Asset Price Dynamics Research Articles

Crowded Trades, Market Clustering, and Price Instability.

Crowded trades by similarly trading peers influence the dynamics of asset prices, possibly creating systemic risk. We propose a market clustering measure using granular trading data. For each stock, the clustering measure captures the degree of trading overlap among any two investors in that stock, based on a comparison with the expected crowding in a null model where trades are maximally random while still respecting the empirical heterogeneity of both stocks and investors. We investigate the effect of crowded trades on stock price stability and present evidence that market clustering has a causal effect on the properties of the tails of the stock return distribution, particularly the positive tail, even after controlling for commonly considered risk drivers. Reduced investor pool diversity could thus negatively affect stock price stability.

A stylized macro-model with interacting real, monetary and stock markets

We propose a model economy consisting of interdependent real, monetary and stock markets. The money market is influenced by the real one through a standard LM equation. Private expenditures depend on stock prices, which in turn are affected by interest rates and real profits, as these contribute to determine the participation level in the stock market. An evolutionary mechanism regulates agents’ participation in the stock market on the basis of a fitness measure that depends on the comparison between the stock return and the interest rate. Relying on analytical investigations complemented by numerical simulations, we study the economically relevant static and dynamic properties of the equilibrium, identifying the possible sources of instabilities and the channels through which they spread across markets. We aim at understanding what micro- and macro-factors affect the dynamics and, at the same time, how the dynamics of asset prices, which are ultimately influenced by the money market, behave over the business cycle. Starting from isolated markets, we show the effect of increasing the market interdependence on the national income, the stock price and the share of agents that participate in the stock market at the equilibrium. Moreover, we investigate the stabilizing/destabilizing role of market integration and the possible emergence of out-of-equilibrium dynamics.

Dynamic Asset Pricing with Interactions between Short-Sale and Borrowing Constraints

Abstract This paper studies the joint effect of borrowing and short-sale constraints under heterogeneous beliefs and risk aversions. Although the constraints never simultaneously bind in equilibrium, interesting economics emerge in the anticipatory effects of potentially future binding constraints. In particular, the risk-free rate and Sharpe ratio experience endogenous jumps at a critical state, where two equilibria coexist. Moreover, a short-sale ban can lead to a lower stock price and higher volatility depending on the relative tightness between the constraints, and tightening the borrowing constraint during a short-sale ban can also make returns more volatile. (JEL G11, G12)

Quality minus junk factor: A study on asset pricing dynamics in the equity market of Pakistan

This study examines the role of quality minus junk factor in explaining cross-sectional differences in stock returns for the equity market of Pakistan. A new factor quality minus junk has been added to the existing Fama & French three factor model (1993) as a fourth factor to check whether it is priced as a risk factor. The study also compares the explanatory power of the newly proposed model with the existing single-factor Capital Asset Pricing Model (CAPM) and Fama & French three factor model (1993). A high quality data set of 70 non-financial firms listed on the PSX is employed as a sample for the period 2008- 2016. Results show that quality minus junk factor is priced in the equity market of Pakistan and this newly proposed four factor model has significantly higher explanatory power than the existing three factor model.

FINANCIAL RISKS OF BROKER’S ACTIVITY

Changes in the Ukrainian economy and the development of the financial market are of interest in solving the problems associated with brokerage activities. These issues are of particular relevance in connection with the increased attention of the state to investment activity and interest in the growth of financial literacy of the population. One of the important tasks in this context is the study of financial risks of professional participants in stock markets. As the dynamics of asset prices in the financial markets have a significant range of risks for both the investor and the broker. And if the investor’s job is to choose the most optimal portfolio of assets and control over possible losses, then the broker assumes the risks of trading decisions of a set of clients. In addition, he should take into account the risks of liquidity and voluntariness of a set of customer positions.
 Today, Ukraine has no single approach to the definition and classification of financial risks of brokerage activities, and therefore this study is intended to analyze the types of financial risks of brokerage companies in the stock market and to clarify certain concepts of types of financial risks.
 The article identifies sources and causes of financial risks of brokerage companies. The interpretation of the concept of «financial risk» by domestic and foreign scientists is researched. Author’s definition of financial risk for the broker is provided. The questions of classification and grouping of financial risks of brokerage companies that arise in the process of activity in the stock market, which allow reducing investor losses and increase the efficiency of management in an unstable market and increase the income of brokerage mines from the provision of services, are considered.
 It is established that the most significant financial risks of brokerage activity are the risks of investor behavior, investment risks and risks of marginal lending, and the determining financial risks for a brokerage company are the risks associated with the behavior of the investor and the investment of capital in financial assets.
 The study of the issues covered by this article will provide an opportunity to contribute to increasing the financial stability of brokerage companies and their investors and will contribute to the improvement of the financial system of the country.

An extended regularized Kalman filter based on Genetic Algorithm: Application to dynamic asset pricing models

This study presents an extended version of the regularized Kalman filter for the application of dynamic asset pricing models, which deploy the Genetic Algorithm to solve a convex optimization problem involving both ℓ1− and ℓ2− based regularization terms in the correction equation. Our approach, namely GA-ErgKF, is firstly verified on synthetic data and then employed in a concrete financial case dealing with U.S. industry portfolios’ analysis over the period from July 1963 to December 2018. The results indicate that the GA-ErgKF algorithm is capable of tracking the unobserved time-varying parameters, even under the mixture noise pattern that contains both the Gaussian noise and sparse noise. Besides, this approach delivers superior performance over the alternative methods, thereby leading to better levels of out-of-sample explanatory power and hedging performance, especially when the asset returns fluctuate wildly. We further explore the microstructures of U.S. industries in the circumstance of a dynamic six-factor model calculated by the GA-ErgKF algorithm. It turns out that the microstructures differ noticeably between the volatile and steady industries, in terms of the density (also distribution) of the sparse noise, the volatilities of the abnormal returns and risk exposures, and the impact of risk factors. In addition, our approach captures fluctuations of the estimations under the economic and financial distress and identifies long-term stable profitability and investment patterns in the Food Products and Consumer Goods sectors.

Bank Runs, Fragility, and Credit Easing

We present a tractable dynamic macroeconomic model of self-fulfilling bank runs. A bank is vulnerable to a run when a loss of investors' confidence triggers deposit withdrawals and leads the bank to default on its obligations. We analytically characterize how the vulnerability of an individual bank depends on macroeconomic aggregates and how the number of banks facing a run affects macroeconomic aggregates in turn. In general equilibrium, runs can be partial or complete, depending on aggregate leverage and the dynamics of asset prices. Our normative analysis shows that the effectiveness of credit easing and its welfare implications depend on whether a financial crisis is driven by fundamentals or by self-fulfilling runs.

Оцінювання земельних активів України банками Російської імперії на початку ХХ століття

The start of the land market in Ukraine began on July 1, 2021, which opened new opportunities for the development of the national economy. At the same time, the issue of assessment of formation of land assets remained insufficiently provided with appropriate mechanisms for the transparency of this market and the establishment of fair land prices. An important component of the formation of a fair valuation of land assets are the previous databases on their sales prices for previous time periods. We do not have such data due to the lack of a land market in Ukraine during the administrative-command system of economic management, being part of the USSR. Therefore, the only systematized databases for the assessment of land assets are studies conducted by the Ministry of the Russian Empire in the early 20th century. This article aims to study the level and dynamics of land asset prices using the historical experience of valuation of Ukrainian land assets by banks of the Russian Empire in the early twentieth century. The article separates and groups data on the valuation of land assets in the Ukrainian provinces, which were part of the Russian Empire. A retrospective analysis of the valuation of land assets in terms of individual regions of Ukraine that were part of the Russian Empire was performed on the basis of selected data. The necessity and importance of today's use of historical experience of valuations of land asset in Ukraine are substantiated in connection with the introduction of the land market. Using the index of change in the value of gold, comparative prices transfer of land assets from the early twentieth century at today's comparable prices. The obtained level of prices for land assets has the prospect of being used as a base during the organization of land auctions to form a fair price for land in Ukraine.

Recursive equilibria in dynamic economies with bounded rationality

This paper provides a general framework to model bounded rationality in dynamic stochastic general equilibrium models with infinitely lived heterogeneous agents. A boundedly rational agent is associated with an information set $I$ and an extra parameter $\epsilon$, which can be interpreted as the ``level of irrationality''. To make decisions, the boundedly rational agent forms a belief of a stationary joint distribution of the exogenous and endogenous variables and uses the marginal distribution (conditional on $I$) to form forecasts. If the equilibrium distribution stays within $\epsilon$ of the forecasted next-period distribution, the agent would consider it as $\epsilon$-stationary. In equilibrium, each agent maximizes utility with an $\epsilon$-stationary belief and markets clear. The main theorem of this paper shows that for any strictly positive $\epsilon$, a recursive equilibrium exists. With a quantifiable ``level of irrationality'', the model incorporates many behavioral economics models as well as rational-expectations models with computational approximations into a unified framework. An illustration example is presented to show that the boundedly rational recursive equilibrium may substantially enrich the asset pricing dynamics of the rational-expectations model even for small $\epsilon$.

Optimal Dynamic Futures Portfolio Under a Multifactor Gaussian Framework

We study the problem of dynamically trading futures in continuous time under a multifactor Gaussian framework. We present a utility maximization approach to determine the optimal futures trading strategy. This leads to the explicit solution to the Hamilton-Jacobi-Bellman (HJB) equations. We apply our stochastic framework to two-factor models, namely, the Schwartz model and Central Tendency Ornstein-Uhlenbeck (CTOU) model. We also develop a multiscale CTOU model, which has a fast mean-reverting and a slow mean-reverting factor in the spot asset price dynamics. Numerical examples are provided to illustrate the investor's optimal positions for different futures portfolios.

Speculative behavior and chaotic asset price dynamics: On the emergence of a bandcount accretion bifurcation structure

<p style='text-indent:20px;'>We study a simple financial market model with interacting chartists and fundamentalists that may give rise to multiband chaotic attractors. In particular, asset prices fluctuate erratically around their fundamental values, displaying a significant bull and bear market behavior. An in-depth analytical and numerical study of our model furthermore reveals the emergence of a new bifurcation structure, a phenomenon that we call a bandcount accretion bifurcation structure. The latter consists of regions associated with chaotic dynamics only, the boundaries of which are not defined by homoclinic bifurcations, but mainly by contact bifurcations of particular type where two distinct critical points of certain ranks coincide.</p>

Ambiguity in a Pandemic Recession, Asset Prices, and Lockdown Policy

Using an asset pricing model of a multi-sector production economy with pandemic disasters, we explain the average stock price boom and significant cross-sectional variation of stock returns in the US and Japan during the COVID-19 pandemic recession. Two features of the pandemic, ambiguity and sector-specific shocks, are crucial determinants of the unusual asset price dynamics. Extending the model, we analyze the welfare effects of lockdown policies during pandemics for heterogeneous households and obtain the following results. Enforcing a lockdown improves the welfare of the asset-holders and the household working in the sector with positive sector-specific shocks. A Pareto optimal lockdown policy controls the tightness of the lockdown so as to maximize the welfare of the household working in the sector with negative sector- specific shocks.

State Space Model to Detect Cycles in Heterogeneous Agents Models

We propose an empirical test to depict possible endogenous cycles within Heterogeneous Agent Models (HAMs). We consider a 2-type HAM into a standard small-scale dynamic asset pricing framework. On the one hand, fundamentalists base their expectations on the deviation of fundamental value from market price expecting a convergence between them. On the other hand, chartists, subject to self-fulling moods, consider the level of past prices and relate it to the fundamental value acting as contrarians. These pricing strategies, by their nature, cannot be directly observed but can cause the response of the observed data. For this reason, we consider the agents' beliefs as unobserved state components from which, through a state space model formulation, the heterogeneity of fundamentalist-chartist trader cycles can be mathematically derived and empirically tested. The model is estimated using the S&P500 index, for the period 1990-2020 at different time scales, specifically, daily, monthly, and quarterly.

Extrapolative Market Participation

This paper proposes a simple dynamic asset pricing model featuring extrapolative market participation by retail investors, that is, increased market participation following high returns in the stock market and high new participation growth (NPG). The model implies that extrapolative market participation induces asset bubbles and large trading volume and produces momentum and value effects simultaneously. More important, the model also implies that NPG positively predicts momentum strategy returns and negatively predicts value strategy returns. Using a composite measure for NPG, we find empirical support for these predictions. The momentum effect is 1.96% per month following high NPG and only 0.51% following low NPG, whereas the value effect is -0.10% per month following high NPG and 0.68% following low NPG. A similar, albeit weaker, pattern also holds for the time-series momentum and value effect.

Cryptocurrency, Mining Pools' Concentration, and Asset Prices

This paper studies the asset pricing implications of mining pools' concentration. We incorporate two features specific to cryptocurrencies into a traditional dynamic asset pricing model. First, we introduce the technological arms race between mining pools, and second, the interdependency between the cryptocurrency price and its transactional benefits, which we call services. Our continuous-time setup admits precise closed-form expressions. We find that an increase in mining pools' concentration decreases cryptocurrency price and increases its volatility, and the effects are amplified when there is more interdependency between the cryptocurrency price and its services. Empirical evidence from Bitcoin supports our model's predictions.

Pricing variance swaps under hybrid CEV and stochastic volatility

In this paper, we consider the problem of pricing a variance swap whose underlying asset price dynamics is modeled under a hybrid framework of constant elasticity of variance and stochastic volatility (SVCEV). Applying the multi-scale asymptotic analysis approach, we obtain a semi-closed form approximation of the fair continuous variance strike. We conduct numerical experiments by applying this approximation formula to calculate the square root of the fair continuous variance strike with different values of parameters. The market data of S&P 500 options are used to obtain calibrations of the SVCEV model, and then the estimated parameters are further used to compute the values of the square root of fair continuous variance strike. In addition, we also analyze and compare the performance of the CEV model, the SVCEV model and the Heston stochastic volatility model.

VALUATION OF EUROPEAN PUT OPTION BY USING THE QUADRATURE METHOD UNDER THE VARIANCE GAMMA PROCESS

Dynamic asset pricing model uses the Geometric Brownian Motion process. The Black-Scholes model known as standard model to price European option based on the assumption that underlying asset prices dynamic follows that log returns of asset is normally distributed. In this paper, we introduce a new stochastic process called levy process for pricing options. In this paper, we use the quadrature method to solve a numerical example for pricing options in the Indian context. The illustrations used in this paper for pricing the European style option. We also try to develop the pricing formula for European put option by using put-call parity and check its relevancy on actual market data and observe some underlying phenomenon.

Nonlinear asset-price dynamics and stabilization policies

We first present a brief review of nonlinear asset-pricing models and contributions in which such models have been used as benchmarks to evaluate the effectiveness of a number of regulatory policy measures. We then illustrate the functioning of one particular asset-pricing model—the seminal framework by Brock and Hommes (J Econ Dyn Control 22:1235–1274, 1998)—and its possible stabilization via a central authority that seeks to counter the destabilizing trading behavior of speculators. Our paper underlines that tools from the field of nonlinear dynamical systems may foster our understanding of the functioning of asset markets, thereby enabling policymakers to design better trading environments in the future.

Likelihood-Based Dynamic Asset Pricing: Learning Time-Varying Risk Premia from Cross-Sectional Models

This paper proposes a new parametric approach to estimate linear factor pricing mod-els with time-varying risk premia. In contrast to recent contributions to the literature,the framework presented abstains from introducing instrument variables to describethe time variation of risk prices. Instead, time-varying risk prices and exposures followa recursive updating scheme constructed to reduce the one-step ahead prediction errorfrom a cross-sectional factor model at the current observation. This agnostic approachis particularly useful in situations where instrument variables are unavailable or of poorquality. Estimation and inference are done by likelihood maximization. A Monte Carlostudy compares the ability of the method to predict risk prices and returns to that ofa regression-based method that uses noisy signals from true risk price predictors. Ina realistic setting, the two approaches keep pace when the signal contains 80 percentcorrect information. An application to a macro-finance model of currency carry tradesillustrates the novel approach.

Asset price dynamics in a “bull and bear market”

We generalize an existing asset market model with heterogenous agents. In particular, we consider the case in which no-trade and low-trade intervals of chartists and fundamentalists respectively are not congruent. Thus we model chartist and fundamentalists who respond to asset prices in agent-specific neighborhoods around the fundamental value with different trade intensities. The resulting asset price dynamics is generated by a one-dimensional 5-piece linear map with discontinuities. Our analysis of this map focusses on coexisting price equilibria. Conditions for their existence and stability are determined analytically. By visualizing the results we allow for a basic bifurcation analysis in a 4-dimensional parameter space. According to our findings the extent of the disparity between the no-trade and low-intervals effects the existence of equilibria but not their stability.