LIQUIDITY RISK IMPLICATIONS FOR MARKET RISK ASSESSMENT IN EMERGING MARKETS

Abstract

Abstract Classical financial market theories built upon the assumption of a perfect market have been coping with frictions on both developed and emerging markets. There are numerous factors affecting the operation of financial markets and their participants’ behavior, but illiquidity is a continuous problem that has important consequences on the financial asset prices and the degree of competition between market participants. Moreover, investments that yield high profits are often the ones related to less liquid financial assets from emerging markets. Since investment decisions are based on risk preferences and investors are commonly risk averse, they tend to limit their risk exposure while defining their investment strategy. Various risk measures can be used to estimate the level of risk. Value at Risk (VaR) is a widely accepted summary measure of market risk that is also recommended by the financial industry regulatory authorities as a risk management tool. The usage of VaR models is rapidly expanding; thus, it is used by both financial and non-financial institutions in order to estimate exposure to financial risks, complement allocation of capital, set trading position limits and evaluate performance of trading strategies. However, the last global financial crisis that occurred in 2007-2008 highlighted some of the weaknesses of this measure as a measure of market risk. The lack of a liquidity parameter in methodologies used to compute VaR significantly decreased the effectiveness of this measure. Therefore, the objective of this research is to examine the implications of asset liquidity risk on market risk assessment, which is obtained by using VaR.

The most frequently used technique for VaR estimation is the parametric (analytic) method, but the constant search for precise prediction models results in a large number of variations of basic parametric and non-parametric methods. Thus, in this research, the parametric VaR and volatility models are implemented on a sample representing the stock indices of the European emerging markets in the period from 2009 to 2017. The results of this study indicate that the application of a liquidity constraint in the VaR model provides more accurate assessment of potential loss, especially in emerging markets, and enables investors to detect the liquidity risk and its effect in comparison with a conventional VaR.