Search results

The author examine the performance of a number of high short interest stocks along with the prices of the GameStop stock and three major stock exchange indices, particularly for the period after the eruption of the Covid-19 crisis.

With the employment of the complexity–entropy causality plane approach, the author categorize the stock prices in terms of the level of informational efficiency.

The author reported that the efficiency level for the index of the high short interest stocks falls considerably, not only at the onset of the Covid-19 crisis but during the health crisis period at hand. This is translated into proof of less uncertainty in predicting the stock prices of these specific stocks. On the other hand, the GameStop prices exhibit the same behavior as those with the high short interest firms, but change considerably in the middle of the crisis. The reversal of the behavior, by obtaining higher informational efficiency levels, is attributed to the short squeeze frenzy that increased the price of the stock many times over. Among the stock market indices, the Dow Jones Industrial Average and the S&P 500 decreased their efficiency levels marginally, after the surge of the crisis, while the Russell 2000 index kept the level intact. The high and stable degree of randomness could be attributed to the measures taken concurrently by the Federal Reserve and the government immediately after the outbreak of the crisis.

This is one of the few studies that examine the impact of short selling behavior on the efficiency level of certain stocks' prices, particularly during the health public crisis. It provides an alternative approach to measuring quantitatively the degree of inefficiency and randomness.

The transmission of monetary policy has received considerable attention due to the sizable enlargement of the Federal Reserve’s balance sheet and consequently of the large reserve balances held by the Depository Institutions. This paper aims to investigate whether changes in the quantity of the reserve balances during the so-called normalization period and the COVID-19 crisis put significant pressure on short-term interest rates and specifically on the Effective Federal Funds rate (EFFR).

Under the new monetary policy regime, with two newly administered interest rates, the authors use the spread of the Federal Funds rates and the Interest on Reserve Balances (as a measure of the price of liquidity. With the means of various models such as the structural vector autoregression, the authors investigate, for two different subsample periods, the effectiveness of the monetary policy and the creation of (any) liquidity effects.

The results showed that when the Fed decreases its balance sheet size, during the normalization period, significant liquidity effects are present meaning that the authorities could influence the stage of the short-term interest rates under the new monetary policy regime. However, this relationship appears to weaken considerably as the level of reserve balances, particularly in response to the COVID-19 pandemic, increases substantially. The authors enriched the findings by highlighting the role of the benchmark repo rate. During the COVID-19 period, and in light of abundant reserve balances, the repo rate reacts more vigorously to a reduction in reserves, whereas an increase in the repo rate seems to exert a strong positive influence on the EFFR.

The findings are very important for the efficiency of the monetary transmission mechanism. An expanded balance sheet is still considered an arcane concept in regard to the structure and its effects on monetary policy implementation. This is one of the only few studies that investigates the effect of the abundant reserve balances on the short-term interest rates for two different in nature subsample periods. It shows as well the interplay between short-term interest rates, secured and unsecured.

This study aims to investigate the cointegration and causality relationships between Hong Kong’s residential property price and stock price, using quarterly data, from the 1st quarter of 1980 to the 3rd quarter of 2015.

In contrast to other studies, the cointegration test used is the autoregressive distributed lag (ARDL) cointegration (bounds testing) approach of Pesaran et al. (2001) that based on the estimation of an unrestricted error correction model and the causality test is based on non-causality test of Granger et al. (2000). Moreover, this research employs recursive least square procedures and Chow (1960) breakpoint test to detect unknown structural break and variation of relationships between residential property and stock price over the whole sample period.

The results of ARDL cointegration tests running from stock to residential property markets provide strong evidence to support the hypothesis that the stock and residential properties are cointegrated. The results of Granger et al. (2000) non-causality test support the view of wealth effect that stock price has an important causal effect on residential property price in Hong Kong but not vice versa. In addition, the results of recursive ordinary least squares coefficients estimates and Chow (1960) test (breakpoint test) for structural instability confirm the variation of the relationships between stock and residential property markets over the sample period.

The empirical results from cointegration and causality tests suggest that the residential asset returns are better predicted by including the lagged difference values of stock price.

This is the pioneering study to examine the cointegration and causality study of stock and residential property price in Hong Kong by employing Pesaran ARDL cointegration approach and Granger non-causality approach. Investors are able to perform an effective evaluation to assist in allocating investment funds, and the government bodies can implement supplement housing policy in response to the public needs.