The Jordanian capital market: Liquidity cost during COVID19 pandemic infection
Bibliographic record
Abstract
The COVID-19 outbreak has affected the entire global financial market in an unprecedented way. Due to disruptions in the global market, the Jordanian financial market also responded to the pandemic and observed sudden volatility. The outbreak of the virus has led the management of the Jordanian market (Amman Securities Exchange / ASE) to halt trading on the secondary market during the period 17 March 2020 – 9 May 2020. Hence, using daily closing prices of listed firms, this paper empirically examines the market’s liquidity cost before its closure (2 January 2020 – 16 March 2020) and after (10 May 2020 – 31 December 2020). The premise of this objective rests on the fact that the trading activity on the secondary market, following the resumption of trading is carried- out within uncertain circumstances. The data used in this study comes from the daily trading reports published by ASE. All listed companies are included in the analysis. Based on the daily closing bid and ask prices, we calculate the daily spreads during two sub-periods (2 January 2020 – 16 March 2020 and 10 May 2020 - 31 December 2020). We then regress the daily spreads on daily stock prices, number of daily contracts, risk, and where the companies list their shares (first or second market). The main findings of this paper are threefold. First, liquidity cost in the ASE is relatively high. Second, following the resumption of trading on the secondary market, liquidity cost has increased. Third, other known determinants of liquidity cost are significant and have the expected coefficient signs. The fact that liquidity cost in the ASE is high, and higher even after the resumption of trading, necessitates some clear policy measures. These include a reduction in the currently used minimum tick.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".