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The aim of this paper is to calibrate the Longstaff, Mithal and Neis (2005) model (LMN model) based on the J-law (see Jerbi (2015) to implement the credit risk in the economic scenarios generator. The LMN model, based on the assumptions of the normality of the risks is used to establish a link between the spread, the probability of default and the liquidity risk. The related assumptions seem unrealistic given the depth of the distribution that characterizes the financial and economic data. In this context, we develop an LMN model based on the J-law taking into account the effects of Skewness and Kurtosis related to the two series of the CDS premium and the corporate bond prices. We use a simulated data that are from January 2009 to December 2016. We estimate the model parameters. The LMN model based on the J-law fit better with the reality than the one based on the normal Law.      

Speculative bubbles are of extreme importance in modern society. They are well known for their dynamics and their dramatic consequences which affect most financial markets. Therefore, many researchers have aimed to fully understand, identify and predict speculative bubbles. However, they still cannot agree on the correct identification and exact prediction of when they will burst ahead. One of the best-known models in this context is the Johansen-Ledoit-Sornette (JLS) model introduced in 1996 and which has then undergone several adjustments over the years. This model states that bubbles are not characterized by exponential growth but rather by faster than exponential growth in prices. This characteristic is due to the imitation and herd behavior of irrational investors which creates positive feedback during the bubble forming period. Thus, this model is mainly based on the log-periodic power law equation (LPPL) which is generally used in physics for the prediction of natural phenomena such as earthquakes. Our contribution through this paper is to examine the ability of standard JLS models as well as its extension to the generalized JLS model to predict the critical time of bubble burst, to measure its size and to calculate the fundamental value of financial assets. Our results are obtained by modeling asset prices of the historical oil bubble of 2008. Indeed, our implemented algorithm is based on a combination between the Levenberg-Marquardt algorithm and the Price Gyration method instead of the Taboo search method. Our obtained results gave rise to precise and correct predictions and the expected characteristics of the JLS model during the bubble period.

The aim of this paper is to evaluate barrier options by considering volatility as stochastic following the CIR process used in Heston (1993). To solve this problem, we used Monte Carlo simulation. We studied the effects of stochastic volatility on the value of the barrier option by considering different values of the determinants of the option. We illustrated these effects in twelve graphs. We found that in general, regardless of the parameter under study, the stochastic volatility model significantly overvalues the in-the-money (ITM) barrier options, and slightly the deep-in-the money (DIP) options, while slightly undervaluing the near-out-the money (NTM) options.

Net interest margin is a significant indicator of the efficiency of the banking financial intermediation. In general, the level of net interest margin is primarily a consequence of result of the level of development and competitiveness of the financial system of country.Therefore, It is important to determine their determinants. In this article, we analyze the determinants of net interest margin of 18 banks in Tunisia between ( 2000…2013). We found that among the internal factors, size, deposits, TLA, CEA, risk have an significant impact  on net interest margin. In external factors, only inflation have a significant impact on net interest margin..

Using bank level data this paper examines how bank’s specific characteristics and macroeconomic indicators affect the profitability in the Tunisian banking industry over the period 1990–2008. The results indicate that the more profitable banks are those higher amount of capital and lower operating costs. Furthermore, it appears that private banks tend to perform better than state owned ones.  Despite the great importance given to the board of directors, it doesn't have a dominant role in the Tunisian commercial banks. Finally, turning to macroeconomic conditions and its impact on banks’ profitability, we find that the real interest rate has a positive effect on bank profitability.

The aim of our research is to investigate the relationship between risk management, corporate governance and performance in lending institutions. Mainly, this research seeks to examine the effect of risk management and some board’s features on financial performance. Empirical analyses are conducted from a sample of 17 Tunisian lending institutions over the period 2002-2011 using an OLS regression. The study shows that board size affect performance significantly. Most importantly, the existence of a risk committee within the institution has a negative and significant effect on performance.

In recent years the financial markets known a rapid development and become more and more complex. So, many regulatory requirements, focused on banks as well as insurance sector, have been developed. These regulatory are concentrated essentially on business risk control and required capital to cover risks. These requirements have influenced the asset allocation issue in insurance industry. These requirements have influenced the asset allocation issue in insurance industry. This section is interested by this issue. In first time it highlights some research works in this issue. Then we will investigate the relation between Solvency and optimal asset allocation. Finally we will explore the principal used methods in modeling asset and in choosing the optimal portfolio composition.