Mengenal Profesi Aktuaris

http://ascuny.com/resources/educational-resources/

Pada umumnya masyarakat luas masih belum begitu mengenal Ilmu Aktuaria (Actuarial Science). Apa itu ilmu aktuaria? Secara umum dapat didefinisikan sebagai bidang keilmuan yang mengombinasikan beberapa disiplin ilmu seperti matematika, probabilitas & statistika, ekonomi-keuangan, dan komputasi untuk mengukur risiko keuangan dan bisnis. Jenis ilmu aktuaria ini tentu sangat diperlukan oleh perusahaan-perusahaan atau industri yang kerap menghadapi berbagai jenis risiko dalam operasionalnya seperti perusahaan Asuransi, Pengelola Dana Pensiun, Manajemen Investasi, Sekuritas, Perbankan dan Institusi Keuangan lainnya. Selain itu, ilmu aktuaria ini juga bermanfaat bagi perusahaan umum yang menerapkan manajemen risiko dalam menjalankan bisnisnya. Karena aktuaria sangat erat dengan risiko bisnis maka ilmu ini menggunakan tag: “Risk is Opportunity”.

Para praktisi ilmu aktuaria biasa disebut dengan Aktuaris (Actuary). Aktuaris adalah seorang profesional jasa keuangan yang memberikan nasihat manajemen terkait risiko finansial di masa depan yang tidak dapat ditentukan dengan pasti (uncertainty). Profesi aktuaris pada umumnya tergabung dalam wadah asosiasi profesi seperti Society of Actuary, Casualty of Actuarial Society, Institute and Faculty of Actuaries dan lainnya. Di Indonesia wadah profesi aktuaris dikenal dengan Persatuan Aktuaris Indonesia (PAI) atau Society of Actuary Indonesia. Tentu untuk menjadi anggota PAI bukanlah hal mudah. Calon anggota harus melalui dua tahapan ujian (examination) yaitu: (1) Associate dan (2) Fellow. Jika lulus tahap pertama akan diberi gelar profesi ajun aktuaris atau Associate of Society of Actuary Indonesia (ASAI) dan jika lulus tahap kedua diberi gelar aktuaris penuh atau Fellow of Society of Actuary Indonesia (FSAI).

Dalam program studi ilmu aktuaria pada umumnya mempelajari Financial Mathematics, Life Insurance Mathematics, Probability & Statistics for Actuarial,  Stochastic for Actuarial, Casualty & Health Insurance, General Insurance, Credibility Theory, Survival Model, Retirement Income System, Risk Theory, Enterprise Risk Management (ERM), Asset & Liabilities, Financial Accounting, Corporate Finance, Economics, Investment & Portfolio Analysis and Business Management. Semua courses di atas tersebut pada umumnya memerlukan keterampilan kuantitatif yang kuat sehingga para aktuaris pada umumnya berlatar belakang sarjana matematika, statistika, teknik, sains, ekonomi keuangan dan bisnis.

Pada umumnya (sekitar 70%) para aktuaris melayani atau bekerja di industri asuransi seperti life insurance, general insurance, retirement/pension funds, and reinsurance company serta actuarial and risk consultants. Dengan kata lain, tanpa aktuaris maka perusahaan asuransi tidak dapat berfungsi. Dengan perkembangan industri keuangan dan investasi yang semakin kompleks saat ini, banyak para aktuaris yang melayani dan berkarir di industri keuangan lainnya seperti investment & assets management, commercial banking, investment banking, risk management, accounting & financial consultants, government/regulator dan akademisi & peneliti. Trend ini menunjukkan bahwa profesi aktuaris semakin diperlukan oleh berbagai bidang bisnis keuangan bahkan ada yang menyebut sebagai “A Career without Boundaries”.

Hal ini dapat dipahami karena kompleksitas bisnis dan ketidakpastian keuangan yang semakin tinggi akan menciptakan risiko keuangan dan bisnis yang semakin besar pula maka profesi aktuaris semakin diperlukan. Dapat dikatakan bahwa dimana ada risiko bisnis, di situ pula aktuaris diperlukan. Di Indonesia sendiri jumlah aktuaris masih sangat minim sehingga peluang berkarir di bidang ini masih terbuka lebar dan tentunya dengan ekspektasi pendapatan yang menjanjikan. Menurut Wall Street Journal (2010) profesi aktuaris adalah jenis pekerjaan yang paling dicari peringkat 1 di USA (Top Ranked Job).

Untuk mendapatkan pendidikan formal ilmu aktuaria, anda dapat mencoba di beberapa perguruan tinggi top dunia seperti University of Waterloo, Australian National University, UNSW, University of Melbourne, Macquarie University, Oxford University, Cambridge University, Columbia University, Universiteit van Amsterdam, University of Illinois, University of Kent, Nanyang Technological University dan lainnya. Di Indonesia sendiri terdapat beberapa universitas yang menawarkan program studi aktuaria tingkat sarjana seperti Matematika ITB, Matematika UI, Statsitika IPB dan Statistika UGM. Untuk tingkat S2-Magister Aktuaria ditawarkan oleh Departemen Matematika ITB dan program MM Aktuaria UI yang bekerjasama dengan PAI. Demikian dan semoga bermanfaat….

Perdana Wahyu Santosa

Apa Itu Financial Engineering?

 Dengan semakin kompleks dan canggihnya perkembangan industri keuangan dan financial market, maka pendekatan melalui ilmu ekonomi dan  keuangan  (financial  economics) menjadi semakin kurang efektif lagi. Maka Ilmu ekonomi keuangan memerlukan kolaborasi baru dengan beberapa  displin ilmu lainnya.  Mengapa demikian? Hal  tersebut disebabkan oleh semakin kompleks dan meningkatnya risiko (volatilitas) yang sulit diprediksi  (unpredictable). Industri  finansial masa depan membutuhkan  “pendekatan baru” yang mampu mengimbangi kerumitan, risiko dan kecepatan  transaksi yang  semakin tinggi. Selain  itu instrumen-instrumen keuangan dan investasi  juga  semakin rumit, eksotis disertai pasar finansial global saling  terkait satu dengan lainnya.

Untuk mengatasi hal tersebut diperlukan sebuah teroboson keilmuan baru yaitu melalui pendekatan quantitative atau matematis dalam bidang  corporate finance dan  financial market & institutions. Disiplin ilmu yang saat ini dikembangkan untuk mengatasi permasalahan tersebut adalah Financial  Engineering. Ilmu financial engineering biasa disebut juga dengan quantitative finance, financial mathematics, atau computational finance. Lalu apakah sejatinya financial engineering tersebut? Columbia University (2015) mendefinisikannya sebagai “Ilmu multidsiplin” yang menggabungkan teori ekonomi keuangan, metode matematika, praktik programming (komputasi) dan konsep engineering.

Secara umum financial engineering menggabungkan beberapa konsep keilmuan sekaligus yang mencakup pemodelan pasar finansial dan instrumen seperti proses stokastik, optimisasi, teknik numerik, simulasi Monte Carlo dan analisis data keuangan. Di samping itu, financial engineering juga dibekali dengan teori portofolio dan analisis investasi, keuangan korporasi, market microstructure theory, financing & risk, valuasi aset & derivatif, manajemen aset, fixed income & term structure, algorithmic trading, structured & hybrid product, financial technology dan analisis risiko keuangan.

Praktisi financial engineering kerap disebut sebagai financial engineers atau “the quants” karena kelebihannya dibidang kuantitatif dan komputasi keuangan. Profesi ini semakin diminati oleh financial management, perusahaan sekuritas, industri perbankan, asuransi, kantor konsultan keuangan, investment bankers, hedge funds dan asset management karena kemampuannya menggabungkan konsep asset pricing & derivative, portfolio optimization, corporate economics dan risk management secara efektif. Sejauh ini program master of financial engineering menawarkan konsentrasi (1) Asset Management & Optimization (2) Finance and Economics (3) Derivatives & Risk Management (4) Computation Finance & Programming (5) Computation & Trading Strategy and (6) Financial Technology. Kita dapat memilih konsentrasi sesuai dengan kualifikasi dan minat profesiional.

Beberapa perusahaan MNC yang kerap menggunakan jasa financial engineers adalah Barclays, Goldman Sach, JP Morgan, Citi Group, Black Rock, Credit Suisse, Bloomberg, Standard & Poor’s, Morgan Stanley, Deutsche Bank, Standard Chartered Bank, AXA Equitable, Ernst & Young, PwC, Perry Capital etc. Selain di perusahaan keuangan, anda dapat berkarir di manajemen keuangan dan tresuri serta manajemen risiko untuk perusahaan industri dan manufaktur lainnya.

Jika berminat menjadi financial engineer, saat ini sudah banyak berbagai universitas kelas dunia yang menyediakan disiplin ilmu ini dengan berbagai nama program seperti financial engineering, quantitative finance, financial mathematics dan computational finance seperti Columbia University, NYU, University of Chicago, UCLA, UC Berkeley, MIT, Standford University, Princeton University, Carnegie-Mellon, Cornel University, Georgia Institute of Technology, University of Southern California, Boston University, University of Washington, National University of Singapore etc. Untuk universitas nasional, Departemen Matematika ITB menawarkan program sarjana Matematika Industri dan Keuangan dan School of Business and Management ITB membuka program magister MSM Finance (Quantitative). Jika anda berlatar belakang matematika, statistika, fisika, teknik, ekonomi keuangan atau menyukai bidang kuantitatif, silakan mencoba tantangan baru ini. Semoga bermanfaat….

Perdana Wahyu Santosa

Rethinking Implied Volatility

By Don Chance, Ph.D., CFA

This article originally appeared in the January/February 2003 issue of Financial Engineering News.

With the possible exception of Value at Risk, probably no topic has received more attention in risk  management research than implied volatility. This research can be classified into two major  categories: research on analytical methods for extracting the implied volatility and research on  methods for modifying existing pricing models to render the observed pattern of implied volatility  consistent with the chosen pricing model. The well-known volatility smile or skew is at the center of  much of this research. Unfortunately, there is little research that addresses the question of why the  existing research provides inconsistent and inexplicable results. The plethora of research on implied  volatility that makes no effort to address this question is astounding. I contend that the most fundamental question is how can the options market tell us that there is more than one volatility for an underlying asset?

The answer is really quite simple: It cannot, but more importantly, it does not.

The volatility smile/skew is inconsistent with an arbitrage-free world. Yet researchers devote countless hours to force-fitting existing models to produce prices that fit the smile/skew. I argue that we are neither asking the right questions nor approaching the problem in the right manner. We are afraid to go down a path we have been down before and thought we would never have to go down again. To understand my point, let us start with an explanation of the difference in two major classes of economic models.

Economic Models: Partial Equilibrium and General Equilibrium

Students of economics spend a great deal of time studying models of economic equilibrium. When markets are in equilibrium, the supply of assets equals the demand for assets, leading to the determination of a market-clearing price and a quantity held of each asset. These results are obtained by aggregation across all assets and market participants. Models of financial markets are a special class of economic models in which equilibrium is derived in the market for financial assets. Financial asset models produce financial asset prices, typically in the form of rates of return required by investors. These required rates of return are normally consistent with the notion that risk-averse investors would expect to earn the risk-free rate at a minimum and a higher return commensurate with the risk assumed, a factor known as the risk premium. When these models are developed in a framework in which all risky financial assets are priced, they are called general equilibrium models. Probably the best-known general equilibrium model of financial markets is the Capital Asset Pricing Model, or CAPM, of Sharpe (1964) and Lintner (1965).

Technically, the CAPM is not restricted to financial assets. It covers any risky asset that an investor  could own. Financial assets would obviously be included, but real estate and metals are good  examples of other non-financial assets that could come under the umbrella of the CAPM. Another  class of models is called partial equilibrium models. These models do not provide results by  aggregating across assets and market participants. They take the existence of a class of assets, the  prices of those assets, and the expectations and preferences of all market participants as given.  Partial equilibrium models then determine the price of one or more other assets relative to the  given class of assets. General equilibrium models show the big picture, while partial equilibrium models show a subset of the big picture. Securities in the form of stocks and bonds are the central assets in financial markets, and options are, of course, derivative assets. Think of securities as the main event, while derivatives are the side show, albeit an interesting and influential side show, that sometimes draws a bigger crowd. Option pricing models are typically partial equilibrium models. They nearly always take the assets in the market and their expected returns as given. Let us start by taking a brief look at the early models of option pricing.

The Archeology of Option Pricing

The first model for pricing options was the celebrated Bachelier (1900) dissertation, which assumed an arithmetic Brownian motion process for the stock. This assumption is generally deemed unacceptable for stocks, although arithmetic Brownian motion may be acceptable for options on spreads or other values that can be negative. Sprenkle (1964), under the assumption that the stock moves according to the more realistic geometric Brownian motion, derives the value of the option as the discounted expectation of its payoff at expiration. His formula requires the expected growth rate of the stock and a discount factor to reflect the investor’s risk aversion. Unfortunately, Sprenkle’s model does not use an interest rate, so the time value of money is ignored. Boness (1964) incorporates an interest rate and risk aversion, but discounts the option payoff at the stock’s discount rate. Each of these problems was solved by Samuelson (1965), but his model still requires discount rates for both the stock and option. All of these models assume that a general equilibrium model is available that would supply the missing link, which is the information on how risk-averse investors discount risky assets. None of these authors found the real insight provided by Black-Scholes (1973) and Merton (1973), which was that the option could be hedged by the stock, leading to the conclusion that the discount rate should be the risk-free rate.

The expected returns on the stock and option were not needed. It was indeed a joyous moment in the history of option pricing. But we know that the Black-Scholes model has problems. Fischer Black himself acknowledged this point and was quite amazed that the model was so successful. See Black (1989), which does not mention the volatility smile/skew.

The Biggest Hole in Black-Scholes

The Black-Scholes model solved the option pricing problem without resorting to a general  equilibrium theory. By invoking the principle that no arbitrage profits should be available, the  model provided the framework for pricing a financial instrument through the process of  replicating its payoffs using instruments with known prices. [Interestingly, the Black-Scholes  model was not the first model for pricing derivatives that was based on the principle that no  arbitrage profits could be earned. Well before the days of Black and Scholes, agricultural economists knew that the price of a futures contract should be the price of the underlying spot asset increased by the costs of holding it and reduced by any implicit yield on the asset. This argument follows from the fact that the asset can be purchased and hedged using futures to produce a risk-free position that should yield the risk-free rate over and above any costs of storage less any yield. It is difficult to pinpoint who first identified this relationship, but see Blau (1944-45) for an early discussion.] The Black-Scholes model is, thus, a partial equilibrium model. The price of an option is determined relative to the price of the underlying, taking into account interest rates and other factors exogenous to the model. It is probably safe to say that the derivatives industry would be stuck in the psychedelic 60s, and many talented mathematicians would still be teaching freshman algebra for $20,000 a year had Black, Scholes and Merton not made their contribution. But the Black-Scholes model has been both a blessing and a curse. It may well be a Pandora’s Box that has caused us to think that we neither can nor should ever look back.

As we said earlier, the Black-Scholes model produces implied volatilities of traded options that can vary by exercise price for a given underlying asset. How should we respond to such a finding? First, we could suggest that the Black-Scholes model is not correct. Since there cannot be more than one volatility of the underlying asset, the model must be incorrect. Case closed. But industry has not responded in that manner. Indeed it has responded in quite the opposite, embracing the Black-Scholes model and seeking to improve on it. The volatility smile notwithstanding, select 20 articles at random on implied volatility and I would be surprised if one of them argued that the Black-Scholes model is fundamentally incorrect. The closest any would come is to argue that perhaps the stochastic process of the underlying is improperly specified. Jumps and fat tails are commonly thought to be the explanation of the smile/skew. But such a conclusion tells us only that other models, perhaps with different stochastic processes, can accommodate multiplied implied volatilities. That should be just as unsettling. The implied volatility is a catch-all that reflects anything important omitted from the model.

Consider a world in which the stock market reveals volatilities but not prices. Then the stock price would catch any omitted inputs in the option pricing process. Options on stocks with different expirations would have multiple implied stock prices. We would then be looking at an implied stock price smile or skew. And that would be absurd. So what is missing? The Black-Scholes model is indeed incorrect. It may well be the case that the stochastic process is improperly specified. But there is something else. The Black-Scholes model is incorrect because of the very reason why the Black-Scholes model is so highly regarded. The Black-Scholes model tells us that the price of the underlying stock and investors’ feelings about risk do not matter in the pricing of options. These things should not matter because options can be perfectly replicated with the underlying stock and risk-free bonds. The model cannot identify the demand for options or distinguish it from the demand for stocks and risk-free bonds, because stocks and risk-free bonds, held in the right proportions, are equivalent to options. This ability to replicate is the glue that holds the model together. It says that some instruments are perfect substitutes for other instruments. A subtle point in this premise is that any one option is a perfect substitute for any other option. What is not so obvious in the Black-Scholes model is the fact that the model says nothing about the demand for options or why anyone would want to buy or sell an option, other than to earn an arbitrage profit. It does not tell us how many options an investor would hold in his or her portfolio. It does not do these things because it is a partial equilibrium model and not a general equilibrium model. The Black-Scholes model gives us only the price of an option, given that demand, preferences, asset prices and interest rates have been determined exogenously.

I emphasize that the reason the Black-Scholes model tells us nothing about the demand for options is that any option on a given underlying is a perfect substitute for any other option in the Black-Scholes world. In fact, in a general equilibrium framework, you can even substitute seemingly different securities. For example, in the CAPM world two stocks with equivalent beta coefficients are effectively the same stock, because they make the same contribution to an investor’s portfolio. In a general equilibrium framework, it could be possible to substitute an option on one stock for an option on another stock. If the assumptions under which the Black-Scholes model is derived do not hold sufficiently in practice, then any option on a given underlying is not a perfect substitute for any other option on the same underlying. If that is the case, then an investor may have needs that can be met only by a particular option. Then that option will have a greater value than some other option on the same stock with a different exercise price. If the Black-Scholes model is then used to obtain the implied volatilities, the former will show a higher implied volatility. To capture the demand for options, we need a general equilibrium model, but that would require that we impose restrictions on investors’ preferences. The prices of options would, thus, no longer be preference-free.

We would be back to a world that probably blends the Samuelson model with the Capital Asset Pricing Model. This does not, however, mean that option prices would violate the no-arbitrage rule. General equilibrium models are consistent with a world of no arbitrage opportunities. Put-call parity and various static trading strategies that lead to boundaries on option prices would indeed hold. But it is unlikely that continuous-time dynamic trading strategies that lead to models like Black-Scholes would hold. Option pricing models would then require expected returns on options.

In Conclusion

When the Black-Scholes model was discovered, researchers were excited that the model did not require the expected return on the stock. Expected returns are difficult to estimate and notoriously unstable. Moreover, they are influenced by investors’ preferences, which are even more difficult to estimate, are unstable, and subject to irrational behavior. Hence, researchers would prefer to salvage the Black-Scholes model than consider the alternatives. But the cost of this approach is the implied volatility smile/skew, which leads to the irrational result that there is no unique volatility for the underlying stock. We may be at a great crossroads in the history of options.

We can continue to find ways to contort the Black-Scholes model so that it will be consistent with the volatility smile. Or we can look to general equilibrium models to give us option prices based on expectations and preferences. As reluctant as we are to turn back the pages of history, we may have to. To do otherwise is to argue that there is more than one volatility of the underlying. We might as well argue that there is more than one sun in our solar system. About the Author Don Chance is a professor of finance at Louisiana State University. He can be contact dchance@fenews.com

References

Bachelier, L. 1964. “Theory of Speculation (English translation),” in P. Cootner, ed. The Random Character of Stock Market Prices. Cambridge: MIT Press. 17-78.

Black, F. 1989. “How to Use the Holes in Black-Scholes.” Journal of Applied Corporate Finance. 1: 67-73.

Black, F. and M. Scholes. 1973. “The Pricing of Options and Corporate Liabilities.” Journal of Political Economy. 81: 637-659.

Blau, G. 1944-45. “Some Aspects of the Theory of Futures Trading.” The Review of Economic Studies. XII: 1-30.

Boness, A.J. 1964. “Elements of a Theory of Stock-Option Value.” Journal of Political Economy. 72: 163-175.

Lintner, J. 1965. “The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets.” Review of Economics and Statistics. 47: 13-37.

Merton. R.C. 1973. “Theory of Rational Option Pricing.” Bell Journal of Economics and Management Science. 4: 141-183.

Samuelson, P. 1965. “Rational Theory of Warrant Pricing.” Industrial Management Review. 6: 13-31.

Sharpe, W.F. 1964. “Capital Asset Prices: A Theory of Asset Equilibrium Under Conditions of Risk.” The Journal of Finance. XIX: 425-442.

Mengenal Indeks Harga Saham dan Jakarta Islamic Index

oleh  Perdana Wahyu Santosa

Pasar modal mempunyai indikator indeks harga saham yang menjadi pintu gerbang sekaligus barometer utama untuk para investor dalam mengambil keputusan stratejiknya. Perhitungan terhadap indeks harga saham dapat dilakukan dengan berbagai cara dan metode. Cara yang umum dilakukan melalui Indeks Harga Saham Gabungan (IHSG) yang merupakan indeks komposit seluruh saham yang listing di BEI. Perhitungan IHSG dilakukan tanpa pembobotan (weighted) dengan asumsi peran setiap saham dinilai sama pengaruhnya terhadap pergerakan harga pasar. Oleh karena itu semua jenis indeks harga saham lainnya merupakan turunan sekaligus anggota IHSG. Pada umumnya pembentukan indeks saham menggunakan metode Laspeyres.

Indeks lainnya yang sangat berpengaruh adalah LQ-45 karena beranggotakan saham-saham unggulan yang sangat aktif (most active). LQ-45 menjadi acuan banyak perusahaan manajemen investasi terkemuka dalam membentuk portofolio dan basis reksadana (mutual fund) termasuk investor individual. Selain itu, LQ-45 juga paling sering dijadikan acuan pemilihan saham dalam berbagai penelitian keuangan dan investasi. Selanjtnya indeks lainnya adalah Kompas-100 yang diterbitkan para analis harian Kompas. Indeks ini juga sangat andal dengan anggota sekitar 100 saham unggulan dan kerap dijadikan acuan reksadana saham. Dengan anggota saham yang lebih banyak, Kompas 100 lebih elastis mengikuti pergerakan IHSG. Indeks saham terbaru adalah Bisnis-27 yang dirilis harian Bisnis Indonesia pada awal 2009. Indeks Bisnis dengan 27 saham index mover berbagai sektor andalan BEI memberikan pilihan yang lebih spesifik lagi. Kelemahan indeks Bisnis-27 ini pergerakannya rentan karena jumlah anggota saham yang relatif kecil. Namun sejauh ini, berdasarkan pengamatan selama 6 bulan pertama sejak dirilis, indeks bisnis ini cukup andal.

Indeks-indeks tersebut di atas tersebut cukup akurat dan reponsif terhadap pergerakan pasar IHSG. Karakter indeks harga saham seperti ini termasuk ke dalam Indeks sampel karena anggota indeks diambil melalui metode sampling tertentu agar mampu merepresentasikan seluruh harga saham sebagai populasinya. Selain itu, terdapat pula indeks saham yang mencerminkan pergerakan harga-harga saham sesuai dengan sektor masing-masing seperti sektor agriculture, mining, finance dan lain sebagainya. Tentu, indeks sektoral bukan dibentuk melalui teknik sampling tertentu karena saham-saham yang digunakan sesuai dengan emiten pada sektor yang dijadikan indeks. Dengan demikian, ragam jenis indeks saham memungkinkan para analis dan investor untuk melakukan penilaian yang lebih objektif terhadap studi komparasi antar indeks saham.

Jakarta Islamic Index

Di samping itu, terdapat indeks harga saham yang lebih spesifik berdasar ajaran islami yaitu Jakarta Islamic Index (JII) dengan anggota 30 saham pilihan. Ke -30 saham anggota JII tersebut dinilai memenuhi syarat yang ditetapkan oleh Dewan Syariah Nasional (DSN) MUI. Intinya saham-saham yang masuk ke dalam JII-30 harus memenuhi unsur yang sama dengan indeks lainnya kecuali unsur haram dalam pandangan MUI. Unsur haram yang disyaratkan DSN MUI pada umumnya terkait dengan kegiatan bisnis  Alkohol, Perjudian, Produksi dengan bahan baku babi, Pornografi, Jasa Keuangan dan Asuransi konvensional.

Ke enam fatwa-fatwa DSN MUI tahun 2004 tersebut mengatur prinsip-prinsip syariah di bidang pasar modal yang menyatakan bahwa suatu sekuritas/efek di pasar modal dipandang telah memenuhi prinsip-prinsip syariah apabila telah memperoleh pernyataan kesesuaian syariah secara tertulis dari DSN-MUI.

Jadi secara khusus, saham-saham yang masuk kriteria JII adalah saham-saham yang operasionalnya tidak mengandung unsur ribawi dan struktur permodalan perusahaan bukan mayoritas dari hutang. Maka saham-saham JII ini pada umumnya mempunyai struktur modal yang sehat dan tidak terbebani bunga hutang berlebihan, dengan kata lain debt-to equity rasionya masih proporsional. Rasio DER yang lebih wajar berpotensi meningkatkan keuntungan emiten dan terhindar dari beban keuangan jangka panjang.

Namun secara prinsip, leveraging merupakan suatu hal yang dianjurkan agar EBIT dan EPS perusahaan terus meningkat. Oleh sebab itu, imbal hasil (return) emiten syariah cukup menjanjikan pada investasi jangka menengah-panjang. Pengelolaannya (manajemen) juga dinilai transparan dan kredibel serta menghormati hak-hak pemegang sahamnya. Saham-saham anggota JII sebagian besar juga anggota indeks lainnya hanya ada sedikit kriteria syariah tersebut. Indeks JII seperti indeks modern lainnya, bersifat dinamis dalam arti secara periodik di update agar senantiasa responsif dengan pergerakan pasar dan sesuai dengan syariah.

Maka sejak keberadaannya 1995, serta melalui berbagai penyempurnaan tahun 2000 dan 2003, saham-saham JII menunjukkan kinerja yang baik dan mampu bersaing dengan saham-saham dari anggota indeks lainnya. Selain itu, saham-saham JII sebagian besar merupakan saham blue chips biasa.

Demikian dan semoga bermanfaat. Salam Investasi

MEMAHAMI VALUE INVESTING

By Perdana Wahyu Santosa

Salah satu metode investasi yang populer sekaligus powerful dalam memberikan imbal hasil (return) yang tinggi dalam sejarah investasi dunia adalah Value Investing. Konsep investasi ini digagas Prof. Benjamin Graham. Salah satu value investor kaliber dunia adalah Warren Buffet yang merupakan salah satu orang terkaya di dunia saat ini. Tentu saja para investor yang ingin menggunakan strategi ini harus memahami teknik evaluasi terhadap nilai-nilai saham sesuai dengan karakter pasar modalnya. Pemahaman terhadap aspek fundamental menjadi kunci keberhasilan value investing ini.

Namun ada baiknya kita memahami dahulu definisi dari value investing tersebut:

Value investing is finding a stock that is selling at a discount to its intrinsic value or companies that the market has undervalued for some reason unrelated to its economic fundamentals.

Dari definisi di atas, kata kuncinya adalah: discount to intrinsic value dan undervalued. Lalu apakah intrinsic value yang dimaksud? Bagaimana menjadi undervalued?. Intrinsic value adalah nilai wajar dan pantas dari saham yang diperdagangkan sedangkan undervalued merupakan kondisi harga yang berada di bawah intrinsic value-nya. Perbedaan antara intrinsic value dan nilai undervalued saham tersebut disebut discount namun dengan catatan nilai undervalued saham tersebut bukan karena masalah fundamental. Masalah utama strategi ini adalah kemampuan analisis kita dalam menentukan intrinsic value pada suatu saham sehingga kita mengetahui undervalued atau overvalued dibandingkan dengan harganya.

Margin of Safety

Merupakan ruang antara intrinsic value dengan nilai undervalued-nya yang menciptakan “safety” setara dengan discount-nya tersebut. Keuntungan yang kita peroleh didapat ketika harga terkoreksi kembali menuju nilai wajarnya yaitu sebesar margin of safety-nya. Hal ini menjadi sangat penting karena kesuksesan investing value terletak pada ketepatan memilih saham pada harga yang tepat pula. Tentunya kemampuan analisis dan riset fundamental dan disiplin menjadi penting. If you could not buy the stock at that price, you would pass.

Rasio Finansial

Beberapa rasio finansial yang penting diperhatikan dalam strtaegi ini adalah:

• price to book ratios

• price to sales ratios

• price to earnings ratios

• price to cash flow ratios

Para value investor di BEI dapat melakukan benchmarking rasio-rasio tersebut dengan indeks yang diyakininya. Secara umum dapat digunakan IHSG, namun untuk tujuan yang lebih akurat dapat membandingkannya dengan LQ-45 atau BI-27 dimana saham yang akan dibeli masuk dalam komposisi indeks tersebut. Bahkan untuk lebih spesifik lagi dapat dibandingkan dengan sektor atau industrinya. Namun, value investing tidak semata-mata mencari saham undervalued yang terlalu murah karena masalah fundamental atau moral hazard manajemennya. Emiten jenis ini hanya akan menciptkan kesulitan dan kerugian bagi strategi value investing.

One of the ways you can make sure the company is on solid footing is to look at its financial ratios and its link of them.

Faktor lain yang sangat penting adalah debt ratio yang relatif rendah dan cash flow yang baik, tentunya. Pereusahaan yang mampu mengelola hutang dan cash flow-nya dengan baik dan wajar akan memberikan market value added yang tinggi di masa depan. Nilai debt ratio yang terlalu tinggi (>200%) akan membuat beban finansial jangka panjang, apalagi menggunakan fasilitas repo dan derivatif secara masif.

Successful value investing depends on identifying a stock that is trading under the intrinsic value of the company and buying with a margin of safety in case you have misjudged the intrinsic value (Little, 2008).

Pada umumnya hanya investor bijak yang dapat mengalahkan pasar. Salam investasi.

Random walk?

by Veryan Allen

Random walk? Advance warnings were in place for a global correction. Smart money has been selling to dumb money for a while. When equity volatility and credit spreads are at lows but financial arrogance and market myopia are at highs, a bear market is usually coming sooner or later. With Sam Zell taking a lot of real estate chips off the table, Warren Buffett searching for a successor and some bottom tier hedge funds even saying they couldn’t find any shorting opportunities(!), the canaries in the coal mine could not have been singing much louder.

Since 1896 there have been 130 worse sell-offs than 27 Feb 2007, or more than 1 each year. We hadn’t had a major drawdown in ages and volatility clusters so perhaps the year of the Golden Boar will see several more. The Dow fell 3.7 sigma which randomly “should” occur every 18 years but Chinese stock indices made a 6 sigma move which, according to the random walkers “should” happen every 2 million years. The VIX rose by a percentage that “shouldn’t” have occurred since this planet was formed. There was nothing random about last week and bearish times are looming. BUYING the VIX on the rare occasions it drops below 10 ALWAYS pays – the implied volatility for daily market movement at such levels is unsustainable. 10/srqt(256)=0.625% was ludicrously low.

Random walk? No predictive information in financial data? Chinese day traders “cause” the recent global correction? On the 9th day of the Lunar New Year (27 Feb in 2007), it is custom to make an offering to ensure continued prosperity. The China “catalyst” had more to do with a desire to take profit and what better day to pay an 8.8% tithe to the Jade Emperor? That’s eight point eight. Eights are a big deal in China as with the Olympics starting at 8pm on 08/08/08. While profit-taking was overdue, it is a stretch to blame Chinese retail investors for global turbulence.

The eclipse over the weekend wasn’t the only syzygy obviously influencing recent investor behavior. Prominent business magazines lined up in a classic convergence to signal a possible pause in the euphoria; when Forbes implies the bull market might just be getting started, Fortune runs a glowing advertorial for private equity and Businessweek says we are in a low, low rate world, you just “know” there could be problems soon.

Then there is the “economies are still doing great” contention. Don’t people realise that market volatility CHANGES the fundamentals? George Soros has never received due credit for his reflexivity theories. The reminder that risk assets actually are risky will change investor and business behaviour. Private equity deals yet to be announced will not now emerge with leverage harder to get and much more expensive. Roach motel illiquid securities (you can check in but you can’t check out) will be evaluated much more closely. Some say the “Greenspan put” or “private equity put” are floors on any sustained market drop but those are myths. Some who would have qualified for a mortgage before will NOT now, which will impact real estate. Credit will be harder to get as will loans to finance other loans coming due.

Many “reasons” have been offered for the “correction”. Ben Bernanke said there was no single trigger but that is ALWAYS the case anyway. Yes subprime mortgages are a disaster but that is not “new” news though it has yet to fully impact the markets. The possibility of recession? What else could Alan Greenspan have said? He had three choices, 1) “Don’t know, don’t care” which wasn’t really an option for him in his position 2) “No way, there is never going to be a recession ever again” (wrong, obviously) or 3) Sure there is a chance. Choice 3 was the only realistic statement, but he gets blamed.

World equity, credit and most commodity markets went down because there were simply more sellers than buyers. Some say it was just a “fluctuation” in the random walk. Really? Why did the drunken man suddenly take such a Bob Beamon like big jump backwards? A corollary to random walk assumptions is that there can be no such thing as investment skill! It is amazing how this rubbish persists in the face of such overwhelming counter evidence.

Truth is the first casualty of war and liquidity is the first casualty of volatility. The second casualty however is rising risky asset correlations. Most commodities, weaker credits and equities dropped last week, almost everywhere. The popular fear gauges of equity implied volatility and credit default protection blew out massively. It is yet more confirmation that in the flat world of global capital markets, it is STRATEGY diversification more than ASSET diversification that is most likely to protect portfolios and make money when most risk assets fall.

Also worth noting is that the stock markets impacted the worst were those that make onshore short sales complicated or illegal. Every market needs such natural BUYERS during sharp corrections and taking profits is easier than cutting losses. Short sellers REDUCE the severity of market drawdowns by buying to cover those prior shorts.

There may be some “smart” investors around but there is far more “dumb” money playing the markets. There is not much connection between intelligence and financial savvy. Whether it was Isaac Newton getting blown up by the markets in 1721, Albert Einstein’s bond trading, the Long-Term Capital Management option pricing “geniuses” in 1998, or the “can’t find any short sales” superstars that got “fluctuated” recently, there is plenty of money for genuinely smart investors to extract from other market participants in bull AND bear markets. It does not particularly matter what the reasons are for a move, what matters is that alpha was extracted and risks were ANTICIPATED. There is NEVER a situation where there is nothing to short. Never.

Alpha capture is really an alpha redistribution game. I don’t know which market offers the most beta but the USA easily has the most alpha available and Japan has the second largest amount. It is trendy for pundits to talk about the US markets being too “efficient”, too “analyzed”, too much “smart money” for anomalies to remain but that is just plain wrong. Last Tuesday, even Dow Jones and NYSE computers couldn’t add up and divide the prices of 30 major stocks. The best money making opportunities are in the US markets because it is so inefficient, so liquid and has the widest range of tradeable securities, derivatives and options. The best source of alpha will continue to be the USA if only because it has the biggest and deepest markets. You have to be sceptical of investors moving into new areas because they are not making money at home. If a hedge fund can’t make money in its “own” country how can it possibly do so elsewhere?

Markets are not random just like coin tosses are NOT random. It would not be particularly difficult, theoretically, to construct a hedge fund strategy around coin flips. Coins “seem” random because most of us only witness single or very low sample sizes. If you toss many coins using the same mechanism and starting conditions the bias is 51/49 which, while sounding slim, is an exploitable edge. If the coin is spun instead, the bias is often in favor of heads, 70/30 according to empirical work by Persi Diaconis. Spin a new 1 cent penny however and the chances are it will come up tails. Look at any coin – is the centre of gravity EXACTLY half-way or isn’t there a tiny bit more metal on one side?

Returning to China, if you got every Chinese citizen to toss a known coin each day, had knowledge of the starting face and modeled a few thousand sample flips from each flipper the non-random bias would be obvious. Bet $1 on each toss and you would have a $1.3 billion hedge fund generating a high annual return from a supposedly random process called coin tossing. It is possible to develop predictive edges from ANY process involving human bias and behavior. NOTHING is random. Not coin tosses, not roulette wheels, not “random” number generators in spreadsheets and definitely NOT financial markets. Bias is omnipresent.

It is noteworthy how the smart money has been selling out while the beta players have been buying. I generated some positive alpha from the sell-off not because of some amazing foresight but primarily because I have stress tested for anything, was sufficiently diversified and am ALWAYS long of options. Vega, volga and vanna are often ignored, obscure to many, but were important recent factors in the markets.

If you have prepared for the chance of the sun not coming up tomorrow, -3.3% drops in the Dow or a steeper fall in a market previously up well over 100% don’t cause a sweat. All I know is that there is bias in EVERYTHING, that neither prices nor volatilities are stochastic and that the risk-reward equation had swung over to the negative outlook a while ago. The reasons for stock market crash don’t particularly matter. It will be interesting to see if this volatility cluster continues. Maybe it will soon blow over, maybe it won’t. But whatever happens it will not be random. It never is.

http://hedgefund.blogspot.com

WARAN (Option)

Perdana Wahyu Santosa

Waran adalah salah satu instrumen pasar untuk memiliki HAK (rights), tak ada unsur kewajiban, sehingga pemegang waran mempunyai hak untuk memesan suatu efek terlebih dahulu dibandingkan mereka tidak memiliki waran. Waran juga sering disebut anak saham oleh para praktisi pasar modal.

Karakter waran mirip dengan option lainnya dimana ada masa berlaku penebusan (exercise) namun biasanya lebih lama dibanding rights lainnya. Pada umumnya waran dapat ditebus hingga 3 tahun dan lebih dari itu dianggap kehilangan haknya atau hangus. Rights lainnya hanya sekitar 3 bulan saja.

Waran sendiri memiliki masa aktif sejak 1st exercise-nya yang berarti sebelum tanggal penebusannya-nya, waran tidak dapat ditebus. Namun waran bebas diperjual-belikan di pasar layaknya saham sejauh waran tsb mempunyai likuiditas yang baik. Maka harga waran pun dapat berfluktuasi yang pada umunya mengikuti harga saham induknya sebagai underlying asset-nya. Secara teknis kode waran hampir sama dgn kode emiten-nya hanya ditambah huruf -w dibelakangnya. Misalnya waran untuk saham Bakrie Telekomunikasi yang kodenya BTEL maka warannya BTEL-W dst.

Seperti halnya option lainnya, pada saat exercise dapat IN The Money dimana harga waran plus harga penebusan dan administarsinya lebih kecil dari harga sahamnya di pasar, artinya pemegang waran mendapatkan keuntungan karena seluruh biaya waran masih di bawah harga sahamnya. Namun jika situasinya terbalik, maka dinamai OUT of The Money karena biaya waran melebihi harga saham pada saat di exercise sehingga pemegang waran akan mengalami kerugian. Namun, pemegang waran mempunyai hak untuk tidak mengexercise-nya jika dianggap merugikannya.

Dalam prakteknya harga waran dipengaruhi oleh berbagai faktor seperti kinerja keuangan, prospek bisnis kedepan, kualitas manajemen, situasi makro ekonomi, stabilitas politik dan persepsi pelaku pasar terhadap emiten waran tsb. Disamping itu, harga waran juga tergantung pada penggunaan dana hasil waran oleh emiten serta harga penebusan (exercise) waran tersebut.

Selama menunggu 1st exercisenya, waran yang diperdagangkan biasanya naik cukup signifikan terkadang melebihi kenaikan sahamnya, namun menjelang tanggal exercisenya sering mengalami penurunan terlebih dahulu. Para traders waran sering memanfaatkan siklus seperti ini untuk mencari keuntungan sesaat sebaliknya para investor jangka panjang tetap hold sampai exersise-nya. Penurunan waran jelang exercise-nya hanyalah bersifat temporary saja karena para traders biasanya melakukan profit taking untuk merealisasikan keuntungannya. Jika kinerja dan prospek bisnis emiten cukup baik dan menjanjikan maka harga saham maupun warannya kembali naik mencari harga wajarnya.

Siklus kembali terulang, dimana waran mendekati masa expired date-nya, maka harganya kembali turun dan berulang seperti masa 1st exercise-nya. Kemudian akan naik lagi jika long term performance emiten menjanjikan prospek bisnis yang baik. Disamping itu, ada juga waran yang gratis diberikan kepada pemegang saham yang biasanya diberikan sebagai “pemikat” saat perusahaan melakukan penawaran perdana kepada pubilik (IPO) atau diberikan cuma-cuma pada saat rights issue.

Semoga bermanfaat bagi kita semua.

Price Earning Ratio (PER)

Perdana Wahyu Santosa

PER: Indikator penting di pasar modal..
Definisi: adalah suatu rasio yang menggambarkan bagaimana keuntungan perusahaan atau emiten saham (company’s earnings) terhadap harga sahamnya (stock price). Perhitungan rasio P/E atau PER dilakukan dengan cara membagi harga saham saat ini (current price of the stock) dengan keuntungan tahunan persaham (annual earnings per share).

Misalkan emiten saham ABCD mempunyai keuntungan bersih persaham (earning per share) sebesar Rp.200, dimana saat ini harga sahamnya Rp.2.000,- perlembar maka PER ABCD adalah 10. Artinya jika kita berinvestasi saat ini pada saham ABCD maka payback period-nya sekitar 10 tahun karena kita membeli saham tsb dengan 10 kali laba bersih persahamnya dengan asumsi inflasi 0% dan ABCD mempunyai tingkat keuntungan tetap Rp. 200,- per saham.

Untuk mendapatkan tingkat imbal hasil saham (return) maka cukup dihitung dengan 1/PER saja, sebagai contoh imbal hasil ABCD adalah 1/10 yaitu 10% pertahunnya. Kemudian kita bandingkan dengan return pasar, apabila return saham lebih tinggi dari return pasar maka saham tsb layak dibeli begitu juga sebaliknya. PER juga dapat dipakai untuk membandingkan kinerja antar saham atau antar sektor bahkan antar pasar dalam skala regional ataupun global.

PER juga merupakan angka psikologis bagi value investor dimana PER yang kecil akan lebih menarik dibandingkan dengan PER tinggi. PER rendah ini disebabkan oleh laba per saham yang relatif tinggi dibandingkan dengan harga sahamnya sehingga tingkat returnnya lebih baik dan payback period-nya lebih singkat lagi. PER yang kecil merupakan salah satu pertimbangan utama bagi value investing disamping faktor-faktor lainnya.

Maka PER saham yang lebih tinggi dari PER pasar kurang baik untuk investasi jangka panjang namun dapat dilakukan untuk short-run atau trading dengan pertimbangan teknikal saja. Seorang investor yang cerdas akan menghindari saham dengan PER tinggi apalagi saham tsb mempunyai volatilitas yang tinggi sehingga memiliki potensi resiko yang tinggi pula.

Pada saat ini dimana harga saham berjatuhan, maka PER saham anjlok drastis hampir sebesar rata-rata 60% dan PER pasar sudah di bawah 10, maka ini merupakan sinyal kuat untuk memulai investasi nilai seiring dengan momentum krisis ekonomi. Bahkan beberapa saham unggulan sudah mencapai PER di bawah 5. Bagi value investor momentum ini merupakan peluang investasi jangka panjangnya.

Semoga bermanfaat, selamat berinvestasi…

Price to Book Value (P/BV)

Perdana Wahyu Santosa
Admin Value Investor Forum

Secara umum, P/BV adalah sebuah indikator penting dalam investasi walaupun sebagian menganggap sudah kurang relevan lagi karena berbagai alasan. Namun bagaimanapun juga P/BV ini merupakan rasio yang secara luas dipakai diberbagai analisis sekuritas dunia. Rasio P/BV ini disefinisikan sebagai perbandingan nilai pasar suatu saham (stock’s market value) terhadap nilai bukunya sendiri (persaham).

Perhitungannya dilakukan dengan membagi harga saham (closing price) pada kuartal tertentu dengan nilai buku kuartal persahamnya. Beberapa pihak menyebutnya dengan “price-equity ratio”

Rumus yang digunakan adalah:

P/BV= Harga Saham/(Total Assets-Intangible Assets dan Liabilities)

Semakin rendah nilai P/BV suatu saham maka saham tsb dikategorikan undervalued yang mana sangat baik untuk investasi jangka panjang. Nilai rendah rasio ini harus disebabkan oleh rendahnya harga saham, sehingga harga saham berada dibawah nilai bukunya atau nilai sebenarnya.

Namun rendahnya nilai P/BV ini juga dapat mengindikasikan menurunnya kualitas dan kinerja fundamental emiten ybs (fundamentally wrong). Oleh karena itu, nilai P/BV harus kita bandingkan juga dengan P/BV sektor yang bersangkutan. Apabila terlalu jauh perbedaannya dengan P/BV industrinya maka sebaiknya perlu dianalisis lebih dalam lagi.

Menariknya, P/BV ini juga memberikan sinyal kepada investor apakah harga yang kita bayar/investasikan kepada perusahaan tersebut terlalu tinggi atau tidak jika diasumsikan perusahaan bangkrut tiba-tiba (bankrupt immediately). Karena jika perusahaan bangkrut, maka kewajiban utamanya membayar hutang terlebih dahulu, baru sisa aset (kalau ada) dibagikan kepada para pemegang saham. Ada kelemahan rasio keuangan ini, dimana nilai ekuitas dipengaruhi langsung oleh saldo laba perusahaan yang diakumulasi dari laba/rugi pada income statement.

Jadi konsep utama P/BV adalah kapitalisasi pasar dibagi oleh nilai buku. Nilai buku dengan basis seluruh perusahaan atau persahamnya saja. Rasio ini jelas membandingkan nilai pasar terhadap nilai perusahaan berdasarkan laporan keuangan (financial statements). Maka dapat diartikan bahwa semakin tinggi nilai P/BV suatu saham mengindikasikan persepsi pasar yang berlebihan terhadap nilai perusahaan dan sebaliknya jika P/BV rendah maka diartikan sebagai sinyal good investment opportunity dalam jangka panjang.

Namun untuk beberapa jenis perusahaan, rasio P/BV ini kurang ampuh lagi karena adanya kesulitan mendasar bagi akuntansi tradisional untuk perusahaan berbasis teknologi tinggi. Asset utama perusahaan jenis ini adalah ”intellectual property” yang merupakan ”great value” yang sulit dicatatkan dalam akuntansi keuangan biasa. Sehingga book value perusahaan jenis ini tidak merefleksikan kekayaan sebenarnya dari perusahaan teknologi ini.

Secara umum nilai P/BV value ini lebih diminati oleh value investor ketimbang growth investor.

Selamat berinvestasi,