why defend bp?

why are some on the right defending bp? rich lowry has a great editorial up on nro making the point that we don't have a dog is this fight while some republicans are determined to get bitten.

15.535

looking at the assignments and exams, i think i understand the concepts just fine, although the intricacies of interpreting how management might be manipulating their accounting numbers are not easy.

2

http://mit.edu/wysockip/www has useful stuff but doesn't have all the stuff from class anymore

peg ratios, often cited

3

cash flows over firm's life cycle

trend analysis: cfo vs ebx

red flags: growing discrepancy between net income and cash flows

undervalued liabilities, overcapitalization

investment activity

key: proceeds from exercise of stock options. good?

firm type: growth options vs assests in place

tech, growth: not much depreciation, financing primarily related to equity

airlines: cfo large compared to net income, even in loss years; large depreciation, investing; debt financing

retailers: walmart has large difference between cfo and net income

4

problems with residual income valuation

p/e or m/b with real options?

5

abnormal earnings with dcf (discrete cash flows)

what do analysts use? refs asquith et al., 2001

earnings multiple 99%

p/e 97

relative p/e 35

revenue multiple 15

price-to-book 25

cf multiple 13

dcf 13

eva 2

'model' 4

estimate price multiples for comparable firms avg/median/etc. why not use distro?

if current earnings are not good prediction for future: forward p/e or pro forma earnings (remove non-recurring) or price to operating cash flow

other p/e: peg, p/cf, levered, (debt+equity)/ebitda

m/b market to book

stock screener links

profitability: roa (return on assets)

roa decomposed into profit margin and asset turnover

roe (return on common equity)

roe decomposed into profit margin, turnover, leverage

short term liquidity

current ratio = current assets/current liabilities: short-term debt paying ability

quick ratio = (current assets-inventory)/current liabilities: acid test ratio

long-term solvency

long term debt ratio = long term debt/(long term debt+shareholder's equity)

d/e = long term debt/shareholders' equity

total liabilities/total assets

7

forecast eps goes down the last 6 months before release due to expectations management

8

detecting earnings management

ratio of volatility (stddev/mean) of accrual income measures to underlying volatility of sales and cfo

12

risk assessment

turnover: accounts receivable turnover, inventory turnover, fixed asset turnover, accounts payable turnover, days payable outstanding

short-term liquidity: current ratio, quick ratio (acid test), operating cash flow to current liabilities

long-term solvency (maybe a good way to value bonds?): debt/equity, long-term debt ratio (simple function of d/e), liabilities/assets

interest coverage ratio, in terms of both income and expenses or cash flow

refs modigliani-miller theorem without explaining: debt and equity financing are equivalent

absolute metrics: interest coverage, current ratio

13

cost of capital

equity cost of capital (discount rate)

capm: estimate beta (key issue) period typically 5 years; bloomberg, analysts, yahoo finance, etc

http://research.stlouisfed.org/fred/data/irates.html for risk-free rate and other data

fama-french 3-factor model extends capm with size, b/m (higher b/m->higher returns)

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html for rates, other data

long run averages: r_m-r_f (market-riskfree) 7.95% per year, r_smb (size premium) 3.32%, r_hml 5.05%

international

segmented/integrated capm: bekaert and harvey 1995

world capm holds if country stock market is integrated: http://www.msci.com/equity/index.html

ow, use r_country

'institutional investor' magazine ranks country credit risk 0-100

impressive fit to data: r_country = alpha + beta*rank

15

expected return depends on systematic risk

alpha = abnormal return = actual return - capm, for example

multiples valuation key assumption: earnings and book equity are comparable

drift strategies

returns over last 6-12 months predict next 6-12 months

post earnings announcement drift from under-reaction to news

red flag: again, gap between reported income and cfo

quality of earnings ratio: (earnings-cfo)/avg total assets

'widely accepted' evidence on fundamental trading strategies

e/p, b/m, cf/p: high->high future abnormal stock returns

var(cf)/p: high->low future abnormal stock returns

v/p (firm value from abnormal earnings model/price): high->low returns

short term reversal: high return this month->low next month

medium term momentum: high return past 6-12 months->high return next 6-12

accrual anomaly: high accounting accruals this quarter->low returns next quarter and beyond

16

bankruptcy detection

http://www.ibbotson.com/content/cc_1v11.asp cost of capital:$15/beta

altman z-score fit from manufacturing firm data

linear function of ratios

moody's, s&p use similar models to z-score to rate corp bonds

http://riskcalc.moodysrms.com/us/research/crm/45768.pdf

http://riskcalc.moodysrms.com/us/research/defrate.asp

17

mergers and acquisitions

'old' purchase method: goodwill asset created and amortized over 40 years

pooling of interests no longer permitted for valuing

18

employee stock options

20

off balance sheet activities

enron background

21

pension plans

defined benefit plans cause accounting problems

22

international financial analysis

insider (code law) codified system

close interplay gov, banks, unions, big firms

continental euro, japan

less public disclosure

outsider (common law)

us, uk, english-speaking

us vs uk differences

23

sarbanes-oxley and review

sarbox 2002

identify comparable firms

multex (?) via yahoo for quick industry benchmarks

will change: accounting rules, tech, market integration, contracting methods

won't change: thought process, economics

guild wars

skills at the end of nightfall:

n: meekness, well of dark

p: harrier's toss, never surrender, stand your ground

memory profiling with python

tough to find good memory profiling for python. heapy-pe and the other (didn't bother to remember the name; pysizer?) turned out to be no good to me with numpy arrays which (surprise!) tend to be the biggest data structures i deal with. here a couple of others to try some time:

meliae is new and more cli-oriented, but looks easy enough to try (and script).

dowser spawned off of cherrypy, but i think it works for any python code with the web server as sort of a gui (i think unlike dozer, which targets wsgi apps. or maybe dozer is just a wsgi version of the 'gui'?).

here's an example of objgraph to analyse memory usage.

i think these are more garbage collector approaches, rather than hook-and-trace, so maybe more likely to work with libs like numpy.

memory_profiler also comes recommended and looks interesting. pure python, so portable and hackable.

r-cran-fimport

ubuntu has a package for downloading free econometrics data: provides import function to access (free) data from Economagic, the US Federal Reserve, Forecasts.Org, Yahoo and other web sources. worth a look to see some sources that would be good to look at. the group of people who wrote this also have a link to a brief discussion of portfolio risk surfaces over the convex hull of achievable sets. interesting... i was thinking something along the same lines, and it's a little gratifying that working pros seem already to be doing something similar.

__get__ method for fun and profit

just learned (or maybe relearned) something cool about python: the __get__ special method gets called when an instance is accessed as an attribute of another instance. not only are there potential uses for this, it also holds the key to understanding the 'self' and 'class' special arg in methods. this is something that confused me a couple of times before, such as passing references to instance vs. class methods from outside the class to be used inside the instance.

so, for example, i could allow instances of one of my classes to know how and where it's getting passed around, and something about the context when something is asked of it. maybe a quick and dirty memory leak tracker, when i know beforehand which objects are the big boys but i don't know who's pointing at them.

or maybe a little internal usage auditor, when i'm considering the impact of a refactor.

valuation books

couple of books recommended by people in the valuation business. one comment about duffie is that he was kind of a disappointment as a consultant, since he likes to stay more in the theoretical than the practical. not sure if this is the best book from him, but it's fairly recent. (search for 'dynamic')

Investment valuation : tools and techniques for determining the value of any asset

Damodaran, Aswath.

interesting that he says most analysis/justification for valuation is on discounted cash flows (as it seems to be in the book), but most valuation in practice is with ratios in relative valuation. contingent claim valuation is a more recent perspective, looking at opportunities available to a firm and pricing them like options. i was disappointed at how little there is on bond and commodity valuation, especially given the promise in the subtitle. interesting chapter on evidence of market efficiency.

Credit risk : pricing, management and measurement

Duffie, Darrell.

financial statement analysis and security valuation, 3rd ed

stephen h. penman

658.15

more on valuation, including slightly less than simple forecasting and detecting financial statement manipulation

dynamics of markets: econophysics and finance

joseph l. mccauley

658.15:519.217

empirical refutation of common modeling assumptions

value at risk: the new benchmark for managing financial risk, 3rd ed

philippe jorion

658.155

different types of risk, some 'industry-standard' real-life practical-experience rules of thumb