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Stock exchanges - Part 4


10. Importance of measuring Liquidity in Stock Exchange Markets as well as in a merger between Stock Exchange Markets

Liquidity is important and beneficial for various market players--stock exchanges markets inclusive. When liquidity is high, investors have higher chances of buying and selling stock more easily, quickly, and at low costs, thus more participation. Because of the increased participation, the price impact of trade is limited and the market stability increases. Authorities should therefore enhance liquidity at all costs. Benefits of liquidity are rooted in the market microstructure considering the forces that affect trade, the prices, and quotes. Liquidity measure is beneficial to the traders in that more assets can be purchased at reduced costs as the portfolio strategy is also affected as a result of stock exchange merger. According to Pastor and Stambaugh (2003), liquidity measure is risk factor priced in the market. Therefore, liquidity is risk-reducing and hence most investors would prefer holding assets that have greater liquidity.

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10.1 Time-related Liquidity Measures

Time-related liquidity measures indicate how often transactions or orders take place. Therefore, high values of these measures indicate high liquidity. It thus helps measure the number of transactions per unit time and the number of orders per given time.

10.2 Spread related liquidity measures

On the other hand the spread related liquidity measures which stems from the difference between ask and the bid price as well as its related ted measures presents an approximation of costs incurred when trading. Essentially, smaller spread related liquidity measure signifies that tye stock exchange market is liquid.

Liquidity measurements helps stock exchange merger attract firms to cross-list. Stock exchange markets which are more liquid are likely to benefit from cross-listing, (Pagano et al. 2001). The measure of liquidity helps determine the level of asset return. Based on this premise, liquidity measurement affects a stock exchange markets decision concerning the optimal capital structure. It therefore implies that the issuance of bonds, debts, shares, internal finance greatly depends on the liquidity of the stock exchange market. This therefore helps determine the capital structure of a given stock exchange market.

There are also liquidity dimensions that are interesting to explore in stock exchange markets. It is of importance to measure liquidity in stock exchange markets as it helps determine how much a trade will cost, how long it will take as well as the impact it will have on the market price. Two additional liquidity measures--namely bid-ask spreads and the Amivest liquidity ratios--capture the cost and market impact dimensions of liquidity. These measures help add on the understanding of how the stock exchange merger is likely to affect the stock liquidity, (Nielsson, 2008).

According to Nielsson, (2008), the Amivest ratio is a liquidity measure that helps determine the depths of the market. Basically, it typifies the impact that the trading has on the market price. It helps understand the notion that even though larger amounts can be traded in a liquid stock exchange, only a minimal significant change in the stock price may be realized or there may be no change in the stock price at all. The Amivest liquidity ratio helps measure the trading volume that is associated with the unit change in the stock price. This ratio helps stock exchange markets measure the average ratio of Euro volume to absolute return, where the average is usually taken over all days in the relevant month. Higher Amivest ratio signifies that investors can go ahead and trade a larger number of shares with less change in price. Therefore, a decrease or an increase in the Amivest ratio signifies a similar decrease or an increase in the market depth. This is one aspect of liquidity importance in stock exchange markets, (Nielsson, 2008).

Concerning the turnover liquidity dimension, it helps signify that positive merger effects. For instance, the effects of a positive merger are concentrated on the larger firms as well as those firms with foreign sales, (Nielsson, 2008). Otherwise, other firms are not affected. This helps explain the deepening in the market.

The liquidity measure help signify the effects of stock capitalization. For example, it helps understand that a market can be substantially deepened as a result of larger capitalization stocks, (Nielsson, 2008). The same applies for firms with foreign sales where the liquidity gain is relatively higher than for other firm types, similar to the results that apply to the turnover liquidity measure. Similarly, according to Nielsson, (2008), the outcome of the turnover liquidity measure, the market activity, is applicable for analyzing the market depth. For example, the turnover liquidity measure helps show that the merger in the stock exchange market is not only associated with an increase in turnover for well established firms but as well raises the market depths of the stocks. Another measure of liquidity signifies the cost dimension of the merger. It shows the turnaround costs associated with transactions in a stock exchange market.

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10.3 One Dimensional Liquidity Measures

This is separated into four groups: capturing the size of the firm, the traded volume and the time between the subsequent trades.

10.4 Volume-related Liquidity Measures

Volume related liquidity measures are computed based on a certain volume or amount of shares, per unit time. Generally, they help capture the depth dimension of liquidity. They relate closely to the time dimension due to the fact that higher volumes in the market signifies shorter time required for trading an already defines amount of shares. High liquidity is realized in situation where the volume related liquidity measures are high. Examples of volume related liquidity measures are the turnover and the trading volume. Turnover is computed under a specified given time interval. Turnover was refined to the net trade volume basically calculated as buyer initiated volume less seller initiated volume. As well, turnover is sometimes redefined to relative turnover. Relative turnover compares turnover to the free float of a stock.

The following three liquidity measures are present at any given time even if no transaction takes place. Only the existence of a bid and an ask quote need to assessed. These liquidity proxies are computed for a given period as explained.

  • Depth is calculated as the summation of ask volume and bid in a given time.
  • Log depths is the sum of the logarithms of the best bid and ask volume in the order book.
  • Dollar depth is conversely often calculated as the average of the quoted bid and ask depths in currency terms, analogously to the average depth.

10.5 Time related liquidity measures

These liquidity measures show how frequent transactions or orders take place. Thus, a higher value of the measures denotes higher liquidity. It helps measure the number of transactions per unit time and the number of orders per time unit which counts the orders inserted into the limit order book within the given time interval.

10.6 Spread-related Liquidity Measures

The difference between the ask and the bid price and its related measures gives an approximation of the cost incurred when trading. In addition to fees and taxes, the trader has to pay the spread as cost for the immediate execution of a trade. It is used to determine where the price discovery takes place. The smaller all the spread-related liquidity measures are, the more liquid is the market. The absolute spread is the difference between the lowest ask price and the highest bid price. It is always positive and its lower limit is the minimum tick size.

11. Importance of measuring Earnings in Stock Exchange Market as well as in a merger between Stock Exchange Markets

The most important thing that investors consider most is the earnings. A proper measure of earnings definitely predicts both the short-term and long-term growth. The earnings are always used to show the market returns. These returns are grouped into three: the capital gains due to the earnings growth, the capital gains due to the changes in Price/Earnings ratio, and the income due to dividends payment. A measure of earnings depict that earnings growth is highly variable depending on the year, however, a trough-to-trough or peak-to-peak measure of earnings demonstrates that earnings have long term consistency in measuring the annual growth.

An analytical perspective shows that the factors that for something to affect the stock market, it must first affect the returns by affecting the earnings growth, the dividends payout, and the price/earnings ratio. A measure of the price/earnings ratio shows the primary effect of interest rates. When the interests rates are falling, then, the falling of earnings yields is encouraged i.e. there is higher price/earnings ratio. As the interest rates rise, the earnings yields is encouraged to rise i.e. the price/earnings ratio falls. When the price/earnings ratio begins at extreme levels, then, the effects are strongest and the market faces extreme dangers or benefits. It should be noted that a measure of the past performance in terms of earnings does not assure future results.

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For accurate measure of earnings, there must be two inputs: the actual value-relevant earnings, and the proxy for the best expectation of those earnings. Construct validity issues affect both the measures as the reported earnings contain temporary, permanent, and value-irrelevant components. Therefore, actual value-relevant earnings do not necessarily equal reported earnings, and measurement error plagues any researcher's attempt to systematically identify the actual earnings that is consistent with the definition of earnings underlying the market's expectations (Ayers, Li, and Yeung 2008). More construct validity issues hinders researchers' attempts to identify a proxy for the market's earnings expectations at any point prior to the earnings announcement (Ramnath et al. 2008a and 2008b).

According to Doyle, Lundholm, and Soliman (2006), firms with large extreme forecast errors in a similar direction to the consensus forecast error experience relatively larger contemporaneous price reactions to earnings announcements. From research, it is found that earnings announcements contain important information about future earnings (Kasznik, McNichols, and Maureen 2002). The measure of earnings relies on actual earnings from I/B/E/S as the proxy for the value-relevant component of reported earnings and a consensus of recent analysts’ forecasts (also from I/B/E/S) as the proxy for the market’s expectation of those value-relevant earnings. Earnings surprise is then computed as the actual earnings per share less the consensus forecast (which is standardized by dividing by a scalar, in most cases the stock price) (Garfinkle, and Sokobin 2006).

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