### Personal information

Philip Ngare is an Associate Professor of  Actuarial Science at University of Nairobi. He received his Ph.D in Financial Mathematics from University of Linz, Austria. His research interests include Finance, Actuarial Science, Probability Modeling, Econometrics, Computational Methods and Simulation.

### 2019

Wamwea, C, Ngare P, Bidima MLDM, Mwelu S.  2019.  Journal of Mathematical Finance. 9(4):698-725. AbstractWebsite

Interest rate derivatives form part of the largest portion of traded financial instruments. Hence, it is important to have models that describe their dynamics accurately. This study aims at pricing Quanto caps and floors using the multi-curve cross-currency LIBOR market model (MCCCLMM) dynamics. A Black Scholes MCCCLMM Quanto caplet and floorlet formula is first derived. The MCCCLMM parameters are then calibrated to exactly match the USD and GBP cap market prices. The estimated model parameters are then used to price the Quanto options in the Black MCCCLMM Quanto caplet and floorlet formula. These prices are then compared to the Quanto cap and floor prices estimated via Monte Carlo simulations so as to ascertain its pricing accuracy

### 2018

Dzupire, NC, Ngare P, Odongo L.  2018.  Journal of Probability and Statistics. 2018(1012647) AbstractA Poisson-Gamma Model for Zero Inflated Rainfall Data

Rainfall modeling is significant for prediction and forecasting purposes in agriculture, weather derivatives, hydrology, and risk and disaster preparedness. Normally two models are used to model the rainfall process as a chain dependent process representing the occurrence and intensity of rainfall. Such two models help in understanding the physical features and dynamics of rainfall process. However rainfall data is zero inflated and exhibits overdispersion which is always underestimated by such models. In this study we have modeled the two processes simultaneously as a compound Poisson process. The rainfall events are modeled as a Poisson process while the intensity of each rainfall event is Gamma distributed. We minimize overdispersion by introducing the dispersion parameter in the model implemented through Tweedie distributions. Simulated rainfall data from the model shows a resemblance of the actual rainfall data in terms of seasonal variation, means, variance, and magnitude. The model also provides mechanisms for small but important properties of the rainfall process. The model developed can be used in forecasting and predicting rainfall amounts and occurrences which is important in weather derivatives, agriculture, hydrology, and prediction of drought and flood occurrences.

### 2014

Githui, T, Ngare P.  2014.  Education and Reseach. :1-6. Abstract

Old age dependency has become a major issue of concern to governments today. This is because a large number of retirees lack any form of regular income to sustain them in retirement. Kenya has one of the highest levels of old age dependency currently estimated at 56%. The purpose of this study was to establish the impact of financial literacy on retirement planning in the informal sector in Kenya. The study found that financial literacy remains low in Kenya. Financial literacy was found to have a positive impact on retirement planning; however the results indicate that other factors such as income levels, age, marital status and level of education are also strongly related to retirement planning. Gender was found to have no impact on retirement planning. The study established that the probability of a financially illiterate person having no retirement planning is significantly high calling for increased investment in financial literacy programs to reverse the trend. The study recommends the development of a curriculum on financial education and pension education in middle level and higher learning institutions as well as community pension awareness programs such as road-shows and aggressive advertising campaigns to enlighten the people on importance of retirement planning

Kweyu, M, Ngare P.  2014.  International Journal of Emerging Trends in Economics and Management Sciences. 5(1) Abstract

Mobile banking service, M-Shwari, allows users to save, earn interest and borrow loan over a short period of time using their mobile phones. The service has a potential to spur economic growth if consumers could understand the concept, its' benefits and adopts it. In our study, we investigated factors that influence the adoption of mobile banking services in Kenya. In particular we have shown empirically that the influence of the intervening demographic factors and the consumer perception may have differential impact in emerging market as compared to developed market situations. We extracted and grouped factors that were perceived by the clients as important in adoption of mobile banking. We then tested if the differences in perceptions on some of the factors extracted by exploratory factor analysis significantly differ between gender categories. The results indicated that there was no significant difference in the perception of ease of use and risk of use between genders in the decision to adopt mobile banking service in emerging market. The findings of our study will therefore provide the financial industry with a better understanding of the factors underlying consumer adoption of mobile banking services and help them formulate marketing and promotional strategies for mobile banking services.

J.Ngalawa, Ngare P.  2014.  Journal of economics and finance. 4(1):11-21. Abstract

We show empirically that bank's exposure to interest rate risk or income gap determines the
structure of the balance sheet. In particular, we show that in Kenya, commercial banks typically
retain a large exposure to interest rates that can be predicted through the income gap. We also
establish the sensitivity of income gaps to market interest rates as determined by the Central Bank
of Kenya (CBK) through treasury instruments. Quantitatively, a 200 basis point change in CBK
rates would lead to a change of net income equivalent to 0.4% of total assets of the bank.

### 2013

Ngare, P.  2013.  Under review.

### 2012

Ngare, P.  2012.  Applied Mathematical Sciences. 6(47):2315-2326.

### 2011

P.Ngare, Leobacher G.  2011.  Applied Mathematical Finance. 18(1):71-91.

### 2010

Ngare, P.  2010.  , Linz- Austria: University of Linz