scholarly journals Emergent volatility in asset markets with heterogeneous agents

2001 ◽  
Vol 6 (3) ◽  
pp. 171-180 ◽  
Author(s):  
Honggang Li ◽  
J. Barkley Rosser
Keyword(s):  
Heterogeneous Agents ◽  
Moving Average ◽  
Asset Price ◽  
Market Price ◽  
Switching Behavior ◽  
Asset Markets ◽  
Technical Trading Rules ◽  
Market Participants ◽  
Fundamental Value ◽  
Discrete Formulation

This paper examines the emergence of complex volatility in dynamic asset markets when there are heterogeneous agents. A discrete formulation is studied with two categories of market participants, fundamentalist traders who buy when the asset price is below the fundamental value and sell when it is above and noise traders who use moving average technical trading rules that can lead them to chase trends. Agents switch from one type of strategy to the other according to relative returns. A variety of outcomes are studied using numerical simulation, including variation of market price responsiveness to changes in excess demand, in switching behavior, and the introduction of noise. Bifurcation analysis of certain parameters is presented.

scholarly journals Leaning against the Bubble: Central Bank Intervention in Walrasian Asset Markets

Risks ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 214
Author(s):  
Chia-Lin Chang ◽  
Jukka Ilomäki ◽  
Hannu Laurila
Keyword(s):  
Central Bank ◽  
Asset Price ◽  
Market Price ◽  
Market Model ◽  
Asset Markets ◽  
Central Bank Intervention ◽  
Risky Assets ◽  
Automatic Stabilizer ◽  
Negative Effect ◽  
Prediction Coefficient

The paper presents a two-period Walrasian financial market model composed of informed and uninformed rational investors, and noise traders. The rational investors maximize second period consumption utility from the payoffs of trading risk-free holdings to risky assets in the first period. The central bank reacts directly to asset price movements by selling or buying assets to stabilize the market price. It is found that the intervention makes the risky asset’s market price per share less sensitive to information shocks, which presses the market price towards its average price thus reducing price variance. The informed investors’ prediction coefficient remains unaffected, but that of the uninformed investors is magnified, which cancels out the negative effect on shock sensitivity thus keeping the expected value of the risky asset’s dividend constant. Finally, the introduction of the policy rule does not affect rational investors’ risk per share. A general conclusion is that the central bank’s policy can be regarded as an effective automatic stabilizer of financial markets.

scholarly journals Stochastic sensitivity of bull and bear states

2021 ◽  
Author(s):  
Jochen Jungeilges ◽  
Elena Maklakova ◽  
Tatyana Perevalova
Keyword(s):  
Additive Noise ◽  
Asset Price ◽  
Market Model ◽  
Asset Market ◽  
Stochastic Version ◽  
Market Participants ◽  
Price Process ◽  
Stochastic Sensitivity ◽  
Stable Equilibria ◽  
Parametric Noise

AbstractWe study the price dynamics generated by a stochastic version of a Day–Huang type asset market model with heterogenous, interacting market participants. To facilitate the analysis, we introduce a methodology that allows us to assess the consequences of changes in uncertainty on the dynamics of an asset price process close to stable equilibria. In particular, we focus on noise-induced transitions between bull and bear states of the market under additive as well as parametric noise. Our results are obtained by combining the stochastic sensitivity function (SSF) approach, a mixture of analytical and numerical techniques, due to Mil’shtein and Ryashko (1995) with concepts and techniques from the study of non-smooth 1D maps. We find that the stochastic sensitivity of the respective bull and bear equilibria in the presence of additive noise is higher than under parametric noise. Thus, recurrent transitions are likely to be observed already for relatively low intensities of additive noise.

scholarly journals Market sentiment and heterogeneous agents in an evolutive financial model

2021 ◽  
Author(s):  
F. Cavalli ◽  
A. Naimzada ◽  
N. Pecora ◽  
M. Pireddu
Keyword(s):  
Time Series ◽  
Heterogeneous Agents ◽  
Financial Time Series ◽  
Financial Model ◽  
Agent Behavior ◽  
Market Sentiment ◽  
Evolutionary Selection ◽  
Animal Spirits ◽  
Return Distributions ◽  
Fundamental Value

AbstractWe study a financial market populated by heterogeneous agents, whose decisions are driven by “animal spirits”. Each agent may have either correct, optimistic or pessimistic beliefs about the fundamental value, which can change from time to time based on an evolutionary mechanism. The evolutionary selection of beliefs depends on a weighted evaluation of the general market sentiment perceived by the agents and on a profitability measure of the existent strategies. As the relevance given to the sentiment index increases, a herding phenomenon in agent behavior may occur and animal spirits can drive the market toward polarized economic regimes, which coexist and are characterized by persistent high or low levels of optimism and pessimism. This conduct is detectable from agents polarized shares and beliefs, which in turn influence the price level. Such polarized regimes can consist in stable steady states or can be characterized by endogenous dynamics, generating persistent alternating waves of optimism and pessimism, as well as return distributions displaying the typical features of financial time series, such as fat tails, excess volatility and multifractality. Moreover, we show that if the sentiment has no or low relevance on belief selection, those stylized facts are abated or are missing from the simulated time series.

scholarly journals Machine learning applied in the stock market through the Moving Average Convergence Divergence (MACD) indicator

2020 ◽  
Vol 17 (4) ◽  
pp. 44-60
Author(s):  
Alberto Antonio Agudelo Aguirre ◽  
Ricardo Alfredo Rojas Medina ◽  
Néstor Darío Duque Méndez
Keyword(s):  
Machine Learning ◽  
Genetic Algorithms ◽  
Stock Market ◽  
Moving Average ◽  
Asset Price ◽  
Technical Analysis ◽  
Investment Strategies ◽  
Historical Data Analysis ◽  
Financial Asset Returns ◽  
Technical Indicator

The implementation of tools such as Genetic Algorithms has not been exploited for asset price prediction despite their power, robustness, and potential application in the stock market. This paper aims to fill the gap existing in the literature on the use of Genetic Algorithms for predicting asset pricing of investment strategies into stock markets and investigate its advantages over its peers Buy & Hold and traditional technical analysis. The Genetic Algorithms strategy applied to the MACD was carried out in two different validation periods and sought to optimize the parameters that generate the buy-sell signals. The performance between the machine learning-based approach, technical analysis with the MACD and B&H was compared. The results suggest that it is possible to find optimal values of the technical indicator parameters that result in a higher return on investment through Genetic Algorithms, beating the traditional technical analysis and B&H by around 4%. This study offers a new insight for practitioners, traders, and finance researchers to take advantage of Genetic Algorithms for trading rules application in forecasting financial asset returns under a more efficient and robust methodology based on historical data analysis.

scholarly journals An Experimental Test of the Lucas Asset Pricing Model

2018 ◽  
Vol 86 (2) ◽  
pp. 627-667 ◽  
Author(s):  
Sean Crockett ◽  
John Duffy ◽  
Yehuda Izhakian
Keyword(s):  
Asset Pricing ◽  
Asset Price ◽  
Consumption Smoothing ◽  
Asset Price Bubbles ◽  
Price Bubbles ◽  
Fundamental Value ◽  
Experimental Treatments ◽  
Marginal Returns ◽  
Dynamic Asset Pricing ◽  
Fundamental Price

Abstract We implement a dynamic asset pricing experiment in the spirit of Lucas (1978) with storable assets and non-storable cash. In the first treatment, we impose diminishing marginal returns to cash to incentivize consumption smoothing across periods. We find that subjects use the asset to smooth consumption, although the asset trades at a discount relative to the risk-neutral fundamental price. This under-pricing is a departure from the asset price “bubbles” observed in the large experimental asset pricing literature originating with Smith et al. (1988) and can be rationalized by considering subjects’ risk aversion with respect to uncertain money earnings. In a second treatment, with no induced motivation for trade à la the Smith et al. design, we find that the asset trades at a premium relative to its expected value and that shareholdings are highly concentrated. Elimination of asset price uncertainty in additional experimental treatments serves to reinforce the same observations, and suggests that speculative behaviour explains the departure of prices from fundamental value in the absence of a consumption-smoothing motive for asset trades.

Monetary Policy and Asset Price Gap Signal Technology in a New Keynesian Framework

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Alexander Mislin
Keyword(s):  
Inflation Rate ◽  
Asset Price ◽  
New Keynesian ◽  
Adjustment Process ◽  
Keynesian Model ◽  
Nominal Rate ◽  
Dynamic Stochastic ◽  
The Difference ◽  
Fundamental Value ◽  
Output Gaps

Abstract This article develops a New Keynesian model in which the inflation rate depends on the present value of future output gaps and asset prices gaps. The latter follows a price adjustment process. These asset price gaps are driven by ‛asset price gap signal technology’, a measure of exponentially distributed asset price gaps with a signalling mechanism. Within a dynamic stochastic optimisation approach, I identify a policy rule for the central bank in which the asset price gap the difference between the actual asset price at time t to its fundamental value plays a crucial role in determining the nominal rate of interest.

Testing Technical Trading Rules: Evidence from SAARC Countries

2018 ◽  
Vol 1 ◽  
pp. 1-36
Author(s):  
Faisal Anees ◽  
Shujahat Haider Hashmi ◽  
Muhammad Asad
Keyword(s):  
Historical Data ◽  
Moving Average ◽  
Technical Analysis ◽  
Moving Averages ◽  
Short Term ◽  
Technical Trading Rules ◽  
Average Rule ◽  
Data Representative ◽  
Simple Average

Technical analysis is widely accepted tool in professional place which is frequently used for investment decisions. Technical analysis beliefs that there exist patterns and trends and by capturing trends and patterns one can bless with above average profits. We test two technical strategies: Moving averages and Trading Range to question, either these techniques can yield profitable returns with the help of historical data. Representative daily indices of Four countries namely Pakistan, India, Srilanka, Bangladesh ranging from 1997 to 2011 have been examined. In case of Moving Average Rule, both simple and exponential averages have been examined to test eleven different short term and long term rules with and without band condition. Our results delivered that buy signals generate consistent above average returns for the all sub periods and sell signals generate lower returns than the normal returns. Intriguing observation is that Exponential average generates higher returns than the Simple Average. The results of Trading Range Break strategy are parallel with Moving average Method. However, Trading Range Strategy found not to give higher average higher return when compared with Moving Averages Rules and degree of volatility in returns is higher when compared with moving Average rule. In attempt to conclude, there exist patterns and trends that yield above average and below average returns which justify the validity of technical analysis.

Are share prices of Gulf corporate council banks predictable? A time-series analysis

2020 ◽  
Vol 21 (1) ◽  
pp. 9-28
Author(s):  
Hesham I. Almujamed
Keyword(s):  
Moving Average ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Accounting Disclosure ◽  
Content Type ◽  
Share Prices ◽  
Market Participants ◽  
Short And Long Term ◽  
Future Evaluation

Purpose This research aimed to evaluate the predictability of moving-average strategies and examined the validity of the weak form of the efficient market hypothesis (EMH) for securities of banks listed in the Gulf Cooperation Council (GCC) stock markets of Bahrain, Kuwait, Qatar and Saudi Arabia. Design/methodology/approach Several statistical analyses and eight moving-average rules were employed where buy and sell signals were produced by comparing a security price’s short- and long-term moving averages. The study covered the daily closing share prices of 40 GCC-listed banks over the 18-year period ending 31 December 2017. Findings The results suggest that securities of banks in the GCC were not weak-form efficient because share prices were predictable. Investors who traded using moving-average strategies could generate higher profits. Analysis of variance found that securities of Kuwaiti banks were the most efficiently priced. Practical implications The findings supported the idea that profitability depended on the moving-average rules and country chosen. Transaction costs did not affect the returns obtained using different trading rules. Originality/value This work facilitates future evaluation of accounting disclosure environments as well as the market efficiency and the performance of securities in the GCC countries. The performance of moving average rules among representative countries that share similar characteristics was analyzed. Different market participants, including investors, analysts and regulators, can benefit from this study for decision-making. These results suggest that new regulations might be drafted that would improve the timeliness of accounting information and the banks’ level of efficiency.

Profitability of Trading Strategies Before and During the Greek Crisis: An Empirical Study.

2017 ◽  
Vol 11 (1) ◽  
pp. 1-26
Author(s):  
Efstathios Xanthopoulos ◽  
Konstantinos Aravossis ◽  
Spyros Papathanasiou
Keyword(s):  
Stock Exchange ◽  
Statistical Tests ◽  
Moving Average ◽  
Efficient Market Hypothesis ◽  
Trading Strategies ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Greek Crisis ◽  
Athens Stock Exchange

This paper investigates the profitability of technical trading rules in the Athens Stock Exchange (ASE), utilizing the FTSE Large Capitalization index over the seven-year period 2005-2012, which was before and during the Greek crisis. The technical rules that will be explored are the simple moving average, the envelope (parallel bands) and the slope (regression). We compare technical trading strategies in the spirit of Brock, Lakonishok, and LeBaron (1992), employing traditional t-test and Bootstrap methodology under the Random Walk with drift, AR(1) and GARCH(1,1) models. We enrich our analysis via Fourier analysis technique (FFT) and more statistical tests. The results provide strong evidence on the profitability of the examined technical trading rules, even during recession period (2009-2012), and contradict the Efficient Market Hypothesis.

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