Valuing the Future, Discounting in Random Environments: A Review

We address the process of discounting in random environments which allows to value the far future in economic terms. We review several approaches to the problem regarding different well-established stochastic market dynamics in the continuous-time context and include the Feynman-Kac approach. We also review the relation between bond pricing theory and discount and introduce the market price of risk and the risk neutral measures from an intuitive point of view devoid of excessive formalism. We provide the discount for each economic model and discuss their key results. We finally present a summary of our previous empirical studies on several countries of the long-run discount problem.

Relationship Between Selected Macroeconomic Variables and the Financial Performance of Investment Banks in Kenya

Currently, investment banks in Kenya are facing a lot of challenges due to persistence losses. However, the available studies are inadequate to aid investment banks in overcoming these challenges in Kenya due to mixed findings, resulting in rising uncertainty on equity investments’ performance, leading to massive losses among investment banks.  This study, therefore, sought to model the relationship between inflation, GDP, interest rates, exchange rates, and financial performance of investment banks. Arbitrage pricing theory, Modern portfolio theory as well as classical economic theory (flow-oriented model) was used. A causal research design was adopted. The study found that inflation has negative significant influence on financial performance of equity investments among investment banks in Kenya. Also, GDP has positive and significant influence on financial performance of equity investments among investment banks in Kenya. Interest rate was also found to have negative and significant influence on financial performance of equity investments among investment banks in Kenya. In addition, exchange rate has negative significant influence on financial performance of equity investments among investment banks in Kenya. The study therefore recommends any investor including financial investors to methodically analyze inflation trends and understand how it affects the company’s financial performance. Investors must also be in a position to predict the future concerning inflation changes.

Relationship Between Selected Macroeconomic Variables and the Financial Performance of Investment Banks in Kenya

Currently, investment banks in Kenya are facing a lot of challenges due to persistence losses. However, the available studies are inadequate to aid investment banks in overcoming these challenges in Kenya due to mixed findings, resulting in rising uncertainty on equity investments’ performance, leading to massive losses among investment banks.  This study, therefore, sought to model the relationship between inflation, GDP, interest rates, exchange rates, and financial performance of investment banks. Arbitrage pricing theory, Modern portfolio theory as well as classical economic theory (flow-oriented model) was used. A causal research design was adopted. The study found that inflation has negative significant influence on financial performance of equity investments among investment banks in Kenya. Also, GDP has positive and significant influence on financial performance of equity investments among investment banks in Kenya. Interest rate was also found to have negative and significant influence on financial performance of equity investments among investment banks in Kenya. In addition, exchange rate has negative significant influence on financial performance of equity investments among investment banks in Kenya. The study therefore recommends any investor including financial investors to methodically analyze inflation trends and understand how it affects the company’s financial performance. Investors must also be in a position to predict the future concerning inflation changes.

Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model

This paper tests a multi-factor asset pricing model that does not assume that the return’s beta coefficients are constants. This is done by estimating the generalized arbitrage pricing theory (GAPT) using price differences. An implication of the GAPT is that when using price differences instead of returns, the beta coefficients are constant. We employ the adaptive multi-factor (AMF) model to test the GAPT utilizing a Groupwise Interpretable Basis Selection (GIBS) algorithm to identify the relevant factors from among all traded exchange-traded funds. We compare the performance of the AMF model with the Fama–French 5-factor (FF5) model. For nearly all time periods less than six years, the beta coefficients are time-invariant for the AMF model, but not for the FF5 model. This implies that the AMF model with a rolling window (such as five years) is more consistent with realized asset returns than is the FF5 model.

Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative study in the Mexican Stock Exchange

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative in the Mexican stock exchange

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

Methodology for calculating risk factors and assessing the sensitivity of portfolio asset returns when investing in personnel

The authors previously proposed an economic and mathematical model of investing in personnel and also the algorithm for determining of risk-free and the size of non-market risks. The goals of the article are to develop the threat rates and risk sensitive search methods during engineering of investment portfolio through arbitrage pricing theory for investment in personnel to return on investment. Questions of risk evaluation when choosing assets to invest in human capital of a company are fully provided. The covariance structure of allocation of funds of risk-free part of investment portfoliois addressed, that helps to calculate covariance between return on assets and threat rates of investment patterns that is necessary to find factor betas of portfolio. Also, the matrix of budget sharpening is offered that shows the detail investment budgets risk-free pieces split for all assets having regard to risks. The elements got standard interpretation. Then there is the balance condition that is to implement the proof of calculation. Finally, the method of how to calculate and estimate them is given.