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文献信息文献标题：Firm’s Size and Solvency Performance: Evidence from the Malaysian Public Listed Firms（公司规模和偿债能力：来自马来西亚上市公司的证据）文献作者：AK Ramin等文献出处：《Journal of Engineering and Applied Sciences》,2017, 12(5): 1240-1244字数统计：英文3045单词，15732字符；中文4929汉字外文文献Firm’s Size and Solvency Performance: Evidence from theMalaysian Public Listed FirmsAbstract Firm solvency is one of the important indicators in measuring firm’s performance. Firm ability to grow and sustaining their business in the highly competitive business environment depends significantly on its cash flow management capacity that subsequently results to a business stay solvent at every phase of business life cycle. Early detection of financial distress is important for every firm of various sizes. Previous findings on firm’s size and solvency performance varies which tendency on agreeing to the assumption that larger firms have the advantages to avoid insolvency as compare to smaller firms. However, previous studies have also revealed that larger firms such as public listed company were not escape from facing financial distress which eventually lead to insolvency. Therefore, the study was aimed to mdentify the influence of firm’s size and solvency performance of public listed firms in Malaysia. A total of 149 firms were used to measure their financial data performance for a period between 2011 and 2014. Firm total assets and paid capital were used as a proxy to firm size. The current ratio and debt ratio were used as a proxy to measure the solvency performance. The study found that firm size measuredby total assets has moderately influence the solvency performance of firms indicated by the debt ratio and current ratio. However the firm size measured by paid-up capital has lesser influence on solvency performance measured by debt ratio and no influence on current ratio.Kev words: Current ratio, debt ratio, firm size. Insolvency, liquidity, SolvencyINTRODUCTIONIn any situation, firms should be able to meet short and long term obligation to achieve operational sustainability. In this situation, firms with operational sustainability were regarded as in the position of solvency. Insolvency occurs when a firm’s total liabilities exceeded a fair valuation of its total assets. Previous study by Brigham and Houston (2012) described technical insolvency as the position whereby firms were unable to meet their current obligations as they fall due (that is the firm’s current assets are lower than its current liabilities) despite having higher total assets than the total liabilities. Early detection of financial distress is important in avoiding insolvency. Public listed firms were relatively capable in managing liquidity to ensure that they remain in solvency position sustainably. Previous findings on the relation ship between firm’s size and solvency performance shows mixed result which tendency on agreeing to the assumption that large firms have the advantages over small firm to remain solvent. However, prior studies have also revealed that larger firms such as public listed companies were not immune from having financial distress which eventually leads to insolvency. Firm ability in servicing and repaying debts was the main indicator of the solvency position measurement of any firms (Zhang and Zhang, 2010). Earlier empirical studies by Coleman (2002), Obert and Olawale (2010) that focus on larger firm in various developed countries suggest that large firms showed that size have significant impact on the ability in serving debts lead to greater chances in sustaining their solvency position. This finding consistent with a study by Sahudin et al. (2011 ) in which larger firms allows a greater level of debt management towards their ability to sustain the solvency position. Despite many findings revealed that larger firms have an advantages over the smaller firms in managing their liquidity,there were cases particularly in which Practice Note (PN 17) was served to considerably large firms listed in Bursa Malaysia as a result of liquidity issues. PN 17 is the control procedure specifically for public listed companies which are facing financial distress and to be delisted from the stock exchange. There were 21 firms subjected to PN 17 as at first half of 2015 bringing the total listing of financial distress firms to 2.32% of the total listed firms on the stock exchange. Shareholders and investors continue to demand for healthy firms to ensure their investments. Solvency and liquidity of firms would remains significant elements for managers to manage for sustainability of the firms. It is pertinent for managers to understand about business failures, its causes and its possible remedies (Sulub, 2014). Therefore, the study was aimed to mdentify the influence of firm’s size on solvency performance of public listed firms on the Bursa Malaysia (BM).LITERIATURE REVIEWPast researchLun and Quaddus (2011 ) in their study among Hong Kong electronic industry propagated that firm size does influence the performance of business. In other findings suggested that smaller firms were more likely to issue equity while larger firms are more likely to issue debt rather than equity which influence the liquidity. Past study done by Cassar and Holmes (2003) and Esperanca et al. (2003) found a positive relationship between firm size and long-term debt but a negative relationship with short-term debt which eventually influence the liquidity. Other study suggested that firm size and capital structure strategy may influence firm’s solvency performances. Other finding by Beck et al. (2008) indicated that firms size influence the firm’s performance which includes the solvency and liquidity operation. Findings from Rajeev indicated that small firms were much faced higher risks of liquidity as compared to those larger firms. Therefore, these two findings show a risk versus return trade-off that exists at the firm performance level in relation to firm’s size. Justification of this findings propagated that larger firms have the advantages to access for better resources and skill competencies to better manage the firm. Otherproponent to this hypothesis added that economies of scale only can only be found at larger firms (Nguyen and Reznek, 1991). Despite many findings propagated that larger firms have better performance in term of solvency, there were findings which argued that smaller firms may also performance better in term of efficiency, growth and liquidity. Recent finding by Vithessonthi and Tongurai (2015), firm size does not influence the firm performances during the 2000-2009 Thailand financial crisis.Other finding by Campos and Sanchis (2015) firm’s size among agricultural industry in Spam does not influence the performance of liquidity and solvency of the industry. In general, performance of firms such as the productivity, firm size to be found in mix ed contribution towards firm’s productivity which could influence the financial health of the operation (Pompe and Bilderbeek, 2005). Earlier finding by Michaelas et al. (1999) also supported that a debt ratio and firm’s size could correlate depending on the other factors within the firms.Other findings by Bourlakis et al. (2014) suggest different small firm performed better in case of agriculture industry in Greek. Small firms preferred to opt for short-term finance as compared to larger firms and better performed as opposed to larger firms. It may caused small firms highly sensitive to short term economic environment as oppose to larger firms. It is concluded that the relationship between firm’s size and firms performance findings varies as many other fac tors may influence the both variables. It is therefore, continuous study on this issues remain relevant as economic factors continue to influence firms operation.Firm sizeFirm size has been widely used as a control variable in empirical research specifically to corporate finance. Firm size matter for many reasons, it is said that larger firms are better in managing their cash flow, therefore difficult to fail and liquidate (Shumway, 2001 ). Size can also be the proxy for the volatility of firm’s assets. Additionally, measurement of firm size varies according to the research perspective. Rajeev suggested that firm size is defined according to the value of a firm’s assets. In addition, Sahudin et al. (2011 ) propagated that the size of firm is defines as the logarithm of total assets of the firms used in business; Firm s= log e,Total asset. Previous scholar such as Kato and Honho and Sun preferred to use total assets value to represent firm’s size to measure liquidity and predictor for bankruptcy. While some researchers used asset value as the proxy to firm’s size, others have suggested alternative measurement such as paid up capital as a proxy for firm’s size. According to Allen paid-up capital for a firms company is the number of shares outstanding multiplies the face value of the shares. Kidanu defined paid-up capital as the amount of capital which is contributed/paid by owner(s) during the establishment of a firm adopting measurement of firm’s size using paid-up capital is a more stable measure of firm size (Ponnu and Okoth, 2009). Other researcher suggested that total assets as a proxy for firm size indicated the influence of firm’s size and solvency performance (Vithessonthi and Tongurai, 2015). In view of the widely adopted by other researcher, this stud y employed this variable as the proxy for firm’s size.SolvencyThe importance of knowing solvency through the optimal debt ratio could help policymakers and financial managers to formulate an appropriate financing policy that could prevent companies from going into financially distressed situation due to excessive level of debt (Ahmad and Abdullah, 2011). Previous researches works widely suggested that ‘Debt Ratio’ (DR) and ‘Debt to Equity Ratio’ (DER) be used as a proxy to solvency (Khidmat and Rehman, 2014). DR was widely used as its reflecting the company’ liability situation and has the best protection degree for borrower’s benefit and it is the basic ratio in translatmg financing structure as well as easy to define and calculate (Li and Jian, 2008). Other proponent on the use of DR was finding by Ahmad and Abdullah (2011) in which DR was consistent with trade-off theory which hypothesize that high debt ratio will lead to financial distress and thus deteriorate the firm value. Other measurement on solvency was based on performance of Current Ratio (CR). The CR measure a firm’s ability to pay current obligations on business such as operating and financial expenses is current ratio. Current ratio consists of cash and near-cash assets (together called “current” assets) of a business on one side and immediate payment obligations (current liabilities) on the other side. Using the CR to measure solvency enable firms to monitor paymentobligations include dues to suppliers, operating and financial expenses that must be paid shortly and maturing installments under long-term debt (Saleem and Rehman, 2011; Altman, 1968). It is therefore, CR and DR were adopted in this study as a proxy for solvency performance.MATERIALS AND METHODSThis study employs quantitative methodology involving collection of secondary audited financial data from 149 firms for a period between 2011 and 2014 representing a sample size of 16% from a total of 934 firms listed on Bursa Malaysia. Quantitative method based on secondary data was employed as simple random sampling technique was employed to select a sample representing type of sector and firm size. Table 1 shows industrial product accounts the largest number of the samples which were 47 firms (31 .5%) and followed by trade and service sector of 35 firms (23.5%). There were 25 firms or 16.8% representing consumer sector. Property sector accounts for 12.1 % or 18 sample firms. The remaining samples came from construction, plantation and technology and hotel industry. Detail breakdown of samples firms is depicted in Table 1 (Dhawan, 2001).Table I : Samples firms by sectorsSector Frequency PercentageIndustrial product 47 31.5Trade and service 35 23.5Consumer 25 16.8Property 18 12.1Construction 9 6.0Plantation 7 4.7Technology 5 3.4Finance 3 2.0Total 149 100.0Data observations covers annual reports from 149 firms for 4 years period were analysis using excel prior to further analysis using SPSS. Firm size was measure by total assets of the firms and paid up capital. Total assets were derived as:Fixed assets + Current assets (1) Debt ratios were calculated as:Total debt/total asset (2)Current ratios were calculated as:Total current assets/Total current liabilities (3)RESULTS AND DISCUSSIONDescriptive analysis on debt ratios and current ratio resulted in their respective mean scores of each firm’s size category as depicted in Table 2 mean score for DR varies according to firm’s size in which small f irms scored mean of 0. 259, medium size; 0.378 and larger firm scored mean of 0. 452. For the CR, small firm scored mean of 6.605, medium firm; 2.534 and larger firm scored 2.562. Correlation test on the relationship between firm size (total assets) and DR yielded p<0. 005 and r-value of 0.313 indicated that there was a moderate positive correlation between two variables as depicted in Table 3. Firm size (total assets) value correlate with the performance firm’s debt ratio indicating that as the asset value increase it will also resulted to moderate and significant increase in the firm’s DR.Table 2: Mean score of DR and CR for various firm’s sizeFrim size (total assets) Mean Debt Ratio (DR) Mean Current Ratio (CR) Small frim (TA<RM 100mil) 0.259 6.605 Medium frim (RM 100mil<TA<RM 499 mil) 0.378 2.534Large frim (TA>RM 499 mil) 0.452 2.562 Table 3: Correlation between total assets and debt ratio from year 2011 -2014 spearman's rho DR TADRCorrelation coefficient 1.000 0.313**Sig. (2-tailed)- 0.000N 149 149TACorrelation coefficient0.313** 1.000Sig. (2-tailed)0.000 -N 149 149* *Correlation is significant at the 0.01 level (2-tailed)Further, test on the correlation between firm sizes (total assets) on CR yielded r-value of 0.194 and p-value of 0.018, p<0. 005 indicated that was a weak and significant positive correlation between the two variables as highlighted in Table 4.Table 4: Correlation between total assets and current ratio from years 2011-2014spearman's rho CR TACRCorrelation coefficient 1.000 0.194*Sig. (2-tailed)- 0.018N 149 149TACorrelation coefficient0.194* 1.000Sig. (2-tailed)0.018 -N 149 149* *Correlation is significant at the 0. 05 level (2-tailed)A test was also conducted on the relationship between firm size measures by paid-up capital against the DR. The finding indicated that there was a weak and significant positive correlationbetween paid-up capital and debt ratio, r = 0.299, p<0. 005 (Table 5 and 6).Table 5: Correlation between paid-up capital and debt ratio from years 2011-2014 spearman's rho DR Paid-up capitalDRCorrelation coefficient 1.000 0.299**Sig. (2-tailed)- 0.000N 149 149Paid-up capitalCorrelation coefficient0.299** 1.000Sig. (2-tailed)0.000 -N 149 149Table 6: Correlation between paid-up capital and current ratio from years 2011-2014 spearman's rho CR Paid-up capitalCRCorrelation coefficient 1.000 0.214**Sig. (2-tailed)- 0.009N 149 149Paid-up capitalCorrelation coefficient0.214** 1.000Sig. (2-tailed)0.009 -N 149 149The final test on the relationship between paid-up capital and current ratio yielded r = 0. 214, p<0. 009. The result indicated that there was a weak and significant positive correlation between the two variables. All in all, the correlation analysis indicates that there exist significant positive correlation between measure of firm sizeand solvency performance. Nevertheless, it is important to note the correlations are rather weak. With highest linear correlation at 0.313 it does suggest that firm size has quite minimum impact on firm’s solvency performance. The findings also support prior studies that the relationship between firm size and solvency performance is mixed.CONCLUSIONSummary of the findings can be concluded that firm’s size measured by total assets does influence the firm’s solvency performance for both measurement of debt ratio and current ratio. The ability to optimize higher assets value may help firm improve their liquidity. This findings was consistence with previous studies by Michaelas et al. (1999), Hall et al. (2000) and Sogorb-Mira (2005) in which a positive relationship between firm size (assets) and leverage and solvency measured in the ratio of total debt (long-term debt).As for the relationship between paid-up capital and solvency performance, the debt ratio found to be influence by the paid-up capital while current ratio showed no relationship with the size of paid-up capital. It was nature of paid-up capital which used as initial resources to start the business operation. Over the time paid up capital relatively experience fewer changes despite the need for additional resources. Firms are preferred to sources external funding as compare to equity financing. However, the use of debt can also increase the financial risk of a firm and lead to the insolvency. According to Coleman and Cohn (2002) and Coleman (2002), debt is one of the variables that can cause insolvency for most of firms. Failure rates in the range of 50-75% were commonly cited for smaller firms, making it difficult for smaller firms to raise external capital from either debt or equity providers. The weak of financial structure as reflected by the gearing (debt-equity ratio) has been found to be the key source of insolvency. Many firms were unable to keep up this high debt ratio and, later become insolvent. A high debt ratio in itself, does not make a firm insolvent as long as the firm is earning enough to cover interest and principal payments when it they come due. However, the more leveraged a firm is the more vulnerable it is tobankruptcy. Therefore, the flow of earnings and the ability of the firm to make interest and principal payments will determine whether the firm will actually become insolvent or otherwise (Kim and Lee, 2002). The prediction and prevention of financial distress is one of the major factors that should be analyzed in advance as an early warning signal and to avoid bankruptcy. In addition to the awareness that can make a company successful, it is also useful for managers to have an understanding of business failures and bankruptcy, its causes and its possible remedies. In conclusion, firm size does matter, although the impact is quite small in term of their influence towards solvency performance. However, equally important is the ability of the managers to leverage available resources within the firms to strive for healthy financial position and remain solvent all the time.中文译文公司规模和偿债能力：来自马来西亚上市公司的证据摘要企业偿债能力是衡量企业绩效的重要指标之一。

融资租赁中英文对照外文翻译文献

融资租赁中英文对照外文翻译文献XXX LeasingSmall and medium-sized companies have XXX in the global economy。

In this article。

we will discuss the XXX.2.XXX LeasingXXX it provides them with a number of advantages。

One of the main XXX without having to make a large upfront investment。

This is particularly XXX that may not have access to the capital XXX.XXX it allows companies to keep up with the latest XXX。

which means that companies can stay up-to-date without having to make nal XXX.3.XXX LeasingXXX whether a small company will choose to lease or not。

One of the most important factors is the cost of leasing versus the cost of purchasing。

Small XXX associated with each n in order to make an XXX.Another factor that can XXX is the length of the XXX。

XXX.4.nIn n。

leasing XXX。

it is XXX.At the turn of the 20th century。

mass n methods neered by Ford Motor Company led people to believe that large-scale business enterprises were the way of the XXX well into the late20th century。

金融学融资融券中英文对照外文翻译文献

中英文对照翻译Margin Trading Bans in Experimental Asset MarketsAbstractIn financial markets, professional traders leverage their trades because it allows to trade larger positions with less margin. Violating margin requirements, however, triggers a margin call and open positions are automatically covered until requirements are met again. What impact does margin trading have on the price process and on liquidity in financial asset markets? Since empirical evidence is mixed, we consider this question using experimental asset markets. Starting from an empirically relevant situation where margin purchasing and short selling is permitted, we ban margin purchases and/or short sales using a 2x2 factorial design to a allow for a comparative static analysis. Our results indicate that a ban on margin purchases fosters efficient pricing by narrowing price deviations from fundamental value accompanied with lower volatility and a smaller bid-ask-spread. A ban on short sales, however, tends to distort efficient pricing by widening price deviations accompanied with higher volatility and a large spread.Keywords: margin trading, Asset Market, Price Bubble, Experimental Finance1.IntroductionHowever, regulators can only have a positive impact on the life-cycle of a bubble, if they know how institutional changes affect prices in financial markets. Note that regulation is a double-edged sword since decision errors may lead from bad to worse. Given the systemic risk posed by speculative bubbles and their long history, it may be surprising how little attention bubbles have received in the literature and how little understood they are. This ignorance is partly due to the complex psychological nature of speculative bubbles but also due to the fact that the conventional financial economic theory has ignored the existence of bubbles for a long-time. But even if theories on bubble cycles have empirical relevance, it is clear that the issues surrounding the formation and the bursting of bubbles cannot be analyzed with pencil and paper. Conclusions on bubble cycles must be backed with quantitative data analysis. Given the limited number of observed empirical market crashes and their non-recurring nature, an experimental analysis of bubble formation involving controlled and replicable laboratory conditions seems to be a promising way to proceed.The paper is organized as follows. Section II reviews the related literature, Section 0 presents the details of the experimental design and section IV reports the data analysis. In section V, we summarize our findings and provide concluding remarks.2. Leverage in asset marketsDo margin requirements have any effects on market prices? Fisher (1933) and also Snyder (1930) mentioned the importance of margin debt in generating price bubbles when analyzing the Great Crash of 1929. The ability to leverage purchases lead to a higher demand, ending up in inflated prices. The subsequently appreciated collateral allowed to leverage purchases even more. This upward price spiral was fueled by an expansion of debt. From the end of 1924, brokers’loans rose four and one-half times (by $6.5 billion) and in the final phase broker’s borrowings rose at more than 100% a year until the bubble crashed. Then, after the peak of the bubble, a debt spiral was initiated. Investors lost trust and started to sell assets. Excess supply deflated prices resulting in a depreciation of collateral. Triggered margin calls lead to forced asset sales pushing supply even further. An increase in defaults on debt, and short sales exacerbated supply and finally assets were being sold at fire sale prices. It only took 6 weeks to extinguish half of the total of brokers’credit. Finally, in 1934, the U.S. Congress established federal margin authority to prevent unjustifiable increases or decreases in stock demand since margin requirements can prevent dramatic price fluctuations by limiting leveraged trades on both sides of the stock market: extremely optimistic margin purchasers and extremely pessimistic short sellers.Recent experimental evidence suggests short sale constraints to increase prices. Ackert et al. (2006)and Haruvy and Noussair (2006) find prices to deflate–even below fundamental value in the latter study –while King, Smith, Williams, and Van Boening (1993) find no effect. In a setting with information asymmetries, Fellner and Theissen (2006) find higher prices with short sale constraints but not depending on the divergence of opinion as predicted by Miller (1977). In a setting with smart money traders, Bhojraj, Bloomfield, and Tayler (2009) report short selling to exacerbate overpricing, even though it reduces equilibrium price levels. Hauser and Huber (2012) find short selling constraints with two dependent assets to distort price levels. Our design deviates from the previous studies in several but one important way: We use a more empirically relevant facility in that traders have to provide collateral facing the threat of margin calls.3. Implementing Margin Purchasing and Short SellingWe conducted four computerized treatments utilizing a 2x2 factorial design as displayed in Table II. Starting from an empirically relevant situation where margin purchases Traders execute margin purchases when they purchase shares by using loan, collateralized with shareholdings evaluated at the current market value.11 In this case, traders make a bull market bet, i.e. they borrow cash to buy shares, wait for the price to rise and sell them with a profit. However, a decline in prices depreciates collateral while keeping loan constant. When prices fall below a certain threshold, such that the loan exceeds the value of the shareholdings (i.e. debt > equity), a margin call is triggered. Immediately, i) the trader’s buttons are disabled, ii) outstanding orders are cancelled, and iii) the computer starts selling shares at the current market price until margin requirements are met again or untilall shares have been sold.12 Traders execute short sales when they sell shares without holding them in their inventory, collateralized with sufficient cash at hand.13 In this case, traders make a bear market bet, i.e. they borrow shares to sell them in the market, wait for the price to decline, buy them back with a profit and return them. Note that the amount of debt equals the total amount the trader has to pay to buy back the outstanding shares. Thus, an increase in prices increases debt and reduces collateral (cash minus value of outstanding shares), simultaneously. When prices exceed a certain threshold, such that the amount to buy back outstanding shares exceeds collateral (i.e. debt > equity), a margin call is triggered. Immediately, i)the trader’s buttons are disabled, ii) outstanding orders are cancelled, and iii) the computer starts buying shares at the current market price until margin requirements are met again or until all short positions have been covered. Note that short sellers have to pay dividends for their short positions at the end of each period.14 After period 15, both long and short positions are worthless.15 In any case, a margin callcan lead to bankruptcy. However, the consequences of a margin call hold even during bankruptcy, i.e. outstanding positions continuously being closed although subjects are bankrupt. This is different to any other asset market experiment considering leverage4. Margin traders tend to make less money than othersBy leveraging purchases and sales, traders take more risks to be able to make more money. But do margin traders make more money at all? To evaluate this question, we classify traders into types, i.e. margin traders, who trade on margin at least once, and others. Table X shows the average end- of round-earnings within types for each treatment along with the number of subjects. The spearman rank correlation between type and end of round earnings is negative in both rounds and in all three treatments. The coefficient is significantly different from zero only in MP|NoSS and NoMP|SS when subjects are once experienced . Subjects, who executed both margin purchases and short sales in MP|SS earned less than subjects who refrained from trading on margin. This is significant only for inexperienced subjects . One final note on the distribution of earnings. Comparing the treatments by evaluating the dispersion of earnings using the coefficient of variation , we find that the average CV in the NoMP|NoSS is lower than any other treatment Although not statistically significant, the results indicate that it is less risky to participate in markets with margin bans than in the markets where margintrading is permitted.5. ConclusionIn an attempt to halt the decline in asset values, recent regulatory measures temporarily banned short sales in financial markets. To assess the impact of banning leveraged trading on market mispricing is a complicated task when being reliant on data from real world exchanges only. it is unclear if possible price increases following a ban on short sales would come from new long positions or from covered short positions, and the announcement of such measures affects an uncontrolled reaction of the market. Owed to the uncontrolled uncertainties in the real world, asset mispricing can be measured only with weak confidence.In comparison to other experimental studies where limits to margin debt and short sales are rare, our design involves margin requirements comparable to the real world. Highly levered investors face margin calls that lead to forced liquidation of positions, affecting a reinforcement of the swings of the market. We have studied the impact of leverage on individual portfolio decisions to find an increase in risk taking characterized by higher concentrations of risky assets eventually resulting in individual bankruptcies. Thus, our experimental results are in line with theories of margin trading by Irvine Fischer (1933) and by recent heterogeneous agents models (Geanakoplos 2009) which conjecture such effects on asset pricing and portfolio decisions. As in any laboratory experiment, the results are restricted to the chosen parameters. The baselineSmith et al. (1988) asset market design has been challenged in recent studies (e.g. Kirchler et al. 2011), arguing that some subjects are confused about the declining fundamental value and believe that prices keep a similar level in the course of time. So it would also be interesting to investigate the effects of bans Jena Economic Research Papers 2012 - 05826 of margin purchases and short sales, to see if our treatment effects can be repeated in an environment with non-decreasing fundamental values. However, recent experiments by Hauser and Huber (2012) show similar effects using multiple asset markets with a complexsystem of fundamental values but without margin calls. It would also be interesting to see how margin requirements change performance in multiple sset markets. We leave these open questions to future research.ReferencesAbreu, D., and M.K. Brunnermeier, 2003, Bubbles and crashes, Econometrica 71, 173–204.Ackert, L., N. Charupat, B. Church and R. Deaves, 2006, Margin, Short Selling, and Lotteries in Experimental Asset Markets, Southern Economic Journal 73, 419–436. Adrangi, B. and A. Chatrath, 1999, Margin Requirements and Futures Activity: Evidence from the Soybean and Corn Markets, Journal of Futures Markets, 19, 433-455. Alexander, G.J, and M.A Peterson, 2008, The effect of price tests on trader behavior and market quality: An analysis of Reg SHO, Journal of Financial Markets 11, 84–111.Bai, Y., E.C Chang, and J. Wang, 2006, Asset prices under short-sale constraints, Mimeo. Beber, A., and M. Pagano, 2010, Short-Selling Bans around the World: Evidence from the 2007-09 Crisis, Tinbergen Institute Discussion Papers TI 10-106 / DSF 1.Bernardo, A. and I. Welch, 2002, Financial market runs, NBER Working Papers 9251, National Bureau of Economic Research, Inc.Bhojraj, S., R.J Bloomfield, and W.B Tayler, 2009, Margin trading, overpricing, and synchronization risk, Review of Financial Studies 22, 2059–2085.Blau, B. M., B. F. Van Ness, R. A. Van Ness, 2009, Short Selling and the Weekend Effect for NYSE Securities, Financial Management 38 (No. 3). 603-630Boehmer, E., Z.R Huszar, and B.D Jordan, 2010, The good news in short interest, Journal of Financial Economic 96, 80–97.Boehme, R.D, B.R Danielsen, and S.M Sorescu, 2006, Short-sale constraints, differences of opinion, and overvaluation, Journal of Financial and Quantitative Analysis 41, 455–487.融资融券禁令在实验资产市场摘要在金融市场，因为专业的交易者杠杆交易允许以较少的保证金进行更大的交易。

企业偿债能力分析外文文献

外文文献原稿与译文原稿IntroductionAlthough creditors can develop a variety of protective provisions to protect their own interests, but a number of complementary measures are critical to effectively safeguard their interests have to see the company's solvency、Therefore, to improve a company's solvency Liabilities are on the rise、On the other hand, the stronger a company's solvency the easier cash investments required for the project, whose total assets are often relatively low debt ratio, which is the point of the pecking order theory of phase agreement、Similarly, a company's short-term liquidity, the stronger the short-term debt ratio is also lower, long-term solvency, the stronger the long-term debt ratio is also lower 、Harris et al、Well, Eriotis etc、as well as empirical research and Underperformance found that the solvency (in the quick ratio and interest coverage ratio, respectively, short-term solvency and long-term solvency) to total debt ratio has significant negative correlation、Taking into account the data collected convenience, this paper represents short-term solvency ratios and to study the long-term solvency by the quick ratio and cash flow impact on the real estate debt capital structure of listed companies、Listed Companies Solvency AnalysisWhen companies need money, the choice of financing preference order, namely in accordance with retained earnings, issuance of bonds, financing order issued shares、According to this theory, strong corporate profitability, retained earnings more For financing first will consider retained earnings、Therefore, the profitability of the total debt ratio should be negatively correlated debt avoidance theory based natural surface that under otherwise identical conditions, a highly profitable company should borrow more debt, because they use avoidance of the need for greater debt, and therefore higher debt ratio、rapid growth of the company's financial leverage without the support, based on this, toselect 378 samples from the 500 largest US companies, the researchers found that regardless of whether there is an optimal capital structure, the company's liabilities are directly correlated with growth、Growth is the fundamental guarantee company solvency, so whether short-term loans or long-term loans and creditors, as the company's growth as a positive signal, so the listed companies in recent years of growth, the higher its rate and short-term assets The higher rate of long-term assets and liabilities, total assets and liabilities naturally higher, but the impact on growth of real estate companies listed on a smaller debt ratio (coefficient is small)、The risk of firm size and capital structure affect the growth has a similar conclusion, it appears that creditors, especially banks that the company scale is a measure of credit risk is an important consideration index, the greater the company size, the more stable cash flow, bankruptcy it is smaller, the creditors are more willing to throw an olive branch large-scale enterprises、The actual controller of the listed companies category to total debt ratio of the impact factor of a 0、040017, indicating that non-state-controlled listed company's total assets and liabilities higher than the state-owned holding companies、The reason for this phenomenon may be non-state-controlled listed companies pay more attention to control benefits, do not want to dilute their control over equity financing, and therefore more inclined to debt financing, which may also explain the non-state-controlled listed companies better use of financial leverage enterprises bigger and stronger impulses、In addition, the actual control of listed companies category short-term impact on asset-liability ratio is a 2、3 times its impact on long-term debt ratio, which shows the non-state-controlled listed companies prefer to take advantage of short-term debt to expand its operations、Current research on factors affecting capital structure point of view there are many factors in various industries concerned is not the same, according to industry characteristics and particularity, we mainly focus on the following aspects to analyze the factors industry capital structure、The article explained variable - capital structure for the asset-liability ratio, generally refers to the total debt ratio, but for more in-depth study of capital structure of listed companies, the paper from the total debt ratio, short-term assets and liabilities and long-term debt ratio of three angles of Capital structure explanatory、At present, domestic and foreign scholars analyzed factors on capital structure mostly used multiple linear regression, as usual statistical regression function in the form of their choice is often subjective factors, but ordinary regression methods to make function with average resistance, most such functions excellent and objectivity are often difficult to reflect、base stochastic frontier model (Stochastic Frontier) in data envelopment analysis (DEA) method, estimate the effective production frontier using mathematical programming method, namely the experience of frontier production function, overcome DEA method assumes that there is no random error term, the better to reflect the objectivity and optimality ¨J function, currently in the field of economic management, sociology and medicine, began to get more and more applications、Therefore, in this paper, stochastic frontier model data on the capital structure factors listed real estate companies conducted a comprehensive analysis, in order to provide a better scientific basis for the study of the optimal capital structure of real estate enterprises、Listed company's solvency and overall asset-liability ratio was significantly negatively correlated with short-term liquidity has a decisive influence on the short-term asset-liability ratio、Similarly, long-term solvency also has a decisive influence on long-term assets and liabilities、Industry higher total debt ratio particularly high proportion of short-term debt is one of the main business risks, thus increasing solvency of listed companies, especially short-term liquidity (that is, to obtain a stable short-term cash flow)、reduce its asset liability ratio and effective risk management choice ROA of listed companies is much greater influence than ROE of asset-liability ratio, and affect the relationship is inconsistent, ROE is higher, the higher the total debt ratio, while the ROA high, the lower the rate of the total assets and liabilities, and short-term liabilities ROA more obvious, this difference is mainly due to the special structure of listed companies due to the nature of the capital, and therefore need to improve the capital structure of listed companies, namely to reduce the total assets and liabilities rate debt structure and the need to reduce the proportion of short-term debt in particular, in order to enhance the company's profitability ROA、growth and company size has a significant positive impact on the capital structure, which is mainly due to the growth of the company's solvency is fundamental, The size of the company is the main indicator to measure the bankruptcy creditor risk、Therefore, listed companies shouldbe radically to grow through continuous growth and development of enterprises, so that the total debt ratio has a high margin of safety, through growth to continue to resolve the financial risk than non-state-owned holding companies controlling more use of financial leverage motivation and apparently relied on short-term liabilities, which may lead to more serious financial risk especially short-term business risks, so that the non-state-owned holding listed companies should establish more strict risk prevention system、译文介绍虽然债权人可以通过制定各种保护性条款来保障自己的利益,但都就是一些辅助性的措施,能够有效保障她们利益的关键还得瞧公司的偿债能力。

企业偿债能力分析外文文献[精品文档]

北京化工大学北方学院毕业设计（论文）——外文文献原稿和译文外文文献原稿和译文原稿IntroductionAlthough creditors can develop a variety of protective provisions to protect their own interests, but a number of complementary measures are critical to effectively safeguard their interests have to see the company's solvency. Therefore, to improve a company's solvency Liabilities are on the rise. On the other hand, the stronger a company's solvency the easier cash investments required for the project, whose total assets are often relatively low debt ratio, which is the point of the pecking order theory of phase agreement. Similarly, a company's short-term liquidity, the stronger the short-term debt ratio is also lower, long-term solvency, the stronger the long-term debt ratio is also lower .Harris et al. Well, Eriotis etc. as well as empirical research and Underperformance found that the solvency (in the quick ratio and interest coverage ratio, respectively, short-term solvency and long-term solvency) to total debt ratio has significant negative correlation. Taking into account the data collected convenience, this paper represents short-term solvency ratios and to study the long-term solvency by the quick ratio and cash flow impact on the real estate debt capital structure of listed companies.Listed Companies Solvency AnalysisWhen companies need money, the choice of financing preference order, namely in accordance with retained earnings, issuance of bonds, financing order issued shares. According to this theory, strong corporate profitability, retained earnings more For financing first will consider retained earnings. Therefore, the profitability of the total debt ratio should be negatively correlated debt avoidance theory based natural surface that under otherwise identical conditions, a highly profitable company should borrow more debt, because they use avoidance of the need for greater debt, and therefore higher debt ratio.北京化工大学北方学院毕业设计（论文）——外文文献原稿和译文rapid growth of the company's financial leverage without the support, based on this, to select 378 samples from the 500 largest US companies, the researchers found that regardless of whether there is an optimal capital structure, the company's liabilities are directly correlated with growth.Growth is the fundamental guarantee company solvency, so whether short-term loans or long-term loans and creditors, as the company's growth as a positive signal, so the listed companies in recent years of growth, the higher its rate and short-term assets The higher rate of long-term assets and liabilities, total assets and liabilities naturally higher, but the impact on growth of real estate companies listed on a smaller debt ratio (coefficient is small). The risk of firm size and capital structure affect the growth has a similar conclusion, it appears that creditors, especially banks that the company scale is a measure of credit risk is an important consideration index, the greater the company size, the more stable cash flow, bankruptcy it is smaller, the creditors are more willing to throw an olive branch large-scale enterprises. The actual controller of the listed companies category to total debt ratio of the impact factor of a 0.040017, indicating that non-state-controlled listed company's total assets and liabilities higher than the state-owned holding companies. The reason for this phenomenon may be non-state-controlled listed companies pay more attention to control benefits, do not want to dilute their control over equity financing, and therefore more inclined to debt financing, which may also explain the non-state-controlled listed companies better use of financial leverage enterprises bigger and stronger impulses. In addition, the actual control of listed companies category short-term impact on asset-liability ratio is a 2.3 times its impact on long-term debt ratio, which shows the non-state-controlled listed companies prefer to take advantage of short-term debt to expand its operations.Current research on factors affecting capital structure point of view there are many factors in various industries concerned is not the same, according to industry characteristics and particularity, we mainly focus on the following aspects to analyze the factors industry capital structure. The article explained variable - capital structure for the asset-liability ratio, generally refers to the total debt ratio, but for more in-depth study of capital structure of listed companies, the paper from the total debt ratio, short-term assets and liabilities and北京化工大学北方学院毕业设计（论文）——外文文献原稿和译文long-term debt ratio of three angles of Capital structure explanatory.At present, domestic and foreign scholars analyzed factors on capital structure mostly used multiple linear regression, as usual statistical regression function in the form of their choice is often subjective factors, but ordinary regression methods to make function with average resistance, most such functions excellent and objectivity are often difficult to reflect. base stochastic frontier model (Stochastic Frontier) in data envelopment analysis (DEA) method, estimate the effective production frontier using mathematical programming method, namely the experience of frontier production function, overcome DEA method assumes that there is no random error term, the better to reflect the objectivity and optimality ¨J function, currently in the field of economic management, sociology and medicine, began to get more and more applications. Therefore, in this paper, stochastic frontier model data on the capital structure factors listed real estate companies conducted a comprehensive analysis, in order to provide a better scientific basis for the study of the optimal capital structure of real estate enterprises.Listed company's solvency and overall asset-liability ratio was significantly negatively correlated with short-term liquidity has a decisive influence on the short-term asset-liability ratio. Similarly, long-term solvency also has a decisive influence on long-term assets and liabilities. Industry higher total debt ratio particularly high proportion of short-term debt is one of the main business risks, thus increasing solvency of listed companies, especially short-term liquidity (that is, to obtain a stable short-term cash flow). reduce its asset liability ratio and effective risk management choice ROA of listed companies is much greater influence than ROE of asset-liability ratio, and affect the relationship is inconsistent, ROE is higher, the higher the total debt ratio, while the ROA high, the lower the rate of the total assets and liabilities, and short-term liabilities ROA more obvious, this difference is mainly due to the special structure of listed companies due to the nature of the capital, and therefore need to improve the capital structure of listed companies, namely to reduce the total assets and liabilities rate debt structure and the need to reduce the proportion of short-term debt in particular, in order to enhance the company's profitability ROA. growth and company size has a significant positive impact on the capital structure, which is mainly北京化工大学北方学院毕业设计（论文）——外文文献原稿和译文due to the growth of the company's solvency is fundamental, The size of the company is the main indicator to measure the bankruptcy creditor risk. Therefore, listed companies should be radically to grow through continuous growth and development of enterprises, so that the total debt ratio has a high margin of safety, through growth to continue to resolve the financial risk than non-state-owned holding companies controlling more use of financial leverage motivation and apparently relied on short-term liabilities, which may lead to more serious financial risk especially short-term business risks, so that the non-state-owned holding listed companies should establish more strict risk prevention system.北京化工大学北方学院毕业设计（论文）——外文文献原稿和译文译文介绍虽然债权人可以通过制定各种保护性条款来保障自己的利益，但都是一些辅助性的措施，能够有效保障他们利益的关键还得看公司的偿债能力。

债务杠杆财务报表分析外文翻译文献

中英文对照外文翻译文献(文档含英文原文和中文翻译)原文：Financial Statement Analysis of Leverage and How It Informs About Protability and Price-to-Book RatiosAbstractThis paper presents a ﬁnancial statement analysis that distinguishes leverage that arises in ﬁnancing activities from leverage that arises in operations. The analysis yields two leveraging equations, one for borrowing to ﬁnance operations and one for borrowing in the course of operations. These leveraging equations describe how the two types of leverage affect book rates of return on equity. An empirical analysis shows that the ﬁnancial statement analysis explains cross-sectional differences in current and future rates of return as well as price-to-book ratios, which are based on expected rates of return on equity. The paper therefore concludes that balance sheet line items for operating liabilities are priced differently than those dealing with ﬁnancing liabilities. Accordingly, ﬁnancial statement analysis that distinguishes the two types of liabilities informs on future proﬁtability and aids in the evaluation of appropriate price-to-book ratios.Keywords: financing leverage; operating liability leverage; rate of return on equity; price-to-book ratioLeverage is traditionally viewed as arising from ﬁnancing activit ies: Firms borrow to raisecash for operations. This paper shows that, for the purposes of analyzing proﬁtability and valuing ﬁrms, two types of leverage are relevant, one indeed arising from ﬁnancing activities but another from operating activities. The paper supplies a ﬁnancial statement analysis of the two types of leverage that explains differences in shareholder proﬁtability and price-to-book ratios.The standard measure of leverage is total liabilities to equity. However, while some liabilities—like bank loans and bonds issued—are due to ﬁnancing, other liabilities—like trade payables, deferred revenues, and pension liabilities—result from transactions with suppliers, customers and employees in conducting operations. Financing liabilities are typically traded in well-functioning capital markets where issuers are price takers. In contrast, ﬁrms are able to add value in operations because operations involve trading in input and output markets that are less perfect than capital markets. So, with equity valuation in mind, there are a priori reasons for viewing operating liabilities differently from liabilities that arise in ﬁnancing.Our research asks whether a dollar of operating liabilities on the balance sheet is priced differently from a dollar of ﬁnancing liabilities. As operating and ﬁnancing liabilities are components of the book value of equity, the question is equivalent to asking whether price-to-book ratios depend on the composition of book values. The price-to-book ratio is determined by the expected rate of return on the book value so, if components of book value command different price premiums, they must imply different expected rates of return on book value. Accordingly, the paper also investigates whether the two types of liabilities are associated with differences in future book rates of return.Standard ﬁnancial statement analysis distinguishes shareholder proﬁtability that arises from operations from that which arises from borrowing to ﬁnance operations. So, return on assets is distinguished from return on equity, with the difference attributed to leverage. However, in the standard analysis, operating liabilities are not distinguished from ﬁnancing liabilities. Therefore, to develop the speciﬁcations for the empirical analysis, the paper pre sents a ﬁnancial statement analysis that identiﬁes the effects of operating and ﬁnancing liabilities on rates of return on book value—and so on price-to-book ratios—with explicit leveraging equations that explain when leverage from each type of liability is favorable or unfavorable.The empirical results in the paper show that ﬁnancial statement analysis that distinguishes leverage in operations from leverage in ﬁnancing also distinguishes differences in contemporaneous and future proﬁtability among ﬁrms. L everage from operating liabilities typically levers proﬁtability more than ﬁnancing leverage and has a higher frequency of favorable effects.Accordingly, for a given total leverage from both sources, ﬁrms with higher leverage from operations have higher price-to-book ratios, on average. Additionally, distinction between contractual and estimated operating liabilities explains further differences in ﬁrms’ proﬁtability and their price-to-book ratios.Our results are of consequence to an analyst who wishes to forecast earnings and book rates of return to value ﬁrms. Those forecasts—and valuations derived from them—depend, we show, on the composition of liabilities. The ﬁnancial statement analysis of the paper, supported by the empirical results, shows how to exploit information in the balance sheet for forecasting and valuation.The paper proceeds as follows. Section 1 outlines the ﬁnancial statements analysis that identiﬁes the two types of leverage and lays out expressions that tie leverage measures to proﬁtab ility. Section 2 links leverage to equity value and price-to-book ratios. The empiricalanalysis is in Section 3, with conclusions summarized in Section 4.1. Financial Statement Analysis of LeverageThe following ﬁnancial statement analysis separates the effects of ﬁnancing liabilities and operating liabilities on the proﬁtability of shareholders’ equity. The analysis yields explicit leveraging equations from which the speciﬁcations for the empirical analysis are developed. Shareholder proﬁtability, return on common equity, is measured asReturn on common equity (ROCE) = comprehensive net income ÷common equity (1) Leverage affects both the numerator and denominator of this proﬁtability measure. Appropriate ﬁnancial statement analysis disentangles the effects of leverage. The analysis below, which elaborates on parts of Nissim and Penman (2001), begins by identifying components of the balance sheet and income statement that involve operating and ﬁnancing activities. The proﬁtability due to each activ ity is then calculated and two types of leverage are introduced to explain both operating and ﬁnancing proﬁtability and overall shareholder proﬁtability.1.1 Distinguishing the Protability of Operations from the Protability of Financing ActivitiesWith a f ocus on common equity (so that preferred equity is viewed as a ﬁnancial liability), the balance sheet equation can be restated as follows:Common equity =operating assets＋financial assets－operating liabilities－Financial liabilities (2) The distinction here between operating assets (like trade receivables, inventory and property,plant and equipment) and ﬁna ncial assets (the deposits and marketable securities that absorb excess cash) is made in other contexts. However, on the liability side, ﬁnancing liabilities are also distinguished here from operating liabilities. Rather than treating all liabilities as ﬁnancing debt, only liabilities that raise cash for operations—like bank loans, short-term commercial paper and bonds—are classiﬁed as such. Other liabilities—such as accounts payable, accrued expenses, deferred revenue, restructuring liabilities and pension liabilities—arise from operations. The distinction is not as simple as current versus long-term liabilities; pension liabilities, for example, are usually long-term, and short-term borrowing is a current liability.Rearranging terms in equation (2),Common equity = (operating assets－operating liabilities)－(financial liabilities－financial assets)Or,Common equity = net operating assets－net financing debt (3) This equation regroups assets and liabilities into operating and ﬁnancing ac tivities. Net operating assets are operating assets less operating liabilities. So a ﬁrm might invest in inventories, but to the extent to which the suppliers of those inventories grant credit, the net investment in inventories is reduced. Firms pay wages, but to the extent to which the payment of wages is deferred in pension liabilities, the net investment required to run the business is reduced. Net ﬁnancing debt is ﬁnancing debt (including preferred stock) minus ﬁnancial assets. So, a ﬁrm may issue bonds to raise cash for operations but may also buy bonds with excess cash from operations. Its net indebtedness is its net position in bonds. Indeed a ﬁrm may be a net creditor (with more ﬁnancial assets than ﬁnancial liabilities) rather than a net debtor.The income statement can be reformulated to distinguish income that comes from operating and ﬁnancing activities:Comprehensive net income = operating income－net financing expense (4) Operating income is produced in operations and net ﬁnancial ex pense is incurred in the ﬁnancing of operations. Interest income on ﬁnancial assets is netted against interest expense on ﬁnancial liabilities (including preferred dividends) in net ﬁnancial expense. If interest income is greater than interest expense, ﬁnancing activities produce net ﬁnancial income rather than net ﬁnancial expense. Both operating income and net ﬁnancial expense (or income) are after tax.3 Equations (3) and (4) produce clean measures of after-tax operating proﬁtability and the borrowing rate:Return on net operating assets (RNOA) = operating income ÷net operating assets (5) andNet borrowing rate (NBR) = net financing expense ÷net financing debt (6) RNOA recognizes that proﬁtability must be based on the net assets invested in operations. So ﬁrms can increase their operating proﬁtability by convincing suppliers, in the course of business, to grant or extend credit terms; credit reduces the investment that shareholders would otherwise have to put in the business. Correspondingly, the net borrowing rate, by excluding non-interest bearing liabilities from the denominator, gives the appropriate borrowing rate for the ﬁnancing activities.Note that RNOA differs from the more common return on assets (ROA), usually deﬁned as income before after-tax interest expense to total assets. ROA does not distinguish operating and ﬁnancing activities appropriately. Unlike ROA, RNOA excludes ﬁnancial assets in the denominator and subtracts operating liabilities. Nissim and Penman (2001) report a median ROA for NYSE and AMEX ﬁrms from 1963–1999 of only 6.8%, but a median RNOA of 10.0%—much closer to what one would expect as a return to business operations.1.2 Financial Leverage and its Effect on Shareholder ProtabilityFrom expressions (3) through (6), it is straightforward to demonstrate that ROCE is a weighted average of RNOA and the net borrowing rate, with weights derived from equation (3): ROCE= [net operating assets ÷common equity× RNOA]－[net financing debt÷common equity ×net borrowing rate (7) Additional algebra leads to the following leveraging equation:ROCE = RNOA＋[FLEV× ( RNOA－net borrowing rate )] (8) where FLEV, the measure of leverage from ﬁnancing activities, isFinancing leverage (FLEV) =net financing debt ÷common equity (9) The FLEV measure excludes operating liabilities but includes (as a net against ﬁnancing debt) ﬁnancial assets. If ﬁnancial assets are greater than ﬁnancial liabilities, FLEV is n egative. The leveraging equation (8) works for negative FLEV (in which case the net borrowing rate is the return on net ﬁnancial assets).This analysis breaks shareholder proﬁtability, ROCE, down into that which is due to operations and that which is due t o ﬁnancing. Financial leverage levers the ROCE over RNOA, with the leverage effect determined by the amount of ﬁnancial leverage (FLEV) and the spread between RNOA and the borrowing rate. The spread can be positive (favorable) or negative (unfavorable).1.3 Operating Liability Leverage and its Effect on Operating ProtabilityWhile ﬁnancing debt levers ROCE, operating liabilities lever the proﬁtability of operations, RNOA. RNOA is operating income relative to net operating assets, and net operating assets areoperating assets minus operating liabilities. So, the more operating liabilities a ﬁrm has relative to operating assets, the higher its RNOA, assuming no effect on operating income in the numerator. The intensity of the use of operating liabilities in the investment base is operating liability leverage:Operating liability leverage (OLLEV) =operating liabilities ÷net operating assets (10) Using operating liabilities to lever the rate of return from operations may not come for free, however; there may be a numerator effect on operating income. Suppliers provide what nominally may be interest-free credit, but presumably charge for that credit with higher prices for the goods and services supplied. This is the reason why operating liabilities are inextricably a part of operations rather than the ﬁnancing of operations. The amount that suppliers actually charge for this credit is difﬁcult to identify. But the market borrowing rate is observable. The amount that suppliers would implicitly charge in prices for the credit at this borrowing rate can be estimated as a benchmark:Market interest on operating liabilities= operating liabilities×market borrowing ratewhere the market borrowing rate, given that most credit is short term, can be approximated by the after-tax short-term borrowing rate. This implicit cost is benchmark, for it is the cost that makes suppliers indifferent in supplying cred suppliers are fully compensated if they charge implicit interest at the cost borrowing to supply the credit. Or, alter natively, the ﬁrm buying the goods or services is indifferent between trade credit and ﬁnancing purchases at the borrowin rate.To analyze the effect of operating liability leverage on operating proﬁtability, w e deﬁne: Return on operating assets (ROOA) =(operating income＋market interest on operating liabilities)÷operating assets(11)The numerator of ROOA adjusts operating income for the full implicit cost of trad credit. If suppliers fully charge the implicit cost of credit, ROOA is the return of operating assets that would be earned had the ﬁrm no operating liability leverage. suppliers do not fully charge for the credit, ROOA measures the return fro operations that includes the favorable implicit credit terms from suppliers.Similar to the leveraging equation (8) for ROCE, RNOA can be expressed as:RNOA = ROOA＋[ OLLEV ×(ROOA－market borrowing rate )] (12) where the borrowing rate is the after-tax short-term interest rate.Given ROOA, the effect of leverage on proﬁtability is determined by the level of operating liability leverage and the spread between ROOA and the short-term after-tax interest rate. Like ﬁnancing leverage, the effect can be favorable or unfavorable: Firms can reduce their operating proﬁtability through operating liability leverage if their ROOA is less than the market borrowing rate. However, ROOA will also be affected if the implicit borrowing cost on operating liabilities is different from the market borrowing rate.1.4 Total Leverage and its Effect on Shareholder ProtabilityOperating liabilities and net ﬁnancing debt combine into a total leverage measure:Total leverage (TLEV) = ( net financing debt＋operating liabilities)÷common equityThe borrowing rate for total liabilities is:Total borrowing rate = (net financing expense＋market interest on operating liabilities) ÷net financing debt＋operating liabilitiesROCE equals the weighted average of ROOA and the total borrowing rate, where the w eights are proportional to the amount of total operating assets and the sum of net ﬁnancing debt and operating liabilities (with a negative sign), respectively. So, similar to the leveraging equations (8) and (12):ROCE = ROOA ＋[TLEV×(ROOA －total borrowing rate)] (13) In summary, ﬁnancial statement analysis of operating and ﬁnancing activities yields three leveraging equations, (8), (12), and (13). These equations are based on ﬁxed accounting relations and are therefore deterministic: Th ey must hold for a given ﬁrm at a given point in time. The only requirement in identifying the sources of proﬁtability appropriately is a clean separation between operating and ﬁnancing components in the ﬁnancial statements.2. Leverage, Equity Value and Price-to-Book RatiosThe leverage effects above are described as effects on shareholder proﬁtability. Our interest is not only in the effects on shareholder proﬁtability, ROCE, but also in the effects on shareholder value, which is tied to ROCE in a straightforward way by the residual income valuation model. As a restatement of the dividend discount model, the residual income model expresses the value of equity at date 0 (P0) as:B is the book value of common shareholders’ equity, X is comprehensive income to common shareholders, and r is the required return for equity investment. The price premium over book value is determined by forecasting residual income, Xt –rBt-1. Residual income is determined in part by income relative to book value, that is, by the forecasted ROCE. Accordingly, leverage effects on forecasted ROCE (net of effects on the required equity return) affect equity value relative to book value: The price paid for the book value depends on the expected proﬁtability of the book value, and leve rage affects proﬁtability.So our empirical analysis investigates the effect of leverage on both proﬁtability and price-to-book ratios. Or, stated differently, ﬁnancing and operating liabilities are distinguishable components of book value, so the question is whether the pricing of book values depends on the composition of book values. If this is the case, the different components of book value must imply different proﬁtability. Indeed, the two analyses (of proﬁtability and price-to-book ratios) are complementary.Financing liabilities are contractual obligations for repayment of funds loaned. Operating liabilities include contractual obligations (such as accounts payable), but also include accrual liabilities (such as deferred revenues and accrued expenses). Accrual liabilities may be based on contractual terms, but typically involve estimates. We consider the real effects of contracting and the effects of accounting estimates in turn. Appendix A provides some examples of contractual and estimated liabilities and their effect on proﬁtability and value.2.1 Effects of Contractual liabilitiesThe ex post effects of ﬁnancing and operating liabilities on proﬁtability are clear from leveraging equations (8), (12) and (13). These expressions always hold ex post, so there is no issue regarding ex post effects. But valuation concerns ex ante effects. The extensive research on the effects of ﬁnancial leverage takes, as its point of departure, the Modigliani and Miller (M&M)(1958) ﬁnancing irrelevance proposition: With perfect capital markets and no taxes or information asymmetry, debt ﬁnancing has no effect on value. In terms of the residual income valuation model, an increase in ﬁnancial leverage due to a substitution of debt for equity may increase expected ROCE according to expression (8), but that increase is offset in the valuation (14) by the reduction in the book value of equity that earns the excess proﬁtability and the increase in the required equity return, leaving total value (i.e., the value of equity and debt) unaffected. The required equity return increases because of increased ﬁnancing risk: Leverage may be expected to be favorable but, the higher the leverage, the greater the loss to shareholders should the leverage turn unfavorable ex post, with RNOA less than the borrowing rate.In the face of the M&M proposition, research on the value effects of ﬁnancial leverage has proceeded to relax the conditions for the proposition to hold. Modigliani and Miller (1963) hypothesized that the tax beneﬁts of debt incr ease after-tax returns to equity and so increase equity value. Recent empirical evidence provides support for the hypothesis (e.g., Kemsley and Nissim, 2002), although the issue remains controversial. In any case, since the implicit cost of operating liabi lities, like interest on ﬁnancing debt, is tax deductible, the composition of leverage should have no tax implications.Debt has been depicted in many studies as affecting value by reducing transaction and contracting costs. While debt increases expected bankruptcy costs and introduces agency costs between shareholders and debtholders, it reduces the costs that shareholders must bear in monitoring management, and may have lower issuing costs relative to equity. One might expect these considerations to apply to operating debt as well as ﬁnancing debt, with the effects differing only by degree. Indeed papers have explained the use of trade debt rather than ﬁnancing debt by transaction costs (Ferris, 1981), differential access of suppliers and buyers to ﬁnancin g (Schwartz,1974), and informational advantages and comparative costs of monitoring (Smith, 1987; Mian and Smith, 1992; Biais and Gollier, 1997). Petersen and Rajan (1997) provide some tests of these explanations.In addition to tax, transaction costs and agency costs explanations for leverage, research has also conjectured an informational role. Ross (1977) and Leland and Pyle (1977) characterized ﬁnancing choice as a signal of proﬁtability and value, and subsequent papers (for example, Myers and Majluf, 1984) have carried the idea further. Other studies have ascribed an informational role also for operating liabilities. Biais and Gollier (1997) and Petersen and Rajan (1997), for example, see suppliers as having more information about ﬁrms than banks and th e bond market, so more operating debt might indicate higher value. Alternatively, high trade payables might indicate difﬁculti es in paying suppliers and declining fortunes.Additional insights come from further relaxing the perfect frictionless capital markets assumptions underlying the original M&M ﬁnancing irrelevance proposition. When it comes to operations, the product and input markets in which ﬁrms trade are typically less competitive than capital markets. Indeed, ﬁrms are viewed as adding value prima rily in operations rather than in ﬁnancing activities because of less than purely competitive product and input markets. So, whereas it is difficult to ‘‘make money off the debtholders,’’ ﬁrms can be seen as ‘‘making money off the trade creditors.’’ In operations, ﬁrms can exert monopsony power, extracting value from suppliers and employees. Suppliers may provide cheap implicit ﬁnancing in exchange for information about products and markets in which the ﬁrm operates. They may also beneﬁt from efﬁciencies in the ﬁrm’s supply and distribution chain, and may grant credit to capturefuture business.2.2 Effects of Accrual Accounting EstimatesAccrual liabilities may be based on contractual terms, but typically involve estimates. Pension liabilities, for example, are based on employment contracts but involve actuarial estimates. Deferred revenues may involve obligations to service customers, but also involve estimates that allocate revenues to periods. While contractual liabilities are typically carried on the balance sheet as an unbiased indication of the cash to be paid, accrual accounting estimates are not necessarily unbiased. Conservative accounting, for example, might overstate pension liabilities or defer more revenue than required by contracts with customers.Such biases presumably do not affect value, but they affect accounting rates of return and the pricing of the liabilities relative to their carrying value (the price-to-book ratio). The effect of accounting estimates on operating liability leverage is clear: Higher carrying values for operating liabilities result in higher leverage for a given level of operating assets. But the effect on proﬁtability is also clear from leveraging equation (12): While conservative accounting for operating assets increases the ROOA, as modeled in Feltham and Ohlson (1995) and Zhang (2000), higher book values of operating liabilities lever up RNOA over ROOA. Indeed, conservative accounting for operating liabilities amounts to leverage of book rates of return. By leveraging equation (13), that leverage effect ﬂows through to shareholder proﬁtability, ROCE.And higher anticipated ROCE implies a higher price-to-book ratio.The potential bias in estimated operating liabilities has opposite effects on current and future proﬁtability. For example, if a ﬁrm books higher deferred revenues, accrued expenses or other operating liabilities, and so increases its operating liability leverage, it reduces its current proﬁtability: Current revenues must be lower or expenses higher. And, if a ﬁrm reports lower operating assets (by a write down of receivables, inventories or other assets, for example), and so increases operating liability leverage, it also reduces current proﬁtability: Current expenses must be higher. But this application of accrual accounting affects future operating income: All else constant, lower current income implies higher future income. Moreover, higher operating liabilities and lower operating assets amount to lower book value of equity. The lower book value is the base for the rate of return for the higher future income. So the analysis of operating liabilities potentially identiﬁes part of the accrual reversal phenomenon documented by Sloan (1996) and interprets it as affecting leverage, forecasts of proﬁtability, and price-to-book ratios.3. Empirical AnalysisThe analysis covers all ﬁrm-year observations on the combined COMPUSTAT (Industry and Research) ﬁles for any of the 39 years from 1963 to 2001 that satisfy the following requirements: (1) the company was listed on the NYSE or AMEX; (2) the company was not a ﬁnancial institution (SIC codes 6000–6999), thereby omitting ﬁrms where most ﬁnancial assets and liabilities are used in operations; (3) the book value of common equity is at least $10 million in 2001 dollars; and (4) the averages of the beginning and ending balance of operating assets, net operating assets and common equity are positive (as balance sheet variables are measured in the analysis using annual averages). These criteria resulted in a sample of 63,527 ﬁrm-year observations.Appendix B describes how variables used in the analysis are measured. One measurement issue that deserves discussion is the estimation of the borrowing cost for operating liabilities. Asmost operating liabilities are short term, we approximate the borrowing rate by the after-tax risk-free one-year interest rate. This measure may understate the borrowing cost if the risk associated with operating liabilities is not trivial. The effect of such measurement error is to induce a negative correlation between ROOA and OLLEV. As we show below, however, even with this potential negative bias we document a strong positive relation between OLLEV and ROOA.4. ConclusionTo ﬁnance operations, ﬁrms borrow in the ﬁnancial markets, creating ﬁnancin g leverage. In running their operations, ﬁrms also borrow, but from customers, employees and suppliers, creating operating liability leverage. Because they involve trading in different types of markets, the two types of leverage may have different value implications. In particular, operating liabilities may reﬂect contractual terms that add value in different ways than ﬁnancing liabilities, and so they may be priced differently. Operating liabilities also involve accrual accounting estimates that may further affect their pricing. This study has investigated the implications of the two types of leverage for proﬁtability and equity value.The paper has laid out explicit leveraging equations that show how shareholder proﬁtability is related to ﬁnancing leverage and operating liability leverage. For operating liability leverage, the leveraging equation incorporates both real contractual effects and accounting effects. As price-to-book ratios are based on expected proﬁtability, this analysis also explains how price-to-book ratios are affected by the two types of leverage. The empirical analysis in the paper demonstrates that operating and ﬁnancing liabilities imply different proﬁtability and are priced differently in the stock market.Further analysis shows that operating liability leverage not only explains differences in proﬁtability in the cross-section but also informs on changes in future proﬁtability from current proﬁtability. Operating liability leverage and changes in operating liability leverage are indicat ors of the quality of current reported proﬁtability as a predictor of future proﬁtability.Our analysis distinguishes contractual operating liabilities from estimated liabilities, but further research might examine operating liabilities in more detail, focusing on line items such as accrued expenses and deferred revenues. Further research might also investigate the pricing of operating liabilities under differing circumstances; for example, where ﬁrms have ‘‘market power’’ over their suppliers.。

企业偿债能力分析中英文对照外文文献

企业偿债能力分析中英文对照外文文献原稿IntroductionAlthough creditors can develop a variety of protective provisions to protect their own interests, but a number of complementary measures are critical to effectively safeguard their interests have to see the company's solvency. Therefore, to improve a company's solvency Liabilities are on the rise. On the other hand, the stronger a company's solvency the easier cash investments required for the project, whose total assets are often relatively low debt ratio, which is the point of the pecking order theory of phase agreement. Similarly, a company's short-term liquidity, the stronger the short-term debt ratio is also lower, long-term solvency, the stronger the long-term debt ratio is also lower .Harris et al. Well, Eriotis etc. as well as empirical research and Underperformance found that the solvency (in the quick ratio and interest coverage ratio, respectively, short-term solvency and long-term solvency) to total debt ratio has significant negative correlation. Taking into account the data collected convenience, this paper represents short-term solvency ratios and to study the long-term solvency by the quick ratio and cash flow impact on the real estate debt capital structure of listed companies.Listed Companies Solvency AnalysisWhen companies need money, the choice of financing preference order, namely in accordance with retained earnings, issuance of bonds, financing order issued shares. According to this theory, strong corporate profitability, retained earnings more For financing first will consider retained earnings. Therefore, the profitability of the total debt ratio should be negatively correlated debt avoidance theory based natural surface that under otherwise identical conditions, a highly profitable company should borrow more debt, because they use avoidance of the need for greater debt, and therefore higher debt ratio. rapid growth of the company's financial leverage without the support, based on this, to select 378 samples from the 500 largest US companies, the researchers found that regardless of whether there is an optimal capital structure, the company's liabilities are directly correlated with growth.Growth is the fundamental guarantee company solvency, so whether short-term loans or long-term loans and creditors, as the company's growth as a positive signal, so the listed companies in recent years of growth, the higher its rate and short-term assets The higher rate of long-term assets and liabilities, total assets and liabilities naturally higher, but the impact on growth of real estate companies listed on a smaller debt ratio (coefficient is small). The risk of firm size and capital structure affect the growth has a similar conclusion, it appears that creditors, especially banks that the company scale is a measure of credit risk is an important consideration index, the greater the company size, the more stable cash flow, bankruptcy it is smaller, the creditors are more willing to throw an olive branch large-scale enterprises. The actual controller of the listed companies category to total debt ratio of the impact factor of a 0.040017, indicating that non-state-controlled listed company's total assets and liabilities higher than the state-owned holding companies. The reason for this phenomenon may be non-state-controlled listed companies pay more attention to control benefits, do not want to dilute their control over equity financing, and therefore more inclined to debt financing, which may also explain the non-state-controlled listed companies better use of financial leverage enterprises bigger and stronger impulses. In addition, the actual control of listed companies category short-term impact on asset-liability ratio is a 2.3 times its impact on long-term debt ratio, which shows the non-state-controlled listed companies prefer to take advantage of short-term debt to expand its operations.Current research on factors affecting capital structure point of view there are many factors in various industries concerned is not the same, according to industry characteristics and particularity, we mainly focus on the following aspects to analyze the factors industry capital structure. The article explained variable - capital structure for the asset-liability ratio, generally refers to the total debt ratio, but for more in-depth study of capital structure of listed companies, the paper from the total debt ratio, short-term assets and liabilities and long-term debt ratio of three angles of Capital structure explanatory.At present, domestic and foreign scholars analyzed factors on capital structure mostly used multiple linear regression, as usual statistical regression function in the form of their choice is often subjective factors, but ordinary regression methods to make function with average resistance, most such functions excellent and objectivity are often difficult toreflect. base stochastic frontier model (Stochastic Frontier) in data envelopment analysis (DEA) method, estimate the effective production frontier using mathematical programming method, namely the experience of frontier production function, overcome DEA method assumes that there is no random error term, the better to reflect the objectivity and optimality ¨J function, currently in the field of economic management, sociology and medicine, began to get more and more applications. Therefore, in this paper, stochastic frontier model data on the capital structure factors listed real estate companies conducted a comprehensive analysis, in order to provide a better scientific basis for the study of the optimal capital structure of real estate enterprises.Listed company's solvency and overall asset-liability ratio was significantly negatively correlated with short-term liquidity has a decisive influence on the short-term asset-liability ratio. Similarly, long-term solvency also has a decisive influence on long-term assets and liabilities. Industry higher total debt ratio particularly high proportion of short-term debt is one of the main business risks, thus increasing solvency of listed companies, especially short-term liquidity (that is, to obtain a stable short-term cash flow). reduce its asset liability ratio and effective risk management choice ROA of listed companies is much greater influence than ROE of asset-liability ratio, and affect the relationship is inconsistent, ROE is higher, the higher the total debt ratio, while the ROA high, the lower the rate of the total assets and liabilities, and short-term liabilities ROA more obvious, this difference is mainly due to the special structure of listed companies due to the nature of the capital, and therefore need to improve the capital structure of listed companies, namely to reduce the total assets and liabilities rate debt structure and the need to reduce the proportion of short-term debt in particular, in order to enhance the company's profitability ROA. growth and company size has a significant positive impact on the capital structure, which is mainly due to the growth of the company's solvency is fundamental, The size of the company is the main indicator to measure the bankruptcy creditor risk. Therefore, listed companies should be radically to grow through continuous growth and development of enterprises, so that the total debt ratio has a high margin of safety, through growth to continue to resolve the financial risk than non-state-owned holding companies controlling more use of financial leverage motivation and apparently relied on short-term liabilities, which may lead to moreserious financial risk especially short-term business risks, so that the non-state-owned holding listed companies should establish more strict risk prevention system.译文。

金融学外文文献英文文献外文翻译担保的作用和个人担保贷款的关系

外文文献原文Material Source: Hitotsubashi University Author: lichiro uesugi Role of collateral and personal guarantees in relationship lending: evidencefrom Japan's SME loan market1 IntroductionA key issue of interest in the recent literature on financial intermediation has been the role of relationship lending. Relationship lending is particularly common in the case of small business lending, because small businesses typically rely on bank loans for a substantial part of their financing needs but also tend to be informationally opaque. An important issue in this context is the use of collateral, which is a common feature of loan contracts between small firms and banks around the world, and a number of theoretical and empirical studies have examined why it is so widespread and how it relates to the incentives for borrowers and lenders and the borrower-lender relationship. For instance, it has been argued that in the presence of information asymmetries between creditors and borrowers, collateral may mitigate the problem of adverse selection (Bester, 1985; 1987) and/or the problem of moral hazard (Bester, 1994; Boot, Thakor, and Udell, 1991). Collateral also affects the incentives of creditors, who will use it either as a substitute for (Manove, Padilla, and Pagano, 2001) or complement to (Rajan and Winton, 1995; Boot 2000; Longhofer and Santos, 2000) screening and monitoring efforts. Another aspect of collateral that studies have concentrated on is that its presence may depend on the length and intimacy of the relationship between creditors and borrowers (Boot, 2000; Boot and Thakor, 1994; Sharpe, 1990). Existing empirical research has yet to reach decisive conclusions about the nature of these relationships.This paper seeks to contribute to the existing literature on collateral using a unique firm-level data set of the small and medium sized enterprise (SME) loan market in Japan. Explicitly differentiating physical collateral (such as real estate) and personal guarantees by business representatives, we investigate how the use of collateral and personal guarantees affects the incentives of borrowers, lenders, and the relationship between them. More specifically, we examine the following three issues. First, we examine whether riskier borrowers are more likely to be required to provide collateral or personal guarantees. Second, we investigate how collateral and personal guarantees affect banks’ monitoring of borrowers. Third, we examine thecorrelation between the use of collateral and personal guarantees on the one hand and the closeness of borrower-lender relationships on the other.The data set we employ is based mainly on the “Survey of the Financial Environment” (SFE) conducted by the Small and Medium Enterprise Agency of Japan in October 2002. In order to focus on firms that mostly depend on bank loans for their financing, we limit the sample to firms satisfying the legal definition of an SME in Japan. We then combine the SFE data for each SME with information on their main bank obt ained from the bank’s financial statements in order to control for lender characteristics as well. Furthermore, to control for the effect of government credit guarantees on collateral and personal guarantees, in the main analysis of this paper we exclude from the sample all firms that enjoyed any form of government credit guarantee.As a result of this screening process, we end up with a sample of 1,702 firms. Our main findings can be summarized as follows. We find that firms’ riskiness does not have a significant effect on the likelihood that collateral is used. Thus, we cannot find firm evidence that the use of collateral mitigates moral hazard. We find, however, that banks whose claims are collateralized monitor borrowers more intensively, and that borrowers who have a long-term relationship with their main bank are more likely to pledge collateral. These findings suggest that collateral is complementary to relationship lending. In contrast, the complementarity between relationship lending and personal guarantees is weaker.As far as we know, this is the first empirical study that systematically examines the role of collateral and personal guarantees in Japan’s SME loan market. The two main contributions of the paper are as follows. First, given that Japan is generally considered to have a relationship-based financial system in which the relationship-lender, the main bank, plays a central role in corporate financing (Rajan and Zingales, 2003), the study helps to improve our understanding of the role of collateral in relationship lending and complements existing studies that focus on the United States and Europe. Second, and more importantly, by distinguishing collateral and personal guarantees, the study detects an important role of collateral in relationship lending that has not been remarked on much before. As we argue below, although a typical SME in Japan has a long-term relationship with its main bank, it actually engages in transactions with several banks, which is not common in other countries. A possible corollary of this is that because of the informationalfree-rider problem it creates, this practice may reduce the main bank’s incentive to screen and monitor borrowers. Since collateral defines the order of seniority among creditors, using collateral may mitigate the free-rider problem and enhance the main bank’s screening and monitoring. This incentive effect for the main bank becomes tenuous for personal guarantees, because personal guarantees do not define the seniority among creditors. Thus, our work provides empirical evidence on how collateral affects relationship lenders’ incentives, and complements previous studies that focus on the problem of borrower incentives (moral hazard and adverse selection).The remainder of the paper is organized as follows. Section 2 develops our empirical hypotheses which are based on previous theoretical models and empirical research. Section 3 describes the data and variables that are used in the paper, and explains our empirical model.Section 4 presents the results of our empirical analysis, and Section 5 concludes.2 Empirical hypotheses2.1 Borrower riskinessMuch of the empirical literature in this field examines theoretical predictions of asymmetric information models on the relationship between risk and collateral. If the bank cannot discern borrowers’ riskiness (hidden information), then collateral may serve as a screening device to distinguish between borrowers and to mitigate the adverse selection problem (Bester, 1985). This follows from the observation that a lower-risk borrower has a greater incentive to pledge collateral than a risky borrower, because of his lower probability of failure and loss of collateral. Hence, the lower-risk borrower will choose the contract with collateral.On the other hand, if the lender can observe the ex-ante risk, but there are information asymmetries with regard to actions taken by the borrower after the loan is extended, collateral potentially provides an incentive to mitigate moral hazard. Thus, opposite to models focusing on hidden information, those concentrating on hidden action suggest that it is observably riskier borrowers that will pledge collateral, because collateral induces more effort by the borrower (Boot, Thakor, and Udell, 1991), or reduces the incentives of strategic default (Bester, 1994).Because our data base only contains measures of firms’ observed riskiness(namely, credit scores), we couch our first empirical hypothesis as follows: Hypothesis 1 (H1): The use of collateral is higher among observably higher-risk (low credit score) borrowers if the lender requires collateral in order to mitigate the extent of moral hazard.Alternatively, if borrowers pledge collateral as a signal of their unobserved high credit quality, then there is negative or no relationship between the use of collateral and the credit score.Consistent with the theory of moral hazard, most existing empirical studies, including Berger and Udell (1990; 1995), have found a positive relationship between collateral and borrowers’ ex-ante risk. Jiménez, Salas and Saurina (2006) directly test the adverse selection and moral hazard hypotheses by separating ex-ante and ex-post measures of borrower riskiness, namely defaults prior to and after the loan origination. Their results suggest that although observed riskiness increases the likelihood that collateral is used, there is also a negative association between collateral and default after the loan has been granted, which is consistent with the adverse selection argument.It should be noted that theories of collateral as a solution to moral hazard and/or adverse selection problems assume collateral is external to the firm.Unfortunately, our measure of the incidence of collateral does not distinguish between firm (inside) collateral and personal (outside) collateral. Hence, throughout our analysis, we will assume that collateral is mostly inside, but allow for the fact that there may also be some outside collateral. As for personal guarantees, they clearly represent outside collateral.2.2 Screening and monitoring by the lenderRecent research on collateral also discusses how collateral affects lenders’ incentives with regard to information production, that is, the screening of borr owers’ quality and the monitoring of their performance. These theories of the effect of collateral on lenders’ incentives apply to both inside and outside collateral. Manove, Padilla, and Pagano (2001), for instance, argue that, from banks’ point of view, collateral can be considered as a substitute for the evaluation of the actual risk of a borrower. Thus, banks that are highly protected by collateral may perform less screening of the projects they finance than is socially optimal.However, several theoretical studies argue that collateral may complement lenders’ screening and monitoring activities. In the presence of other claimants,lenders’ incentive to monitor borrowers is reduced due to the informational free-rider problem. In order to enhance le nders’ incentive to monitor, loan contracts must be structured in a way that makes lenders’ payoff sensitive to borrowers’ financial health. Rajan and Winton (1995) argue that collateral may serve as a contractual device to increase lenders’ monitoring incentive, because collateral is likely to be effective only if its value can be monitored. Moreover, the use of collateral as an incentive will be more extensive when the value of such collateral (as in the case of accounts receivable and inventories, for example) depreciates rapidly if business conditions deteriorate, than when the value of collateral is relatively stable (as in the case of, e.g., real estate). Longhofer and Santos (2000) argue that collateral serves as an incentive for information production by the principal lender in the presence of several creditors, because taking collateral is effective in making its loan senior to other creditors’ claims. Thus, the bank that provides collateralized loan is able to reap the benefits of screening and monitoring activities. Note that this argument does not straightforwardly apply to personal guarantees, because, in general, personal guarantees do not define seniority among several creditors.As we have a proxy variable for the intensity of monitoring by the principal lender, our second hypothesis for the empirical analysis is as follows: Hypothesis 2 (H2): The use of collateral decreases with the intensity of monitoring by the principal lender if collateral reduces lenders’ incentive to exert effort in loan management. Alternatively, if collateral serves as an incentive device to induce monitoring efforts by the principal lender in the presence of other claimants, then we expect a positive relationship between the use of collateral and monitoring intensity.To our knowledge, there are only two existing studies that empirically assess whether the use of collateral and personal guarantees substitute for or complement screening and monitoring by the lender. Examining Spanish loan data, Jiménez, Salas and Saurina (2006) found that banks with a lower level of expertise (smaller banks and savings banks) in small business lending use collateral more intensively. This is consistent with the theory that collateral is used as a substitute for the evaluation of credit risk. The present study complements these works investigating the relationship between collateral and screening by focusing on the relationship between collateral and monitoring using Japanese firm data. Our proxy variable for monitoring intensity is the frequency of document submissions tothe main bank.2.3 Relationship between the borrower and the lenderThe existing literature on relationship lending provides conflicting predictions on how the strength of the relationship between borrower and lender affects the likelihood of collateral being pledged. By establishing a solid relationship with the borrower, the lender learns about the hidden attributes and actions of the borrower, thus reducing information asymmetries. Hence, the terms of loan contracts may become more favorable to the borrower if the firm has transactions with a specific relationship lender over a long period of time and thus establishes trust, resulting in a lower likelihood of collateral being pledged (Boot and Thakor, 1994). However, a solid relationship may become detrimental to the borrower if the bank exerts its information monopoly by charging higher interest rates or requiring more collateral (Sharpe, 1990). If such a hold-up problem is indeed common, then there is likely to be a positive correlation between the strength of a relationship and the use of collateral. It should be noted that these theories assume that the collateral is outside collateral. In addition, collateral can also be used as an incentive device in mitigating the soft-budget constraint problem in relationship lending (Boot, 2000). For example, consider the case where a borrower in difficulty asks the bank for more credit and reduced interest obligations in order to avoid default. Although a transaction-based lender would not lend to such a borrower, a relationship lender that has already made loans might accept the borrower’s request in the hope of recovering a previous loan. However, once the borrower realizes he can renegotiate the loan contract relatively easily, he has an incentive to misbehave ex ante (the soft budget problem). In such cases, collateral will increase the ex-post bargaining power of the lender and hence reduce the extent of the soft-budget constraint problem, because collateral makes the value of the lender’s claim less sensitive to the borrower’s total net worth. These theoretical considerations apply to inside collateral as well as outside collateral and lead to the following hypothesis: Hypothesis 3 (H3): Borrowers that establish a solid relationship with their principal lender are less likely to use collateral if the relationship reduces information asymmetries and enhances mutual trust between the borrower and the lender. Alternatively, borrowers with a strong relationship with their principal lender are more likely to use collateral if the effects of the hold-up problem or the mitigation of the soft-budget constraint problem dominate.外文文献译文资料来源: 日本一桥大学作者：lichiro uesugi担保的作用和个人担保贷款的关系：来自日本的中小企业贷款市场的证据在中小企业的贷款中关系贷款非常的普遍，小企业的贷款主要是依靠银行融资，但是小企业却存在财务不透明的问题。

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债务融资外文翻译文献(文档含中英文对照即英文原文和中文翻译)译文:股权集中度，“控制权私人收益”和债务融资摘要：基于快速成长的'法律和经济’文献，本文分析了主要所有者在以牺牲小股东利益而获取“控制权私人收益”的环境中进行债务融资的公司治理。

这表明，所有权集中是与作为一个公司的负债比率和衡量投资的财政资源的使用效率较低有关，而这并不取决于最大股东的身份，固定的具有支配权的股东可以串通股权持有者进行控股溢价。

这个结论的其中一个可能的结果就是债务市场的企业信贷压缩，这有转型期经济体的证据支持。

关键词：所有权，控制权收益，债务引言有一个大量研究金融经济学和战略管理的文献显示获得控制权私人收益的方式和数量与管理行为和企业业绩有关。

(Gibbs, 1993；Hoskisson et al., 1994；Jensen and Warner, 1988)然而，大多以往的研究集中于大型、公开的在传统的美国/英国公司控制模型的框架范围内分散所有权的上市公司，很少是关于所有权集中的公司治理（Holderness and Sheehan, 1988；Short,1994）。

快速成长的企业所有制结构的优化取决于“控制权私人收益”的水平。

（e.g., Bennedsen and Wol fenzon, 2000； Grossman and Hart, 1988；Harris and Raviv, 1988）。

文献已超出传统的治理研究美国/英国环境，并在最近成为理论和政策辩论。

（Bebchuk, 1994；Filatotchev et al., 2001；La Porta et al., 1998；2000b；Modigliani and Perotti, 1997）这项研究对中小投资者受较少保护而控股股东广泛控制小股东的国家特别重要。

这种对控制权的行使可采取多种形式，比如利用公司机会、关联方交易、转移定价，资产转移和其他“隧道行为”剥夺企业的资产和收入。

（见La Porta等，1998年；一个广泛的讨论）。

因此，在这样一种机构环境下的主要问题不是职业经理人不能满足分散的股东的目标，而是大宗股东对小股东的控制。

（La Porta et al., 2000a；Shleifer and Vishny, 1997）。

这种机会主义行为会阻止外来投资并对公司的价值产生负面影响（Jensen and Meckling,1976； La Porta et al., 1998; Wruck, 1989）。

然而，尽管代理成本与大宗股权相关，集中股东可能抵制甚至长期进行他们的股权稀释。

Modigliani and Perotti (1997)表明，在一个法律执行不健全的环境，控制权价值通常较控股股东通过出售股份进行股权投资价值更大。

Bebchuck (1994; 1999)对公司所有权结构提出了“借贷-保护”理论，建议当控制权私人利益很大时，集中所有权是唯一可行的办法。

在他的模型中，控股股东将倾向于保持控制权，因为放弃控制权会吸引对手组建一个控制股份来获取这些私人利益。

这些论点提出了一系列重要理论和实际影响。

首先，这在所有权集中度相对较高的发达国家和发展中国家的经济中对受保护程度低的小股东来说可能是一个平衡反应。

在Jensen and Meckling(1976)提出的机构框架上一些作者提出更高的主权控制会增强他们对不可分配的分散股份的兴趣。

(Filatotchev et al., 2001；La Porta et al., 2000a)当获取控制权私人利益涉及产品成本，大宗股东股权的增加将减少获取的边际收益。

（see Bennedsen and Wolfenzon, 2000; Claessens et al., 1999, for a discussion)。

第二，不适当的立法和执法框架可能妨碍股票市场的发展，并且和直接股权融资相比占用相对大量的信用中介。

(LaPorta et al., 1997； Modigliani and Perotti, 1997；Schleifer and Vishny, 1997)此外，固定股权持有人可以提供拥有现金流量权的机会主义行为的集中业主一个有效制衡。

(Hart,1995；Jensen, 1986)债务可以为需要进行利息支付和因不能支付这些利息而要进行破产调用程序的时候提供一个硬机制。

它也可以是通过银行积极监管定期提供信息、面对面的会议、对违反公约的灵活解释等。

(Holland, 1994;Myers and Majluf, 1984）最后，Dewatripont and Tirole (1994)认为，负债与公平有效的公司治理存在互补性。

然而，尽管这些大量的研究很先进，基于“控制权私人收益”的优化所有制结构理论存在理论与实际的不足而需要进一步分析。

首先，在“法律和经济”框架内的研究大部分都集中在股权融资。

第二，以往的研究主要涉及股票持有人对小股东之前的投资比例分配利润的控制。

然而，机会主义行为者会尝试选择在投资项目之前进行事前错误安排。

最后，先前关于债务管理作用的调查很少有关于固定股东和大股东之间共谋的管理，而且，关于相同组织的联合的结果调查也很少。

在本文中我们目标在于弥补这些缺陷，并制定一个概念框架来分析在少数股东利益没有得到有效保护的环境下大股东和定息股东潜在勾结带来的影响。

文章结构如下：在下一个章节，我们对“控制权私人收益”在组织决策和公司绩效方面的有关文献作一个回顾。

第二章节，我们主要讨论在一个简单的理论模型框架下的集中所有制和债务融资问题。

接下来我们从经济转型中举例分析大股东和定息股东的通过控制资金流动使得企业被“挤出”融资市场的可能，并分析其后果。

最后一节是结论。

理论框架和文献回顾以往的研究已证实一些大股东对公司治理的作用，其中一些可能会有价值提升，而其他有可能产生负面影响。

（see Filatotchev et al., 2001; Shleifer and Vishny, 1997, for an extensive discussion）这两个战略和机构观点往往都集中在分析可能的与集中股权相关的激励效应上。

Jensen and Meckling (1976)例如，解释了提高企业家/经理的现金流量权对消费额外津贴的制约，从而对企业的估值产生积极的影响。

进一步研究表明，大宗外来所有权可能也是一个对管理机会主义的有效制衡。

公司可能由很大、单一的股东发挥重要的领导和监督作用。

他们有鼓励机制和手段抑制自我服务的管理人员的行为。

（Maug, 1998; McConnel and Servaes, 1990; Zeckhauser and Pound, 1990）。

此外，他们与雇员和其他利益相关者私下签订有利于价值提升的合同。

（Shleifer and Summers, 1988）从战略管理角度来看，大股东可能不允许不完善的战略，如由多样化演变成业绩不佳，因此减少结构调整的幅度。

（Gibbs, 1993; Hoskisson et al., 1994）一些研究人员指出集中持股可能建立除了激励效应外的堑沟效应。

（McConnell and Servaes, 1990;Mikkelson and Partch, 1989; Morck et al., 1988）不是强加一种有效监测和管理权控制，大股东可能产生他们自己提供的代理成本（Roe, 1990）。

特别是，缺乏多样化意味着大股东都受到该公司的个别风险的影响。

（Maug, 1998）这种风险降低了其主观价值投资，他们可以利用机会勾结经理把少数股东财富转移到自己那。

Gibbs(1993)认为，无党派股票持有者通常是被动的，支持管理人员对其发展的追求，而不是剩余价值。

Pound (1988)也表明，股票持有者很可能与经营者持同样观点，（战略性调整假说）或者受经营者现有的商业关系的影响（受冲突假说）。

在这项研究的基础之上，一些创办人指出，当多数股东有可能以牺牲少数股东利益为代价来滥用自身的主导地位，特别是当少数股东的法律保护很弱时，股权集中本身可能对企业的价值带来负面影响。

（Bebchuk,1994; Stiglitz, 1985）这种滥用可能得益于特定的法律安排，如特定的选举权。

（Grossman and Hart, 1988; Harris and Raviv, 1988）它可以有多种形式，从现金流量拨款、资产剥夺到以交叉持股和以金字塔的方式进行的资产倒卖。

（La Porta et al., 1998）现金流量权的集中可能伴随选举权的增长比例。

因为它降低了少数股东有效沟通对抗控股股东的几率，这种集中的股票控制权可以使剥夺代价更小。

此外,在某种程度上的股权集中度与外界人士之间的界限变得模糊了。

股票持有者不管他们的身份是什么，他们都有强烈的动机去转移资源，以牺牲其他股东利益为代价使自己获利。

(Wruck, 1989)。

然而，控股股东剥夺少数股东权益的意愿可能受囿于财政激励。

Jensen and Meckling (1996)在由Jensen和Meckling (1996)发起的机构框架基础上，大量的创办人将这些激励机制跟控股股东的资本所有权联系起来以提高他们对非扭曲股息分配的兴趣。

假设对剥夺私人利益的控制牵涉到诸如法律操纵，设定金字塔等的代价，那么大量股东股权的增长将减少资产剥夺的净收益。

（see La Porta et al., 2000a, for a discussion）。

和其他事情一样，既然激励机制与管理机制相互抵触，股权集中应该导致资产剥夺的减弱。

因此，大量的股权控制被少数股东作为好企业被认可的一种信号。

（Bennedsen and Wolfenzon, 2000）并且这些观点和在建立贸易公司的过程中股权集中是法律保护在提供公司管理方法的作用上的一种替代是一致的。

（La Porta et al., 1998）换句话说，一个企业的股权结构可以是一个企业经营特点以及它所处的竞争性、合法性环境的一种平衡的响应。

（Demsetz and Lehn, 1985; Jensesn and Warner, 1988; Roe, 1990）。

在这项研究的基础之上，大量的学者提出拥有现金流量权的控股股东应减缓对少数股东资产剥夺的刺激，但不必消除这种做法。

（Filatotchev et al., 2001; La Porta et al., 1999）结果，普通股市场在从GNP中获利的水平更大、有好的合法保护小股东的国家的市场结构中发展更深(La Porta et al., 1997; 1999)。