Peningkatan Literasi Keuangan Melalui Pelatihan dan Sertifikasi Perencanaan Keuangan Keluarga Syariah Pada Perangkat Desa di Kelurahan Lumbungrejo, Sleman, Yogyakarta

Kelurahan Lumbungrejo terletak di Kapanewon Tempel Yogyakarta yang terdiri dari 7000 penduduk tersebar di 10 dusun. Mata pencaharian utama adalah petani, buruh dan pedanag dengan tingkat pendapatan per bulan rata-rata 1 juta rupiah. Namun demikian, Ibu rumah tangga di kapanewon tempel mengaku pernah terlilit lintah darat dan secara umum mengaku tidak mengetahui konsep perencanaan keuangan keluarga yang benar. Latar belakang Pendidikan SMP dan SMA< serrta adanya warga yang menjadi tenaga migran di luar negeri, memberikan kesan bahwa literasi keuangan dan otomatis perencanaan keuangan di daerah ini masih rendah. Berdasarkan kondisi ini, maka program pengabdian ini mencoba untuk memberikan pemahaman dan meningkatkan tingkat literasi keuangan masyarakat di kapanewon tempel. Metode yang kami lakukan adalah (1) pembuatan modul perencanaan keuangan Syariah beserta pendampingan penggunaan aplikasi perencanaan keuangan (Indonesia Financial Planning Engine – IFPE Syariah), dan (2) mengundang 15 peserta yang direkomendasikan oleh Kepala Kelurahan Lumbungrejo yang mencakup 10 orang perwakilan dari dukuh dan 5 orang perwakilan dari staf kelurahan, dan (3) pelatihan dan sertifikasi perencanaan keuangan keluarga berbasis aplikasi, serta (4) launching komunitas perencana keuangan sebagai wadah untuk bertukar info dan kegiatan. Dalam praktiknya, kami berkolaborasi dengan Lembaga Sertifikasi Profesi Universitas Internasional Semen Indonesia (UISI) yang memiliki izin dalam melakukan sertifikasi. Setelah mengikuti pelatihan selama 2 hari penuh, ke-15 peserta mengikuti ujian yang meliputi ujian: (1) perencanaan anggaran, (2) perencanaan asuransi jiwa syariah, (3) perencanaan dana pension, (4) perencanaan dana Pendidikan anak, (5)perencanaan pembelian rumah, (6) perencanaan ibadah haji, dan (7) laporan keuangan pribadi. Setelah kami nilai dan cermati, ke-15 peserta dinyatakan lulus dan mendapat gelar non akademik Associate Wealth Planner (AWP) Syariah. Selain itu, berdasarkan survey evaluasi kegiatan, 90 persen peserta menyatakan puas, 96 persen mengaku kegiatan ini penting dan bermanfaat, serta berdasarkan pre-dan post tes, didapatkan ada kenaikan 13 persen dalam hal tingkat literasi keuangan peserta dari 60% ke 73%. Pihak kelurahan dan peserta berharap kegiatan ini bisa berlanjut melalui kegiatan yang dikelola dalam komunitas perencana keuangan yang sudah di launching

Educational Programs For Financial Planning in Jogahan Village, Kulon Progo, Yogyakarta

Financial education is a strategy for mitigating the effects of unexpected financial crises. Planning is essential not only for organizations, but also for people and households. However, when compared to financial planning in practice, such as investment or saving recommendations, study focusing on financial education is uncommon. In our situation, for example, residents of Jogahan village are illiterate and admit to lacking financial planning expertise. As a result, the purpose of this study is to evaluate the efficacy of a month-long financial education program aimed primarily at children, youth, and society in general. According to the results, the programs achieve an 80% degree of success from the intended targets. The programs helped them improve their financial literacy, which included financial planning. However, this application did not teach them using an algorithm that can indicate the optimal composition of assets accumulated in order to maintain their life sustainability. Financial education, in the long term, contributes to a more sustainable existence as well as a more resilient economic society

A Stochastic Programming Approach for Multi-Period Portfolio Optimization

presented in this paper. The basic model involves Multi-Period decisions (portfolio optimization) and deals with the usual uncertainty of investment returns and future liabilities. Therefore, is it well suited to a stochastic programming approach. We consider the problem of rebalancing policy to accomplish some investment’s criteria. Transaction costs have also been a subject of concern in this paper. In particular, a large amount of transactions usually make asset price move in an unfavorable direction. Therefore, the first problem neglects transactions cost while the second does not

HMM based scenario generation for an investment optimisation problem

This is the post-print version of the article. The official published version can be accessed from the link below - Copyright @ 2012 Springer-Verlag.The Geometric Brownian motion (GBM) is a standard method for modelling financial time series. An important criticism of this method is that the parameters of the GBM are assumed to be constants; due to this fact, important features of the time series, like extreme behaviour or volatility clustering cannot be captured. We propose an approach by which the parameters of the GBM are able to switch between regimes, more precisely they are governed by a hidden Markov chain. Thus, we model the financial time series via a hidden Markov model (HMM) with a GBM in each state. Using this approach, we generate scenarios for a financial portfolio optimisation problem in which the portfolio CVaR is minimised. Numerical results are presented.This study was funded by NET ACE at OptiRisk Systems

Joined-Up Pensions Policy in the UK: An Asset-Libility Model for Simultaneously Determining the Asset Allocation and Contribution Rate

The trustees of funded defined benefit pension schemes must make two vital and inter-related decisions - setting the asset allocation and the contribution rate. While these decisions are usually taken separately, it is argued that they are intimately related and should be taken jointly. The objective of funded pension schemes is taken to be the minimization of both the mean and the variance of the contribution rate, where the asset allocation decision is designed to achieve this objective. This is done by splitting the problem into two main steps. First, the Markowitz mean-variance model is generalised to include three types of pension scheme liabilities (actives, deferreds and pensioners), and this model is used to generate the efficient set of asset allocations. Second, for each point on the risk-return efficient set of the asset-liability portfolio model, the mathematical model of Haberman (1992) is used to compute the corresponding mean and variance of the contribution rate and funding ratio. Since the Haberman model assumes that the discount rate for computing the present value of liabilities equals the investment return, it is generalised to avoid this restriction. This generalisation removes the trade-off between contribution rate risk and funding ratio risk for a fixed spread period. Pension schemes need to choose a spread period, and it is shown how this can be set to minimise the variance of the contribution rate. Finally, using the result that the funding ratio follows an inverted gamma distribution, shortfall risk and expected tail loss are computed for funding below the minimum funding requirement, and funding above the taxation limit. This model is then applied to one of the largest UK pension schemes - the Universities Superannuation Scheme

Un modèle de programmation stochastique pour l'allocation stratégique d'actifs d'un régime de retraite partiellement provisionné

Dans cet article, nous présentons des techniques novatrices d'ALM basées sur la programmation stochastique. Leur application a été développée pour le choix de l'allocation stratégique d'actifs des régimes de retraite par répartition partiellement provisionnés. Une nouvelle méthodologie pour la génération de l'arbre des scénarios a été également adoptée. Une étude comparative du modèle d'ALM développé avec celui basé sur la stratégie Fixed-Mix a été effectuée. Différents tests de sensibilité ont été par ailleurs mis en place pour mesurer l'impact du changement de certaines variables clés d'entrée sur les résultats produits par notre modèle d'ALM.gestion actif-passif, allocation stratégique d'actifs, génération de scénarios économiques, programmation stochastique

Asset liability modelling and pension schemes: the application of robust optimization to USS

This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks

Modelos de otimização para a gestão de ativos e passivos nos fundos de pensões

Mestrado em Decisão Económica e EmpresarialNo futuro teme-se que as pensões de reforma por velhice possam estar subfinanciadas, devido ao envelhecimento da população e também ao início tardio da vida laboral. É possível que, para tentar contornar esta situação, seja necessário um aumento significativo no nível das contribuições feitas pelos empregadores e empregados. Uma forma de procurar minimizar esse aumento é o recurso a modelos de otimização, que serão aplicados precisamente à gestão dos ativos e passivos associados a fundos e planos de pensões. Este trabalho, que é essencialmente um estudo teórico, está dividido em duas partes. Na primeira, apresentam-se os aspetos essenciais dos planos e fundos de pensões e também os conceitos fundamentais na gestão de ativos e passivos (Assets and Liabilities Management - ALM), pois não são temas tratados na parte curricular do mestrado, nem na licenciatura. Na segunda, depois de uma análise bastante exaustiva da volumosa literatura existente sobre o tema, apresentam-se oito trabalhos que foram selecionados atendendo ao propósito de procurar dar a conhecer, tanto quanto as restrições de dimensão do texto o possibilitam, as diferentes abordagens para a resolução do importante problema em causa.Retirement pensions may be at risk in a future not so far, because of aged populations and late start of working life. This means that an increase of contributions by the sponsors, employers and employees, may be required. Another way to mitigate the risk of this happening is to apply optimization models in the management of the assets and liabilities for pension funds and pension plans. This document is essentially a theoretical text, in two parts. The first part presents the main features about pension funds and pension plans and fundamental concepts regarding assets and liabilities management (ALM), because these are "new" topics, in the sense that there is no course in the Masters program (or in the Bachelors program) in which they are covered. The second part gives the possible review of the existing extensive literature; a particular detail is given to eight contributions that give very interesting different approaches to solve the ALM problem for pension funds

Socially responsible investment portfolios: does the optimization process matter?

This study investigates the impact of the choice of optimization technique when constructing Socially Responsible Investment (SRI) portfolios. Corporate Social Performance (CSP) scores are price sensitive information that is subject to considerable estimation risk. Therefore, uncertainty in the input parameters is greater for SRI portfolios than conventional portfolios, and this affects the selection of the appropriate optimization method. We form SRI portfolios based on six different approaches and compare their performance along the dimensions of risk, risk-return trade-off, diversification and stability. Our results for SRI portfolios contradict those of the conventional portfolio optimization literature. We find that the more “formal” optimization approaches (Black-Litterman, Markowitz and robust estimation) lead to SRI portfolios that are both less risky and have superior risk-return trade-offs than do more simplistic approaches; although they also have more unstable asset allocations and lower diversification. Our conclusions are robust to a series of tests, including the use of different estimation windows and stricter screening criteria