Wednesday, December 7, 2011

Prospective Research areas in Financial Engineering at Qcfinance

Abstract: I have discussed about areas in Finance pertinent to old areas that I have been working and trying to expand and add value to that work with the help of my new knowledge.

Working White Papers (At QCFinance.in):
1) Applying Quantitative Game Theory in International Business and novel methods for computing Nash Equilibria
2) Monte Carlo Simulation for Investment Banking / exotic derivative pricing in MATLAB/R
3) Recent Trends in International business and Game Theory (theory)
4) Strategic Finance for Commercialization of CNT and Decision Tree Analysis (90% complete for Tri Nano)
5) Copula Modeling in MATLAB/R
6) Review of Research Trends in HPC / CUDA for Financial Engineering
7) Merton Model on R / MATLAB

Research areas of Financial Engineering to be applied:
  1. Game Theory
  2. Energy Risk
  3. Nanotech
  4. SMC in Finance
  5. FRA for Nanotech companies
  6. Nano solar
  7. Intentional Business and International politics


There has been good research done in the area of Energy risk and financial aspects of energy, but less has been discovered about the implications of alternative energy solutions like Solar and Fuel Cells. to understand the implications of this new type of energy one needs to know about the conventional financial instruments used and also about the research trends in solar and fuel cells. There are various parameters that define what I company can do to hedge its risk from conventional energy and its instruments to this new area, but this has be done in compatibility with the current financial policy of the company. When I was looking around on the internet there is a very good course called the "Energy Risk Management" which has an excellent amount of reading for the oil and other energy sources.What I will be doing in my research is to add the new Nanotech-energy solutions and its implications. For this one needs to understand the current models and instruments.

SMS(Secure Multi Party computations) is a way of performing secure computations when parties donot want to reveal their data, this becomes very important in the world where no one trust no other and information is the major tool for competitiveness.There are some research papers available on this subject but a comprehensive research is still lacking.

Nanotech is an area where a lot of research is not realizable and it becomes very tough for an company to understand how to use it in the most efficient way. I will be looking ahead to add the findings in this area to my old work.

Game theory which involves a lot of Maths and computations is very rare in financial instruments and there is a lot of scope of imbibing this subject with the current models and how to make it relevant to current research and analysis.

Much of the research of Quant Games are not applied and used in real life, because of many reasons, and in this work I will be working on how these Quant games can be used in the subject of international business. I will link the maths and define some parameters with real modeling options for the subject. Nash Equilibrium is the heart of Game theory. 

This Nash equilibrium takes into account all moves that the opposite party can take, and hence reduces your loss  due to wrong moves. Thus if our competitor is not working on the same he will move to different direction and keep on losing.


The areas that I will show in real sense of Quant Game theory in international business are:
  1. Geometric games
  2. Isovalue surfaces
  3. Differential Games
  4. Multi stage games
  5. Optimality
Their linkages with various real examples are shown to develop a strategy for international business.



International Business & Politics are also closely linked with this idea, because war in middle east always triggers oil prices, and which has a very wide effect on countries like India. So Game theory and strategy can be applied to do Business keeping all these scenarios in mind. Not only game theory but the models of Financial engineering can also be applied to these scenarios of International strategy making.

Will revisit Articles on Game theory + Finance, Nanotechnology + Finance, SMC and Finance, Energy Alt + Finance in the month of Dec 2011.

Green Energy Strategies for implementations:
My research includes working on these parameters:

  • Energy solar cell, financial derivatives on how each movement will affect the expected use and pricing
  • Some breakthrough points in research in solar cells that may trigger the future expected device realization
  • Decision making tree, taking data from neural network using regression
  • Neural network and system and signals engineering, in itself this topic is immense
  • Regression coefficient selection for Green energy models
  • ROE, profit loss models, ratios, etc
  • Game theory on how to move ahead to diversify the scenarios, because other competetiors are working using the same models
  • Demands of oil and crude price and its effect on alternative energy market like solar cell and fuel cells, this can be modeled using regression coefficient
  • Not just technology, politics, wars, crude prices, recessions will also effect the scnerio which needs to be taken into consideration
  • Game theory for research in solar and fuel cells for energy
  • Next research breakthrough in Nano solar and its possible impact, on productions and solar
  • Making the decision tree and pointing the probability
  • Effect of extreme events and research implications on solar energy
  • And also time to commercialize and strategy from a company perspective
  • Important research that will effect are on special type of solar cell and reliability and modeling and manufacturing and making a decision tree on how these things adds up to commercialization
These are the points I am expanding in my research paper.


Strategic Finance in Green Energy
Energy made from solar cell and other alternative forms will be preferred by the consumers of the future. If one can study this behavior and use the financial derivatives on the current energy options and how each movement will affect the expected use and pricing of alternative energy; then he/she could make some good prediction on the usage of alternative energy. This is because energy derivatives and other models can help you to predict the demand of energy as well as price of energy markets of the future.  Macroeconomic factors and their operators: Economy plays an effect on each of the models that we make in the predictive modeling.
Suppose as the price of oil increases there is shift toward the sales of solar cells or fuel cells or wind turbines then these changes can be modeled empirically. As price of oil increases the demand of old decreases and the demand of alt energy product increases [derive Maths relations Sales= ax-by, for simplicity reasons this is taken linear].
Demand = Function (Energy futures, consumer demands, macro economy, technology, growth in current companies, extreme events)
STEP 1: Looking at Energy Derivatives (Crude Oil Prices, Energy, coal)
STEP 2: Inferring expected price and demands & Macro economic factors
STEP 3: Looking at technology breakthroughs, like reliability packaging
STEP 4: Linking both to make a model to find out demand for alternative energy solutions
STEP 5: Making of decision trees and neural networks, using right distributions
STEP 6: Observing financial ratios of current companies and predicting future
STEP 7: Looking for extreme events (Financial Risk Management)
STEP 8: Use Game theory to understand competitors Behavior
STEP 9: Implementation models: HPC, Multi Scale, Reverse Reliability Models
Demands of oil and crude price and its effect on alternative energy market like solar cell and fuel cells; this can also be modeled using regression coefficient using appropriate data, but in this work we have not focused on that. Regression coefficient selection for Green energy models. Energy options vs. investing in green energy alternatives.
Some breakthrough points in research in solar cells that may trigger the future expected device realization. Example of nanotech enabled solar cells, packaging, etc. A. Vora[2] has described the possible breakthrough in technology.  Modeling using HPC[3], multi scale properties, understand things in more details will be an important area. This research can be linked down to the same in modeling the future. This will be one part of the model which will be discussed in detail in this work on how much the research work is going to affect the entire model and to quantify that. We will be using our earlier models like TTC model[4].
Decision making tree and taking data to form neural network using regression models. Smaller version of decision trees are shown in our earlier papers [4]. In this part we will make regression models on how to move to various branches. We will also associate probability distribution to each event in the appropriate manner. Neural network and system and signals engineering, in itself this topic is immense. Because in Neural network we have system (boxes) with input and outputs. Again make a tree on commercialization of Green nano solutions.
ROE, profit loss models, ratios, etc which are the part of any financial analysis. Optimum ratios for green energy models from FRA. Next research breakthrough in Nanotechnology solar and its possible impact, on productions and solar. And I we will list down all areas that will help. And also time to commercialize and strategy from a company perspective: future and current. Energy project finance is another important area. For this data can be collected from the current companies, now after observing the sales of the past we can get some trend about how things have behaved in the past.
Game theory for research in solar and fuel cells for energy. Game theory on how to move ahead to diversify the scenarios, because other competitors are working using the same models. Hence price and strategy adjusts as new and current players take some steps or take a move. We can define some of the games from our readings of game theory, for example if we analyze some special type of games and the Nash Equilibrium of the games then analysis becomes easy. We will be expanding our models of GT from [4].
Effect of extreme events and research implications on solar energy: defined on financial, political, environmental, wars, research breakthroughs etc. Not just technology, politics, wars, crude prices, recessions will also affect the scenario which needs to be taken into consideration. Also international business will play a very important role with this regard. Operators for all such event needs to included. This includes today’s political scenario like wars or anarchies in the middle east which is described by Arpit[2].
Important research that will effect are on special type of solar cell and reliability and modeling and manufacturing and making a decision tree on how these things adds up to commercialization. These technical areas will be discussed in details. Technical knowhow’s on its relation with reliability and packaging.
Proposal on implementing these models on HPC, use of multi scale modeling to find abstraction layers of research.
Contemporary solutions for the perception of the people, and how this would affect the change or sales and which of this part is perception or price movements or other parameters.
Selection of probability distribution: Normal, log normal, tale adjustment, skewness.
Expected implementation: SAS Predictive modeling tools, other options as well
Complexity of research and applicability of nanotechnology in solar cells. Kind of derivative pricing model for the same like Brownian motion models. Linking down physics of nano levels. Linking stochastic calculus for deriving right black sholes models.
 

 [1] A. Vora’s research on breakthrough points on solar cells
[2] A. Ludhiyani’s research on international politics
[3] HPC Research related to this area of R. Patak
[4] Linking Reliability engineering to this area, application of risk old papers, my old research, esp the 2
 

Important points to look into:
  1. Sample games in extreme scenarios, risk cases, game type, maths of games, linking it down to business. Like wars in middle east. 
  2. I am looking at different games that are there so that we can put in some more light in the political international business. 
  3. Decision tree vs game theory or adding the research done in both areas?
  4. Diagrams of decision trees that are used in the system, making diagrams of hypothetical cases.
  5.  Deriving Research from Financial Risk to Political Risk in business.. Quantification of political risk, and adjusting quant methods of derivatives in this place
  6. Polto-Monte-Carlo model for International Business: Where we can put these equations and look at political movements. Brownian motion derivation form stochastic calculus.
References:
[1] springer.game.theory.decisions.interaction.and.evolution.2007.1846284236
[2] Quantitative_and_Qualitative_Games__Volume_58__Mathematics_in_Science_and_Engineering_
[3] 20081188511397467 GAMES AND INFORMATION  FOURTH EDITION
[4] Compleat_Strategyst__Being_a_Primer_on_the_Theory_of_Games_of_Strategy

Recent Trends in International business and Game Theory:

This paper is about a survey of game theory and its application in Finance

How to use research of game theory in here
Decision tree for international business, exploiting the new research
Politics and energy, and politics of energy
Trade and politics, what are the future linkages
Define game types[1,3], game based on number of players [4], change decision tree
Statistics inferences, regression models, probability distributions, and using them in the GT models [2]      Review of research and adding modern tools to international business and Finance
Linking down effects of Financial and Political Scenarios using game theory
 
International Politics & Game Theory Model outlook: How do international games looks like, mathematical games:

Step1: Define the game time

Step 2: Decide the probabilities on each point, and games of cooperation

Step 3: Make the decision tree with the branches (Monte Carlo simulations fittings and motivations)

Step 4: Also check Value at Risk, Extreme events and Distributions

Step 5: Use neural networking

Step 6: Re-check the model

Step 7: Decide the modeling tools

How to make good research presentations.

http://qcfinance.in/research/

Important points includes citing the right reference, using mathematical equations, graphs should be properly made and cited, history and present of the thing should be discussed, online reference of the detailed presentation should be given (ex. Blog entry).

8 comments:

  1. Working White Papers (At QCFinance.in):
    1) Applying Quantitative Game Theory in International Business and novel methods for computing Nash Equilibria
    2) Monte Carlo Simulation for Investment Banking / exotic derivative pricing in MATLAB/R
    3) Recent Trends in International business and Game Theory (theory)
    4) Strategic Finance for Commercialization of CNT and Decision Tree Analysis (90% complete for Tri Nano)
    5) Copula Modeling in MATLAB/R
    6) Review of Research Trends in HPC / CUDA for Financial Engineering
    7) Merton Model on R / MATLAB

    ReplyDelete
  2. Abstract: Exotic derivative pricing is one area which is not explored much, and also pricing or modeling short straddle index and its modeling on R/MATLAB. This is an area which can be explored and computed and then scaled to HPC or CUDA as required. Most of the equations are derieved from B/S and contrains are changed accordingly. Exotic derivative on fixed incmoe or custom indices based on theri strategy has become an important area of research. This work will introduce and explore research dimensions for the subject.

    ReplyDelete
  3. Abstract: Although an important area Quant Game theory and Nash eqlibria has become imporant tool when Monte carlo simluations has taken a big lead on the valuation metodology. We explroe old mathematical theories and propose their applicabilty i monte carlo simuatlions. this reseach brings tohether old classical maths and new omonte calro (computation finance) areas.

    ReplyDelete
  4. Abstract: Copulas have become improtnat, espeically in pricing CDS and tranching deefauly probabilties. Very less applications and modelign is avaiable and researched base don market data. R / MATALB makes modeling very eaasy, and we ahve brought some data from the data feeds and computed correlatiosn from the copula methodoogy.

    ReplyDelete
  5. Abstract: Merton model is extensively used to compute default probability from market rates. OPart of is already uploaded which can retrieve from files of FGGC blog.

    ReplyDelete
  6. Latest Research and Working Papers for 2013
    Deadlines are April End for 2 papers.
    May blank for CFA classes.
    July all for research and nothig but research.

    ReplyDelete
  7. Abstract: Interest rate derivatives and itnerest rate models are also very interesting as they were the reason of mis models combined with wrong computation of prob odf deault in 2008. there is a lot of scoep in their improvement so that we can get a better idea on the pricing and risks of the instruemtns we are using.

    ReplyDelete
  8. http://www.youtube.com/results?filters=long&search_query=monte+carlo+simulation&lclk=long

    ReplyDelete