Time-frequency comovement among green bonds

The primary objective is to explore whether any significant correlations exist between the prices of green bonds, stocks, commodities, clean energy and conventional bonds over a three year timeframe. By analyzing their relationships with respect to both frequency distribution (intra-day) and mean reversion (longer term), we can gain insight into how they behave individually or collectively when exposed to external shocks. In addition, by studying the correlations between these asset classes we can identify potential diversification benefits that investors may be able to exploit in order maximize portfolio returns while minimizing risk exposure.

In order to achieve these objectives, weekly closing prices data will be extracted from relevant stock exchanges over a 24 month period beginning June 2020 through June 2022. This data would then be incorporated into time series analyses which utilize ARIMA models for intra-day price movements; spectral density estimation techniques such as maximum entropy spectral analysis (MESA); wavelet coherency tests; Granger causality tests; copulas; kernel regressions; Kalman filters etc., as appropriate statistical methods for measuring cointegration among different assets and their respective frequencies during different conditions in the market. Once complete there should be clear insights into possible cross dependencies between different asset classes within same time frame – enabling informed investment decisions about best times come out ahead rivals investing same instruments ..

Finally study conclude empirical evidence expected around degree timing frequency comovement individual investable products allow better management portfolios due ability diversify holdings minimize risk while maximizing gains under various situations circumstances . Therefore end project results expected demonstrate great deal understanding established surrounding interactions interdependence financial markets helping create more efficient cost effective strategies twenty first century investor’s arsenal ..