UPDATE – Quantpedia’s Site Maintenance

22.August 2019

Hello,

We’ve launched our new website with the updated core back-end technology. Therefore it’s required for all users to change their password (your previous will not work anymore).

It’s really simple, just visit this link:
http://quantpedia.com/login/?action=forgot_password

If you would like to submit any feedback regarding our new website, please let us know at info@quantpedia.com

We appreciate your patience and understanding.

Thanks,

Radovan Vojtko

CEO

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Media Attention and the Low Volatility Effect

18.August 2019

The low volatility factor is a well-known example of a stock trading strategy that contradicts the classical CAPM model. A lot of researchers are trying to come up with an explanation for driving forces behind the volatility effect. One such popular explanation is the ‘attention-grabbing’ hypothesis – which suggests that low-volatility stocks are ‘boring’ and therefore require a premium relative to ‘glittering’ stocks that receive a lot of investor attention. Research paper written by Blitz, Huisman, Swinkels and van Vliet tests this theory and concludes that ‘attention-grabbing’ hypothesis can't be used to explain outperformance of low volatility stocks.

Related to: #7 – Low Volatility Factor Effect in Stocks

Authors: Blitz, Huisman, Swinkels, van Vliet

Title: Media Attention and the Volatility Effect

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Metcalfe’s Law in Bitcoin

12.August 2019

Cryptocurrencies are a new asset class, and researchers have just started to understand better fundamental forces which are behind their price action. A new research paper shows that Bitcoin’s price can be modeled by Metcalfe’s Law. Bitcoin (and other cryptocurrencies) are in this characteristic very similar to Facebook as their value depends on the number of active users – network size

Authors: Peterson

Title: Bitcoin Spreads Like a Virus

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Three New Insights from Academic Research Related to Equity Momentum Strategy

4.August 2019

What are the main insights?

– the momentum spread (the difference of the formation-period recent 6-month returns between winners and losers) negatively predicts future momentum profit in the long-term (but not in the following month), the negative predictability is mainly driven by the old momentum spread (old momentum stocks are based on whether a stock has been identified as a momentum stock for more than three months)

– the momentum profits based on total stock returns can be decomposed into three components: a long-term average alpha component that reverses, a stock beta component that accounts for the dynamic market exposure (and momentum crash risk), and a residual return component that drives the momentum effect (and subsumes total-return momentum)

– the profitability and the optimal combination of ranking and holding periods of momentum strategies for a sample of Core and Peripheral European equity markets the profitability vary across markets

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Quantpedia in July 2019

30.July 2019

Dear readers,

With summer at full steam, July was a busy month for the Quantpedia team. Four new Quantpedia Premium strategies have been added into our database and four new related research papers have been included into existing Premium strategies.

Additionally, we have produced 21 new backtests written in QuantConnect code. Our database currently contains 90 strategies with such codes/backtests.

Also, four new blog posts you may find interesting have been published on our Quantpedia blog:

50 Years in PEAD (Post Earnings Announcement Drift) Research
Authors:  Sojka
Title:  50 Years in PEAD Research

Equity Factor Strategies In Frontier Markets
Authors: Zaremba, Maydybura, Czapkiewicz, Arnaut
Title:  Trends Everywhere

Two Versions of CAPM
Author:  Siddiqi
Title:  CAPM: A Tale of Two Versions

Factor Investing in Currency Markets
Authors:  Baku, Fortes, Herve, Lezmi, Malongo, Roncalli, Xu
Title:  Factor Investing in Currency Markets: Does it Make Sense?

Best regards,

Team Quantpedia.com
 


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Factor Investing in Currency Markets

26.July 2019

A new research paper related to multiple currency strategies:

#5 – FX Carry Trade
#8 – Currency Momentum Factor
#9 – Currency Value Factor – PPP Strategy

Authors: Baku, Fortes, Herve, Lezmi, Malongo, Roncalli, Xu

Title: Factor Investing in Currency Markets: Does it Make Sense?

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3415700

Abstract:

The concept of factor investing emerged at the end of the 2000s and has completely changed the landscape of equity investing. Today, institutional investors structure their strategic asset allocation around five risk factors: size, value, low beta, momentum and quality. This approach has been extended to multi-asset portfolios and is known as the alternative risk premia model. This framework recognizes that the construction of diversified portfolios cannot only be reduced to the allocation policy between asset classes, such as stocks and bonds. Indeed, diversification is multifaceted and must also consider alternative risk factors. More recently, factor investing has gained popularity in the fixed income universe, even though the use of risk factors is an old topic for modeling the yield curve and pricing interest rate contingent claims. Factor investing is now implemented for managing portfolios of corporate bonds or emerging bonds.

In this paper, we focus on currency markets. The dynamics of foreign exchange rates are generally explained by several theoretical economic models that are commonly presented as competing approaches. In our opinion, they are more complementary and they can be the backbone of a Fama-French-Carhart risk factor model for currencies. In particular, we show that these risk factors
may explain a significant part of time-series and cross-section returns in foreign exchange markets. Therefore, this result helps us to better understand the management of forex portfolios. To illustrate this point, we provide some applications concerning basket hedging, overlay management and the construction of alpha strategies.

Notable quotations from the academic research paper:

"In this paper, we propose analyzing foreign exchange rates using three main risk factors: carry, value and momentum. The choice of these market risk factors is driven by the economic models of foreign exchange rates. For instance, the carry risk factor is based on the uncovered interest rate parity, the value risk factor is derived from equilibrium models of the real exchange rate, and the momentum risk factor bene fits from the importance of technical analysis, trading behavior and overreaction/underreaction patterns. Moreover, analyzing an asset using these three dimensions helps to better characterize the fi nancial patterns that impact an asset: its income, its price and its trend dynamics. Indeed, carry is associated with the yield of the asset, value measures the fair price or the fundamental risk and momentum summarizes the recent price movements.

FX Carry

FX Value

FX Momentum

By using carry, value and momentum risk factors, we are equipped to study the cross-section and time-series of currency returns. In the case of stocks and bonds, academics present their results at the portfolio level because of the large universe of these asset classes. Since the number of currencies is limited, we can show the results at the security level.

For each currency, we can then estimate the sensitivity with respect to each risk factor, the importance of common risk factors, when speci fic risk does matter, etc. We can also connect statistical figures with monetary policies and regimes, illustrating the high interconnectedness of market risk factors and economic risk factors. The primary goal of building an APT model for currencies is to have a framework for analyzing and comparing the behavior of currency returns. This is the main objective of this paper, and a more appropriate title would have been "Factor Analysis of Currency Returns". By choosing the title "Factor Investing in Currency Markets", we emphasize that our risk factor framework can also help to manage currency portfolios as security analysis always comes before investment decisions.

This paper is organized as follows. Section Two is dedicated to the economics of foreign exchange rates. We fi rst introduce the concept of real exchange rate, which is central for understanding the di fferent theories of exchange rate determination. Then, we focus on interest rate and purchasing power parities. Studying monetary models and identifying the statistical properties of currency returns also helps to defi ne the market risk factors, which are presented in Section Three. These risk factors are built using the same approach in terms of portfolio composition and rebalancing. Section Four presents the cross-section and time-series analysis of each currency. We can then estimate a time-varying APT-based model in order to understand the dynamics of currency markets. The results of this dynamic model can be used to manage a currency portfolio. This is why Section Five considers hedging and
overlay management."


Are you looking for more strategies to read about? Check http://quantpedia.com/Screener

Do you want to see performance of trading systems we described? Check http://quantpedia.com/Chart/Performance

Do you want to know more about us? Check http://quantpedia.com/Home/About


Follow us on:

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