Factor investors face numerous choices that do not end even after picking the set of factors. For instance, should they neutralize the factor exposure? If the investor pursues sector neutralization, does the decision depend on a particular factor? Or are the choices different for the long-only

Most of you have probably heard the saying that somebody “averaged” into or out of his investment position. But what does it exactly mean, and what different dollar-cost averaging strategies exist? We plan to unveil our new “Dollar-Cost Averaging” report for Quantpedia Pro clients next week,

Do common equity factors suffer during bear markets? Undoubtedly, the market factor is a rather unpleasant investment during bear markets, but what about the long-short factors? Are they able to deliver performance? The research paper by Geertsema and Lu (2021) provides several answers and

Equities provide significant long-term returns, but the growth certainly is not constant or even stable. Anyway, this holds for almost every financial asset. Bear markets alternate bull markets, and expansion periods rotate with recession periods. Since recessions and bear markets come hand in hand

Indisputably, we are witnesses of an ETF mega boom. From passive to active ETFs, their numbers seem to be ever-increasing. Since these exchange-traded funds can be excellent (accessible, transparent, liquid) instruments, it is a great necessity to examine their possible usage in active and

In general, a factor is described as a characteristic that can be associated with a group of assets, and it helps to explain their returns and risks. As noted in the literature focusing on CAPM, the market itself can be viewed as the primer and most significant equity factor. Besides the market

As usual, at this time of the year, let us do a short recapitulation of posts on our blog in the previous 12 months. We have published nearly 70 short analyses of academic papers and our own research articles on this blog in 2021. We want to use this opportunity to summarize 10 of them, which were

Grid trading is an automated currency trading strategy where an investor creates a so-called “price grid”. The basic idea of the strategy is to repeatedly buy at the pre-specified price and then wait for the price to rise above that level and then sell the position (and vice versa with shorting

A long time ago, before elevators were a thing, a simple mechanism was used to get the miners in and out of the mines. This mechanism is called a “Man Engine” (or “Fahrkünst” in German language) and works on a simple principle of two reciprocating ladders and stationary platforms. The two

It is indisputable that the data are changing financial markets – computing power has increased, allowing to rise the trends of ML/AI and big data (number of possible predictors or granularity) or HFT strategies. Indeed, not all the datasets are worth the time of academics, investors or traders,

Although the factors in asset pricing models offer a premium in the long run, they are undergoing bull and bear market cycles in the short term. One would expect that it is due to their connection to the business cycles as the factor premium represents a reward for bearing the macroeconomic risks. A

This blog post is the continuation (and finale) of series about Quantconnect’s AlphaMarket strategies. This part is related to the multi-factor strategies notoriously known from the majority of asset classes. We continue in the examination of factor strategies built on top of social trading

Today we will again talk more about the portfolio management theory, and we will focus on techniques for combining quantitative strategies into one multi-strategy portfolio. So, let’s imagine we already have a set of profitable investment strategies, and we need to combine them. The goal of such

Nobody would argue that nowadays, we live in an information-rich society – the amount of available information (data) is constantly rising, and news is becoming more accessible and frequent. It is indisputable that this evolvement has also affected financial markets. Machine learning algorithms

Understanding the risks of any quantitative trading strategy is one of the pillars of successful portfolio management. Of course, we can hope for good future performance, but to survive market whipsaws, we must have tools for sound risk management. The “Value at Risk” measure is such a standard

Ray Dalio, the founder of Bridgewater Associates L.P. and the creator of the All-Weather investment strategy, recommends having some gold in a contemporary environment. He states, “In a world of ongoing pressure for policymakers across the globe to print and spend, zero interest rates, tectonic

Corporate insiders often have insight into a company’s private information, which might help them predict how the shares’ price will move in the coming days. However, laws and regulations are designed to keep them from trading based on this knowledge, as it would be unfair and hurt the

There are many ways one can lose money when investing, and exchange rates are one of the potential risk factors. Luckily, there are several ways to minimize this type of loss in your portfolio. Systematic tactical FX hedging that uses currency factor strategies (for example currency carry, currency

Order book information is crucial for traders, but it can be complex. With the numbers of stocks listed in stock exchanges, it is impossible to track all the available information for the human mind. Therefore, the order flows could be an interesting dataset for machine learning models. The novel

This is the third and final article from the clustering series. If you’ve missed the previous parts, here you can find the first and second parts of the series. This section examines trading strategies based on previously introduced clustering methods. The complete Portfolio Clustering report will

The CAPM model was a breakthrough for asset pricing, but the times where the market factor was most widely used are long gone. Nowadays, if we exaggerate a bit, we have as many factors as we want. Therefore, it might not be straightforward which factor model should be used. Hanauer et al. (2021)

At the beginning of October, we plan to introduce for our Quantpedia Pro clients a new Quantpedia Pro report dedicated to clustering methods in portfolio management. The theory behind this report is more extensive; therefore, we have decided to split the introduction into our methodology into three

The application of alternative data is currently a strong trend in the investment industry. We, too, analyzed few datasets in the past, be it ESG data, sentiment, or company fillings. This article continues the exploration of the alt-data space. This time, we use the research paper by Joenväärä

As mentioned several times, Quantpedia is a big fan of transferring ideas from one asset class to another. This article is another example; we use an idea originally tested on Chinese stocks and apply it to the commodity futures investment universe. The resultant return new asymmetry investment

Finally, what are the five top-performing quantitative trading strategies in 2021? In part 1 of our article, we analyzed tendencies and trends among the Top 10 quantitative strategies of 2021. Thanks to Quantpedia Pro’s screener, we published several interesting insights about them. In part 2 of

As we have mentioned several times, the best course of action for a quant analyst who wants to develop a new trading strategy is to understand a well-known investment anomaly/factor fundamentally and then improve it. Quantpedia is a big fan of transferring ideas derived from academic research from

The year 2021 has been an incredible year for passive equity investors so far. However, in the first part of our article, we talked about quantitative strategies which achieved even better results in 2021 than passive US equity investors. Indeed, there do exist such strategies, at least definitely

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. Although the results are insightful, they are not straightforward, and further analysis could be made.

Around a month ago, we launched a series of short videos called “Quantpedia Explains“, in which we plan to show and explain some of the themes out of quantitative finance that we think are worth mentioning. We have started with a quick intro to individual Quantpedia Pro reports, and now, we have

Nowadays, we see an increasing number of machine learning based strategies and other related financial analyses. But can the machines replace us? Undoubtedly, AI algorithms have greater capacities to “digest” big data, but as always in the markets, everything is not rational. Cao et al. (2021)

As we have promised, we present a short article as an introduction into the methodology of the Quantpedia Pro CPPI reports. Quantpedia Pro clients can use the model portfolio built in the Portfolio Manager as a risky asset to test various variants – Basic CPPI, Drawdown Based CPPI and Dynamic

Nowadays, social media are involved in fields that were unimaginable in the past. Among others, the world of finance, trading and investing is no exception. For example, Stocktwits is a strong community in this area, Seeking Alpha connects (non)professional analysts, and Twitter connects

We again present a short article as an insight into the methodology of the Quantpedia Pro report – this time for the Markowitz Portfolio Optimization. As usually, Quantpedia Pro allows the optimization of model portfolios built from the passive market factors (commodities, equities, fixed income,

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

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

A firm as an independent entity is engaged in a wide range of activities that affect its value. While the impact of some activities on the firm’s value is immediate and indisputable, there also exists a variety of activities that might impact the firm’s value in the future, while their outcome

One of the most popular reports in the Portfolio Analysis section of our Quantpedia Pro tool is “Volatility Targeting”. In this article, we will explain some theory behind this portfolio management method. And then, we will go more in-depth, pick several examples and explain some common

Practitioners widely use asset pricing models such as CAPM or Fama French models to identify relationships between their portfolios and common factors. Moreover, each asset class has some widely-recognized asset pricing model, from equities through commodities to even cryptocurrencies. However,

We hinted in the past few blogs that we were preparing a small surprise. And now it’s time to unveil what we have been cooking during the previous several months. Quantpedia’s main mission is to help with the discovery of new ideas for systematic trading strategies. Our users can quickly

We would like to present our newest own-research about factor allocation and passive versus active strategies clash. However, respecting our blog format, this version is largely shortened and we invite you to read the full version. Introduction In the equity market, there are two types of investing:

Our own research paper ESG Scores and Price Momentum Are More Than Compatible utilized the Knapsack problem to make the ESG strategies more profitable or Momentum strategies significantly less risky. The implementation of the Knapsack problem was created in R, using slightly modified Simulated

The usage of alternative data is now a main-stream topic in investment management and algorithmic trading. So let’s together explore the textual analysis of 10-K & 10-Q filings and analyze how these datasets could be used as a profitable part of investment portfolios. We invite you to read

The presidential campaign is becoming hotter as we are moving closer to this year’s election. But we still have enough time to dig deeper into data about the past elections and prepare for the autumn. Therefore, we have prepared a short video recapitulation of our paper on the pre-election drift.

Our main goal in Quantpedia is to broaden the horizons of our readers in the field of systematic investing and quantitative trading. We do not aim to sell trading signals but to inspire and give fresh ideas, of how to invest limited time and resources on quantitative research. Clients can adopt

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

Momentum in stocks is not only a key strategy in the many portfolios of practitioners, but it is also an attractive research topic for academics. The original idea behind momentum, is that past winner tend to perform well in the near future, and vice versa, past loser tend to underperform (Jegadeesh

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

How should be equity factor strategies implemented? In a long-only (smart beta) way? As a long-short strategy, as most of the hedge funds usually do? Or in a partially-hedged fashion by going long equity factor and shorting market to offset some of the market risks? There is no one universal answer

Nearly two months ago, in a time of the highest turmoil during the current pandemic crisis, we performed a quick assessment of the status of performance of equity factor strategies. The world has still not been able to ward-off health-care crisis completely, but a lot of countries have made

Socially Responsible Investing (also called ESG Factor Investing) grows in popularity. More and more investors enter the stock market not just to invest their savings, but they are also want to support companies that bring positive social or environmental change. ESG factor investing can bring