus? Algorithms accelerated market moves, both up and down.
As US stock markets came off recent highs, it was noted that other markets were more strongly correlated with equities than in the past, making hedging of downside stock market risk more difficult. Investors typically hold a portfolio of bonds and stocks, as bond prices tend to rise when equities fall and there is a “flight to quality” as investors seek the relative haven of bonds. However, with low interest rates and the chance of more rate-cuts slim, bond prices aren’t moving enough to offset the impact of falling equities.
In modern financial markets, most of the trading volume is executed electronically. E-trading has been expanding, not only in the speed and sophistication of the computer models and infrastructure, but also through expansion to new asset classes and markets. The expansion in e-trading will continue, and innovations such as machine learning and artificial intelligence are sure to add further complexity.
As assets held in funds that track broad equity-market indexes in the U.S. exceeded those in actively managed funds for the first on August 31, I thought it would be worth revisiting the impact of index rebalance trades on stock prices.
As other markets started becoming more electronic, our quants started seeing opportunities to flex in these new areas. The huge spot FX markets, with trading around the clock, seemed like fertile grounds for the quants, so we started to trade on electronic platforms like EBS.
Blockchain technology will play a significant role in the further evolution of global securities markets