Evaluating Investors’ Recognition Abilities for Risk and Profit in Online Loan Markets Using Nonlinear Models and Financial Big Data

Financial big data are obtained by web crawler, and investors’ recognition abilities for risk and profit in online loan markets are researched using heteroskedastic Probit models. The conclusions are obtained as follows: First, the preference for the item is reflected directly in the time and indirectly in the number of participants for being full, and the larger the preference, the shorter the time and the fewer the participants. Second, investors can discriminate the default risk not reflected by the interest rate, and the bigger the default risk, the longer the time and the more participants being full. Third, investors can discriminate the pure return rate deducted from the maturity term and credit risk, and the higher the return, the shorter the time and the fewer the participants being full. Fourth, default risks are reflected well by online loan platform interest rates, and inventors do not choose the item blindly according to the interest rate but consider comprehensively the profit and the risk. In the future, interest rate liberalization should be deepened, the choosing function of interest rates should be played better, and the information disclosure, investor education, and investor effective usage of other information should be strengthened.

Private Equity and the Resolution of Financial Distress

We examine the role private equity (PE) sponsors play in the resolution of financial distress of portfolio companies. PE-backed firms have higher leverage and default at higher rates than other companies borrowing in leveraged loan markets. But, PE-backed firms restructure more quickly, avoid bankruptcy court more often, and liquidate less often compared to other highly leveraged firms experiencing financial distress. PE owners are also more likely to retain control post-restructuring, often by infusing capital as firms approach distress. While default frequencies are higher among PE-backed firms, PE investors appear to manage financial distress at lower cost compared to other owners.

Credit derivatives design to facilitate loan purchase agreements in the secondary loan market in Thailand

Purpose This paper aims to study a strategic decision of banks in Thailand to signal their types to the market and derive the optimal credit derivatives contract to guarantee their loans and credibly signal their quality under different economic determinants, namely, the maximum credit risk investment constraint, opportunity cost and opaqueness of the credit derivative market. Design/methodology/approach Contract theory is deployed to derive the expected payoff of different bank types under different economic and financial constraints. Hence, different bank types offer derivatives contracts to signal their loan quality and resell their loans in the secondary loan markets of Thailand. Findings The optimal derivatives contract is constructed on a basis of asymmetric information when banks have more private information concerning quality of their loans. A digital credit default swap is an optimal derivatives contract to send credible signal when banks are restricted to the maximum investment constraint. Moreover, profit of banks is reduced, as the optimal derivatives contract is more costly when banks are subjected to positive opportunity cost and opacity of the credit derivatives market. These results depict impact of changes of the maximum credit risk investment constraint on Thai credit derivatives market. Originality/value The optimal credit derivatives design that signifies bank types and facilitates loan purchase agreement has not been studied in Thai secondary loan markets before. In addition, this study provides insights of banks' strategic decisions to signal their types and transfer risk to risk buyers in Thai markets.

Concentration in the banking sector and housing lending in Russian regions

The article examines the global and Russian experience in analyzing the influence of concentration and competition on the functioning of the banking sector, including the mortgage market. The information on housing loans issued by banks in the regions of Russia is used and the level of concentration in the regional housing lending markets is estimated. It is shown that regional housing loan markets are highly concentrated. It has been revealed that the concentration level negatively affects the dynamics of housing lending in the regions of the country. High concentration is also associated with slightly higher lending interest rates and their smaller spread. This may be the evidence that high concentration hinders the development of lending in the regions of Russia, which means that the level of competition in the banking sector is insufficient.