Rossitsa Yalamova

• Professor (Associate) at University of Lethbridge

This paper explores the dynamic nature of financial markets through the lens of complex adaptive systems (CAS) theory, aiming to provide a comprehensive understanding of how financial markets deviate from the Efficient Market Hypothesis in extreme events such as bubbles and crashes. Traditional economic models often struggle to capture the intricat...

We review various alternative sustainability strategies for combating climate change as goal posts for meeting CO2 reduction targets towards zero net economy periodically have to be replaced. Research on policy success in reducing CO2 emissions through taxation and emission pricing/trading in various countries is analyzed to provide insight for pol...

Researchers from multiple disciplines have tried to understand the mechanism of stock market crashes. Precursory patterns before crashes agree with various empirical studies published by econophysicists, namely the prolific work of Didier Sornette. We intend to add more empirical evidence of synchronization of trading and demonstrate the prospect o...

The goal is to reveal scale-dependent topology of the network structure of stock market participants. The correlation structure of stock price series reveals the correlation network between traders. The partition decoupling method reveals the topological structure. The relation of the structural organization to dynamical complexity involves synchro...

The goal is to reveal scale-dependent topology of the network structure of stock market participants. The correlation structure of stock price series reveals the correlation network between traders. The partition decoupling method reveals the topological structure. The relation of the structural organization to dynamical complexity involves synchro...

Researchers from multiple disciplines have tried to understand the mechanism of stock market crashes. Precursory patterns before crashes agree with various empirical studies published by econophysicists, namely the prolific work of Didier Sornette. We intend to add more empirical evidence of synchronization of trading and demonstrate the prospect o...

We examine the effects of the 2008 financial crisis on the cross-market efficiency of the Hong Kong and Shanghai stock markets. Our results show a sharp decline in the cross-market efficiency during the financial crisis. We investigate whether this is due to lower internal market efficiency or higher market co-movement. The results show no evidence...

We test whether “detrended fluctuation analysis” (DFA)—an econophysics method—identifies the transition from efficient-market trading to herding behavior and the rise of the NASDAQ dot.com stock market bubble. DFA divides a time series into “segments” of varying lengths and then tests whether power-law distributions exist within the segments. A pow...

Putting a price on carbon emissions has, in recent years, emerged as the single most promising component of any combination of strategies necessary to mitigate climate change, and is an attempt at correcting externality-omissions in cost calculations within capitalist economic frameworks. Our study examines some design alternatives for such a prici...

The objective of this research is to find empirical evidence of self-organization and bubble build up in the stock market preceding crashes. Nonlinear methods will be used to detect interdependent trading behavior and propose regulatory mechanism that will break the synchronization of trading and bring the market back to efficiency. We will propose...

Mathematical descriptions of financial markets with respect to the efficient market hypothesis (EMH) and fractal finance are now equally robust but EMH still dominates. EMH and other current paradigms are extended to accommodate situations having higher information complexity and interactions coupled with positive feedback. The “herding behavior” l...

Firm performance and resource-based theory: an application with DEA

A heuristic approach to explaining of the Black-Scholes option pricing model in undergraduate classes is described. The approach draws upon the method of protocol analysis to encourage students tòthink aloud' so that their mental models can be surfaced. It also relies upon extensive visualizations to communicate relationships that are otherwise ina...

The multifractal spectrum calculated with wavelet transform modulus maxima (WTMM) provides information on the higher moments of market returns distribution and the multiplicative cascade of volatilities. This paper applies a wavelet based methodology for calculation of the multifractal spectrum of financial time series. WTMM methodology provides a...

The market risk of a portfolio calculated at different scales (time horison) improves portfolio risk measure accuracy. The multiscale Capital Asset Pricing Model test uses wavelets to perform multiple scale analysis in one step. Wavelet methods measure risk at different scales and the flow of volatility from one scale to the other. This paper tests...

The financial markets have been shown to be similar to complex dy-namical systems (Johansen et al., 2000). Complex dynamics may lead to chaos. Lovejoy and Schetzer (1999) argue chaos allows for the presence of scale invariance, e.g. multifractals produced in cascade processes. Mul-tifractal nature of stock prices leads to volatility clustering (con...

This paper argues for the superiority of multifractal over ARCH methods where the objective is to understand market microstructure based on accurate volatility modeling. The paper examines the multifractality of index price series on daily data of Nikkei 225, All Ordinaries, Hang Seng, KLSE Composite and Straits Times Index. Wavelets, short form wa...

The multifractal model of asset returns captures the volatility persistence of many financial time series. Its multifractal spectrum computed from wavelet modulus maxima lines provides the spectrum of irregularities in the distribution of market returns over time and thereby of the kind of uncertainty or randomness in a particular market. Changes i...

Banking is one of the most regulated industries. The central role of banks in the financial intermediation system necessitates international effort to adopt common bank capital standards. Bank capital adequacy has been a subject of interest, especially during economic downturn when bank failures further destabilize the financial system. This paper...

The Multifractal Model of Asset Returns (Mandelbrot et al. 1997) incorporates the thick tails and volatility persistence exhibited by many financial time series. The multifractal spectrum calculated with wavelet transform modulus maxima provides information on the higher moments of market returns distribution and the multiplicative cascade of volat...

We attempt empirical detection and characterization of power laws in financial time series. Fractional Brownian motion is defined. After testing for multifractality we calculate the multifractal spectrum of the series. The multifractal nature of stock prices leads to volatility clus- tering (conditional heteroscedasticity) and long memory (slowly d...

We use the Tisean C++ package to quantify chaos around Black Monday (crash of 1987). We calculate Lyapunov exponents following the algorithm proposed by Rosenstein et al (1993). A positive Lyapunov exponent correlates with chaos. The negative exponent during the time period centered around Black Monday suggests a lack of chaos surrounding the finan...

Thesis (Ph. D.)--Kent State University, 2003. Includes bibliographical references (leaves 98-104).