Algorithmic Models of Investor Behavior

2021 ◽  
Vol 1 (1) ◽  
pp. 1-29
Author(s):  
Andrew Lo ◽  
Alexander Remerov
Keyword(s):  
Behavioral Finance ◽  
Historical Data ◽  
Asset Returns ◽  
Investor Behavior ◽  
Investment Strategies ◽  
Investment Performance ◽  
Evolutionary Forces ◽  
Asset Class ◽  
Functional Forms ◽  
The Mean

We propose a heuristic approach to modeling investor behavior by simulating combinations of simpler systematic investment strategies associated with well-known behavioral biases—in functional forms motivated by an extensive review of the behavioral finance literature—using parameters calibrated from historical data. We compute the investment performance of these heuristics individually and in pairwise combinations using both simulated and historical asset-class returns. The mean-reversion or momentum nature of a heuristic can often explain its effect on performance, depending on whether asset returns are consistent with such dynamics. These algorithms show that seemingly irrational investor behavior may, in fact, have been shaped by evolutionary forces and can be effective in certain environments and maladaptive in others.

Model of Bias-Driven Trend Followers and Interaction with Manipulators

2017 ◽  
Vol 16 (02) ◽  
pp. 573-590
Author(s):  
Ke Liu ◽  
Kin Keung Lai ◽  
Jerome Yen ◽  
Qing Zhu
Keyword(s):  
Financial Markets ◽  
Behavioral Finance ◽  
Real Data ◽  
Investor Behavior ◽  
Individual Investors ◽  
Investment Performance ◽  
Behavioral Biases ◽  
The Common ◽  
And Performance ◽  
Manipulation Detection

Stock investors are not fully rational in trading and many behavioral biases that affect them. However, most of the literature on behavioral finance has put efforts only to explain empirical phenomena observed in financial markets; little attention has been paid to how individual investors’ trading performance is affected by behavioral biases. As against the common perception that behavioral biases are always detrimental to investment performance, we conjecture that these biases can sometimes yield better trading outcomes. Focusing on representativeness bias, conservatism and disposition effect, we construct a mathematical model in which the representative trend investor follows a Bayesian trading strategy based on an underlying Markov chain, switching beliefs between trending and mean-reversion. By this model, scenario analysis is undertaken to track investor behavior and performance under different patterns of market movements. Simulation results show the effect of biases on investor performance can sometimes be positive. Further, we investigate how manipulators could take advantage of investor biases to profit. The model’s potential for manipulation detection is demonstrated by real data of well-known manipulation cases.

scholarly journals “Ombro-Cabeça-Ombro”: Testando a Lucratividade do Padrão Gráfico de Análise Técnica no Mercado de Ações Brasileiro

2009 ◽  
Vol 7 (3) ◽  
pp. 265 ◽  
Author(s):  
Pedro Gabriel Boainain ◽  
Pedro L. Valls Pereira
Keyword(s):  
Null Hypothesis ◽  
Predictive Power ◽  
Historical Data ◽  
Future Price ◽  
Bootstrap Sample ◽  
Investment Strategies ◽  
Basic Form ◽  
Price Trend ◽  
Price Series ◽  
The Mean

Starting from an adapted version of Osler and Chang (1995) methodology, this article empirically evaluates the profitability of investment strategies based on identification of the Head and Shoulders chart pattern in the Brazilian stock market. For that purpose, several investment strategies conditioned by the identification of the Head and Shoulders pattern (in its basic and inverted forms) by a computer algorithm in daily price series of 30 stocks from January 1994 to January 2009 were defined. Confidence intervals consistent with the null hypothesis that no strategies with positive returns can be based only on historical data were constructed using the Bootstrap sample inference technique in order to test the predictive power of each strategy. More specifically, the mean returns obtained by each strategy when applied to the stock's price series were compared to those obtained by the same strategies when applied to 1.000 artificial price series -- for each stock -- generated in a parametric manner, by an E-GARCH, and in a nonparametric one. Overall, our results show that it is possible to create strategies conditioned by the occurrence of Head and Shoulders, with positive returns, which indicates that these patterns can capture from stock historical prices some signals about their future price trend that makes possible to create profitable strategies. Nevertheless, the same conclusions are not valid for the pattern in its inverted form and when the effects of taxes and transaction costs are considered, depending on their magnitude, neither in its basic form.

Commodity Exchange-Traded Funds

2018 ◽  
Author(s):  
Christopher Milliken
Keyword(s):  
Portfolio Diversification ◽  
Futures Contracts ◽  
Spot Price ◽  
Exchange Traded Funds ◽  
Investment Strategies ◽  
Regulatory Structure ◽  
Commodity Exchange ◽  
Asset Class ◽  
Exchange Traded Fund

Commodity exchange-traded funds (ETCs), which debuted in 2004, enable investors to access an asset class previously difficult or expensive to access. Although a small segment of the overall exchange-traded fund (ETF) universe, ETCs have grown in popularity with both speculators and investors looking for long-term portfolio diversification. Examples of the types of commodities that are now accessible through ETCs include gold, oil, and agricultural. The literature on ETCs is limited, but academic and industry work has centered on using futures contracts to replicate the performance of the underlying commodities spot price as well as the effect additional capital has had on the integrity of the futures market. This chapter covers this topic by reviewing the growth, investment strategies, and regulatory structure of ETCs as well as the underlying effects these funds have had on the underlying markets with which they engage.

scholarly journals Operating Rooms efficiency: leveraging data to improve management of elective surgery

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
C Quercioli ◽  
G A Carta ◽  
G Cevenini ◽  
G Messina ◽  
N Nante ◽  
...  
Keyword(s):  
Historical Data ◽  
Elective Surgery ◽  
District General Hospital ◽  
Operating Rooms ◽  
Accurate Estimation ◽  
Surgical Time ◽  
Accurate Analysis ◽  
Management Efficiency ◽  
Scheduling Model ◽  
The Mean

Abstract Background Careful scheduling of elective surgery Operating Rooms (ORs) is crucial for their efficient use, to avoid low/over utilization and staff overtime. Accurate estimation of procedures duration is essential to improve ORs scheduling. Therefore analysis of historical data about surgical times is fundamental to ORs management. We analyzed the effect, in a real setting, of an ORs scheduling model based on estimated optimum surgical time in improving ORs efficiency and decreasing the risk of overtime. Methods We studied all the 2014-2019 elective surgery sessions (3,758 sessions, 12,449 interventions) of a district general hospital in Siena's Province, Italy. The hospital had3 ORs open 5 days/week 08:00-14:00. Surgery specialties were general surgery, orthopedics, gynecology and urology. Based on a pilot study conducted in 2016, which estimated a 5 times greater risk of having an OR overtime for sessions with a surgical time (incision-suture)>200 minutes, from 2017 all the ORs were scheduled using a maximum surgical time of 200 minutes calculated summing the mean surgical times for intervention and surgeon (obtained from 2014-2016 data). We carried out multivariate logistic regression to calculate the probability of ORs overtime (of 15 and 30 minutes) for the periods 2014-2016 and 2017-2019adjusting for raw ORs utilization. Results The 2017-2019 risk of an OR overtime of 15 minutes decreased by 25% compared to the 2014-2016 period (OR = 0.75, 95%CI=0.618-0.902, p = 0.003); the risk of a OR overtime of 30 minutes decreased by 33% (OR = 0.67, 95%CI= 0.543-0.831, p < 0.001). Mean raw OR utilization increase from 62% to 66% (p < 0.001). Mean number of interventions per surgery sessions increased from 3.1 to 3.5 (p < 0.001). Conclusions This study has shown that an analysis of historical data and an estimate of the optimal surgical time per surgical session could be helpful to avoid both a low and excessive use of the ORs and therefore to increase the efficiency of the ORs. Key messages An accurate analysis of surgical procedures duration is crucial to optimize operating room utilization. A data-based approach can improve OR management efficiency without extra resources.

scholarly journals DETERMINANTS INFLUENCING PENSION FUND INVESTMENT PERFORMANCE IN KENYA

2018 ◽  
Vol 3 (1) ◽  
pp. 14
Author(s):  
Anthony Kyanesa Mutula ◽  
Dr. Assumptah Kagiri
Keyword(s):  
Pension Fund ◽  
Multiple Linear Regression Model ◽  
Target Population ◽  
Pension Funds ◽  
Primary Data ◽  
Investment Strategies ◽  
Investment Performance ◽  
Descriptive Research ◽  
Fund Investment ◽  
Regulation Compliance

Purpose: The purpose of the study was to investigate the determinants influencing pension fund investment performance in Kenya.Methodology: The study employed a descriptive research design. The study target population was all the 33 registered pension funds in Kenya, and the sample size was 66 senior employees involved in decision making. The study adopted a census approach and therefore data was collected from all the 33 registered pension funds. A questionnaire was used to collect primary data from the selected respondents. The data collected was analyzed using the statistical package for social sciences (SPSS) version 23.0. The software was used to produce frequencies, descriptive and inferential statistics which was used to derive generalizations and conclusions regarding the population. Multiple linear regression model was used to measure the relationship between the independent variables and the dependent variable. The study findings were presented using figures and tables.Results: The study findings revealed a positive and significant relationship between diversification decisions, management competency, investment strategies, regulation compliance and investment performance of pension funds in Kenya.Unique contribution to theory, practice and policy: The study recommended that the management of pension funds should establish a strong organization structure and policy implementation, which will enhance their portfolio composition; the firms should have highly competent management; should incorporate investment literacy and capability programs in their organizations; and should continue adhering to the set regulations.

scholarly journals Abnormal Portfolio Asset Allocation Model: Review

2020 ◽  
Vol 1 (1) ◽  
pp. 46-54
Author(s):  
Nurfadhlina Bt Abdul Halima ◽  
Dwi Susanti ◽  
Alit Kartiwa ◽  
Endang Soeryana Hasbullah
Keyword(s):  
Asset Allocation ◽  
Asset Returns ◽  
Higher Moments ◽  
Investment Portfolio ◽  
Allocation Model ◽  
Model Review ◽  
The Mean ◽  
Mean Variance ◽  
Skewness And Kurtosis ◽  
Normally Distributed

It has been widely studied how investors will allocate their assets to an investment when the return of assets is normally distributed. In this context usually, the problem of portfolio optimization is analyzed using mean-variance. When asset returns are not normally distributed, the mean-variance analysis may not be appropriate for selecting the optimum portfolio. This paper will examine the consequences of abnormalities in the process of allocating investment portfolio assets. Here will be shown how to adjust the mean-variance standard as a basic framework for asset allocation in cases where asset returns are not normally distributed. We will also discuss the application of the optimum strategies for this problem. Based on the results of literature studies, it can be concluded that the expected utility approximation involves averages, variances, skewness, and kurtosis, and can be extended to even higher moments.

scholarly journals Mapping similarities in temporal parking occupancy behavior based on city-wide parking meter data

2018 ◽  
Vol 1 ◽  
pp. 1-5
Author(s):  
Fabian Bock ◽  
Karen Xia ◽  
Monika Sester
Keyword(s):  
Similarity Measure ◽  
Historical Data ◽  
Parking Space ◽  
Number Of Clusters ◽  
Occupancy Patterns ◽  
Silhouette Index ◽  
The Mean ◽  
Occupancy Behavior ◽  
Maximum Occupancy ◽  
Repetitive Pattern

The search for a parking space is a severe and stressful problem for drivers in many cities. The provision of maps with parking space occupancy information assists drivers in avoiding the most crowded roads at certain times. Since parking occupancy reveals a repetitive pattern per day and per week, typical parking occupancy patterns can be extracted from historical data.<br> In this paper, we analyze city-wide parking meter data from Hannover, Germany, for a full year. We describe an approach of clustering these parking meters to reduce the complexity of this parking occupancy information and to reveal areas with similar parking behavior. The parking occupancy at every parking meter is derived from a timestamp of ticket payment and the validity period of the parking tickets. The similarity of the parking meters is computed as the mean-squared deviation of the average daily patterns in parking occupancy at the parking meters. Based on this similarity measure, a hierarchical clustering is applied. The number of clusters is determined with the Davies-Bouldin Index and the Silhouette Index.<br> Results show that, after extensive data cleansing, the clustering leads to three clusters representing typical parking occupancy day patterns. Those clusters differ mainly in the hour of the maximum occupancy. In addition, the lo-cations of parking meter clusters, computed only based on temporal similarity, also show clear spatial distinctions from other clusters.

scholarly journals Real estate as a portfolio risk diversifier

2016 ◽  
Vol 13 (2) ◽  
pp. 45-52
Author(s):  
Ahmad Etebari
Keyword(s):  
Real Estate ◽  
Portfolio Risk ◽  
Optimal Portfolios ◽  
Investment Performance ◽  
Optimization Framework ◽  
Expected Inflation ◽  
Common Stocks ◽  
Asset Class ◽  
The U.S ◽  
Return Data

This study provides evidence on the investment performance of real estate relative to bonds and common stocks in the U.S. Using quarterly total return data over the years 1978-2012, the analyses show that, over this period, on a risk-adjusted basis real estate was the top performing asset class, outperformed both bonds and stocks. Real estate, in the Eastern U.S., was the top performer, outperforming both bonds and stocks. The results also show that real estate provided a partial hedge against actual and expected inflation, and that, in combinations with bonds and stocks, it made up a major share of optimal portfolios constructed for various target returns within the Markowitz optimization framework

scholarly journals State-Dependent Utility

2009 ◽  
Vol 46 (1) ◽  
pp. 55-70 ◽  
Author(s):  
Jaime A. Londoño
Keyword(s):  
General Setting ◽  
Optimal Consumption ◽  
Investment Strategies ◽  
Economic Agents ◽  
State Dependent ◽  
Portfolio Problem ◽  
Functional Forms ◽  
Secondary Result ◽  
The One ◽  
Optimal Consumption And Investment

We propose a new approach to utilities in (state) complete markets that is consistent with state-dependent utilities. Full solutions of the optimal consumption and portfolio problem are obtained in a very general setting which includes several functional forms for utilities used in the current literature, and consider general restrictions on allowable wealths. As a secondary result, we obtain a suitable representation for straightforward numerical computations of the optimal consumption and investment strategies. In our model, utilities reflect the level of consumption satisfaction of flows of cash in future times as they are (uniquely) valued by the market when the economic agents are making their consumption and investment decisions. The theoretical framework used for the model is the one proposed in Londoño (2008). We develop the martingale methodology for the solution of the problem of optimal consumption and investment in this setting.

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