The Impact of Financial Repression on the Economy of Bangladesh

Md. Yousuf — Mon, 27 May 2024 00:00:00 +0000

Purpose: The study's objective is to examine the impact of financial repression on Bangladesh's economy. Moreover, the impact of individual policy tools such as real deposit rate, interest rate restriction, capital account control, share of state-owned commercial bank in total advances, and statutory liquidity ratio will be investigated to find the specific policy that hampers economic activities.

Method: The autoregressive distributed lag (ARDL) method, originated by Pesaran and Shin (1999) and expanded by Pesaran, Shin, and Smith (2001), will be used to look at the long-term relationship. The study uses time series data for Bangladesh's economy from 1973 to 2022.

Results: The findings of the ARDL approach confirm that repressive policies reduce economic growth over the sample period, and the effect becomes weaker after liberalizing the foreign exchange market. However, among the repressive policies, interest rate restrictions, statutory liquidity ratio, and the share of the state-owned bank in the commercial banks have significant adverse effects on economic growth.

Implication: Policymakers should take proper measures to liberalize the financial sector to boost economic activity. The interest rate restrictions, which are already in effect and hamper the fair functioning of the loan market, should be withdrawn.

A Comparative Study of the Equal-Weight Method and Hierarchical Risk Parity in Portfolio Construction

Debjani Palit, Victor R. Prybutok — Tue, 23 Apr 2024 00:00:00 +0000

Purpose: Portfolio optimization is a process in which the capital is allocated among the portfolio assets such that the return is maximized while the risk is minimized. Portfolio construction and optimization has long been an active research area in finance. For the portfolios with highly correlated assets, the performance of traditional risk-based asset allocation methods such as, the mean-variance (MV) method is limited because quadratic optimizers require an inversion of the covariance matrix of the portfolio to distribute weight among the portfolio assets.

Methods: A possible solution to the limitations of traditional risk-based asset allocation methods can be provided by a hierarchical clustering-based Machine Learning method because it uses hierarchical relationships between the covariance of assets in the portfolio to distribute the weight, and inversion of the covariance matrix is not required. A comparison of the performance of a simple non-optimization technique called the Equal-weight (EW) method to the two optimization methods, the Mean-variance method and the HRP method, which is a machine learning method, was conducted in this research.

Results: It was found that in terms of cumulative returns, the equal-weight method has outperformed several more sophisticated optimization techniques, the mean-variance method, and the HRP method. For most of the period, the Sharpe ratio of the HRP method was observed to be similar to the mean-variance method and equal-weight method.

Implications: This research supports the idea that HRP is a feasible method to construct portfolios with correlated assets because the performance of HRP is comparable to the performances of the traditional optimization method and the non-optimization method.

Finance & Economics Review

The Impact of Financial Repression on the Economy of Bangladesh

A Comparative Study of the Equal-Weight Method and Hierarchical Risk Parity in Portfolio Construction