پیش بینی جریان نقد با استفاده از فرایندهای تصادفی پیوسته

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری حسابداری، واحد تهران شمال، دانشگاه آزادسلامی، تهران، ایران.

2 دانشیار، گروه مدیریت مالی، واحد تهران شمال، دانشگاه آزاد اسلامی، تهران، ایران.

3 استادیار، گروه حسابداری، واحد تهران شمال، دانشگاه آزاد اسلامی، تهران، ایران.

4 استادیار، گروه اقتصاد، واحد تهران شمال، دانشگاه آزاد اسلامی، تهران، ایران.

چکیده

از آنجا که وضعیت نقدینگی مبنای قضاوت بسیاری از اشخاص درباره موقعیت واحد اقتصادی است، این مطلب مورد توجه گروه‌های ذینفع از جمله اعتباردهندگان و سرمایه‌گذاران قرارگرفته‌است. هدف این پژوهش درک جدیدی از رفتار جریان نقد و پیش­بینی مانده نقد است. جامعه آماری پژوهش حاضر  مانده نقد روزانه یکساله ۴۸ شعبه بانک معین است. برای این منظور مدل بهینه از بین 4 مدل؛ براونی هندسی، براونی حسابی، واسیسک و مدل ریشه مربعات اصلاح شده در سه سطح میکروسکوپی، مسسکوپی و ماکروسکوپی بررسی گردیده است و مدل براونی هندسی به عنوان مدل بهینه تایید شده است؛ سپس با استفاده از مدل بهینه مذکور پیش‌بینی مانده نقد در افق‌های زمانی متفاوتی صورت‌گرفته‌است. نتیجه نشان می­دهد که قدرت مدلGBM  با افزایش طول افق زمانی پیش­بینی ثابت نمی­ماند و با افزایش افق زمانی پیش­بینی، نتایج متفاوتی دارند صحت پیش­بینی مدل با از معیار MAPEدر افق 14روزه در سطح مناسبی می­باشد. 

کلیدواژه‌ها


عنوان مقاله [English]

Cash flow forecasting using Continuous-Time Stochastic Processes

نویسندگان [English]

  • Elham Danesh 1
  • Ali Saeedi 2
  • Ehsan Rahmani nia 3
  • Amir Gholami 4
1 Ph.D. Candidate in Accounting, North Tehran Branch, Islamic Azad University, Tehran, Iran.
2 Associate Prof., Department of Financial Management, North Tehran Branch, Islamic Azad University, Tehran, Iran.
3 Assistant Prof., Department of Accounting, North Tehran Branch, Islamic Azad University, Tehran, Iran
4 Assistant Prof., Department of Economics, North Tehran Branch, Islamic Azad University, Tehran, Iran.
چکیده [English]


Since the liquidity situation is the basis for many people to judge the position of the economic unit, this issue has been considered by stakeholders including creditors and investors.The purpose of this study is a new understanding of cash flow behavior and cash balance forecasting. The statistical population of the present study is the annual cash balance of 48 branches of a certain bank. For this purpose, the optimal model out of 4 models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root Model at three levels of microscopic, mesoscopic and macroscopic have been investigated and the geometric Brownie model has been approved as the optimal model; Then, using the mentioned optimal model, the cash balance is predicted in different time horizons. The result shows that the strength of the GBM model does not remain constant with increasing the length of the forecast time horizon and with increasing the forecast time horizon, they have different results. The accuracy of the model forecast with the MAPE criterion at the 14-day horizon is at an appropriate level.

کلیدواژه‌ها [English]

  • Cash flow
  • Cash balance
  • Stochastic Processes
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