Questions related to Portfolio Management
Dear scientific community,
I would be very interested to hear your input regarding the scaling-up of LCA studies to a portfolio level. I know there is a plethora of product LCAs and plenty of them consider several individual products or product variants in parallel. However, I have not found an awful lot of studies that extend to several hundred, let alone thousands of individual products within the scope of one study (as opposed to equally as many individual case studies).
Surely, more people have approached this apparent research gap. So for anyone that has been active in this area: I would greatly appreciate you sharing what experience you have made or you pointing me at any related publications in the field.
Many thanks and best regards
P.S: If you are interested what my colleagues and I have done in this field, feel free to check this framework article and the case study we presented at LCM 2021 conference:
Conference Paper The Sustainability Data Science Life Cycle for automating mu...
Conference Paper Detecting environmental hotspots in extensive portfolios thr...
I'm replicating Fama-French five factor mode. I have formed factor portfolios. I'm not sure how to the average monthly percent excess returns for portfolios. In other words, I want to get the Table 1 in their paper.
Thanks in advance
I would like to investigate some areas in Project/Progaram or Portfolio management to an extent of creating a review paper.
I am also open for areas in risk management, scheduling managemnt and Work Breakdonw Structure.
I am working on portfolio optimization using lower partial moment of order 1, can someone help me how to implement LPM-1 in excel sheet using "tau" as my threshold value as 0.00% and order (n) as 1.
Thank you all in advance for your contributions to my question.
Curious to know how Art as an alternative asset can be included in an investor's portfolio to generate significant alpha (if possible); and how & to what extent can this asset be fully maximised as a hedge or diversification tool?
Understand that this is a relatively new area with limited historical prices available for further analysis and research, but I am highly curious as to how Art can potentially be used as an investment tool.
I'm open to further reading on this topic! If anyone has solid research materials to share with me—please do!
I am keen on venturing into art portfolio management, specifically including Art as an asset into financial portfolios, and not just pure-art portfolios.
I'd like to know how I can begin analysing and tracking the performance of an Art-inclusive investment portfolio? Will traditional models be suitable/optimal for this?
What is the best way to construct investment portfolios: based on asset prices or based on the changes in asset prices through time? E.g., if Asset A is 55 in 2010 and 60 in 2011, should I use 55 and 60 as data points or should I use 5 (i.e, 60 minus 55)? Thank you in advance.
I am planning on constructing a Fama french 3 factor model for a period from 1.1.1998-31.12.2015 for a portfolio of about 120 stocks. I have collected the monthly returns for each stock over 36 months since their IPO. The process of doing a Fama french 3 factor model for a single stock is very straight forward as seen in this video: https://www.youtube.com/watch?v=b2bO23z7cwg
However, how should I proceed with a portfolio with returns that all have different starting dates (as each firms have a different IPO date)?
My tough was as follows:
- Calculate the average 1 month return, 2 month return,, 3 month return, ….36 month return from all the stocks in the portfolio.
- Calculate the 1 month average, 2 month average, 3 month average, ….36 month average of the Rf, HML, SMB, Mkt-Rf
- Subtract 1 month average Rf from average 1 month return, repeat until the 36th month.
- Proceed with running the regression.
Many papers, such as the one by Levis (The Performance of Private
Equity-Backed IPOs), have used the Fama French 3 factor model but do not explain the mechanics behind the process.Any help is more than appreciated.
Any help is greatly appreciated
Any suggestion about the usage of graph theory and network analysis in the stock market (e.g. price prediction, portfolio management, correlation-based network representation of the market, etc.) would be appreciated.
I am writing this to gather some suggestions for my thesis topic.
I am a student of MSc Quantitative Finance. I am in need of some suggestions from the experienced members for a research topic in Portfolio management.
My expertise are in statistics and empirical analysis. I believe that I will be able to present some good work in field portfolio analysis. Currently, I am researching for some good topics where I can apply machine learning or machine intelligence e.g. for forecasting portfolio performance or may be use it to asses portfolio optimization strategies.
I will be very grateful for you suggestions and guidance. If it suits you, you can also email me on email@example.com
- Is there a benefit of having lower gap between 'in-sample' variance of portfolio daily returns and 'out-of-sample' variance of portfolio daily returns? (= better estimates the out-of-sample variance)
Question in more detail
- I have developed a way of optimizing a portfolio, based on Global Minimum Variance portfolio optimization.
- There are upside and downside of my portfolio optimization method.
cons : It cannot lower the `out-of-sample variance' of portfolio daily returns than the GMV portfolio. In other words, my portfolio optimization method fails to achieve better portfolio performance such as Sharpe ratio.
pros : However, my portfolio optimization method has lower gap between 'in-sample variance' and 'out-of-sample' variance than the GMV portfolio.
- For illustration, let me give you an example. During training period to come up with how much weight to put on each stock, GMV portfolio optimization calculates the stock weight with variance 100 of daily returns. However, during the investment period (test period), it gives me 125 for 'out-of-sample' variance.
- My portfolio method gives me 150 variance for 'in-sample variance' and 130 for 'out-of-sample' variance. As you can see, the actual variance is still low with the result of GMV portfolio optimization method. However, my method expects the 'out-of-sample' variance better than GMV method. GMV method is wrong by 25 percent, while my method is wrong by 13 percent.
- As such, I am curious to know if my portfolio optimization method would be useful in any case of trading in stock market nowadays.
The BCG matrix (named after the Boston Consulting Group that created it) is a portfolio management tool used by a company to help justify investments in products based on their market position. , their growth and the share that each of them represents in terms of turnover... !
The BCG matrix makes it possible to optimize the distribution of resources among the various SBA (Strategic Business Area) of a company.
So, How can the relative market share of the company be measured for a particular SBA?
How do you approach the selection and implementation of an information system for managing projects, programs and portfolios in an organization? What are the main criteria for choosing and implementing a management information system you can recommend?
Most Organizations manage pretty well the latter but have hard time to cope with the first. Breakthrough invention collapses paradigm, and challenges established wisdom that made the Entity successful. We cannot return in the past and fix what lead to the present culture. We can wait for the slow but more and more brutal death by obsolescence or irrelevancy. We can set up skunk works so should the path to be scouted leads to a dead end it doesn't compromise the entire Organization and portfolio management mitigates the risk. We can embrace the world and pray charismatic decision makers don't let their hubris doom all of us. But in fine, better lucky than smart. Open minded expertise, hard work and courageous decision making process help and make our chances.
I have a keen interest in investment, so i want to research what factors play vital role in PMS rendering process.
By reading multiple research papers online. I realized the current portfolio optimization (industry standards) involves building factor models, perform (conditional) value at risk optimizations, (covariance matrix shrinkage) and even robust portfolio optimization and (even though very few people cited, the method to impute price histories when different instruments have different inception dates). But the information is really very scattered, I wonder if anyone could suggest some list of current state of the art portfolio management/ active portfolio managements(trading signals) methods that I could read into to understand more with the goal of being able to implement state of the art methods by myself.
portfolio management best practices in quantitative indicators demonstrate the last condition of the best companies in the business market against risk factors and competitors.
I have worked out a solution on computing the expected return from the market portfolio E(Rm) when the following information is not given:
Expected Market Return'
Beta of Individual assets
Variance of the market returns
Covariance of each security with the market.
We came across different fundamental indicators of firm such as total assets, revenue or current assets of a firm. What is the best forecasting technique that can be used to forecast the future assets in a uni-variate analysis?
Dear colleagues, is there any information or papers about linking good corporate governance to portfolio selection? Thanks in advance for any help.
My area of interest is the effect of interest regime switches on asset allocation. While asset allocation may remain the same under interest rate volatility because of its cycle nature, it should be expected that in order to maximise returns, asset allocation changes with interest rate regime switches. The gist of the research is whether fund managers are taking into account interest rate regime switches in portfolio management, and whether portfolios are optimal. Failure to do so may lead to lower returns for retirees and may be a threat to security in retirement.
I welcome reference to relevant research papers on the subject and any suggestions/comments
I'm currently looking for a scenario tree modeling the return of some stocks or indices. As scenario tree generation is not the focus of my work, but I need some to test my portfolio model, it would be nice, if someone could send me his work. There is no need that the data is up-to-date. Ideally the tree has 3-5 stages and 3-5 stocks/indices.
Thank you very much!
in the moment I'm dealing with time consistency for optimization problems in the sense of Shapiro(2009). My problem in the moment is, that I think that a minimal expected return constraint for the final wealth normally leads to time inconsistent problems but I cannot find any papers about this topic. Carpentier et al. (2012) adresses this question in the Markovian setting, but I cannot find anything for the general one.
This leads to my final questions: Is there some literature adressing the question, how far minimal expected return constraints have effect on the "degree" of time inconsistency of the optimization problem? Are there similar formulations (for example for intertemporal return) that are mitigating this problem?
Thanks for your help.
my idea is to take a property index, for example the Austrian Residential Property Prices Data Index(the actual index can be found under ) and translate it into a risk number to stress the market price of a property portfolio.
I am not sure if measuring the volatility of the index at point t, is a good measure for, "how much market risk is in the current market state".
Any suggestion, what is the best way to do that? Any good paper suggestions?
I appreciate your replies!
I have created a forecasting model, which comes up with future values for a rental index.
Further, I have transformed this volatile values into percentage risk, whereas 100% is the highest point in this values and 0% the lowest.
For example let`s take the time series:
2010 100 -> risk: 0%
2011 150 -> risk: 100%
2012 125 -> risk: 50%
2013 130 -> risk: ~68%
2014 140 -> risk: 75%
I would like to use the risk values on a real estate portfolio, to simulate the outcome and visualize cyclicality for a portfolio manager. Has something like that being done?
Currently, I couln`t find any research doing what I would like to do? However, I was wondering if there exists some related field or research to this idea.
I kindly ask you for good papers / theses of using "risk on property portfolios"?
Thx in advance for your replies!
Dear all members,
In stock market , forex and commodity market many brokers or some external firms give a sure shot suggestions for Trading to the Daily Traders with a monthly or annual charge. For example : they give 5 Intraday calls daily as Buy or sell particular share with Target of some price and stop loss of some price.
When looking after their performance the calls given by them are achieved to extent of atleast 80%. which is a good thing. But my doubt is how to they able to predict it with good success rate. Are they using Technical Analysis or they do fundamental analysis? If they use technical analysis what kind of analysis they incorporate?
I just have a Electre tri software.
I'm going to compare some sorting methods (around 5) in a stock portfolio problem. then I should find some proper sorting methods and softwares.
Working on a research topic, I am faced with this question " How can we propose a Product Portfolio Management framework for Engineer-to-Order industries?" Although, these industries have certain product families, they offer totally different products to their customers, based on what customers need. Sometimes they accept orders from customers, they design products and services just for them, but at the end they notice that the process was not as profitable as what they expected.
So, how can these industries define their product portfolio in a way in which they still have demands and the whole design, manufacturing and delivery process remains profitable for them?
Are there any related case-studies or articles in the literature? Thank you for your help and kind answers in advance.
The requirement of organizational strategy is to provide direction to increase stakeholders’ value at the same time reduce business risks. Strategic decisions today transcendent the boundaries of business, society and ecology. The question is regarding the strategic portfolio management in the complex and uncertain situation.
We are writing an experience report on our empirical model to predict the effort and cost of application management transitions. We have not been able to locate existing models. This may be due to diffuse use of terminology in the field of application management.
Carhart´s 4-Factor-Model is often quoted in Carhart (1997). But as mentioned in this paper he worked out the model in his dissertation 1995. The title is: Survivor Bias and persistence in mutual fund performance. As it is not published, does anyone have this document or knows where to find it?
Rolls shows, that conventional tests of the CAPM are tautological, as, due to its mathmatical properties, any security or portfolio satifies ex-post the CAPM-Equation resp. lies on the SML, as long as the benchmark-portfolio, which is used to calculate the securities or portfolios beta, is efficient.
(A short description and proof is found, for instance, here
However, this has very important implications for CAPM-based performance measures. The Jensen-Alpha, for instance, measures performance ex-post as the distance between the performance of a portfolio, that is predicted by its beta, and its actual performance.
Now, if ex-post any security or portfolio satifies the CAPM-Equation resp. lies on the SML, if the benchmark-portfolio used is efficient, how can the Jesen-Alpha significantly deviate from 0? If course, one reason my be that the benchmark-portfolio is not efficient. That, however, would question the validity of the Jensen-Measure, at all.
Has anyone an idea, how to solve this puzzle?
Small and medium companies that sell to other small and medium companies have limited or no access to credit bureaus.
Those SME do have sometimes historical database of past transactions with its own customers.
Is there any credit algo/model out there, or previous study on calculating credit scoring, default, etc. based on past registered revenue (receivable) vs actual cash-flow information? Another question is related to building optimum portfolio based on receivables vs actual cash flow.