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5 days ago

What Can We Extract From the Financial Influencers’ Advice?

Social media are often the main and primary choice of information in almost every area of our lives, and they also influence the financial decisions of retail traders and investors. A lot of people give opinions anywhere on the Internet; some are respected, others are disrespected, some are more well-known, and others obscure. But the power of those people, financial influencers, as a group, is substantial as they create the market sentiment. But what’s the real value of their advice? Can we extract useful information from their opinions?

Finfluencers

1 min read

What Can We Extract From the Financial Influencers’ Advice?
What Can We Extract From the Financial Influencers’ Advice?
Finfluencers

1 min read


Nov 15

Military Expenditures and Performance of the Stock Markets

“Si vis pacem, para bellum“, is an old Roman proverb translated to English as “If you want peace, prepare for war”, and it is the main idea behind the military policy of a lot of modern national states. In the current globally interconnected world, waging a real “hot war” has…

Military Spending

1 min read

Military Expenditures and Performance of the Stock Markets
Military Expenditures and Performance of the Stock Markets
Military Spending

1 min read


Nov 13

Less is More? Reducing Biases and Overfitting in Machine Learning Return Predictions

Machine learning models have been successfully employed to cross-sectionally predict stock returns using lagged stock characteristics as inputs. The analyzed paper challenges the conventional wisdom that more training data leads to superior machine learning models for stock return predictions. Instead, the research demonstrates that training market capitalization group-specific machine learning models can yield superior results for stock-level return predictions and long-short portfolios.

Machine Learning

1 min read

Less is More? Reducing Biases and Overfitting in Machine Learning Return Predictions
Less is More? Reducing Biases and Overfitting in Machine Learning Return Predictions
Machine Learning

1 min read


Nov 10

Decreasing Returns of Machine Learning Strategies

Traditional asset pricing literature has yielded numerous anomaly variables for predicting stock returns, but real-world outcomes often disappoint. Many of these predictors work best in small-cap stocks, and their profitability tends to decline over time, particularly in the United States. As market efficiency improves, exploiting these anomalies becomes harder. The fusion of machine learning with finance research offers promise. Machine learning can handle extensive data, identify reliable predictors, and model complex relationships. The question is whether these promises can deliver more accurate stock return predictions…

Machine Learning

1 min read

Decreasing Returns of Machine Learning Strategies
Decreasing Returns of Machine Learning Strategies
Machine Learning

1 min read


Nov 6

Quantpedia in October 2023

– A new Quantpedia AI Chatbot unveiled – 12 new Quantpedia Premium strategies have been added to our database – 11 new related research papers have been included in existing Premium strategies during the last month – Additionally, we have produced 7 new backtests written in QuantConnect code – 6 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

Artificial Intelligence

1 min read

Quantpedia in October 2023
Quantpedia in October 2023
Artificial Intelligence

1 min read


Nov 2

Is It Good to Be Bad? — The Quest for Understanding Sin vs. ESG Investing

What are our expectations from the ESG theme on the portfolio management level? The question is whether ESG investing also offers some kind of “alternative alpha”, or outperformance against the traditional benchmarks. There are managers and academics who are enthusiastic and hope for the outperformance of the good ESG stocks. However, the academic research community is really split. Some academic papers show positive alpha for “Saints” (good ESG stocks); others show significantly positive alpha for “Sinners” (bad ESG stocks). So, how it’s in reality? Is it “Good to be Bad”? Or the other way around?

Esg Investing

1 min read

Is It Good to Be Bad? — The Quest for Understanding Sin vs. ESG Investing
Is It Good to Be Bad? — The Quest for Understanding Sin vs. ESG Investing
Esg Investing

1 min read


Oct 29

Estimating Stocks-Bonds Correlation from Long-Term Data

There are a few concepts in the world of finance that are taken for granted, and one of them is the free lunch of diversification. Investors like to mix stocks and bonds into a simple allocation portfolio and hope for better outcomes than investing in just one asset. But the favorable return-to-risk profile of those asset allocation strategies relies on the low correlation between those two asset classes, which, as we will see from today’s contribution, we can’t take for granted. We hope the recent study sheds more light on this topic.

Correlation

1 min read

Estimating Stocks-Bonds Correlation from Long-Term Data
Estimating Stocks-Bonds Correlation from Long-Term Data
Correlation

1 min read


Oct 24

Which Alternative Risk Premia Strategies Works as Diversifiers?

In the ever-evolving world of finance, the quest for stable returns and risk mitigation remains paramount. Traditional asset classes, such as stocks and bonds, have long been the cornerstone of investment portfolios, but their inherent volatilities and susceptibilities to market fluctuations necessitate a more diversified approach. Enter the domain of alternative risk premia (ARP) — strategies designed to capture returns from diverse sources of risk, often orthogonal to traditional market risks. Our exploration in this blog post delves deep into this subject, shedding light on which ARP strategies can truly serve as robust diversifiers in the complex financial tapestry.

Alternative Investments

1 min read

Which Alternative Risk Premia Strategies Works as Diversifiers?
Which Alternative Risk Premia Strategies Works as Diversifiers?
Alternative Investments

1 min read


Oct 18

Hello ChatGPT, Can You Backtest Strategy for Me?

You may remember our blog post from the end of March, where we tested the current state-of-the-art LLM chatbot. Time flies fast. More than six months have passed since our last article, and half a year in a fast-developing field like Artificial intelligence feels like ten times more. So, we are here to revisit our article and try some new hacks! Has the OpenAI chatbot made any significant improvement? Can ChatGPT be used as a backtesting engine? We retake our risk parity asset allocation and test the limits of current AI development again!

ChatGPT

1 min read

Hello ChatGPT, Can You Backtest Strategy for Me?
Hello ChatGPT, Can You Backtest Strategy for Me?
ChatGPT

1 min read


Oct 13

What’s the Key Factor Behind the Variation in Anomaly Returns?

In a game of poker, it is usually said that when you do not know who the patsy is, you’re the patsy. The world of finance is not different. It is good to know who your counterparties are and which investors/traders drive the return of anomalies you focus on. We discussed that a few months ago in a short blog article called “Which Investors Drive Factor Returns?“. Different sets of investors and their approaches drive different anomalies, and we have one more paper that helps uncover the motivation of investors and traders for trading and their impact on anomaly returns.

Factor Investing

1 min read

What’s the Key Factor Behind the Variation in Anomaly Returns?
What’s the Key Factor Behind the Variation in Anomaly Returns?
Factor Investing

1 min read

Quantpedia

Quantpedia

946 Followers

Quantpedia.com — The Encyclopedia of Quantitative and Algorithmic Trading Strategies

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