Science topic

Option Pricing - Science topic

Explore the latest questions and answers in Option Pricing, and find Option Pricing experts.
Questions related to Option Pricing
  • asked a question related to Option Pricing
Question
5 answers
Power and gas retailers, are exposed to a variety of risks when selling to domestic customers. Many of these risks arise from the fact that customers are offered a fixed price, while the retailer must purchase the gas and power to supply their customers from the wholesale markets. The risk associated with offering fixed price contracts is exacerbated by correlations between demand and market prices. For example, during a cold spell gas demand increases and wholesale prices tend to rise, whilst during milder weather demand falls and wholesale prices reduce.
Relevant answer
Answer
Examples of uncertainty-based risks include:
  • damage by fire, flood or other natural disasters.
  • unexpected financial loss due to an economic downturn, or bankruptcy of other businesses that owe you money.
  • loss of important suppliers or customers.
  • decrease in market share because new competitors or products enter the market.
  • asked a question related to Option Pricing
Question
2 answers
Exactly from which date gold options are introduced on gold futures in India and on which derivatives exchange.
is the historical data on gold options( option price,strike price, open interest, no. of contracts etc.,) available. if so, from which data?
please let me know
thanks in advance
Relevant answer
Answer
vest in the World's most Popular Assets. Start Trading Now with Our Free Demo Account. Online Stock Trading & Investment Platform. 10$ Minimum Deposit. 1$ Minimum Investment. 103 604 853+ Traders. 1$ Minimum Trade Amount. Free Education. Fast Payouts.
  • asked a question related to Option Pricing
Question
2 answers
When the value of our Trading Account is PI and our cash is equal PI-qS.
q is number of shares of stock (S).Where q is between one and minus one.(why?)
we know:
  1.  dPI=r(PI-qs)ds+qds
  2. ds=s(mu)dt+s(sigma)dX
Relevant answer
Answer
n the theory of evolution and natural selection, the Price equation (also known as Price's equation or Price's theorem) describes how a trait or allele changes in frequency over time. The equation uses a covariance between a trait and fitness, to give a mathematical description of evolution and natural selection. It provides a way to understand the effects that gene transmission and natural selection have on the frequency of alleles within each new generation of a population. The Price equation was derived by George R. Price, working in London to re-derive W.D. Hamilton's work on kin selection. Examples of the Price equation have been constructed for various evolutionary cases. The Price equation also has applications in economics.[1]
It is important to note that the Price equation is not a physical or biological law. It is not a concise or general expression of experimentally validated results. It is rather a purely mathematical relationship between various statistical descriptors of population dynamics. It is mathematically valid, and therefore not subject to experimental verification. In simple terms, it is a mathematical restatement of the expression "survival of the fittest" which is actually self-evident, given the mathematical definitions of "survival" and "fittest".
  • asked a question related to Option Pricing
Question
4 answers
By introducing certain constraints, It is common that in some of the existing literature that solves the American style options, the early exercise feature and the Greeks are either not computed accurately or unavailable.
I am seeking insight and would love to inquire about various numerical, analytical, and/or analytical approximation techniques for computing the early exercise feature in a high-dimensional American options pricing problem.
Relevant answer
Answer
Thank you, J. Rafiee, Lilian Mboya and Paul A Agbodza for the great suggestion and insight. I will go through all your suggestions accordingly.
  • asked a question related to Option Pricing
Question
3 answers
Hi Guys,
I am trying to do option pricing using QuantLib in Java, I have downloaded the relevant jar library and also the dll and they work perfectly. I am just looking to find a simple example of option pricing code in Java which I can then extend. There is a C++ example in here:
But I can not figure out how to create the Java version.
Cheers
Pooia
Relevant answer
Answer
What a pain. . Looks like this has not been supported for some time. The joys of using open source software
Have not used it but what about Strata opengamma.
have you tried posting a question on the quantlib user group.
you will have to use SWIG. To link the C++ version of quantlib to Java. sounds messy
  • asked a question related to Option Pricing
Question
5 answers
Urbon call options are Islamic terms as an alternative to option pricing. It is needed in the project.
Relevant answer
Answer
Following
  • asked a question related to Option Pricing
Question
26 answers
There are main categories of financial markets like stock markets, bond Markets, sukuk, .. Etc
Kindly, could you write what are all other categories of financial markets with the main references which discuss the details of financial markets or something if them
Thanks for your kind consideration
Regards
Ahmed
Relevant answer
Answer
Dear Ahmed,
The attached document is part of my class notes in Investments Course.
However, if you need some references, below are some potential ones (Research Papers, Books, and Textbooks):
1. Al Janabi, Mazin A. M., and Arreola Hernandez, Jose, Forecasting of dependence, market and investment risks of a global index portfolio”. Journal of Forecasting, Vol. 39, No. 3, pp. 512-532, 2020. [Publisher: Wiley-Blackwell].
2. Al Janabi, Mazin A. M., Ferrer, Roman, and Shahzad, Syed Jawad Hussain, “Liquidity-adjusted value-at-risk optimization of a multi-asset portfolio using a vine copula approach”. Physica A: Statistical
3. Al Janabi, Mazin A. M., Grillini, Stefano, Sharma, Abhijit, Ozkan, Aydin, “Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model“. International Review of Financial Analysis, Vol. 64, pp. 145-158, 2019. [Publisher: Elsevier, Inc.]
4. Al Janabi, Mazin A. M., “Derivatives Securities in Emerging MENA Markets: Structuring Lessons from other Financial Markets”, Journal of Banking Regulation, Vol. 13, No. 1, pp. 73-85, 2012. [Publisher: Palgrave Macmillan Publishers Ltd.].
5. Al Janabi, Mazin A. M., “Internal Regulations and Procedures for Financial Trading Units”, Journal of Banking Regulation, Vol. 9, No.2, pp. 116-130, 2008. [Publisher: Palgrave Macmillan Publishers Ltd.].
6. Al Janabi, Mazin A. M., “On the Inception of Sound Derivative Products in Emerging Markets: Real-World Observations and Viable Solutions”, Journal of Financial Regulation and Compliance, Vol. 14, No. 2, pp. 151-164, 2006. [Publisher: Emerald Group Publishing Limited].
7. Al Janabi, Mazin A. M., “On the Use of Value-at-Risk for Managing Foreign Exchange Exposure in Large Portfolios”, Journal of Risk Finance, Vol. 8, No. 3, pp. 260-287, 2007. [Publisher: Emerald Group Publishing Limited].
8. Al Janabi, Mazin A. M., “Internal Risk Control Benchmark Setting for Foreign Exchange Exposure: The Case of the Moroccan Dirham”, Journal of Financial Regulation and Compliance, Vol. 14, No. 1, pp. 84-111, 2006. [Publisher: Emerald Group Publishing Limited]
9. Al Janabi, Mazin A. M., “Foreign Exchange Trading Risk Management with Value at Risk: Case Analysis of the Moroccan Market”, Journal of Risk Finance, Vol. 7, No. 3, pp. 273-291, 2006. [Publisher: Emerald Group Publishing Limited].
10. Al Janabi, Mazin A. M., “Optimal Commodity Asset Allocation with a Coherent Market Risk Modeling”, Review of Financial Economics, Vol. 21, No. 3, pp. 131-140, 2012. [Publisher: Elsevier, Inc.]
11. Al Janabi, Mazin A. M., “Optimal and Investable Portfolios: An Empirical Analysis with Scenario Optimization Algorithms under Crisis Market Prospects”, Economic Modelling, Vol. 40, pp. 369-381, 2014. [Publisher: Elsevier, Inc.]
12. Al Janabi, Mazin A. M., Arreola Hernandez, Jose, Berger, Theo, Khuong Nguyen, Duc, “Multivariate Dependence and Portfolio Optimization Algorithms under Illiquid Market Conditions”, European Journal of Operational Research, Vol. 259, No. 3, pp. 1121-1131, 2017. [Publisher: Elsevier, Inc.]
13. Al Janabi, Mazin A. M., Khuong Nguyen, Duc, Arreola Hernandez, Jose, Hammoudeh, Shawkat, Reboredo, Juan Carlos, “Global Financial Crisis and Dependence Risk Analytics of Sector Portfolios: A Vine Copula Approach”, Applied Economics, Vol. 49, No. 25, pp. 2409–2427, 2017.[Publisher: Routledge; Taylor & Francis Group].
14. Al Janabi, Mazin A. M., “Liquidity Risk Management in Emerging and Islamic Markets in Post-Financial Crisis in Gulf Cooperation Council”, in M. Kabir Hassan, University of New Orleans (Ed.), The Edward Elgar Handbook of Empirical Studies on Islam and Economic Life, 2017. [Publisher: Edward Elgar Publishing]
15. Al Janabi, Mazin A. M., “Value at Risk Prediction under Illiquid Market Conditions: A Comparison of Alternative Modeling Strategies”, in Buchanan, Bonnie, Nugyyen, Duc Khuong, and Boubaker, Sabri (Eds.), Risk Management in Emerging Markets: Issues, Framework and Modeling, 2016. [Publisher: Emerald Group Publishing Limited]
16. Al Janabi, Mazin A. M., Khuong Nguyen, Duc, Arreola Hernandez, Jose, Hammoudeh, Shawkat “Time lag dependence, cross-correlation and risk analysis of U.S. energy and non-energy stock portfolios”, Journal of Asset Management, Vol. 16, No. 7, pp. 467-483, 2015. [Publisher: Palgrave Macmillan Publishers Ltd.]
17. Al Janabi, Mazin A. M., “Scenario Optimization Technique for the Assessment of Downside-Risk and Investable Portfolios in Post-Financial Crisis”, Int. J. of Financial Engineering (Formerly, Journal of Financial Engineering), Vol. 2, No. 3, pp. 1550028-1 to 1550028-28, 2015.[Publisher: World Scientific Publishing Co., Inc.]
18. Al Janabi, Mazin A. M., “Tactical Risk Analysis in Emerging Markets in the Wake of the Credit Crunch and Ensuing Sub-prime Financial Crisis”, in Nugyyen, Duc Khuong, Arouri, Mohamed and Boubaker, Sabri (Eds.), Emerging Markets and the Global Economy: A Handbook, pp. 413-446, 2014. [Publisher: Elsevier, Inc.].
19. Al Janabi, Mazin A. M., “Risk Analysis, Reporting and Control of Equity Exposure: Viable Applications to the Mexican Financial Market”, Journal of Derivatives & Hedge Funds, Vol. 13, No. 1, pp. 33-58, 2007. [Publisher: Palgrave Macmillan Publishers Ltd.].
20. Al Janabi, Mazin A. M., “Trading Risk Management: Practical Applications to Emerging-Markets”, in Motamen-Samadian S. (Ed.), Risk Management in Emerging Markets, Palgrave/MacMillan, United Kingdom, pp. 91-136, 2005. [Publisher: Palgrave Macmillan Publishers Ltd.].
21. Al Janabi, Mazin A. M., “Financial Risk Management: Applications to the Moroccan Stock Market”. Consulting/Advisory Book in Financial Trading Risk Management, ISBN: 9954-413-47-2, Al Akhawayn University in Ifrane (AUI), Ifrane, Morocco, 2005. [Publisher: AUI University Press].
22. Al Janabi, Mazin A. M., “Formulation of Successful Derivatives Products in Emerging-Markets”. Consulting/Advisory Book in Financial Risk Management, ISBN: 9954-413-30-8, Al Akhawayn University in Ifrane (AUI), Ifrane, Morocco, 2003. [Publisher: AUI University Press].
23. Fundamentals of Investments: Valuation & Management, Jordan & Miller, 5th Edition (2010), McGraw-Hill International Edition.
24. Investments: Analysis and Management Charles P. Jones, (2007), 10th edition, John Wiley and Sons.
25. Benninga, Simon, Financial modeling, 3rd edition, The MIT Press, Cambridge, Massachusetts, 2008.
26. Robert Haugen, Modern Investment Theory, 5th Edition, Prentice Hall, 2001.
27. Alexander, Sharpe, Bailey, Fundamentals of Investments, 3rd Edition, Prentice Hall, 2001.
28. Reilly, Frank, Keith C. Brown, Investment analysis and portfolio management, South-Western College Pub; 10th edition, 2011.
29. Chincarini, Ludwig B., Quantitative Equity Portfolio Management: An Active Approach to Portfolio Construction and Management (McGraw-Hill Library of Investment and Finance), 2006.
30. Zvi. Bodie, Alex Kane, Investments, McGraw-Hill Education; 10th edition, 2013.
31. Burton, G., Malkiel, A Random Walk Down Wall Street, W. Norton & Company; 9 edition, 2007.
32. Edwin J. Elton, Martin J. Gruber, Stephen J. Brown, William N. Goetzmann, Modern portfolio theory and investment analysis, 9th edition. Wiley, 2014.
33. Saunders A. and Cornett M., Financial Markets and Institutions (The Mcgraw-Hill / Irwin Series in Finance, Insurance and Real Estate) 6th Edition, 2014.
34. Jacque, Management and Control of Foreign Exchange Risk, Kluwer Academic Publishers, 1996.
35. Giddy, Global Financial Markets, D.C. Heath, 1994.
36. Dufey and Giddy, The International Money Market, Prentace Hall, 2nd edition, 1994.
37. Brealey, Myers and Marcus, Fundamentals of Corporate Finance, McGraw-Hill.
38. Brealey and Myers, Principles of Corporate Finance, McGraw-Hill.
39. Ross, Westerfield and Jordan, Essentials of Corporate Finance, McGraw-Hill.
40. Chambers, Lacey, Modern Corporate Finance, Theory and Practice, Pearson Education, Addison Wesley.
41. Rao, Financial Management: Concepts and Applications, South-Western College Publishing.
Prof. Dr. Mazin A. M. Al Janabi
Full Professor of Finance & Banking and Financial Engineering
EGADE Business School, Tecnologico de Monterrey,
Santa Fe Campus, Mexico City, Mexico.
  • asked a question related to Option Pricing
Question
7 answers
It is required for the preparation of the presentation.
Relevant answer
Answer
Sir J. W. Nieuwenhuis, in this book, the derivation for multiple stocks is not clear. Please give me a reference where the derivation for multiple stocks is given.
  • asked a question related to Option Pricing
Question
8 answers
I take a Derivatives Course and the professor uses Matlab. Are there any good finance related books for Matlab?
Relevant answer
Answer
Hi,
Stochastic Simulation and Applications in Finance with Matlab Programs. Huynh, Lai and Soumaré.
  • asked a question related to Option Pricing
Question
6 answers
I have to use "Merton Jump diffusion model" for estimating the price of options for my research work.
i am using VBA as a back-end program for MS-Excel.
I have calcualted all the variables required for the model except the two variables
1. Number of jumps per year and
2. % of the total volatility explained by the jumps.
how to estimate those two variables.
i read program manual, but no information is available about it.
can anybody help in in this regard
thanks in advance
Relevant answer
Answer
I teach Merton's model among others at Copenhagen University. My notes are freely available on slideshare:
Slide 139 to 149 are dedicated to Merton's jump model.
In addition, I explain the model and its implementation in C++ in my book:
Chapter 13, section 13.2.
Finally, I would advise to avoid VBA, instead, code models in C++ and export your code to Excel. I wrote a tutorial to show how to do this quickly and with minimal pain:
You can also download my Merton code in:
I hope it helps. Kind regards.
  • asked a question related to Option Pricing
Question
5 answers
As we know implied volatility is derived by interpolation of market price and the guess of the volatility by using the option pricing formula.
what are the real life applicaiton of implied volatiltiy
thanks in advance
Relevant answer
Answer
An option trader needs the implied volatility, at least of liquid options, not to price, the price is given by the market, but to hedge the options, by means of the underlying assets and a proxy of a bankaccount. I advise you, to pay a visit to option traders, in order to get a picture of what is going on in the trading pit!
  • asked a question related to Option Pricing
Question
7 answers
I have to use Heston estimating the price of energy options(gas and electricity) for my research work
Iam using Matlab for model calibration and I have derived first the short term forward contract price(following a paper by Kellerhalls 2001)
I have since acknowledged the vast literature on Heston but all of it is on equity options
Can i calibrated Heston parameters using the derived forward price and day ahead spot prices or observed futures prices?
Relevant answer
Answer
Hello Leon
Thank you for your discussion on my research. I do understand the strong seasonality patterns of gas but iam thinking if my model use hourly data won't that put the spikes aside. Of course i have also modeled Heston with jumps but would it be practically usable? There is a paper by Geman and Eyedland(1998):Power derivatives if you have access please share because the one iam following is silent on electricity short term model , why spikes and seasonal effects are not modeled there. Is it also possible to get hourly option prices? I have coded in Matlab Heston calibration using monthly implied volatilities. Please guide further.
  • asked a question related to Option Pricing
Question
14 answers
There are a lot of efficient and accurate methods about the PDEs fractional order, but can someone use these methods in option pricing (Black-Scholes or etc.) because of arbitrage?
Relevant answer
Answer
Dear Fabrizio,
Thank you very much for your nice answer...
  • asked a question related to Option Pricing
Question
4 answers
I am working on Introduction to Levy processes where I need to derive an option price using Esscher Transform and compare the derived option price with Black-Scholes model. The comparison part is giving a challenge. I am using Eberlein and Prause as a guide. Describing one of the examples in the paper is my challenge.  
I will very glad if the question is giving a quick attention.
Thanks in advance.
Relevant answer
Answer
You may take a look at Gerber, Shiu. "Option Pricing by Esscher Transforms" 1994 and especially Boyarchenko, Levendorski "Non-Gaussian Merton-Black-Scholes Theory"
  • asked a question related to Option Pricing
Question
5 answers
This involves cnx nifty indrx options, out of money call and put options.This strategy gives positive returns every month, so to show this as a useful strategy in future as it has remained in past. What kind of tests should i use.
Relevant answer
Answer
You need to have a reference return rate to compare. For example, if the average return in the market is 1.5% per year and you have 2% per month, a simple standard score may be used:
Z = (Xobs - Xmarket) / S
Elsewhere the denominator may be sigma. Here, we use S. For example, if your monthly returns for 12 months are: 
Jan 2.00
Feb 2.50
Mar 2.30
Apr 2.40
May 2.50
Jun 2.80
Jul 2.20
Aug 2.10
Sep 2.00
Oct 2.40
Nov 2.50
Dec 2.20
MEAN: 2.33
STD: 0.24
For the month of January: (2 - 1.5) / 0.24 = 2.08. The standard score is 2.083. Now go to the Z table, look for the critical value 2.08, the corresponding F(X) or percentage probability is 0.981 or 98.1%. Compare this to 95% confidence interval (if using 95% CI), then a percentage rate return of 2% in January compared to the market yield is 1.5% is statistically significant. Do the same for all months. Do it once for the entire year by using the mean for 12 months or 2.33.
I hope this is hopeful. Cheers. See some links below for materials on standard score.
  • asked a question related to Option Pricing
Question
6 answers
Hello guys,
Please, I will like to know how orthogonal polynomials in particular (Hermite) can be applied to finance in option pricing.
Thanks
Relevant answer
Answer
Dear Oluwatosin,
Hermite polynomials and other orthogonal polynomials are exploited to construct  financial market models with better probabilistic properties. As a result, the option pricing formulas (in particular, the Black-Scholes formula) can be improved too.
With best regards,
Alexander Melnikov.
  • asked a question related to Option Pricing
Question
4 answers
Hi,
  1. Is there any demand to implement high-order numerical schemes to Black Scholes model for option pricing? I saw some papers regarding this issue but it's not really clear wheather there is substantial commercial demand for this kind of things.
  2. What are the open questions in the field of option pricing and numerical methods? Are there any essential disadvantages in current methods that need to be solved or improved somehow?
Thanks,
Ory.
  • asked a question related to Option Pricing
Question
1 answer
One ex-VP at a big investment bank said once that it uses Racorean’s equation (see. http://arxiv.org/abs/1307.6727 ) for pricing bitcoin options.
-σ^4/r(σ^2+r) (d^2 ψ_((S) ))/(dS^2 )+1/S^2 ψ_((S) )=r/σ ψ_((S) )
Is there anybody else that uses the time-independent pricing for pricing bitcoin options or for trading binary /weekly/American options?
Relevant answer
Sorry about this but I thought Bitcoins have been made illegal somewhere and anyway I have shown (all papers on my RG page) fiat money has enough problems of its own so far as financial and asset markets are concerned. Instead of merging with other types of private money you can socially improve welfare by merging with more innovative financing options.
  • asked a question related to Option Pricing
Question
2 answers
I am using a barrier option, in particular a Down-And-Out call option, to simulate default probability of a firm where the asset values follow a geometric brownian motion. For reasonable values of volatility, drift, barrier and strike price, the code returns me default probability larger than one. The formula for PD is that of Black,Cox (1976) but with constant barrier (Reisz, Perlich 2007).
Relevant answer
Answer
Hello Markus,
many thanks for your answer. Yes, the formula that I am working is (A5). It should be the same as in Black,Cox (1976) but with a constant barrier instead of a time dependent barrier. Is not it? I checked also other sources and it should be right, so I do not know if I need to add some boundary condition (for example, PD=min(PD,1)), but I thought that as probability measure, it was constrained to be between 0 and 1 by construction.