Oxford Square Stock Forecast - Naive Prediction

OXSQ Stock  USD 2.63  0.04  1.50%   
The Naive Prediction forecasted value of Oxford Square Capital on the next trading day is expected to be 2.62 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.49. Oxford Stock Forecast is based on your current time horizon. Although Oxford Square's naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Oxford Square's systematic risk associated with finding meaningful patterns of Oxford Square fundamentals over time.
  
At this time, Oxford Square's Inventory Turnover is relatively stable compared to the past year. As of 11/27/2024, Receivables Turnover is likely to grow to 9.26, while Payables Turnover is likely to drop 6.76. . As of 11/27/2024, Net Income Applicable To Common Shares is likely to grow to about 18.4 M, while Common Stock Shares Outstanding is likely to drop slightly above 43.9 M.

Oxford Square Cash Forecast

Forecasting financial indicators like cash flow involves analysts applying various statistical methods, techniques, and algorithms. These tools reveal hidden trends within the Oxford Square's financial statements to estimate their effects on upcoming price movements.
 
Cash  
First Reported
2003-12-31
Previous Quarter
30 M
Current Value
43.2 M
Quarterly Volatility
31.2 M
 
Housing Crash
 
Credit Downgrade
 
Yuan Drop
 
Covid
A naive forecasting model for Oxford Square is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Oxford Square Capital value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Oxford Square Naive Prediction Price Forecast For the 28th of November

Given 90 days horizon, the Naive Prediction forecasted value of Oxford Square Capital on the next trading day is expected to be 2.62 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.0009, and the sum of the absolute errors of 1.49.
Please note that although there have been many attempts to predict Oxford Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that Oxford Square's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Oxford Square Stock Forecast Pattern

Backtest Oxford SquareOxford Square Price PredictionBuy or Sell Advice 

Oxford Square Forecasted Value

In the context of forecasting Oxford Square's Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. Oxford Square's downside and upside margins for the forecasting period are 1.70 and 3.55, respectively. We have considered Oxford Square's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Market Value
2.63
2.62
Expected Value
3.55
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Oxford Square stock data series using in forecasting. Note that when a statistical model is used to represent Oxford Square stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.
AICAkaike Information Criteria111.0948
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0244
MAPEMean absolute percentage error0.0087
SAESum of the absolute errors1.4907
This model is not at all useful as a medium-long range forecasting tool of Oxford Square Capital. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Oxford Square. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Oxford Square

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Oxford Square Capital. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Oxford Square's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Hype
Prediction
LowEstimatedHigh
1.712.633.55
Details
Intrinsic
Valuation
LowRealHigh
2.263.184.10
Details
1 Analysts
Consensus
LowTargetHigh
4.324.755.27
Details

Other Forecasting Options for Oxford Square

For every potential investor in Oxford, whether a beginner or expert, Oxford Square's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Oxford Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Oxford. Basic forecasting techniques help filter out the noise by identifying Oxford Square's price trends.

Oxford Square Related Equities

One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with Oxford Square stock to make a market-neutral strategy. Peer analysis of Oxford Square could also be used in its relative valuation, which is a method of valuing Oxford Square by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Oxford Square Capital Technical and Predictive Analytics

The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Oxford Square's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of Oxford Square's current price.

Oxford Square Market Strength Events

Market strength indicators help investors to evaluate how Oxford Square stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Oxford Square shares will generate the highest return on investment. By undertsting and applying Oxford Square stock market strength indicators, traders can identify Oxford Square Capital entry and exit signals to maximize returns.

Oxford Square Risk Indicators

The analysis of Oxford Square's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in Oxford Square's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting oxford stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Pair Trading with Oxford Square

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Oxford Square position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Oxford Square will appreciate offsetting losses from the drop in the long position's value.

Moving against Oxford Stock

  0.53DHIL Diamond Hill InvestmentPairCorr
  0.39BEN Franklin ResourcesPairCorr
  0.37BY Byline Bancorp Fiscal Year End 23rd of January 2025 PairCorr
  0.34AX Axos FinancialPairCorr
  0.33BX Blackstone Group Fiscal Year End 23rd of January 2025 PairCorr
The ability to find closely correlated positions to Oxford Square could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Oxford Square when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Oxford Square - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Oxford Square Capital to buy it.
The correlation of Oxford Square is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Oxford Square moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Oxford Square Capital moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Oxford Square can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching

Additional Tools for Oxford Stock Analysis

When running Oxford Square's price analysis, check to measure Oxford Square's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Oxford Square is operating at the current time. Most of Oxford Square's value examination focuses on studying past and present price action to predict the probability of Oxford Square's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Oxford Square's price. Additionally, you may evaluate how the addition of Oxford Square to your portfolios can decrease your overall portfolio volatility.