Articles
<![CDATA[Evaluasi Kualitas Pengungkapan Value at Risk Perbankan Indonesia ]]>
<![CDATA[Buddi Wibowo]]>;
<![CDATA[Hasna Fadhila]]>
<![CDATA[ Jurnal Ilmiah Akuntansi dan Bisnis Vol 14 No 2 (2019) ]]>
Publisher : <![CDATA[Fakultas Ekonomi dan Bisnis, Universitas Udayana bekerjasama dengan Ikatan Sarjana Ekonomi Cabang Bali ]]>
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DOI: 10.24843/JIAB.2019.v14.i02.p12
<![CDATA[Market risk measurement of bank investment portfolios is a still problem not only among practitioners, but also among academicians. The accuracy and quality of market risk disclosures are important issues because transparency of the bank risk level encourages market control in the form of market discipline and it also improves the quality of risk management carried out internally by the bank. This research measures the quality of Value at Risk disclosures carried out by Indonesian banks. The accuracy of Value at Risk in this research is measured from the Value at Risk component which contains information of yield volatility of bank trading treasury activities. To measure Value at Risk disclosure, this research runs various methods of Value at Risk measurement. This research shows that Historical Simulation is the most widely used method of measuring Value at Risk by Indonesia banks. The empirical test results however show that using asymmetric volatility gives better quality Value at Risk parametric measures than the historical Value at Risk Simulation method. This research shows that Value at Risk as measured by Historical Simulation method contains the least information on bank trading treasury yields. Keywords: Value at risk; disclosure; market risk; volatility]]>
<![CDATA[Uji Empirik Crowding Out Surat Utang Pemerintah dan Korporasi di Pasar Modal Indonesia ]]>
<![CDATA[Buddi Wibowo]]>;
<![CDATA[Hendrikus Passagi]]>;
<![CDATA[Muhammad Budi Prasetyo]]>
<![CDATA[ Jurnal Ekonomi Kuantitatif Terapan 2018: Vol. 11, No.1, Februari 2018 (pp. 1-144) ]]>
Publisher : <![CDATA[Universitas Udayana ]]>
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DOI: 10.24843/JEKT.2018.v11.i01.p02
<![CDATA[Financing government budget deficit through emission of government bonds may create a crowding out in corporate bond market. Crowding out caused the cost of funds incurred by the corporation to be expensive so the corporate bond market is stagnant and banks become the only major source of funding. Sources of funding that are so dependent on the banking sector could threaten financial stability and the country's economy as a whole because of the banks’ systemic risk. Default of a bank not only can influence other banks but also can have a serious impact on the national economy. This research empirically examine the phenomenon of crowding out in Indonesia with a fixed effect model of panel data FGLS and show existence of crowding out, where the yield spread tends to rise when the government issued new debt securities. But the rise in the yield spread was more due to the increase in Credit Default Swaps (CDS) spreads which reflect the default risk of Indonesia, as well as showing the influence of foreign investors in the Indonesian capital market which is strongly influenced by CDS.]]>
<![CDATA[METODE PENGUKURAN PROBABILITAS KEBANGKRUTAN BANK DAN ANALISIS HUBUNGANNYA DENGAN DIVERSIFIKASI SUMBER PENDAPATAN: KASUS PERBANKAN INDONESIA ]]>
<![CDATA[Buddi Wibowo]]>
<![CDATA[ Matrik : Jurnal Manajemen, Strategi Bisnis dan Kewirausahaan Volume 11 Nomor 1 Tahun 2017 ]]>
Publisher : <![CDATA[Universitas Udayana ]]>
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DOI: 10.24843/MATRIK:JMBK.2017.V11.i01.p05
<![CDATA[Abstrak Metode pengukuran probabilita kebangkrutan bank adalah masalah riset klasik. Metode pengukuran menggunakan analisis diskriminan dan model logit seperti Altman’s Z score dan Model Ohlson tidak memiliki dasar teoretik keuangan yang memadai karena variable-variabel yang ada di dalam model dipilih secara arbitrer dan sangat tergantung pada data yang digunakan utuk mengestimasinya. Model Merton adalah model pengukuran probabilita default yang diakui secara luas sebagai model yang memiliki dasar teroretik yang kuat namun memiliki masalah tersendiri pada implementasinya karena variabel yang digunakannya bersifat unobservable. Probabilita default sendiri dipengaruhi oleh tingkat diversifikasi pendapatan bank. Beberapa riset menghasilkan kesimpulan yang bertentangan. Pada perbankan Indonesia hubungan antara kedua variable tersebut bersifat kuadaratik (U shape) dimana diversifikasi yang natural awalnya dapat menurunkan probabilita default bank, namun sampai suatu titik diversifikasi yang terlampau tinggi justru mendorong probabilita default menjadi naik. Kata Kunci: Bank, Risiko, Probabilitas Kebangkrutan, Diversifikasi, Abstract Bank’s probability of default measurement method is one of the classic research problem. The measurement methods using discriminant analysis and logit models such as Altman's Z score and Ohlson Model do not have adequate financial theoretical foundation because variables in the models are chosen arbitrarily and depend heavily on the data used in estimation. Merton’s model of default probability is a measurement model that is widely recognized as a model that has a strong theoretical basis but has its own problems in its implementation because it uses unobservable variables. Default probability itself is influenced by the level of income diversification. Some research resulted in conflicting conclusions. We show that in Indonesian banking industry, relationship between these two variables are quadratic (U shape) which show natural diversification can reduce the bank’s probability of default, until reach a infelction point that too high diversification would encourage the probability of default to be increased Key word: Bank, Risk, Probability of Default, Diversification]]>
<![CDATA[Price Discovery Pada Pasar Obligasi Pemerintah Indonesia ]]>
<![CDATA[Buddi Wibowo]]>
<![CDATA[ Matrik : Jurnal Manajemen, Strategi Bisnis dan Kewirausahaan Volume 15 Nomor 2 Tahun 2021 ]]>
Publisher : <![CDATA[Universitas Udayana ]]>
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DOI: 10.24843/MATRIK:JMBK.2021.v15.i02.p02
<![CDATA[Penelitian ini bertujuan untuk menjelaskan peran berbagai pelaku pasar yang berbeda dalam proses price discovery di pasar obligasi pemerintah. Memahami price discovery sangat penting dalam mengidentifikasi faktor-faktor yang mempengaruhi terciptanya harga. Penelitian ini akan mencakup dua jenis pasar. Jenis pertama adalah pasar interdealer dan kedua adalah pasar pelanggan. Hasil analisis menyimpulkan bahwa pada pasar obligasi pemerintah Indonesia terdapat perbedaan jenis order flow dari pelaku pasar yang mempengaruhi harga yaitu order flow dealer berpengaruh dalam jangka pendek dan order flow dari customer untuk jangka Panjang dan menengah. Dalam perdagangan obligasi pemerintah Indonesia, kelompok customer terbukti tidak hanya melakukan perdagangan berdasarkan pertimbangan likuiditas saja namun memiliki informasi dalam mengambil keputusan atau membuat portofolio investasi dengan memanfaatkan informasi yang bersifat atau berdampak jangka pendek. Hal ini terlihat dari hanya order flow jangka pendek dari customer yang mempengaruhi perubahan yield obligasi berjangka waktu Panjang dan menengah. Hasil penelitian juga menunjukkan peran dealer secara individual, bahwa dealer memiliki peran secara heterogen dan memiliki segmen pasar yang berbeda pula.]]>
<![CDATA[Determinan Agresivitas Bank Dalam Pengambilan Risiko: Kasus Indonesia ]]>
<![CDATA[Pittauli Lidia Simanjuntak]]>;
<![CDATA[Buddi Wibowo]]>
<![CDATA[ Matrik : Jurnal Manajemen, Strategi Bisnis dan Kewirausahaan Volume 13 Nomor 2 Tahun 2019 ]]>
Publisher : <![CDATA[Universitas Udayana ]]>
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DOI: 10.24843/MATRIK:JMBK.2019.v13.i02.p10
<![CDATA[This study is aimed to identify and analyze the important factors that affect the aggressiveness of bank risk taking in Indonesia. Referring to previous research in several countries, market interest rate, bank capitalization, profitability, bank asset size, bank income diversification and bank efficiency are the influential factors that drives bank risk taking behavior. This study uses Jakarta Interbank Offered Rate, Indonesia Government Bonds Yield, Bank Indonesia Rate, and Bank Level Lending Rate as market interest rate measures. Level of aggressiveness in taking risk is measured by using the amount of risky assets owned by banks and bank credit risk. Credit risk is measured by using loan loss reserves. The results show that Bank Indonesia Rate is the most interest rate affecting bank aggressiveness in risk taking as measured by risk assets and measured by loan loss reserves. Efficiency, income diversification, and profitability are significant factor that affect bank risk taking.]]>
<![CDATA[Uji Empiris Pengaruh Idiosyncratic Volatility Terhadap Expected Return: Aplikasi Fama-French Five Factor Model ]]>
<![CDATA[Muhammad Pudjianto]]>;
<![CDATA[Buddi Wibowo]]>
<![CDATA[ MIX: JURNAL ILMIAH MANAJEMEN Vol 9, No 2 (2019): MIX: Jurnal Ilmiah Manajemen ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/mix.2019.v9i2.002
<![CDATA[Penelitian ini bertujuan untuk melakukan pengujian pengaruh antara idiosyncratic volatility dengan expected return. Idiosyncratic volatility dihitung dengan pendekatan langsung (direct method), yaitu standar deviasi dari residual yang dihasilkan model asset pricing Fama-French Five Factor. Penelitian ini menguji idiosyncratic volatility secara contemporaneous dan ex-ante. One-month lagged idiosyncratic volatility digunakan sebagai proksi dari expected idiosyncratic volatility. Metode yang digunakan dalam menguji model penelitian adalah Fama-Macbeth Cross-Sectional Regression. Hasil penelitian menunjukkan bahwa terdapat pengaruh yang positif dan signifikan antara realized idiosyncratic volatility dengan expected return pada waktu yang bersamaan (contemporaneous). Sedangkan secara ex-ante terdapat pengaruh yang negatif dan signifikan antara one-month lagged idiosyncratic volatility dengan expected return.]]>
<![CDATA[PEMODELAN DETERMINAN NIAT BERWIRAUSAHA DAN EFEK PENGARUH EDUKASI KEWIRAUSAHAAN DI KALANGAN MAHASISWA ]]>
<![CDATA[Buddi Wibowo]]>
<![CDATA[ MIX: JURNAL ILMIAH MANAJEMEN Vol 6, No 2 (2016): MIX: Jurnal Ilmiah Manajemen ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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<![CDATA[Abstract. Entrepreneurial intentions among undergraduates students need deeper studyin order to reveal entrepreneurial intention formation model, intention determinantvariables, and how those variables interact each other that affect intention formationprocess and intention strength level. Personal attitudes and social norms are the mostimportant variable influencing entrepreneurial intentions, besidesperceived behavioralcontrol. These three variables are the most important entrepreneurial intentionsdeterminant variable that direcly are influenced by personal beliefs about these factors.Entrepreneurship educations are aimed to change all personal beliefs to be morepositive to entrepreneurial activity so we could find strong entrepreneurial intentionsamong undergraduate students. Empirical test show that entrepreneurship educationsignificantly influence personal attitude dan perceived behavior control to be morefavorable in developing entrepreneurship edcuationKeyword: entrepreneurial intention, beliefs, educationAbstrak. Niat berwirausaha di kalangan mahasiswa memerlukan studi yang dapatmengungkap model pembentukan niat, variabel-variabel yang menjadi determinan niatserta bagaimana interaksi antar variabel tersebut menentukan proses pembentukan niatdan kekuatan niat yang dihasilkannya. Sikap personal dan norma sosial terhadapaktivitas entrepreneurial menjadi dua faktor yang sangat menentukan pembentukan niatberwirausaha selain kepercayaan terhadap kemampuan diri sendiri yang menjadi faktorketiga yang secara bersamaan menentukan niat wirausaha. Ketiga faktor penentu niattersebut pada gilirannya sendiri dipengaruhi oleh beliefs yang dimiliki seorang individuterhadap masing-masing faktor itu. Pengaruh dari edukasi kewirausahaan yang ada dikampus diduga dan dimaksudkan memang untuk dapat mengubah dan mengarahkanseluruh beliefs menjadi lebih positif terhadap aktivitas entrepreneurial sehingga niatberwirausaha dapat terbentuk lebih kuat di kalangan mahasiswa. Hasil uji empirikmenunjukkan edukasi kewirausahaan secara signifikan memengaruhi pembentukan niatberwirausahaKata kunci: niat berwirausaha, kepercayaan, pendidikan]]>
<![CDATA[Analysis of Asset Growth Anomaly on Cross-Section Stock Returns: Evidence from Indonesia Stock Exchange ]]>
<![CDATA[Muhammad Iqbal]]>;
<![CDATA[Buddi Wibowo]]>
<![CDATA[ Journal of Economics, Business, & Accountancy Ventura Vol 19, No 3 (2016): December 2016 - March 2017 ]]>
Publisher : <![CDATA[STIE Perbanas Surabaya ]]>
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DOI: 10.14414/jebav.v19i3.515
<![CDATA[Assorted types of market anomalies occur when stock prices deviate from the prediction of classical asset pricing theories. This study aims to examine asset growth anomaly where stocks with high asset growth will be followed by low returns in the subsequent periods. This study, using Indonesia Stock Exchanges data, finds that an equally-weighted low-growth portfolio outperforms high-growth portfolio by average 0.75% per month (9% per annum), confirming existence of asset growth anomaly. The analysis is extended at individual stock-level using fixed-effect panel regression in which asset growth effect remains significant even with controlling other variables of stock return determinants. This study also explores further whether asset growth can be included as risk factor. Employing two-stage cross-section regression in Fama and Macbeth (1973), the result aligns with some prior studies that asset growth is not a new risk factor; instead the anomaly is driven by mispricing due to investors’ overreaction and psychological bias. This result imply that asset growth anomaly is general phenomenon that can be found at mostly all stock market but in Indonesia market asset growth anomaly rise from investors’ overreaction, instead of playing as a factor of risk.]]>
<![CDATA[Determinan risiko sistemik perbankan Indonesia: Aplikasi metode marginal expected shortfall ]]>
<![CDATA[Mutiara Hikmah]]>;
<![CDATA[Buddi Wibowo]]>
<![CDATA[ Jurnal Ekonomi dan Bisnis Vol 23 No 1 (2020) ]]>
Publisher : <![CDATA[Fakultas Ekonomika dan Bisnis Universitas Kristen Satya Wacana ]]>
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DOI: 10.24914/jeb.v23i1.2475
<![CDATA[The purpose of this study is to measure systemic risk with a method that is able to calculate predictions of bank capital losses when the market is in a crisis, namely Marginal Expected Shortfall (MES) and empirically test the factors that influence it. Systemic risk arises when banks experiencing capital losses and transmit the problem to other banks and to other financial companies so that the financial system collapses. This MES model has advantages over other systemic risk measurement models because it is calculated with data available in the market, namely stock prices and volatility so that we can measure each bank’s impact to banking systemic risks. This study shows that control variable such as Non-Performing Loans (NPL) influence systemic risk but other variables such as CAR, and bank profitability (ROA) do not have significant effect on systemic risk.]]>
<![CDATA[Monetary policy and stock market reaction: developed market and emerging market comparison ]]>
<![CDATA[Buddi Wibowo]]>
<![CDATA[ BISMA (Bisnis dan Manajemen) Vol. 13 No. 2 (2021) ]]>
Publisher : <![CDATA[Universitas Negeri Surabaya ]]>
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DOI: 10.26740/bisma.v13n2.p135-147
<![CDATA[This research examines the correlation between monetary policy and stock market reaction. Monetary policy is represented by short term interest rate and exchange rate to USD. This quantitative research uses OLS Regression, SUR, and Panel Regression Method. The results suggest that monetary policy affects the movement of the stock market return. Using OLS and SUR, this study finds that short-term interest rates have a significant negative correlation to return, and exchange rates positively correlate with returning. Using the Panel Data Model, this study finds that short-term interest rates have significant correlations in G7 and emerging countries. Still, the exchange rate is only significant in the emerging market. With SUR, there are common factors that affect the global return to move together. Domestic monetary policy is not an effective tool to influence the stock market because there are common factors in a region. From a financial management perspective, this result gives a practical reason for an investor to create an optimal portfolio through regional stock market diversification. Considering monetary policy in a country as a crucial factor in rebalancing the portfolio, standard regional monetary policy becomes an appropriate strategy.]]>
