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Y.E.A. North America

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Dobrynya Krasilnikov
Dobrynya Krasilnikov

Buy Low And Sell High

The strategy behind buying low and selling high relys on trying to time the market. Buying low means trying to determine when stocks have hit bottom price and purchasing shares in the hope of them going up. Conversely, selling high relies on figuring out when the market has hit its peak. Once stocks have hit their maximum value, investors sell their shares and reap the rewards.

buy low and sell high

Investors who look to buy low and sell high look at several factors to determine if the price of a stock is within the right range. It can be challenging to implement this strategy consistently, so traders look for certain markers to make an informed decision.

On the other end, investors who want to maximize earnings look for indications that stock prices have gone up high enough. Once the value has gone high enough to constitute a sell signal, traders sell the stocks and pocket the difference.

During a bear market, stock prices go down and investors tend to sell off shares as fear takes over. This is the time to buy at a discount as long as you have the capital and the knowledge to evaluate the best stocks to purchase.

But trying to figure out the best time to buy and sell a stock is generally considered a bad idea for the average investors since there are many factors that play into stock prices, and markets are, by their nature, unpredictable,.

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The best investors know that trends are only one piece of an ever-changing puzzle. They know when to ignore trends and follow their own method when deciding to incorporate a buy low, sell high strategy.

The title may appear to be so obvious; after all, who does not know that buying stocks at the bottom and selling at the peak can lead to big gains. But it is much easier said than done. It is almost impossible for most people to be right not once but twice every time they make a trade. In fact, most retail investors end up doing the opposite, not by design but for a host of other reasons.

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We develop a High Frequency (HF) trading strategy where the HF trader uses her superior speed to process information and to post limit sell and buy orders. By introducing a multi-factor mutually-exciting process we allow for feedback effects in market buy and sell orders and the shape of the limit order book (LOB). Our model accounts for arrival of market orders that influence activity, trigger one-sided and two-sided clustering of trades, and induce temporary changes in the shape of the LOB. We also model the impact that market orders have on the short-term drift of the midprice (short-term-alpha). We show that HF traders who do not include predictors of short-term-alpha in their strategies are driven out of the market because they are adversely selected by better informed traders and because they are not able to profit from directional strategies.

Figure 2. Total net energy losses (GWh) and energy value (Million $) to date. Batteries lose energy in the process of charging and discharging but generate savings and reduce GHG emissions by buying low and selling high.

While the goal of almost every investment is to sell your assets for more than you bought them for, buy low sell high refers specifically to a strategy used by active traders. Long-term investors or passive investors may employ different strategies such as dividend investing or indexing.

Investors who use the buy low, sell high strategy tend to pay close attention to pricing trends or technical indicators in order to time their trades. Tracking trends for individual securities, for particular stock market sectors, or the market as a whole can help investors understand what kind of momentum is driving prices.

Investors who give in to biases may find themselves following a herd mentality when it comes to making trades. If news of a pending interest rate hike spreads fear in the markets, investors may begin panic selling. This can, in turn, lead to lower prices. On the other hand, irrational exuberance for a specific stock or type of security can lead to higher prices, causing an unsustainable market bubble.

A buy low sell high approach can also help investors to beat the market if their portfolio performs better than expected. If an investor is skilled in timing their trades, consistently buying low and selling high, they have a better chance of beating the market than investors who buy and hold.

This strategy is most commonly used to discuss stock trading, but it can be utilized when investing in almost any security and asset class. Many collectibles investors utilize trends of consumer sentiment to time when they should purchase and sell rare collectibles, for example.

An investor in the three cheapest factors would have outperformed an investor in the equally weighted factor mix by about 3.7%. Even though the approach has a systematic bias away from the factors with the highest structural alphas, our focus on the cheapest strategies overcomes that headwind, with 370 bps a year of room to spare.

The performance difference between the three cheapest factors and the three most expensive factors in the US market, reported in Panel B of Table 3, was 7.2% a year over the period from January 1977 to August 2016. With a t-statistic of 3.62, the difference is highly economically and statistically significant.14 In international markets, the difference is far smaller and not significant, which is perhaps a consequence of currently stretched factor (and smart beta) strategy valuations in non-US markets. If these markets mean revert, the gap (and its significance) will presumably rise. Interestingly, even with the stretched valuations, buying the cheaper strategies and factors would have proved beneficial.

In our analysis of the eight smart beta strategies, we observe that a combination of the three strategies with the most attractive (least expensive) valuations tends to generate a higher return relative to an equally weighted mix of all eight strategies. The higher return does not come with an improvement in the Sharpe ratio because of the loss in diversification relative to the well-diversified equally weighted mix. To further study the benefits of diversification, we simulate one more strategy:

The performance of this strategy is presented in Figure A1. We compare its return and risk to three other approaches: an equally weighted allocation, a contrarian approach combining the three worst-performing strategies/factors, and a combination of the three strategies/factors with the least-expensive valuations. For both smart beta strategies and factors, the tilted-diversification-toward least-expensive strategy results in lower performance when compared to the least-expensive, less-diversified strategy, but it does have a higher Sharpe ratio. More details on the performance of the strategies and their opposites are reported in Table A1.

The large-cap universe is then subdivided by various factor signals to construct high-characteristic and low-characteristic portfolios, following Fama and French (1993) for the US and Fama and French (2012) for international markets. (Note that slight variations in data cleaning and lagging, as well as different rebalance dates, could lead to slight differences between our factors and those of Fama and French.) As an example, in order to simulate the value factor in the United States, we construct the value stock portfolio from stocks above the 70th percentile on the NYSE by book-to-market ratio, and we construct the growth stock portfolio from stocks below the 30th percentile by the same measure. Internationally, we construct the value stock portfolio from stocks above the 70th percentile in their region (North America, Japan, Asia Pacific, and Europe) by book-to-market, and the growth stock portfolio from stocks below the 30th percentile in their region.

For example, if it comes out that a company is severely in debt, people may sell their shares in fear the company is about to go bankrupt. The lessened supply causes a drop in the stock price. There is a herd instinct that affects stock prices and as the price drops, more people may sell.

With the buy low, sell high strategy, investors try to do the opposite of the general public. When others are fearful, they buy at low prices. Then, when people start purchasing more stocks again, investors sell at higher prices.

Buy low, sell high is a simple concept to understand, but it can be challenging in practice. Even with thorough research conducted, public sentiment is hard to predict and pinpointing highs and lows is much easier in retrospect than ahead of time. 041b061a72


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