طراحی مدل پیش‌بینی بازده بورس اوراق بهادار تهران با استفاده از مدل های خودرگرسیون میانگین متحرک (ARMA) و خودرگرسیون میانگین متحرک با ورودی‌های خارجی (ARMAX) و ارزیابی عملکرد آن ها

نوع مقاله : علمی - پژوهشی

نویسنده

استادیار دانشگاه شهید بهشتی

چکیده

بازده بازارهای سرمایه تحت‌تأثیر عوامل مختلفی هستند. این عوامل دامنه گسترده و وسیعی از عوامل کلان جهانی تا رفتارهای تاریخی متغیر وابسته را شامل می‌شود. پژوهشگران زیادی، هریک بخش یا بخش‌هایی از این دامنه گسترده عوامل تأثیرگذار بر بازده بازار سرمایه را در کشورهای مختلف، انتخاب و اقدام به مدل‌سازی برای پیش‌بینی بازده بازار سرمایه مربوطه کرده‌اند. پژوهش حاضر نیز با هدف مدل‌سازی و پیش‌بینی بازده بورس اوراق بهادار تهران، از مدل‌های خود توضیحی و ترکیبی استفاده کرده است. به‌گونه‌ای که از مدل‌های خودرگرسیون میانگین متحرک و خودرگرسیون میانگین متحرک با ورودی‌های خارجی برای مدل‌سازی و پیش‌بینی بازده بورس اوراق بهادار تهران یاری گرفته است. در پژوهش حاضر، برای تبیین هر چه کامل‌تر مدل و به‌کارگیری عوامل حداکثری، پس از بررسی موضوع بازده و عوامل مؤثر بر بازده، موضوع پیش‌بینی و روش‌های متداول آن و انواع مدل‌های پیش‌بینی بازده بازار سرمایه بررسی شده است. سپس از مدل‌های رگرسیون خطی کلاسیک، خود رگرسیون میانگین متحرک (ARMA) و خود رگرسیون میانگین متحرک با ورودی‌های خارجی (ARMAX) برای پیش‌بینی بازده بورس اوراق بهادار تهران استفاده شد. پس از تخمین مدل‌های یادشده، با‌استفاده‌از داده‌های 99 دوره‌ای و تأیید قدرت تصریح آن‌ها بااستفاده‌از به‌کارگیری آزمون‌های تشخیصی، بازده بورس اوراق بهادار تهران برای 4 دوره آتی پیش‌بینی شد. پیش‌بینی‌های صورت‌پذیرفته با‌استفاده‌از مدل‌های تخمینی با داده‌های واقعی مورد‌مقایسه قرار گرفته و مدل بهینه با‌استفاده‌از معیارهای اطلاعاتی آکائیک، شوارزبیزین و حنان ـ کوئیک و همچنین معیار MSE,MAE,MAPE انتخاب شد. نتیجه نهایی مؤید برتری مدل ARMA بر مدل ARMAX است.

کلیدواژه‌ها

عنوان مقاله [English]

Designing a Model for Projection of Tehran Exchange Return Employing Autoregressive Moving Average (ARMA) and Autoregressive Moving Average with External Inputs (ARMAX) Models and Assessing the Performance Thereof

نویسنده [English]

  • Mohammad Hasannejad
Shahid Beheshti University - Faculty member
چکیده [English]

Capital markets’ return is influenced by multiple and various factors. These factors range from macro global factors to dependent variable historical behaviors. Each of many researchers has selected a segment or segments of this vast range of factors impacting capital market return in different countries and embarked on devising a model for projection of the respective capital market return. The present research has utilized self-explanatory and combined models for the purpose of modeling and projecting Tehran Exchange’s return using Autoregressive Moving Average (ARMA) and Autoregressive Moving Average with External Inputs (ARMAX) models. In this research, to utterly expound the model and to factor in maximum factors, following examination of  return issues and the factors impacting return, the subject of projection and the common methodology thereof have been surveyed and different models of projecting capital market return have been examined in detail. Then, Classic Linear Regression Models, Autoregressive Moving Average (ARMA) and Autoregressive Moving Average with External Inputs (ARMAX) models were used to predict the return of Tehran Exchange. After estimating the above models, deploying 99-period data and confirming the power of expressing them via applying diagnostic tests, the return of Tehran Exchange for the next 4 periods was projected. These predictions by applying estimation models were compared with the real data and the optimum model was selected using Akaike Information Criterion (AIC), Schwartz-Bayesian Information Criterion, Hannan-Quinn and also MSE, MAE, MAPE criteria. The final result indicates superiority of ARMA over ARMAX

کلیدواژه‌ها [English]

  • Return
  • Capital Market
  • prediction
  • Auto Regression
  • Moving Average
  • Auto Regression Moving Average
  • Autoregressive Moving Average with External Inputs

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