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Why the Internet did not kill RadioShack

See the original article posted on Fortune Insider here>>

Although the electronics retailer is the latest victim in the rise of e-commerce, several other missteps led to its demise.

We’ve seen the downfall of many bricks and mortar stores over the last decade, including Borders, Circuit City, and most recently, RadioShack — to name just a few. As e-commerce continues to rise, it’s seemingly becoming more difficult for traditional stores to stay in business.

It’s true that online shopping has significantly grown over the last 10 years. Even in the last year, we’ve seen a noticeable uptick. According to the U.S. Census, total e-commerce sales for 2014 in the U.S. were estimated at $304.9 billion, which is a 15.4% increase from 2013. However, plenty of bricks and mortar stores are still healthy. Is it fair to blame e-commerce for every store closing and bankruptcy?

As a U.S. bankruptcy judge on Tuesday said he would approve a plan by the electronics retailer to sell 1,740 of its stores to the Standard General hedge fund and exit bankruptcy, it’s worth taking a closer look at why RadioShack failed. E-commerce wasn’t the only culprit. One big mistake involved poor strategic decisions over its financials. Feeling undervalued, the retailer bought back $400 million in stock in 2010 when its net profit was $206 million. It did something similar in 2011 when its net profit had declined to $72 million and it did another buy back for $113 million. In the end, it spent more than $500 million trying to push up the stock price.

However, the company didn’t make enough money to finance the buy back and had to borrow money, which increased its debt-to- value ratio and left RadioShack vulnerable to a declining profits. Rather than buying back so much of the stock and taking on debt, it should have accepted the valuation, closed a few inefficient stores and avoided bankruptcy.

Another significant mistake was its decision to change its product market strategy. In prior years, RadioShack was known as the place to go for hard-to-find parts and components needed to build things. It also had knowledgeable staff who could help customers with high-level customer service. Customers were willing to pay higher prices because of this additional value. After all, there is a difference between getting helpful information in person and trying to explain an issue via the phone, an online chat, or a Google search.

When RadioShack changed its business model to sell finished products like laptops and phones, it lost that competitive edge. Customers could get those finished products from many other retailers and e-commerce sites at lower prices. And a higher-level of customer service wasn’t needed for those products.

While it’s too late for RadioShack, its demise offers some important takeaways for other bricks and mortar stores:

Find a competitive edge. If you offer a unique product, like RadioShack did with selling specialty components, don’t disregard that strength.

Be aware of price sensitivities. A big challenge for bricks and mortar stores is that they have to pay for overhead whereas online retailers don’t, allowing them to charge lower prices. Customers are more likely to price shop for larger and more expensive items, especially ones readily available online like phones and tablets. They tend to be less price sensitive about small and specific goods like the components previously sold by RadioShack.

Focus on customer experience. A big draw for RadioShack was its knowledgeable staff. When it moved to selling finished products, the need for that staff — and consumer willingness to pay higher prices — disappeared. Many people still value talking to a real person.

Looking ahead, it won’t be smooth sailing for traditional stores. But it won’t be all doom and gloom either if they can learn from the mistakes of retailers like RadioShack.

Andrey Malenko is the Jon D. Gruber Career Development Assistant Professor of Finance at the MIT Sloan School of Management.

What is the optimal trading frequency in financial markets?

Trading speeds in financial markets have increased dramatically over the last decade. In markets for equities, futures and foreign exchange, transactions take place in milliseconds to microseconds (or even nanoseconds). Markets for fixed-income securities like corporate bonds and over-the-counter derivatives like interest rate swaps and CDS are also catching up quickly by adopting electronic trading.

The dramatic speed-up of financial transactions can perhaps only be matched by the intensity of the events and debates surrounding it, especially in the context of high-frequency trading. To many, the Flash Crash of May 2010 was a wakeup call for reevaluating market structure. A series of technology glitches proved to be highly costly for some brokers, proprietary firms and marketplaces in terms of profits and reputation. The SEC launched investigations into HFT firms and their strategies. The French regulators introduced financial transaction tax. Michael Lewis wrote “Flash Boys.” The list goes on.

With these events and controversy come important economic questions: What are the costs and benefits to investors for speeding up trading? Is there an “optimal” trading frequency at which the financial market should operate? And does a faster market affect one group of investors more than another?

In a recent research paper, Welfare and Optimal Trading Frequency in Dynamic Double Auctions, my coauthor Prof. Songzi Du (Simon Fraser University) and I attempt to answer these questions.

Our starting point is very simple. Trading frequency can be measured by how often investors transact through market. A higher-frequency market allows investors to access the market more often per unit of clock time. When investors meet each other in the market, they trade. Trading can be motivated by new information about future asset value and idiosyncratic trading incentives such as tax or inventory considerations.

A fundamental function of financial market is to reallocate assets from investors who value them less to investors who value the assets more, at the right price. The better this function is fulfilled, the more efficient the market is in reallocating the asset. We say that the market “improve welfare”—that is, make all investors better off—if it makes the reallocation of assets more efficient.

The bright side and dark side of a higher-frequency market

A higher trading frequency is double-edged sword. The optimal trading frequency depends on how the benefit and cost balance each other.

On the bright side, a higher-frequency market is more responsive to new information. Investors benefit from being able to react immediately to news. For example, following earnings announcements or merger-acquisition news, an investor may find his previous allocation on a stock no longer desirable. The sooner investors react to this information by trading, the better off they are. This effect favors a high-frequency market.

On the dark side, a higher-frequency market reduces the aggressiveness of investors’ trades. Investors are said to be more aggressive if they are willing to tolerate a greater market impact to achieve their target asset position. For example, aggressive execution means trading larger quantities more quickly. By contrast, unaggressive execution means splitting a large order into many small pieces and trading them gradually over time. The more frequently the market allows investors to transact, the stronger is their incentive to split orders over time to avoid price impact; hence, it takes longer to reach desired asset positions, and this is inefficient. If, however, a market opens infrequently, it encourages investors to trade aggressively now—failing to trade now means waiting for longer for the next opportunity to trade; this in turn leads to a faster convergence to efficient allocations. In this sense, somewhat counter intuitively, a lower-frequency market enhances allocation efficiency.

Scheduled versus stochastic news

We show that the optimal trading frequency depends on the nature of information arrivals, which determines the tradeoff between the benefit and cost of a higher trading frequency.

For scheduled arrivals of information, such as earnings announcements and macroeconomic data releases, we find that the optimal trading frequency should be equal to or lower than the frequency of information arrivals. For example, if news only arrives once per day, it is never optimal for investors to trade more than once a day. Moreover, if the market is competitive enough, the optimal trading frequency is equal to the information frequency.

For stochastic arrivals of information, such as surprise news of mergers and acquisitions, we show that the optimal trading frequency can be much higher. Moreover, if the market is competitive enough, continuous trading (the highest-frequency market) turns out to be optimal.

What does this tell us about optimal trading frequency in reality? Assets such as large-cap stocks or Treasuries that have frequent, unpredictable news shocks should be traded close to continuously. Small, illiquid stocks or bonds that have scarce news may best trade in a low-frequency market that only opens a few times a day; concentrating trading interests at specific time creates a deeper market. Therefore, there is no “one size fits all” optimal trading frequency for all securities.

For more details of this research, see “Welfare and Optimal Trading Frequency in Dynamic Double Auctions”, by Songzi Du and Haoxiang Zhu, http://ssrn.com/abstract=2040609.

Haoxiang Zhu is an Assistant Professor of Finance at MIT Sloan School of Management.

Professor Zhu’s research on this topic has also been featured on MarketWatch, click to view the article.