English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Market indicators such as CPI and GDP have been widely used over decades toidentify the stage of business cycles and also investment attractiveness ofsectors given market conditions. In this paper, we propose a two-stagemethodology that consists of predicting ETF prices for each sector using marketindicators and ranking sectors based on their predicted rate of returns. Weinitially start with choosing sector specific macroeconomic indicators andimplement Recursive Feature Elimination algorithm to select the most importantfeatures for each sector. Using our prediction tool, we implement differentRecurrent Neural Networks models to predict the future ETF prices for eachsector. We then rank the sectors based on their predicted rate of returns. Weselect the best performing model by evaluating the annualized return,annualized Sharpe ratio, and Calmar ratio of the portfolios that includes thetop four ranked sectors chosen by the model. We also test the robustness of themodel performance with respect to lookback windows and look ahead windows. Ourempirical results show that our methodology beats the equally weightedportfolio performance even in the long run. We also find that Echo StateNetworks exhibits an outstanding performance compared to other models yet it isfaster to implement compared to other RNN models.

Two-Stage Sector Rotation Methodology Using Machine Learning and Deep Learning Techniques