مدل‌سازی مالی

مدل‌سازی مالی

یادگیری مدل‌سازی مالی

مدل‌سازی مالی می‌تواند راه شما را برای رسیدن به برنامه‌ریزی و ارزیابی مالی هموار کند.

ممکن است قبلاً به عنوان یک متخصص امور مالی و حسابداری، صورت‌های مالی و اصول حسابداری را درک کرده باشید.

با این حال، یادگیری مدل‌سازی مالی برای ارتقای مهارت‌های شما و کمک به تیم برنامه‌ریزی و ارزیابی مالی سازمان شما ضروری است.

این موضوع شامل استفاده از تکنیک‌ها و ابزارهای مختلف برای ساخت مدل‌های مالی است، که می‌تواند برای پیش‌بینی، بودجه‌بندی، ارزش‌گذاری و تصمیم‌گیری استفاده شود.

یادگیری مدل‌سازی مالی می‌تواند به شما در ارتقای چشم‌انداز شغلی خود در برنامه‌ریزی و ارزیابی مالی کمک کند.

با پشتکار و تمرین، می‌توانید مهارت‌های مورد نیاز برای تبدیل‌شدن به یک فرد حرفه‌ای و موثر در برنامه‌ریزی و ارزیابی مالی را به دست آورید.

مزایای یادگیری مدل‌سازی مالی

   بهبود تصمیم‌گیری

   پیش‌بینی‌های پیشرفته

   تحلیل سناریو

   ارزش‌گذاری

   پیشرفت شغلی

   تحلیل‌داده‌ ها

   تحلیل سرمایه‌گذاری

مراحل یادگیری مدل‌سازی مالی

– درک مفاهیم مالی

– یادگیری نرم‌افزار اکسل

– شناخت صورت‌های مالی

– مدل‌سازی جریان‌های نقدی

– جریان نقدی تنزیل‌شده

– تحلیل سناریو

– تحلیل حسّاسیت

– توابع پیشرفته اکسل

– پیش‌بینی‌های پیچیده

– ارزش‌گذاری پیشرفته

– ادغام و تملک

– خرید اهرمی

مدیریت مالی، مالی، مدلسازی مالی، مدل‌سازی مالی

مدل‌سازی مالی بیشتر بخوانید »

pestel

PESTEL

آیا می‌دانستید که این عوامل خارجی می‌توانند کسب‌وکار شما را تخریب کرده و یا شکست دهند؟

 PESTEL شامل موارد زیر است :

   سیاسی

   اقتصادی

   اجتماعی

  فنّاوری

   زیستمحیطی

  عوامل قانونی


چرا تجزیه و تحلیل PESTEL مهم است؟

در تصمیم‌گیری استراتژیک کمک می‌کند.

– دید وسیع‌تری از محیط کسب و کار ارائه می‌دهد.

به درک عوامل خارجی مؤثر بر کسب و کار کمک می‌کند.

سازمان را برای کاهش خطرات احتمالی(عوامل خارجی) آماده می‌کند.

 چگونه یک تجزیه و تحلیل PESTEL انجام دهیم؟

۱. عوامل PESTEL مربوط به صنعت خود را فهرست کنید.

۲.  ارزیابی کنید که هر عامل چگونه بر کسب و کار شما تأثیر می‌گذارد.

۳.  استفاده از فرصت‌ها و مقابله با تهدیدها.

مدیریت، پستل، PESTEL، کسب و کار

pestel بیشتر بخوانید »

Scenario Analysis

تحلیل حساسیت

Scenario Analysis

Scenario Analysis – The Worst Case Probabilities. RCSA and its various exercises are often known and discussed by risk managers and auditors but there is almost little or no knowledge about Scenario analysis. Scenario Analysis also known as ” What if ” case or worst possible case scenario has the potential to absolutely obliterate the organizations especially financial institutions if not taken seriously In this post we will try to shed some light on it. Scenario Analysis – Defined As per Basel II , Scenario Analysis is a mechanism, where in Banks use expert opinion in conjunction with external data to evaluate its exposure to high-severity events. This approach draws on the knowledge of experienced business managers and risk management experts to derive reasoned assessments of plausible severe losses. Scenario Analysis talks about fat tail events i.e the events which are extremely unlikely to occur but may cause catastrophic losses or disruptions or both to an organization. Scenario Analysis – Methods Scenario Analysis is generally done via a) Workshop Method Requires facilitation from the operational risk department. The residual risks are scored on the scale of High, medium, low scale Probabilities. b) Interview Method The questionnaire is distributed to each department for self assessed scores. Scenario Analysis – Preparation The preparation is similar to RCSA exercises done in the organization. a) The team interviews the key business and functional managers for the area under consideration b) Various earlier audits and compliance reports are also reviewed c) Internal & External loss events are analysed d) List of Possible scenarios are shortlisted on the basis of above research via interview or workshop method for consideration Scenario Analysis – Output The goal of scenario analysis is to deduce reasoned assessments of plausible severe losses Some methods produce an average loss estimate, a worst case loss estimate and frequency estimates for each. Others produce a range of loss estimates with frequency estimates for each loss. This output is then used to calculate for capital calculation requirements for the Bank. Scenario Analysis – Challenges The biggest challenge in truly implementing scenario analysis is inherent biases and they are particularly two classes of biases a) Judgemental Bias such as Anchoring, bias basis on past records b) Motivational bias (based on personal interests) Scenario analysis though designed to produce fat- tail estimates is often also responsible for the identification of significant risk mitigation activities in the organizations. As the process of RCSA and scenario analysis is almost similar there remains a chance of overlap but as RCSA doesn’t consider Fat tail events, the identified KRI (risk) in RCSA is often also mimicked for fat tail events for better assessment and monitoring of operational risk management.
Scenario Analysis – The Worst Case Probabilities. RCSA and its various exercises are often known and discussed by risk managers and auditors but there is almost little or no knowledge about Scenario analysis. Scenario Analysis also known as ” What if ” case or worst possible case scenario has the potential to absolutely obliterate the organizations especially financial institutions if not taken seriously In this post we will try to shed some light on it. Scenario Analysis – Defined As per Basel II , Scenario Analysis is a mechanism, where in Banks use expert opinion in conjunction with external data to evaluate its exposure to high-severity events. This approach draws on the knowledge of experienced business managers and risk management experts to derive reasoned assessments of plausible severe losses. Scenario Analysis talks about fat tail events i.e the events which are extremely unlikely to occur but may cause catastrophic losses or disruptions or both to an organization. Scenario Analysis – Methods Scenario Analysis is generally done via a) Workshop Method Requires facilitation from the operational risk department. The residual risks are scored on the scale of High, medium, low scale Probabilities. b) Interview Method The questionnaire is distributed to each department for self assessed scores. Scenario Analysis – Preparation The preparation is similar to RCSA exercises done in the organization. a) The team interviews the key business and functional managers for the area under consideration b) Various earlier audits and compliance reports are also reviewed c) Internal & External loss events are analysed d) List of Possible scenarios are shortlisted on the basis of above research via interview or workshop method for consideration Scenario Analysis – Output The goal of scenario analysis is to deduce reasoned assessments of plausible severe losses Some methods produce an average loss estimate, a worst case loss estimate and frequency estimates for each. Others produce a range of loss estimates with frequency estimates for each loss. This output is then used to calculate for capital calculation requirements for the Bank. Scenario Analysis – Challenges The biggest challenge in truly implementing scenario analysis is inherent biases and they are particularly two classes of biases a) Judgemental Bias such as Anchoring, bias basis on past records b) Motivational bias (based on personal interests) Scenario analysis though designed to produce fat- tail estimates is often also responsible for the identification of significant risk mitigation activities in the organizations. As the process of RCSA and scenario analysis is almost similar there remains a chance of overlap but as RCSA doesn’t consider Fat tail events, the identified KRI (risk) in RCSA is often also mimicked for fat tail events for better assessment and monitoring of operational risk management.

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