Разработка системы индикаторов финансовой нестабильности на основе высокочастотных данных
In this paper we propose a system of financial stress indicators for Russia based on high frequency data. Unlike previous studies, we identify financial instability for different types of financial risks (credit, liquidity, currency, interest rate, external finance risk), not for different segments of financial market. With constructed composite indicator of systemic risk at hand, we identify crisis events in the Russian financial market in 2008–2009 and in 2014–2015, which were caused by both the negative impact of external financial shocks and the deterioration of domestic macroeconomic conditions. In addition, we find strong evidence in favor of different types of financial risks co-movement.
The paper presents a review of stochastic framework for term structure modeling and shows comparative advantages of commonly used techniques. The main application of the research is coherent modeling of credit and interest rate risk for Euro zone issuers.
In textbook the main issues connected with organization of credit analysis in a commercial bank were considered. The role of credit analysis in risk management system is shown. The methodology and specific methods for assessing the creditworthiness of borrowers used by banks are set out by complex approach. The textbook includes international recommendations for introduction of internal credit risk assessment systems in banks. With the aim at presenting the material examples from the practice of commercial banks, analytical tables, diagrams and figures were used.
World fi nancial crisis and increased volatility of major economic indicators raised attention to the problem of fi nancial risk management in corporations, and to the possibilities of fi nancial derivatives usage for hedging. In perfect markets hedging by means of derivatives allows corporations to mitigate fi nancial risks allowing for minimum costs. Current paper examines factors that restrict usage of derivatives for hedging currency risks by corporations on Russian fi nancial market. It is concluded that on Russian market it is reasonable to use internal facilities as basic method of currency risk management: asset/liability management, regulation of debt
currency structure, diversifi cation, etc. Derivatives should be used in addition to these facilities in very limited volumes for hedging the most predictable sources of risk.
Carry trades consistently generate high excess returns with high Sharp ratios, but are subject to crash risk. I take a closer look at the link between the carry trade returns and the stock market to understand the risks involved and to determine when and why currency crashes happen. Every period, I sort currencies of developed and emerging economies by their interest rates and form portfolios to diversify the idiosyncratic risk. First, I find a strong negative relationship between portfolio returns and skewness of exchange rate changes. In fact, skewness and coskewness with the stock market have a much greater explanatory power in the cross-section of excess returns than consumption and stock market betas. But separating the market beta into upside and downside betas improves the validity of the CAPM significantly. Downside beta has a much greater explanatory power than upside beta, and it correlates with coskewness almost perfectly. This means that carry trades crash exactly in the worst states of the world, when the stock market goes down. After controlling for country risk, the downside beta premium in the currency market is comparable to that in the stock market and equals 2-4 percentage points p.a. I also find that country risk proxies well for the downside beta and skewness. This suggests that there is unwinding of carry trades and a “flight to quality” when the stock market plunges, and that lower interest rate currencies serve as a “safe haven”. Finally, I estimate even higher downside betas of the top portfolios and I find an even greater explanatory power of the downside beta in the early 2000s. The growing volume of carry activities might have contributed to the closer link between the currency and the stock markets.
Some currencies persistently move together with the stock market and crash in periods of market downturns or high volatility, while others serve as a “safe haven”. In this paper, I study whether or not countries’ macroeconomic characteristics are systematically related to the market risk of their currencies. I find that the market risk is not random, especially on the downside, and it can be predicted by macroeconomic variables. Moreover, the market risk has increased significantly since the 2000s, and its predictability also increased. The real interest rate has the highest explanatory power in accounting for the cross-section of currency market risk. Currencies of countries with high local real interest rates have high market betas, especially downside betas, while low real interest rate currencies are immune to stock market changes. Nominal interest rates also have some explanatory power, but only to the extent to which they correlate with the real interest rates. Other variables considered seem to be irrelevant.
In the paper some prominent features of a modern financial system are studied using the model of leverage dynamics. Asset securitization is considered as a major factor increasing aggregate debt and hence systems uncertainty and instability. A simple macrofinancial model includes a logistic equation of leverage dynamics that reveals origins of a financial bubble, thus corresponding closely to the Minsky financial instability hypothesis. Using ROA, ROE, and the interest rate as parameters, the model provides wide spectrum of leverage and default probability trajectories for the short and long run.
The book presents a logically structured study of the development of global economy beginning from the 1970s. The major evolutionary processes are emphasized and the core problems for the present period of time are identified. Also, a separate scenario forecasts for the next 5-10 years are formulated. In the course of the analysis it was separately allocated problems associated with the functioning of global financial markets and their negative impact on economic growth.
The paper considers the financial choice of entrepreneurs at their initial stage of development as a key criterion of a new firm potential riskiness. The main objective of the research is the methodology elaboration aimed at the numerical estimation of the role of informal financial resources involved in the small business creation. Two fundamental considerations have been tested. The former implies that informal investment is a substitution for unavailable formal sources, including venture capital (because of the lack of essential networks and connections with business associations). The latter performs the opposite concept of negative effects: economic reasoning discouragement and inefficient resources allocation. A special technique is introduced in order to measure the credit quality of early entrepreneurial activity and to estimate its contingency with the financial strategy. The methodology validation is realised under Global Entrepreneurship Monitor conceptual framework. The results are received for 42 countries in 2006-2007, depicting the influence of informal support on potential losses under the second consideration. As a result, informal investments are inefficient when the concentration of credit risk in the economy is rather high. Investorsђ expectations about the entrepreneurial growth of the firm are pessimistic, anticipated returns on investments are too low to be economically reasonable. The outcome leads to the irrecoverable losses, both financial (short-received profitability) and nonfinancial (decreased output, the lack of innovativeness, flexibility, and inventiveness).
The mortgage crisis that started in the U.S. in 2007 and lasted until 2009 was characterized by an unusually large number of defaults on the subprime mortgage market. As a result, it developed into a global economic recession and placed the stability of the world banking system in jeopardy. Therefore, the issues of credit risk modeling showed the shortcomings of the current credit risk practice. Truncation, or partial observability, and simultaneous equations bias causes sample selection bias. As a result, parameter estimates are biased and inconsistent. Firstly, we provide an overview of current approaches in the mortgage literature to control for the sample selection bias correction, such as the Heckman model and bivariate probit model with selection. Secondly, a review of the most significant mortgage studies discussing this problem is introduced. Specifically, different structural models, specific datasets and empirical results are regarded. In addition, we discuss such key credit risk determinants as borrower characteristics, terms of the mortgage contract, mortgage characteristics, and macroeconomic conditions. Finally, we conclude the discussion with possible research questions.