Risk Parity Asset Allocation

This article is a primer into the methodology we use for the Portfolio Risk Parity report, which is a part of our Quantpedia Pro offering. We explain three risk parity methodologies – Naive Risk Parity (inverse volatility weighted), Equal Risk Contribution and Maximum Diversification. Quantpedia Pro allows the design of model risk parity portfolios built not just from the passive market factors (commodities, equities, fixed income, etc.) but also from systematic trading strategies and uploaded user’s equity curves.

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Quantpedia in April 2021

The time flies very fast, and like every month, I have again a bunch of interesting improvements I would like to present to all of you. We again have two new reports for Quantpedia Pro (the Market Phase Analysis and the Portfolio Risk Parity reports) that I will describe soon.

But first, let’s recapitulate Quantpedia Premium development. Ten new Quantpedia Premium strategies have been added to our database, and twelve new related research papers have been included in existing Premium strategies during the last month. Additionally, we have produced 11 new backtests written in QuantConnect code. Our database currently contains over 430 strategies with out-of-sample backtests/codes.

Additionally, four new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month …

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Hunt for Yield

Thanks to quantitative easing, we see record-low interest rates. While yields for short to intermediate maturities in the US are lower than the inflation but still positive, other developed markets such as Japan or European countries even have bond yields negative. Still, it does not implicate that investors have withdrawn from the fixed income markets. Both individual and institutional investors still participate in bond trading. However, the critical question is how these conditions influence the investors. Does their behavior change? Do they reach for yield and prefer riskier bonds in the search for (positive) real yields? In this blog post, we present three novel research papers that offer insights into this topic.

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Market Sentiment and an Overnight Anomaly

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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