More on Facebook privacy and data collecting

By , August 9, 2011 7:33 pm

 

If Facebook offers more privacy options, it makes people feel safer sharing their information, and they would likely share more. Example: I want to share information A to group X but not group Y; I am comfortable with (or even have incentive to) revealing interest B to group T but not group U.

Facebook can then perform data mining on the information, it’s inside Facebook’s great wall anyway.

Privacy can hinder those who want to collect data on Facebook only through information visible to them. But not to those who are willing to pay Facebook for the data mining.

Facebook benefits both way.

A summary of what Mark Hurd has been doing with HP

By , August 9, 2011 7:32 pm
  • Change focus from doing (mega)deals to operations
  • Focus on strengths i.e. printer
  • Separated printer and PC businesses
  • Cost saving
  • Manage supply chain and turn Intel and AMD against each other
  • Develop distribution network with retailers

Results

  1. Overtook Dell
  2. Shareholder value
  3. A smart deal with Palm
  4. HP with Plate is currently in best position against Apple in the tablet segment

Portfolio Optimization of S&P 500 assets and Forecast of Efficiency in turbulence

By , August 9, 2011 7:31 pm
Portfolio Optimization of S&P 500 assets and Forecast of Efficiency in turbulence

Thuy Nguyen, Tai Tran, Huy Truong

October 2009

Abstract

Optimization is one key activity to portfolio management practice. This document draws portfolio selection and optimization guidelines from Harry Markowitz, William Sharpe, Treynor & Black and Modigliani & Modigliani works to optimize portfolios constructed from the S&P 500 and fixed income assets. We build efficient portfolios using their adjusted daily historical data through an observation of 15 years. We find that, under short-selling liquidity constraint, Wal-Mart outperforms the market and its peers, and prevails through macro-economic fluctuations. Short-cuts to portfolio construction and rebalancing using Black method reduces input management efforts, while comes at a slight trade-off of accuracy. We also forecast portfolio returns for subsequent years and adjust our models to cope with possible turbulence. The efficient portfolios still produces better results than bogey portfolios do.

A brief summary of Amazon capabilities

By , August 9, 2011 7:25 pm
Amazon positions itself as a technology company, not a retailer
  1. Target the long-tail with million titles, while the largest physical book store may only store 400,000
  2. Intensive investment in technology
  3. Location: Seattle, near computer talents
  4. Product search, data mining, personalized shopping
  5. In-house software systems
  6. Leader in cloud computing
  7. Supplementary product: Kindle
  8. Scalability
  9. B2C to C2C
Jeff Bezos’s vision and financial expertise
  1. Prior to Amazon: Princeton Computer Science & Electrical Engineering graduate, 2 years in Commercial Banking and 4 years in NY Investment Banking
  2. Focus on customer service, avoid price war
  3. Started with books then diversified
  4. Act like a Venture Capitalist to other younger e-commerce firms then get advertising fees from these partners
  5. Lock out competition with this partnership network
  6. Use sophisticated financial structure including:
    • Private equity (only $1 in 1994)
    • Convertible preferred shares ($8 in 1996)
    • $326m 10% senior discount notes mature in 10 years
    • Debt repurchase
    • $1.25b 4.75% convertible subordinated notes mature in 10 years
    • $680m 6.875% euro-denominated subordinated notes mature in 10 years
    • Live many years on credit rating CCC but the company has had enough cash to spend. Good governance!
  7. Good accounting compliance
Operations
  1. Revenue sources: commission, advertising, affiliate marketing, cloud computing leasing
  2. Order from suppliers after customer has made an order
  3. Weathered the dot-com bubble and GFC well

Reference

Cott J., Palepu K., ‘Amazon.com’

Efficiency and Morale

By , August 9, 2011 7:17 pm

I doubt the relationship is an exact parabola, but yeah, that’s the idea

Foster’s Group Limited Analysis and Valuation

By , August 9, 2011 7:13 pm
Foster’s Group Limited Analysis and Valuation
Investment Decision Making Support

June 2010

Phuong Ho, Thanh Luong, Hanh Pham, Khoi Tran, Tai Tran, Huy Truong

Abstract

Valuation is the key activity for investment decisions. This document analyses Strategy, Accounting, and Financial conditions of Foster’s Group Limited within the context of the Australian Alcoholic Beverage Industry. The information is ultimately synthesized for Forecast and Valuation of the company. Time-series analysis is done for the 2007-2009 period with reference to the 2005-2006 period. Cross-sectional analysis puts Foster in contrast to its major competitor Lion Nathan. All information is from publicly available academic and reputable business sources.

On industry level, Foster is the largest player in a concentrated market. Foster can take advantage of the acquisition of Lion Nathan to move ahead in the competition. In terms of strategy, Foster is implementing various initiatives so as to maintain its position in Australasia and expand to the US and Asia. Accounting of the company is at high quality; however a concern of write-down is raised. On financial performance, Foster’s business is more fluctuating resulting from turbulence of its operations in the US market, compared to its opponent Lion Nathan. The volatility of earnings and growth may account for uncertainty of market perception toward the company and thus result in an undervaluation. Forecast of company sales growth ranges between 2.7% to 3.1% which is higher than industry value weighted average, and forecast of net operating profit margin is 18%. Valuation using three difference methods yields a fair price of AUD 5.85. We find the stock currently undervalued while the company has great prospects in long-term horizon, thus recommend Buy and Hold strategy. This recommendation receives analysts’ consensus.

To receive the document, please comment on this post with your real email (won’t be publicized).

The Australian Market for Corporate Control and how Firms create value

By , August 9, 2011 7:12 pm
The Australian Market for Corporate Control and how Firms create value

2010

Xuan Huang, Logan Robertson, Tai Tran, Huy Truong, Frank Wong

Abstract

Academic literature has devoted much effort to analyse merger and acquisition activities. Event studies are conducted to look at factors affecting shareholder returns in M&As. In particular, Moeller et al (2004) documented a size effect of US firms’ cumulative abnormal return around acquisition announcements. Using similar methodology on a sample of 1578 takeover deals from 2001 to 2007, this report attempts to i) assist Australian managers to select potential takeover target, ii) assist investors to make informed investment decision. We documented that Cumulative abnormal return (CAR) are on average positive at 4.15%, but average dollar CAR loss $11.66 million. However, once we take into account the skewness of Australian firm, the median for both CAR and dollar CAR are positive. OLS, multivariate and Probit regression methods were employed to confirm our analysis. Our result did not indicate a significant firm size effect in our dataset of Australian Acquirers. We also find highest abnormal return in stock-financed deals where targets are private. Additionally, we link the positive result of combined cumulative abnormal return to synergy motivation for doing acquisitions. Our findings should be of interest to financial managers in Australia who plan on merger engagements. Finally, our probit regression indicates that larger acquirer size is no more likely to make value reducing deals than those who are smaller.

Information as Value Creator

By , August 9, 2011 7:12 pm

And here come $126 Chinese iPed and $35 Indian iPad clone.This is not to mention the not-so-an-imitationHewlett-Packard’s Slate.

The real value Apple is creating, however, is not only encapsulated in the hardware. What matters, and cannot be imitated by competitors, is the information exchange platform AppStore through which Apple has earned sweet royalties. Furthermore, while thousands of third-party companies and developers strive their best to be profitable building applications, Apple reaps the reward and share none of the failure.

Same does Facebook. And Wii.

This is the era where hardware has become commodities and information and services bring more value. And revenue.

What other platforms are you thinking of?

Intraday Liquidity Pattern calculation using Ox

By , August 9, 2011 7:11 pm
/*
* Stefan Binder, Duk Jang, Tai Tran
* This Ox program calculates liquidity pattern from a trading period for a stock
* The intraday pattern assists trading strategies formation
*/

const decl ROWS = 3416;
const decl COLUMNS = 4;
const decl PARCELS = 6;
const decl PRICE = 0;
const decl VOLUME = 1;
const decl DAY = 2;
const decl HOUR = 3;
const decl OPEN = 10;
const decl NUMBEROFPARCELS = 6;
const decl CLOSE = OPEN + NUMBEROFPARCELS - 1;
const decl NUMBEROFDAYS = 5;
const decl FILENAME = "tradedata.csv";
const decl PARCELOUTPUT = "ParcelLiquidity.csv";
const decl DAYOUTPUT = "DayLiquidity.csv";

main()
{
decl m;
decl liquidity=0;
decl parcel;
decl day;
decl parcelPercent;
decl dayPercent;
decl i,j,k;
decl fileParcel,fileDay;

m = new matrix[ROWS][COLUMNS];
m = loadmat(FILENAME);
day = new matrix[1][NUMBEROFDAYS];
dayPercent = new matrix[1][NUMBEROFDAYS];
parcel = new matrix[1][PARCELS];
parcelPercent = new matrix[1][PARCELS];

for (i = 0 ; i < ROWS ; i++)
{
for (j = 0 ; j < NUMBEROFPARCELS ; j++) if (m[i][HOUR] == OPEN+j) parcel[0][j] += m[i][VOLUME];

for (k = 0 ; k < NUMBEROFDAYS ; k++) if (m[i][DAY] == k+1) day[0][k] += m[i][VOLUME];

liquidity += m[i][VOLUME];
}

for (i = 0 ; i < PARCELS ; i++) parcelPercent[0][i] = parcel[0][i] / liquidity;
for (i = 0 ; i < NUMBEROFDAYS ; i++) dayPercent[0][i] = day[0][i] / liquidity;

fileParcel = fopen(PARCELOUTPUT,"w");
fileDay = fopen(DAYOUTPUT,"w");

for (i = 0 ; i < NUMBEROFPARCELS ; i++)
{
print("\nLiquidity from ", OPEN+i, " to ", OPEN+i+1, " is ", parcel[0][i], " which is ", parcelPercent[0][i]*100, " percent");
fprint(fileParcel, "\nLiquidity from ", OPEN+i, " to ", OPEN+i+1, " is ", parcel[0][i], "," ,parcelPercent[0][i]*100);
}

for (i = 0 ; i < NUMBEROFDAYS ; i++)
{
print("\nLiquidity on day ", i+1, " is ", day[0][i], " which is ", dayPercent[0][i]*100, " percent");
fprint(fileDay, "\nLiquidity on day ", i+1, " is,", day[0][i], "," ,dayPercent[0][i]*100);
}
}

Why selling after an institutional block ask is irrational but sensible

By , August 9, 2011 7:11 pm

Large institutional sale on the market should not be interpreted as a negative signal of the asset. Most if not all institutional traders are bounded by a variety of constraints (e.g. portfolio performance evaluation timing) and structured with investment strategies (e.g. exit or cut-loss thresholds). In fact, a block sale may also indicate that the investor has already reaped target return. I don’t see reasons for retailers to take action upon knowing a block sale, especially in markets when short-sell is not allowed.

Nevertheless, in a young market where the majority of mom-and-pop investors tend to panic at an institutional exit, selling the stock for speculative purpose is an option because the negative price effect that irrationally occurs might be permanent.

On the other hand, institutional purchase should be a good signal for the targeted assets. Whether for investing or speculating purpose, the introduction (or increased weight) of an asset to an institutional portfolio may be a result of privileged information.

Mimicking the long position in absence of existing strategy is one simple option.

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